VI111
Systems and Signals - Modeling, Identification and Signal Processing
VI111-01 Data-Driven Methods for Decisions and Control   Invited Session, 4 papers
VI111-02 Data-Driven Modeling and Learning in Dynamic Networks   Open Invited Session, 11 papers
VI111-03 Data-Driven Process Monitoring and Control for Complex Industrial Systems   Open Invited Session, 13 papers
VI111-04 Machine Learning for Monitoring and Control of Chemical and Biological Processes   Open Invited Session, 13 papers
VI111-05 Modelling, Identification and Control of Quantum Systems   Open Invited Session, 12 papers
VI111-06 Results on Nonlinear System Identification Benchmarks   Open Invited Session, 5 papers
VI111-07 Application of System Identification   Regular Session, 4 papers
VI111-08 Bayesian Methods   Regular Session, 16 papers
VI111-09 Classification, Estimation, and Filtering   Regular Session, 11 papers
VI111-10 Estimation, Identification, and Discretization of Continuous-Time Systems   Regular Session, 17 papers
VI111-11 Fault Detection and Diagnosis   Regular Session, 34 papers
VI111-12 Identification for Control   Regular Session, 9 papers
VI111-13 Linear Systems Identification   Regular Session, 7 papers
VI111-14 Learning for Modeling, Identification, and Control   Regular Session, 13 papers
VI111-15 Modeling, Identification and Control of Dynamic Networks   Regular Session, 7 papers
VI111-16 Nonlinear System Identification   Regular Session, 32 papers
VI111-17 Particle Filtering/Monte Carlo Methods   Regular Session, 5 papers

VI111-01
Data-Driven Methods for Decisions and Control	Invited Session
Chair: Carè, Algo	University of Brescia, Italy
Co-Chair: Garatti, Simone	Politecnico Di Milano
Organizer: Campi, Marco	University of Brescia
Organizer: Carè, Algo	University of Brescia, Italy
Organizer: Garatti, Simone	Politecnico Di Milano
Paper VI111-01.1
PDF · Video · Robust Force Control for Brake-By-Wire Actuators Via Scenario Optimization (I)
Riva, Giorgio	Politecnico Di Milano
Nava, Dario	Politecnico Di Milano
Formentin, Simone	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Randomized methods Abstract: Clamping force control in Electro Mechanical Brakes (EMBs) is a challenging task, mainly due to the nonlinear dynamics of the system and the uncertainty affecting its physical parameters. In this paper, a robust tuning of a PID control loop for an EMB is proposed. First, a control-relevant linear model of the system is derived. Then, the optimal parameters of the controller are tuned by solving a convex pole-placement problem and probabilistic robustness guarantees are provided according to the scenario theory. Finally, the performance of the proposed strategy is assessed on a complex nonlinear simulator of the EMB dynamics, and compared with the state of the art approach for robust control of EMBs.
Paper VI111-01.2
PDF · Video · Data-Driven Control of Unknown Systems: A Linear Programming Approach (I)
Tanzanakis, Alexandros	ETH Zurich
Lygeros, John	ETH Zurich
Keywords: Learning for control Abstract: We consider the problem of discounted optimal state-feedback regulation for general unknown deterministic discrete-time systems. It is well known that open-loop instability of systems, non-quadratic cost functions and complex nonlinear dynamics, as well as the on-policy behavior of many reinforcement learning (RL) algorithms, make the design of model-free optimal adaptive controllers a challenging task. We depart from commonly used least-squares and neural network approximation methods in conventional model-free control theory, and propose a novel family of data-driven optimization algorithms based on linear programming, off-policy Q-learning and randomized experience replay. We develop both policy iteration (PI) and value iteration (VI) methods to compute an approximate optimal feedback controller with high precision and without the knowledge of a system model and stage cost function. Simulation studies confirm the effectiveness of the proposed methods.
Paper VI111-01.3
PDF · Video · No-Regret Learning from Partially Observed Data in Repeated Auctions (I)
Karaca, Orcun	ETH Zurich
Sessa, Pier Giuseppe	ETH Zurich
Leidi, Anna	ETH Zurich
Kamgarpour, Maryam	Swiss Federal Institute of Technology
Keywords: Multi-agent systems, Stochastic control and game theory, Learning for control Abstract: We study a general class of repeated auctions, such as the ones found in electricity markets, as multi-agent games between the bidders. In such a repeated setting, bidders can adapt their strategies online using no-regret algorithms based on the data observed in the previous auction rounds. Well-studied no-regret algorithms depend on the feedback information available at every round, and can be mainly distinguished as bandit (or payoff-based), and full-information. However, the information structure found in auctions lies in between these two models, since participants can often obtain partial observations of their utilities under different strategies. To this end, we modify existing bandit algorithms to exploit such additional information. Specifically, we utilize the feedback information that bidders can obtain when their bids are not accepted, and build a more accurate estimator of the utility vector. This results in improved regret guarantees compared to standard bandit algorithms. Moreover, we propose a heuristic method for auction settings where the proposed algorithm is not directly applicable. Finally, we demonstrate our findings on case studies based on realistic electricity market models.
Paper VI111-01.4
PDF · Video · A Scenario-Based Approach to Multi-Agent Optimization with Distributed Information (I)
Falsone, Alessandro	Politecnico Di Milano
Margellos, Kostas	University of Oxford
Prandini, Maria	Politecnico Di Milano
Garatti, Simone	Politecnico Di Milano
Keywords: Multi-agent systems, Randomized methods, Learning for control Abstract: In this paper, we consider optimization problems involving multiple agents. Each agent introduces its own constraints on the optimization vector, and the constraints of all agents depend on a common source of uncertainty. We suppose that uncertainty is known locally to each agent through a private set of data (multi-agent scenarios), and that each agent enforces its scenario-based constraints to the solution of the multi-agent optimization problem. Our goal is to assess the feasibility properties of the corresponding multi-agent scenario solution. In particular, we are able to provide a priori certificates that the solution is feasible for a new occurrence of the global uncertainty with a probability that depends on the size of the datasets and the desired confidence level. The recently introduced wait-and-judge approach to scenario optimization and the notion of support rank are used for this purpose. Notably, decision-coupled and constrained-coupled uncertain optimization programs for multi-agent systems fit our framework and, hence, any distributed optimization scheme to solve the associated multi-agent scenario problem can be accompanied with our a priori probabilistic feasibility certificates.

VI111-02
Data-Driven Modeling and Learning in Dynamic Networks	Open Invited Session
Chair: Van den Hof, Paul M.J.	Eindhoven University of Technology
Co-Chair: Rantzer, Anders	Lund Univ
Organizer: Van den Hof, Paul M.J.	Eindhoven University of Technology
Organizer: Chiuso, Alessandro	University of Padova
Organizer: Goncalves, Jorge M.	University of Luxembourg
Paper VI111-02.1
PDF · Video · Graph Theoretic Foundations of Cyclic and Acyclic Linear Dynamic Networks (I)
Johnson, Charles	Brigham Young University
Woodbury, Nathan	Brigham Young University
Warnick, Sean	Brigham Young Univ
Keywords: Dynamic Networks Abstract: Dynamic Networks are signal flow graphs explicitly partitioning structural information from dynamic or behavioral information in a dynamic system. This paper develops the mathematical foundations underlying this class of models, revealing structural roots for system concepts such as system behavior, well-posedness, causality, controllability, observability, minimality, abstraction, and realization. This theory of abstractions uses graph theory to systematically and rigorously relate LTI state space theory, developed by Kalman and emphasizing differential equations and linear algebra, to the operator theory of Weiner, emphasizing complex analysis, and Willem’s behavioral theory. New systems concepts, such as net effect, complete abstraction, and extraneous realization, are introduced, and we reveal conditions when acyclic abstractions exist for a given network, opening questions about their use in network reconstruction and other applications.
Paper VI111-02.2
PDF · Video · Recursive Estimation of Three Phase Line Admittance in Electric Power Networks (I)
Mishra, Aditya	University of California San Diego
de Callafon, Raymond	University of California, San Diego
Keywords: Dynamic Networks, Machine learning, Recursive identification Abstract: Synchronized phasor measurements in power transmission and distribution networks enable real-time monitoring of voltage and currents. Such measurements can be used to monitor power flow, but also to monitor important electric parameters of the network. In this paper, it is shown how synchrophasor measurements can be used for real-time monitoring of the admittance of the connections between buses in a power network, typically the three-phase transmission or distribution lines. The objective is to formulate admittance monitoring capabilities in which changes in three-phase line admittance can be monitored in real-time and achieved by the formulation of synchrophasor-based recursive estimation techniques over short time intervals.
Paper VI111-02.3
PDF · Video · Excitation Allocation for Generic Identifiability of a Single Module in Dynamic Networks: A Graphic Approach (I)
Shi, Shengling	Eindhoven University of Technology
Cheng, Xiaodong	Eindhoven University of Technology
Van den Hof, Paul M.J.	Eindhoven University of Technology
Keywords: Dynamic Networks, Identifiability, Input and excitation design Abstract: For identifiability of a single module in a dynamic network, excitation signals need to be allocated at particular nodes in the network. Current techniques provide analysis tools for verifying identifiability in a given situation, but hardly address the synthesis question: where to allocate the excitation signals to achieve generic identifiability. Starting from the graph topology of the considered network model set, a new analytic result for generic identifiability of a single module is derived based on the concept of disconnecting sets. For the situation that all node signals are measured, the vertices in a particular disconnecting set provide the potential locations to allocate the excitation signals. Synthesis approaches are then developed to allocate excitation signals to guarantee generic identifiability.
Paper VI111-02.4
PDF · Video · Consistent Identification of Dynamic Networks Subject to White Noise Using Weighted Null-Space Fitting (I)
Fonken, Stefanie	TUe
Ferizbegovic, Mina	KTH
Hjalmarsson, Håkan	KTH
Keywords: Dynamic Networks Abstract: Identification of dynamic networks has been a flourishing area in recent years. However, there are few contributions addressing the problem of simultaneously identifying all modules in a network of given structure. In principle the prediction error method can handle such problems but this methods suffers from well known issues with local minima and how to find initial parameter values. Weighted Null-Space Fitting is a multi-step least-squares method and in this contribution we extend this method to rational linear dynamic networks of arbitrary topology with modules subject to white noise disturbances. We show that WNSF reaches the performance of PEM initialized at the true parameter values for a fairly complex network, suggesting consistency and asymptotic efficiency of the proposed method.
Paper VI111-02.5
PDF · Video · Single Module Identification in Dynamic Networks - the Current Status (I)
Van den Hof, Paul M.J.	Eindhoven University of Technology
Ramaswamy, Karthik R.	Eindhoven University of Technology
Keywords: Dynamic Networks, Identifiability, Closed loop identification Abstract: Over the last decade, the problem of data-driven modeling in linear dynamic networks has been introduced in the literature, and has shown to contain many different challenging research questions, that go far beyond the classical problems in open-loop and closed-loop identification. The structural and topological properties of networks become a central ingredient in the related identification setting, as well as the selection of locations for signals to be sensed and for excitation signals to be added. In this seminar we will present an overview of recent results that are obtained for the problem of identification of a single link/module in a dynamic network of which the topology is given. The surveyed methods include extensions of the direct and indirect methods of closed-loop identification, as well as Wiener filter approaches and Bayesian kernel-based methods. Particular attention will be given to the selection of signals that need to be available for measurement/excitation, and accuracy properties of the estimated models in terms of consistency and minimum variance properties.
Paper VI111-02.6
PDF · Video · Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems (I)
Gusrialdi, Azwirman	Tampere University
Qu, Zhihua	University of Central Florida
Keywords: Distributed control and estimation, Learning for control Abstract: The paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.
Paper VI111-02.7
PDF · Video · Minimax Adaptive Control for State Matrix with Unknown Sign (I)
Rantzer, Anders	Lund Univ
Keywords: Learning for control Abstract: For linear time-invariant systems having a state matrix with uncertain sign, we formulate and solve a minimax adaptive control problem as a zero sum dynamic game. Explicit expressions for the optimal value function and the optimal control law are given in terms of a Riccati equation. The optimal control law is adaptive in the sense that past data is used to estimate the uncertain sign for prediction of future dynamics. Once the sign has been estimated, the controller behaves like standard H-infinity optimal state feedback.
Paper VI111-02.8
PDF · Video · Inferring Individual Network Edges - with Application to Target Identification in Gene Networks (I)
Wang, Yu	KTH Royal Institute of Technology
Jacobsen, Elling	KTH Royal Institute of Technology
Keywords: Dynamic Networks Abstract: The paper considers the problem of inferring individual network edges from time-series data. This is the problem faced in target identification, but also important in cases where it is of interest to learn whether two specific network nodes interact directly as well as in cases where there is insufficient information to infer the full network. The proposed inference method is based on taking a geometric perspective on a corresponding regression problem. We show that, by considering the span of individual node response vectors in sample space, it is possible to identify a given edge with a label of confidence even if the available data are not informative to infer other parts of the network. Furthermore, the method points to what further experiments are needed to infer edges for which the available response data are not sufficiently informative. We demonstrate the results on a target identification problem of a nonlinear 20-gene network and show that targets can be identified independently from a single time-series experiment using significantly fewer samples than the number of nodes in the network.
Paper VI111-02.9
PDF · Video · Data-Driven Verification under Signal Temporal Logic Constraints (I)
Salamati, Ali	Ludwig Maximilian University of Munich
Soudjani, Sadegh	Newcastle University
Zamani, Majid	University of Colorado Boulder
Keywords: Bayesian methods, Experiment design, Grey box modelling Abstract: We consider systems under uncertainty whose dynamics are partially unknown. Our aim is to study satisfaction of temporal properties by trajectories of such systems. We express these properties as signal temporal logic formulas and check if the probability of satisfying the property is at least a given threshold. Since the dynamics are parameterized and partially unknown, we collect data from the system and employ Bayesian inference techniques to associate a confidence value to the satisfaction of the property. The main novelty of our approach is to combine both data-driven and model-based techniques in order to have a two-layer probabilistic reasoning over the behavior of the system: one layer is related to the stochastic noise inside the system and the next layer is related to the noisy data collected from the system. We provide approximate algorithms for computing the confidence for linear dynamical systems.
Paper VI111-02.10
PDF · Video · Learning Sparse Linear Dynamic Networks in a Hyper-Parameter Free Setting (I)
Venkitaraman, Arun	KTH Royal Institute of Technology
Hjalmarsson, Håkan	KTH
Wahlberg, Bo	KTH Royal Institute of Technology
Keywords: Dynamic Networks Abstract: We address the issue of estimating the topology and dynamics of sparse linear dynamic networks in a hyperparameter-free setting. We propose a method to estimate the network dynamics in a computationally efficient and parameter tuning-free iterative framework known as SPICE (Sparse Iterative Covariance Estimation). Our approach does not assume that the network is undirected and is applicable even with varying noise levels across the modules of the network. We also do not assume any explicit prior knowledge on the network dynamics. Numerical experiments with realistic dynamic networks illustrate the usefulness of our method.
Paper VI111-02.11
PDF · Video · A Motif-Based Approach to Processes on Networks: Process Motifs for the Differential Entropy of the Ornstein-Uhlenbeck Process (I)
Schwarze, Alice	University of Washington
Wray, Jonny	E-Therapeutics
Porter, Mason A.	University of California Los Angeles
Keywords: Dynamic Networks, Time series modelling, Closed loop identification Abstract: A challenge in neuroscience and many other fields of research is the inference of a network's structure from observations of dynamics on the network. Understanding the relationship between network structure and dynamics on a network can help improve methods for network inference. We consider ``process motifs'' on a network as building blocks of processes on networks and propose to distinguish process motifs and graphlets as two different types of network motifs. We demonstrate that the analysis of process motifs can yield insights into the mechanisms by which processes and network structure contribute to differential entropy and other information-based properties of stochastic processes on networks, and we discuss the relationship between process motifs and graphlets.

VI111-03
Data-Driven Process Monitoring and Control for Complex Industrial Systems	Open Invited Session
Chair: Shardt, Yuri A.W.	Technical University of Ilmenau
Co-Chair: Yang, Xu	University of Science and Technology Beijing
Organizer: Shardt, Yuri A.W.	Technical University of Ilmenau
Organizer: Brooks, Kevin	BluESP
Organizer: Yang, Xu	University of Science and Technology Beijing
Organizer: Torgashov, Andrei	Institute for Automation and Control Processes FEB RAS
Paper VI111-03.1
PDF · Video · Soft Sensor Design for Restricted Variable Sampling Time (I)
Griesing-Scheiwe, Fritjof	TU Chemnitz
Shardt, Yuri A.W.	Technical University of Ilmenau
Pérez Zuñiga, Gustavo	Pontifical Catholic University of Peru
Yang, Xu	University of Science and Technology Beijing
Keywords: Frequency domain identification, Subspace methods, Closed loop identification Abstract: Difficult-to-obtain variables in industrial applications have led to the rise of soft sensors, which use prior system information and measurements to estimate these difficult-to-obtain variables. In real systems, the measurements that need to be estimated by a soft sensor are often infrequently measured or delayed. Sometimes, these delays and sampling time are variable in time. Though there are papers considering soft sensors in the presence of time delays and different sampling times, the variation of those parameters has not been considered when evaluating the adequacy of the soft sensors. Therefore, this paper will evaluate the impact of such variations for a data-driven soft sensor and propose modifications of the soft sensor that increase its robustness. The reliability of its estimate will be shown using the Bauer-Premaratne-Durán Theorem. Furthermore, the soft sensor will be simulated applying it to a continuous stirred tank reactor. Simulation showed that the modified soft sensor gives good estimates, whereas the traditional soft sensor gives an unstable estimate.
Paper VI111-03.2
PDF · Video · Sensor Fault Detection for Salient PMSM Based on Parity-Space Residual Generation and Robust Exact Differentiation (I)
Jahn, Benjamin	Nidec driveXpert GmbH / TU Ilmenau
Brückner, Michael	Nidec driveXpert GmbH
Gerber, Stanislav	Nidec driveXpert GmbH
Shardt, Yuri A.W.	Technical University of Ilmenau
Keywords: Fault detection and diagnosis, Nonlinear system identification, Filtering and smoothing Abstract: An online model-based fault detection and isolation method for salient permanent magnet synchronous motors is proposed using the parity-space approach. Given the polynomial model equations, Buchberger’s algorithm is used to eliminate the unknown variables (e.g. states, unmeasured inputs) resulting in analytic redundancy relations for residual generation. Furthermore, in order to obtain the derivatives of measured signals needed by such a residual generator, robust exact differentiators are used. The fault detection and isolation method is demonstrated using simulation of various fault scenarios for a speed controlled salient motor showing the effectiveness of the presented approach.
Paper VI111-03.3
PDF · Video · Mechatronics Applications of Condition Monitoring Using a Statistical Change Detection Method (I)
Mazzoleni, Mirko	University of Bergamo
Scandella, Matteo	University of Bergamo
Maurelli, Luca	University of Bergamo
Previdi, Fabio	Universita' Degli Studi Di Bergamo
Keywords: Fault detection and diagnosis, Nonparametric methods, Machine learning Abstract: In this paper, we propose the use of a change detection method to perform condition monitoring of mechanical components. The aim is to look for statistical changes in the distribution of features extracted from raw measurements, such as Root Mean Square or Crest Factor indicators. The proposed method works in a batch fashion, comparing data from one experiment to another. When these distributions differ by a specified amount, a degradation score is increased. The approach is tested on three experimental industrial applications: (i) an Electro-Mechanical Actuator (EMA) employed in flight applications, where the focus of the monitoring is on the ballscrew transmission; (ii) a CNC workbench, where the focus is on the vertical axe bearing, (iii) an industrial EMA with focus on the ballscrew bearing. All components undergone a severe experimental degradation process, that ultimately led to their failure. Results show how the proposed method is able to assess components degradation prior to their failure.
Paper VI111-03.4
PDF · Video · Data-Driven Model Predictive Monitoring for Dynamic Processes (I)
Jiang, Qingchao	East China University of Science and Technology
Yi, Huaikuan	East China University of Science and Technology
Yan, Xuefeng	Key Laboratory of Advanced Control and Optimization ForChemical
Zhang, Xinmin	Kyoto University
Huang, Jian	University of Science and Technology Beijing
Keywords: Fault detection and diagnosis Abstract: Process monitoring plays an important role in maintaining favorable process operation conditions and is gaining increasing attention in both academic community and industrial applications. This paper proposes a data-driven model predictive fault detection method to achieve efficient monitoring of dynamic processes. First, a measurement sample is projected into a dominant latent variable subspace that captures main variance of the process data and a residual subspace. Then the dominant latent variable subspace is further decomposed as a dynamic feature subspace and a static feature subspace. A fault detection residual is generated in each subspace, and corresponding monitoring statistic is established. By using the model predictive monitoring scheme, not only the status of a process but also the type of a detected fault, namely a dynamic feature fault or a static feature fault, can be identified. Effectiveness of the proposed data-driven model predictive monitoring scheme is tested on a lab-scale distillation process.
Paper VI111-03.5
PDF · Video · Data Quality Assessment for System Identification in the Age of Big Data and Industry 4.0 (I)
Shardt, Yuri A.W.	Technical University of Ilmenau
Yang, Xu	University of Science and Technology Beijing
Brooks, Kevin	BluESP
Torgashov, Andrei	Institute for Automation and Control Processes FEB RAS
Keywords: Frequency domain identification, Identifiability, Closed loop identification Abstract: As the amount of data stored from industrial processes increases with the demands of Industry 4.0, there is an increasing interest in finding uses for the stored data. However, before the data can be used its quality must be determined and appropriate regions extracted. Initially, such testing was done manually using graphs or basic rules, such as the value of a variable. With large data sets, such an approach will not work, since the amount of data to tested and the number of potential rules is too large. Therefore, there is a need for automated segmentation of the data set into different components. Such an approach has recently been proposed and tested using various types of industrial data. Although the industrial results are promising, there still remain many unanswered questions including how to handle a priori knowledge, over- or undersegmentation of the data set, and setting the appropriate thresholds for a given application. Solving these problems will provide a robust and reliable method for determining the data quality of a given data set.
Paper VI111-03.6
PDF · Video · An Optimal Distributed Fault Detection Scheme for Large-Scale Systems with Deterministic Disturbances (I)
Zhang, Jiarui	University of Duisburg-Essen
Li, Linlin	University of Duisburg Essen
Keywords: Fault detection and diagnosis, Distributed control and estimation Abstract: The main objective of this paper is to develop an optimal distributed fault detection (FD) approach for large-scale systems in the presence of unknown deterministic disturbances using the measurement of sensor networks. To be specific, the design approach consists of two phases: the distributed offline training phase and the online implementation phase. The offline training phase includes distributed iterative learning and average consensus algorithm. It is worth mentioning that, the distributed approach avoids enormous computational costs and complex information exchanges. Finally, a numerical example is illustrated to show that the distributed approach can successfully and efficiently accomplish the FD task.
Paper VI111-03.7
PDF · Video · Multimode Process Monitoring and Fault Diagnosis Based on Tensor Decomposition (I)
Zhao, Shanshan	University of Science and Technology Beijing
Zhang, Kai	University of Duisburg-Essen
Peng, Kaixiang	Univ of Science and Technology, Beijing, China
Zhang, Chuanfang	University of Science and Technology Beijing
Yang, Xu	University of Science and Technology Beijing
Keywords: Fault detection and diagnosis, Subspace methods Abstract: Nowadays, many industrial processes generate large amounts of multimode data,which generally have a natural tensor structure, causing some faults invisible with traditional process monitoring (PM) and fault diagnosis (FD) methods. Tensor decomposition (TD) is a more practical approach for its effectiveness in solving high dimensionality problems as well as indicating the links between different modes. This paper proposes a common and individual feature extraction method based on TD, which identifies and separates the common and individual features from multimode data. The newly proposed approach is applied to a typical multimode hot strip mill process (HSMP), where common and individual feature for all steel products are existing. The final results indicate that the proposed approach can accurately detect and identify different faults in the HSMP.
Paper VI111-03.8
PDF · Video · A Study of Complex Industrial Systems Based on Revised Kernel Principal Component Regression Method (I)
Chengyuan, Sun	Northeastern University
Ma, HongJun	Northeastern University
Keywords: Fault detection and diagnosis, Nonlinear system identification, Identification for control Abstract: As a data-driven process monitoring method, multivariable statistics techniques have special potentials and advantages to handle the increasingly prominent "Big data challenge" in the complex industrial systems. However, the standard partial least square (PLS) method and the principal component regression (PCR) method cannot maintain stable function in the nonlinear operating environment. In order to capture the precise relation of process variables and product variables, an approach called the revised kernel PCR (RKPCR) method is proposed in this thesis to resolve the problems encountered in the traditional PCR method. In addition, a brief and effective diagnosis logic is designed to decrease the difficulty of fault diagnosis. Finally, the effectiveness of the RKPCR algorithm is illustrated utilizing the Tennessee Eastman case (TEC) platform.
Paper VI111-03.9
PDF · Video · Data Selection Methods for Soft Sensor Design Based on Feature Extraction (I)
Caponetto, Riccardo	Univ of Catania
Graziani, Salvatore	University of Catania
Xibilia, M. Gabriella	Universita' Degli Studi Di Messina
Keywords: Nonlinear system identification, Machine learning Abstract: Data selection is a critical issue in data-driven soft sensor design. The paper proposes a new method for data selection based on a feature extraction step, followed by data selection algorithms. The method has been applied to an industrial case study, i.e., the estimation of the quality of processed wastewater produced by a Sour Water Stripping plant working in a refinery. The paper reports the results obtained with different data selection algorithms. The comparison has been performed both by using raw data and the feature extraction phase.
Paper VI111-03.10
PDF · Video · Fault Detection in Shipboard Integrated Electric Propulsion System with EEMD and XGBoost (I)
Liu, Sheng	Harbin Engineering University
Sun, Yue	Harbin Engineering University
Zhang, Lanyong	Harbin Engineering University
Keywords: Fault detection and diagnosis, Machine learning Abstract: In this paper, a fault detection method of shipboard medium-voltage DC (MVDC) integrated electric propulsion system (IEPS) based on Ensemble Empirical Mode Decomposition (EEMD) and XGBoost is proposed. Particle swarm optimization (PSO) is used to optimize the parameters to solve the problem that the standard deviation of auxiliary white noise in EEMD needs to be artificially selected. Firstly, the voltage signal on the DC bus is preprocessed by PSO-EEMD, which is decomposed into a set of Intrinsic Mode Functions (IMFs) according to the local characteristic time scale of the signal, and then the energy entropy is calculated as the fault feature vector. The fault feature vector is used to train and test the fault classifier based on XGBoost, and finally the fault detection is completed. The simplified model of shipboard MVDC IEPS is built in AppSIM Time Simulator. The faults on generator output and DC cable are used to verify the proposed fault detection method. Fault feature extraction method and fault classifier design are completed in Python. Verification by simulation platform and comparison with other intelligent detection methods, it is proved that proposed detection method can detect different faults quickly and accurately, is enabled for future practical use.
Paper VI111-03.11
PDF · Video · Feature Based Causality Analysis and Its Applications in Soft Sensor Modeling (I)
Yu, Feng	Tsinghua University
Cao, Liang	University of British Columbia
Li, Weiyang	Tsinghua University
Yang, Fan	Tsinghua University
Shang, Chao	Tsinghua University
Keywords: Time series modelling, Grey box modelling Abstract: In industrial processes, causality analysis plays an important role in fault detection and topology building. Aiming to attenuate the influence of common correlation and noise, a feature based causality analysis method is proposed. By using the orthogonality and de-noising in feature analysis, it can capture more efficient causal factors. Moreover, better causal factors can make better predictions. Soft sensors based on least-squares regression and two neural networks are tested to compare the performance when using different causal factors and not using causal factors. The results show that the causal feature based soft sensors obtain the best performance and causal factors are crucial to prediction performance. Hence, it has great application potential owing to its strong interpretability and good accuracy.
Paper VI111-03.12
PDF · Video · Optimal Estimation of Gasoline LP-EGR Via Unscented Kalman Filtering with Mixed Physics-based/Data-Driven Components Modeling (I)
Kim, Kwangmin	Seoul National University
Kim, Jinsung	Hyundai Motor Company
Kwon, Oheun	Hyundai Motor Company
Oh, Se-Kyu	Hyundai Motor Company
Kim, Yong-Wha	Hyundai Motor Company
Lee, Dongjun	Seoul National University
Keywords: Estimation and filtering, Machine learning, Mechanical and aerospace estimation Abstract: We propose a novel optimal estimation methodology for gasoline engine LP (low-pressure) EGR (exhaust gas recirculation) air-path system, which allows us to implement virtual sensors for oxygen mass fraction at the intake manifold and EGR mass flow rate at the LP-EGR valve, real sensors for them too expensive to deploy in production cars. We first decompose the LP-EGR air-path system into several sub-components; and opportunistically utilize physics-based modeling or data-driven modeling for each component depending on their model complexity. In particular, we apply the technique of MLP (multi-layer perceptron) as a means for data-driven modeling of LP-EGR/throttle valves and engine cylinder valve aspiration dynamics, all of which defy accurate physics-based modeling, that is also simple enough for real-time running. We further optimally combine these physics-based and data-driven modelings in the framework of UKF (unscented Kalman filtering), and also manifest via formal analysis that this mixed physics-based/data-driven modeling renders our estimator much faster to run as compared to the case of full data-driven MLP modeling. In doing so, we also extend the standard UKF theory to the more general case, where the system contains non-additive uncertainties both in the measurement and process models with cross-correlations and state-dependent variances, which stems from the inherent peculiar structure of our mixed physics-based/data-driven modeling approach, for the UKF formulation. Experiments are also performed to show the theory.
Paper VI111-03.13
PDF · Video · A Data-Driven Predictive Control Structure in the Behavioral Framework (I)
Wei, Lai	University of New South Wales
Yan, Yitao	University of New South Wales
Bao, Jie	The University of New South Wales
Keywords: Machine learning, Learning for control Abstract: This paper presents a data-driven predictive control (DPC) algorithm for linear time-invariant (LTI) systems in the behavioral framework. The system is described by the parametrization of the Hankel matrix constructed from its measured trajectories. The proposed structure follows a two-step procedure. The existence of a controlled behavior is firstly verified from the perspective of dissipativity with the aid of quadratic difference forms (QdFs), then the controlled trajectory is selected from the original uncontrolled behavior through optimization. An illustrative example is presented to demonstrate the effectiveness of the proposed approach.

VI111-04
Machine Learning for Monitoring and Control of Chemical and Biological Processes	Open Invited Session
Chair: Tulsyan, Aditya	Massachusetts Institute of Technology
Co-Chair: Lee, Jong Min	Seoul National University
Organizer: Gopaluni, Bhushan	University of British Columbia
Organizer: Tulsyan, Aditya	Massachusetts Institute of Technology
Organizer: Chachuat, Benoit	Imperial College London
Organizer: Chiang, Leo	The Dow Chemical Company
Organizer: Huang, Biao	Univ. of Alberta
Organizer: Lee, Jong Min	Seoul National University
Paper VI111-04.1
PDF · Video · Developing a Deep Learning Estimator to Learn Nonlinear Dynamic Systems (I)
Wang, Kai	Central South University
Chen, Junghui	Chung-Yuan Christian Univ
Wang, Yalin	Central South University
Keywords: Nonlinear system identification, Machine learning, Estimation and filtering Abstract: Process complexities are characterized by strong nonlinearities, dynamics and uncertainties. Modeling such a complex process requires a flexible model with deep layers describing the corresponding strong nonlinear dynamic behavior. The proposed model is constructed by deep neural networks to represent the process of state transition and observation generation, both of which together constitute a stochastic nonlinear state space model. This model is evolved from the variational auto-encoder learned by the stochastic expectation-maximization algorithm. To solve the complexity of posteriors for dynamic processes, the posterior distributions with respect to state variables are constructed by a forward-backward recurrent neural network. One example is given to validate that the proposed method outperforms the comparative methods in modeling complex nonlinearities.
Paper VI111-04.2
PDF · Video · Fault Detection for Geological Drilling Processes Using Multivariate Generalized Gaussian Distribution and Kullback Leibler Divergence (I)
Li, Yupeng	China University of Geoscience
Cao, Weihua	China University of Geosciences
Hu, Wenkai	China University of Geosciences
Gan, Chao	China University of Geosciences
Wu, Min	China University of Geosciences
Keywords: Fault detection and diagnosis, Machine learning, Time series modelling Abstract: The presence of downhole faults compromises the safety and also leads to increased maintenance costs in complex geological drilling processes. In order to achieve timely and accurate detection of downhole faults, a systematic fault detection method is proposed based on the Multivariate Generalized Gaussian Distribution (MGGD) and the Kullback Leibler Divergence (KLD). Uncorrelated components are obtained from the original drilling process signals using the principle component analysis; then, the distribution of components is estimated using the MGGD; afterwards, the KLD is calculated based on a deduced analytic formula; last, the downhole faut is detected by comparing the calculated KLD with the alarm threshold obtained from normal data. The effectiveness and practicality of the proposed method are demonstrated by application to a real drilling process.
Paper VI111-04.3
PDF · Video · Condition-Based Sensor-Health Monitoring and Maintenance in Biomanufacturing (I)
Tulsyan, Aditya	Massachusetts Institute of Technology
Garvin, Christopher	Amgen Inc
Undey, Cenk	Amgen Inc
Keywords: Machine learning, Fault detection and diagnosis Abstract: In the Biotechnology 4.0 paradigm, process analytical technology (PAT) tools are being increasingly deployed in biomanufacturing to gain improved process insights through extensive use of advanced and automated sensing techniques. Critical parameters, such as pH, dissolved oxygen (DO), temperature and metabolite concentrations, are routinely measured and controlled in a cell culture process. While these extensive networks of sensors generate critical process information and insights, they are also prone to failures and malfunctions. In this paper, we propose a condition-based maintenance (CbM) framework for real-time sensor-health management, with a focus on fault detection, diagnosis, and prognostics. To this effect, a slow-feature analysis (SFA)-based platform is proposed for the detection and diagnosis of sensor- health. For health prognostics, a Gaussian process (GP) model is proposed for forecasting the remaining useful life (RUL) of the sensor along with the probability of failure. The efficacy of the proposed sensor-heath management strategy is demonstrated in a biomanufacturing process.
Paper VI111-04.4
PDF · Video · A Hybrid Modeling Method Based on Neural Networks and Its Application to Microwave Filter Tuning (I)
Bi, Leyu	China University of Geosciences, Wuhan
Cao, Weihua	China University of Geosciences
Hu, Wenkai	China University of Geosciences
Yuan, Yan	China University of Geosciences
Wu, Min	China University of Geosciences
Keywords: Machine learning, Hybrid and switched systems modeling, Mechanical and aerospace estimation Abstract: In performance tuning of many electromechanical devices, well-trained operators are in great demand. However, manual tuning is costly and time-consuming, and thus do not conform to the trend of smart manufacturing. Microwave filters are typical electromechanical devices. Their tuning performance is limited by low extraction accuracy and high dimensionality of circuit features. In this paper, a hybrid modeling method based on neural networks is proposed to get better tuning performance. First, a curve-shape-based modeling method using Convolutional Neural Networks is presented to bypass the cumbersome extraction of circuit features. Second, an multi-model optimized fusion model based on Elman Neural Networks is constructed to cope with the high-dimensional property of circuit features, and further improve modeling accuracy. The effectiveness of the hybrid modeling method is demonstrated through experiments. It achieves better tuning performance with fewer samples compared with two single modeling methods.
Paper VI111-04.5
PDF · Video · Robust Interval Prediction Model Identification with a Posteriori Reliability Guarantee (I)
Wang, Chao	Tsinghua University
Shang, Chao	Tsinghua University
Yang, Fan	Tsinghua University
Huang, Dexian	Tsinghua University
Yu, Bin	Hengli Petrochemical Co., Ltd
Keywords: Stochastic system identification, Randomized methods, Nonlinear system identification Abstract: In classical paradigm of model identification, a single prediction value is returned as a point estimate of the output. Recently, the interval prediction model (IPM) has been receiving increasing attentions. Different from generic models, an IPM gives an interval of confidence as the prediction that covers the majority of training data while being as tight as possible. However, due to the randomness of sampling training data, the reliability of IPM constructed is uncertain. In this paper, we focus on a general class of IPMs where a fraction of data samples can be discarded to pursue robustness, and establish an appropriate a posteriori reliability guarantee. It relies on counting the "decisive" constraints associated with the optimal solution, and generally leads to reduced conservatism and better estimation performance than the existing performance bounds. Moreover, the guarantee holds irrespective of the data generation mechanism, which informs the decision maker of the prediction confidence in the absence of precise knowledge about data distribution. Its effectiveness is illustrated based on numerical examples.
Paper VI111-04.6
PDF · Video · Wave Propagation Patterns in Gas Pipelines for Fault Location (I)
Peralta, Jesús	Instituto De Ingeniería, UNAM
Verde, Cristina	Inst. De Ingenieria, UNAM
Delgado, Fermin	Universidad Nacional Autónoma De México
Keywords: Fault detection and diagnosis, Time series modelling, Frequency domain identification Abstract: Based on the reflectometry phenomenon and the behavior of an acoustic signal in a gas pipeline, this work proposes a fault location test for pipelines, which is formally justified for an infinite-dimension model of acoustic wave propagation in a closed conduit with viscous absorption. The test consists of disturbing the medium by an acoustic pulse at one extreme of the pipeline and of registering the transient response at an observation point. In this way, the waveform of the transient response of the pressure allows distinguishing the pattern of a healthy system from a pipeline with diverse faults and to allow locating the position of the damage.
Paper VI111-04.7
PDF · Video · Multirate Fusion of Data Sources with Different Quality (I)
Sansana, Joel	University of Coimbra
Rendall, Ricardo	Dow
Wang, Zhenyu	Tufts University
Chiang, Leo	The Dow Chemical Company
Seabra dos Reis, Marco P.	University of Coimbra
Keywords: Filtering and smoothing, Machine learning, Bayesian methods Abstract: The chemical process industry makes increasingly use of a diversity of data collectors, that should be properly integrated to build effective solutions for process monitoring, control and optimization. Concerning the assessment of products properties, one of the most common scenarios involve the collection of data from plant laboratories that provide more accurate measurements at lower rates, together with more frequent measurements or predictions of lower quality. Soft sensors and online analyzers are examples of viable alternatives for acquiring more frequent and updated information, although with a higher uncertainty. All of these data collectors have informative value and should be considered when it comes to estimate key product attributes. This is the goal of fusion methods, whose importance grows together with the increase in the number of sensors and data sources available. In this article, two fusion schemes that address prevailing characteristics of industrial data are proposed and compared: one version of the classic tracked Bayesian fusion scheme (TBF) and a novel modification of the track-to-track algorithm, designated as bias-corrected track-to-track fusion (BCTTF). The proposed methodologies are able to cope with the multirate nature of data and irregularly sampled measurements that present different uncertainty levels. An application to a real industrial case study shows that BCTTF presents better prediction performance, higher alarm identification sensitivity and leads to a smoother estimated signal.
Paper VI111-04.8
PDF · Video · Dynamic Weighted Canonical Correlation Analysis for Auto-Regressive Modeling (I)
Zhu, Qinqin	University of Waterloo
Liu, Qiang	Northeastern University
Qin, S. Joe	University of Southern California
Keywords: Fault detection and diagnosis, Machine learning, Time series modelling Abstract: Canonical correlation analysis (CCA) is widely used as a supervised learning method to extract correlations between process and quality datasets. When used to extract relations between current data and historical data, CCA can also be regarded as an auto-regressive modeling method to capture dynamics. Various dynamic CCA algorithms were developed in the literature. However, these algorithms do not consider strong dependence existing in adjacent samples, which may lead to unnecessarily large time lags and inaccurate estimation of current values from historical data. In this paper, a dynamic weighted CCA (DWCCA) algorithm is proposed to address this issue with a series of polynomial basis functions. DWCCA extracts dynamic relations by maximizing correlations between current data and a weighted representation of past data, and the weights rely only on a limited number of polynomial functions, which removes the negative effect caused by strongly collinear neighboring samples. After all the dynamics are exploited, static principal component analysis is then employed to further explore the cross-correlations in the dataset. The Tennessee Eastman process is utilized to demonstrate the effectiveness of the proposed DWCCA method in terms of prediction efficiency and collinearity handling.
Paper VI111-04.9
PDF · Video · Assessing Observability Using Supervised Autoencoders with Application to Tennessee Eastman Process (I)
Agarwal, Piyush	University of Waterloo
Tamer, Melih	Sanofi Pasteur
Budman, Hector M.	Univ. of Waterloo
Keywords: Machine learning, Fault detection and diagnosis, Identifiability Abstract: This work presents a novel approach to calculate classification observability using a supervised autoencoder (SAE) neural network (NN) for classification. This metric is based on a minimal distance between every two classes in the latent space defined by the hidden layers of the auto-encoder. Quantification of classification observability is required to address whether the available sensors in a process are sufficient to observe certain outputs (phenomenon) and which additional measurements are to be included in the dataset to improve classification accuracy. The efficacy of the proposed method is illustrated through case-studies for the Tennessee Eastman Benchmark Process.
Paper VI111-04.10
PDF · Video · Study on a Sub-Databases-Driven (S-DD) Controller Using K-Means Clustering (I)
Wakitani, Shin	Hiroshima University
Nakanishi, Hiroki	Hiroshima University
Yamamoto, Toru	Hiroshima Univ
Keywords: Machine learning, Learning for control, Adaptive gain scheduling autotuning control and switching control Abstract: A database-driven PID (DD-PID) control method is one of the effective control methods for nonlinear systems. In the conventional DD-PID control method, there is a problem that the calculation cost and required memory for creating an optimal database are large. For the above problem, this paper proposes a method to implement the DD-PID controller with small-sized sub-databases. In the proposed method, one database that includes past I/O data and PID gains are created, and the database is updated in an offline manner. Moreover, sub-databases are constructed by clustering the created database using the k-means clustering method. The number of clusters for k-means clustering is determined automatically based on kernel functions. The effectiveness of the proposed method is presented by numerical examples.
Paper VI111-04.11
PDF · Video · Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey (I)
Gopaluni, Bhushan	University of British Columbia
Tulsyan, Aditya	Massachusetts Institute of Technology
Chachuat, Benoit	Imperial College London
Huang, Biao	Univ. of Alberta
Lee, Jong Min	Seoul National University
Amjad, Faraz	University of Alberta
Damarla, Seshu	University of Alberta
Kim, Jong Woo	Seoul National University
Lawrence, Nathan P.	University of British Columbia
Keywords: Machine learning, Consensus and Reinforcement learning control Abstract: Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.
Paper VI111-04.12
PDF · Video · Reinforcement Learning Based Design of Linear Fixed Structure Controllers (I)
Lawrence, Nathan P.	University of British Columbia
Stewart, Greg E.	Honeywell Automation & Control Sol
Loewen, Philip D.	Univ. of British Columbia
Forbes, Michael Gregory	Honeywell
Backstrom, Johan	Honeywell
Gopaluni, Bhushan	University of British Columbia
Keywords: Learning for control, Randomized methods, Model reference adaptive control Abstract: Reinforcement Learning has been successfully applied to the problem of tuning PID controllers in several applications. The existing methods often utilize function approximation, such as neural networks, to update the controller parameters at each time-step of the underlying process. In this work, we present a simple finite-difference approach, based on random search, to tuning linear fixed-structure controllers. For clarity and simplicity, we focus on PID controllers. Our algorithm operates on the entire closed-loop step-response of the system and iteratively improves the PID gains towards a desired closed-loop response. This allows for prescribing stability requirements into the reward function without any modeling procedures.
Paper VI111-04.13
PDF · Video · Optimal PID and Antiwindup Control Design As a Reinforcement Learning Problem (I)
Lawrence, Nathan P.	University of British Columbia
Stewart, Greg E.	Honeywell Automation & Control Sol
Loewen, Philip D.	Univ. of British Columbia
Forbes, Michael Gregory	Honeywell
Backstrom, Johan	Honeywell
Gopaluni, Bhushan	University of British Columbia
Keywords: Learning for control, Consensus and Reinforcement learning control, Nonlinear adaptive control Abstract: Deep reinforcement learning (DRL) has seen several successful applications to process control. Common methods rely on a deep neural network structure to model the controller or process. With increasingly complicated control structures, the closed-loop stability of such methods becomes less clear. In this work, we focus on the interpretability of DRL control methods. In particular, we view linear fixed-structure controllers as shallow neural networks embedded in the actor-critic framework. PID controllers guide our development due to their simplicity and acceptance in industrial practice. We then consider input saturation, leading to a simple nonlinear control structure. In order to effectively operate within the actuator limits we then incorporate a tuning parameter for anti-windup compensation. Finally, the simplicity of the controller allows for straightforward initialization. This makes our method inherently stabilizing, both during and after training, and amenable to known operational PID gains.

VI111-05
Modelling, Identification and Control of Quantum Systems	Open Invited Session
Chair: Dong, Daoyi	University of New South Wales
Co-Chair: Wu, Re-bing	Department of Automation, Tsinghua University,
Organizer: Dong, Daoyi	University of New South Wales
Organizer: Li, Jr-Shin	Washington University in St. Louis
Organizer: Wu, Re-bing	Department of Automation, Tsinghua University,
Paper VI111-05.1
PDF · Video · Robust Control Optimization for Quantum Approximate Optimization Algorithms (I)
Dong, Yulong	University of California, Berkeley
Meng, Xiang	University of California, Berkeley
Lin, Lin	University of California, Berkeley
Kosut, Robert	SC Solutions
Whaley, K. Birgitta	UC Berkeley
Keywords: Dynamic Networks Abstract: Quantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation.
Paper VI111-05.2
PDF · Video · Quantum Adiabatic Elimination at Arbitrary Order for Photon Number Measurement (I)
Sarlette, Alain	INRIA
Rouchon, Pierre	Mines-ParisTech, PSL Research University
Essig, Antoine	ENS Lyon
Ficheux, Quentin	University of Maryland
Huard, Benjamin	ENS Lyon
Keywords: Subspace methods Abstract: Adiabatic elimination is a perturbative model reduction technique based on timescale separation and often used to simplify the description of composite quantum systems. We here analyze a quantum experiment where the perturbative expansion can be carried out to arbitrary order, such that: (i) we can formulate in the end an exact reduced model in quantum form; (ii) as the series provides accuracy for ever larger parameter values, we can discard any condition on the timescale separation, thereby analyzing the intermediate regime where the actual experiment is performing best; (iii) we can clarify the role of some gauge degrees of freedom in this model reduction technique.
Paper VI111-05.3
PDF · Video · Optimal Quantum Realization of a Classical Linear System (I)
Thien, Rebbecca	Australian National University
Vuglar, Shanon	Princeton University
Petersen, Ian R	The Australian National University
Keywords: Continuous time system estimation, Identification for control, Dynamic Networks Abstract: Additional noise in a quantum system can be detrimental to the performance of a quantum coherent feedback control system. This paper proposes a Linear Matrix Inequality (LMI) approach to construct an optimal quantum realization of a given Linear Time-Invariant (LTI) system. The quantum realization problem is useful in designing coherent quantum feedback controllers. An optimal method is proposed for solving this problem in terms of a finite horizon quadratic performance index, which is related to the amount of quantum noise appearing at the system's output. This cost function provides a measure of how much the additional quantum noise in the coherent controller will alter the feedback control system.
Paper VI111-05.4
PDF · Video · Capability Comparison of Quantum Sensors of Single or Two Qubits for a Spin Chain System (I)
Yu, Qi	UNSW (The University of New South Wales)
Dong, Daoyi	University of New South Wales
Wang, Yuanlong	University of New South Wales, Canberra
Petersen, Ian R	The Australian National University
Keywords: Identifiability Abstract: Quantum sensing, utilizing quantum techniques to extract key information of a quantum (or classical) system, is a fundamental area in quantum science and technology. For quantum sensors, a basic capability is to uniquely infer unknown parameters in a system based on measurement data from the sensors. In this paper, we investigate the capability of a class of quantum sensors for a spin-1/2 chain system with unknown parameters. The sensors are composed of qubits which are coupled to the object system and can be initialized and measured. We consider the capability of the single- and two-qubit sensors and show that the capability of single-qubit quantum sensors can be enhanced by adding an extra qubit into the sensor under a certain initialization and measurement setting.
Paper VI111-05.5
PDF · Video · Coherent H-Infinity Control for Markovian Jump Linear Quantum Systems (I)
Liu, Yanan	University of New South Wales
Dong, Daoyi	University of New South Wales
Petersen, Ian R	The Australian National University
Gao, Qing	Beihang University
Ding, Steven X.	Univ of Duisburg-Essen
Yonezawa, Hidehiro	University of New South Wales
Keywords: Fault detection and diagnosis Abstract: The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H-infinity control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H-infinity controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).
Paper VI111-05.6
PDF · Video · Measurement-Induced Boolean Dynamics from Closed Quantum Networks (I)
Qi, Hongsheng	Chinese Academy of Sciences
Mu, Biqiang	AMSS, CAS
Petersen, Ian R	The Australian National University
Shi, Guodong	The Australian National University/The University of Sydney
Keywords: Stochastic hybrid systems Abstract: In this paper, we study the induced probabilistic Boolean dynamics for dynamical quantum networks subject to sequential quantum measurements. In this part of the paper, we focus on closed networks of quits whose states evolve according to a Schr"odinger equation. Sequential measurements may act on the entire network, or only on a subset of qubits. First of all, we show that this type of hybrid quantum dynamics induces probabilistic Boolean recursions as a Markov chain representing the measurement outcomes. Particularly, we establish an explicit and algebraic representation of the underlying recursive random mapping driving such induced Markov chains. Next, with local measurements, we establish a recursive way of computing such non-Markovian probability transitions.
Paper VI111-05.7
PDF · Video · Measurement-Induced Boolean Dynamics from Open Quantum Networks (I)
Qi, Hongsheng	Chinese Academy of Sciences
Mu, Biqiang	AMSS, CAS
Petersen, Ian R	The Australian National University
Shi, Guodong	The Australian National University/The University of Sydney
Keywords: Stochastic hybrid systems Abstract: In this paper, we study the induced probabilistic Boolean dynamics for dynamical quantum networks subject to sequential quantum measurements. In this part of the paper, we focus on closed networks of quits whose states evolutions are described by a continuous Lindblad master equation. When measurements are performed sequentially along such continuous dynamics, the quantum network states undergo random jumps and the corresponding measurement outcomes can be described by a probabilistic Boolean network. First of all, we show that the state transition of the induced Boolean networks can be explicitly represented through realification of the master equation. Next, when the open quantum dynamics is relaxing in the sense that it possesses a unique equilibrium as a global attractor, structural properties including absorbing states, reducibility, and periodicity for the induced Boolean network are direct consequences of the relaxing property. Finally, we show that for quantum consensus networks as a type of non-relaxing open quantum network dynamics, the communication classes of the measurement-induced Boolean networks are encoded in the quantum Laplacian of the underlying interaction graph.
Paper VI111-05.8
PDF · Video · Positive Real Properties and Physical Realizability Conditions for a Class of Linear Quantum Systems (I)
Maalouf, Aline	The Australian National University
Petersen, Ian R	The Australian National University
Keywords: Estimation and filtering Abstract: Theoretical developments in the field of quantum optics and quantum superconducting electrical circuits involving continuous measurement based feedback control as well as coherent control are an important prerequisites for advances in the domain of quantum technology. Within these perspectives, this paper considers positive real properties for a class of quantum systems whose quantum stochastic differential equation model involves annihilation operators only and then relates them to corresponding bounded real properties and consequently to physical realizability conditions developed earlier by the authors. Based on the positive real properties of these quantum systems, it is anticipated that it is possible to use the Brune algorithm in order to find an electrical circuit that can physically implement these quantum systems. This theory, in the case of one-port circuits, may be useful for the implementation of microwave circuits related to quantum filters found in the field of quantum computing.
Paper VI111-05.9
PDF · Video · One Port Impedance Quantization for a Class of Annihilation Operator Linear Quantum Systems (I)
Maalouf, Aline	The Australian National University
Petersen, Ian R	The Australian National University
Keywords: Estimation and filtering;Quantized systems Abstract: This paper provides a procedure for building a one port impedance quantization involving annihilation operators only for a class of linear quantum systems having a positive real impedance transfer function matrix. Based on the positive real properties of these quantum systems, it is shown that it is possible to use the Brune algorithm in order to find an electrical circuit that can physically implement these quantum systems. This theory, illustrated for one port circuits may be useful for the implementation of superconducting microwave circuits used in quantum filters found in the field of quantum computing.
Paper VI111-05.10
PDF · Video · Frequency-Domain Computation of Quadratic-Exponential Cost Functionals for Linear Quantum Stochastic Systems (I)
Vladimirov, Igor	Australian National University
Petersen, Ian R	The Australian National University
James, Matthew R.	Australian National Univ
Keywords: Stochastic control and game theory, Synthesis of stochastic systems Abstract: This paper is concerned with quadratic-exponential functionals (QEFs) as risk-sensitive performance criteria for linear quantum stochastic systems driven by multichannel bosonic fields. Such costs impose an exponential penalty on quadratic functions of the quantum system variables over a bounded time interval, and their minimization secures a number of robustness properties for the system. We use an integral operator representation of the QEF, obtained recently, in order to compute its infinite-horizon asymptotic growth rate in the invariant Gaussian state when the stable system is driven by vacuum input fields. The resulting frequency-domain formula expresses the QEF growth rate in terms of two spectral functions associated with the real and imaginary parts of the quantum covariance kernel of the system variables. We also discuss the computation of the QEF growth rate using homotopy and contour integration techniques and provide an illustrative numerical example with a two-mode open quantum harmonic oscillator.
Paper VI111-05.11
PDF · Video · The Dynamical Model of Flying-Qubit Control Systems (I)
Li, Wenlong	Tsinghua University
Zhang, Guofeng	The Hong Kong Polytechnic University
Wu, Re-bing	Department of Automation, Tsinghua University,
Keywords: Stochastic control and game theory Abstract: The control of flying qubits is crucial for the nterconnection of quantum information processing units in the future applications. Physically, this class of problems can be modeled by the radiation of opticalelds from a standing qubit (natural or artificial atoms). The photon statistics of the output field emitted from a quantum system coupled to multiple waveguides is complicated when the exciton number is not conserved, especially in presence of coherent driving that is crucial for control and optimization. In this paper, we use quantum stochastic differential equation (QSDE) todescribe the photon generation process, and derive the dynamical jumps induced by photon emission. Numerical simulations show that this model can be applied to analyze the manipulation process of single qubits.
Paper VI111-05.12
PDF · Video · Measurement-Based Feedback Control of Linear Quantum Stochastic Systems with Quadratic-Exponential Criteria (I)
Vladimirov, Igor	Australian National University
James, Matthew R.	Australian National Univ
Petersen, Ian R	The Australian National University
Keywords: Synthesis of stochastic systems, Stochastic control and game theory Abstract: This paper is concerned with a risk-sensitive optimal control problem for a feedback connection of a quantum plant with a measurement-based classical controller. The plant is a multimode open quantum harmonic oscillator driven by a multichannel quantum Wiener process, and the controller is a linear time invariant system governed by a stochastic differential equation. The control objective is to stabilize the closed-loop system and minimize the infinite-horizon asymptotic growth rate of a quadratic-exponential functional (QEF) which penalizes the plant variables and the controller output. We combine a frequency-domain representation of the QEF growth rate, obtained recently, with variational techniques and establish first-order necessary conditions of optimality for the state-space matrices of the controller.

VI111-06
Results on Nonlinear System Identification Benchmarks	Open Invited Session
Chair: Schoukens, Maarten	Eindhoven University of Technology
Co-Chair: Noël, Jean-Philippe	Eindhoven University of Technology
Organizer: Schoukens, Maarten	Eindhoven University of Technology
Organizer: Noël, Jean-Philippe	Eindhoven University of Technology
Paper VI111-06.1
PDF · Video · On the Initialization of Nonlinear LFR Model Identification with the Best Linear Approximation (I)
Schoukens, Maarten	Eindhoven University of Technology
Tóth, Roland	Eindhoven University of Technology
Keywords: Nonlinear system identification Abstract: Balancing the model complexity and the representation capability towards the process to be captured remains one of the main challenges in nonlinear system identification. One possibility to reduce model complexity is to impose structure on the model representation. To this end, this work considers the linear fractional representation framework. In a linear fractional representation the linear dynamics and the system nonlinearities are modeled by two separate blocks that are interconnected with one another. This results in a structured, yet flexible model structure. Estimating such a model directly from input-output data is not a trivial task as the involved optimization is nonlinear in nature. This paper proposes an initialization scheme for the model parameters based on the best linear approximation of the system and shows that this approach results in high quality models on a set of benchmark data sets.
Paper VI111-06.2
PDF · Video · A Novel Multiplicative Polynomial Kernel for Volterra Series Identification (I)
Dalla Libera, Alberto	Università Degli Studi Di Padova
Carli, Ruggero	Univ of Padova
Pillonetto, Gianluigi	Univ of Padova
Keywords: Nonparametric methods, Nonlinear system identification, Time series modelling Abstract: Volterra series is especially useful for nonlinear system identification, also thanks to is capability to approximate a broad range of input-output maps. However, its identification from a finite set of data is hard, due to the curse of dimensionality. Recent approaches have shown how regularization strategies can be useful for this task. In this paper, we propose a new regularization network for Volterra models identification. It relies on a new kernel given by the product of basic building blocks. Each block contains some unknown parameters that can be estimated from data using marginal likelihood optimization or cross-validation. In comparison with other algorithms proposed in the literature, numerical experiments show that our approach allows to better select the monomials that really influence the system output, much increasing the prediction capability of the model. The method immediately extends also to polynomial NARMAX models.
Paper VI111-06.3
PDF · Video · Data-Driven Modelling of the Nonlinear Cortical Responses Evoked by Continuous Mechanical Perturbations (I)
Nozari, Hasan Abbasi	Faculty of Electrical and Computer Engineering, Babol Noshirvani
Rahmani, Zahra	Babol Noshirvani University of Technology
Castaldi, Paolo	University of Bologna
Simani, Silvio	University of Ferrara
Sadati, Jalil	Faculty of Electrical and Computer Engineering, Babol Noshirvani
Keywords: Nonlinear system identification, Identification for control, Frequency domain identification Abstract: Cortical responses to external mechanical stimuli recorded by electroencephalography have demonstrated complex nonlinearity with fast dynamics. Hence, the modelling of the human nervous system plays a crucial role in studying the function of the sensorimotor system and can help in disentangling the sensory-motor abnormalities in functional movement disorders. In this paper, a non-parametric model is proposed based on locally-linear neuro-fuzzy structures trained by an evolutive algorithm named local linear model tree. In particular, a simulation model as well as a multi-step predictor model is considered to describe the nonlinear dynamics governing the cortical response. The proposed modelling method is applied to an experimental dataset, where brain activities from ten young healthy subjects are recorded by electroencephalography signals while robotic manipulations were applied to their wrist joint. The obtained results are satisfactory and are also compared to those achieved with different modelling strategies applied to the same benchmark.
Paper VI111-06.4
PDF · Video · Initialization Approach for Decoupling Polynomial NARX Model Using Tensor Decomposition (I)
Karami, Kiana	University of Calgary
Westwick, David	University of Calgary
Keywords: Nonlinear system identification Abstract: The Nonlinear Auto-regressive eXogenous input (NARX) model has been widely used in nonlinear system identification. It's chief disadvantages are that it is a black-box model that suffers from the curse of dimensionality, in that the number of parameters increases rapidly with the nonlinearity degree. One approach to dealing with these problems involves decoupling the nonlinearity, but this requires solving a non-convex optimization problem. Solving non-convex optimization problems has always been challenging due to the possibility of getting trapped in a sub-optimal local optima. As a result, these kinds of optimization problems are sensitive to the initial solution. Providing an appropriate initial solution can increase the likelihood of finding the globally optimal solution. In this paper, an initialization technique that uses the polynomial coefficients in a full, albeit low order, NARX model is proposed. This technique generates a tensor from the coefficients in the from full polynomial NARX model and applies a tensor factorization in order to generate an appropriate starting point for decoupled polynomial NARX model optimization problem. The proposed technique is applied to nonlinear benchmark problem and the results are promising.
Paper VI111-06.5
PDF · Video · Tuning Nonlinear State-Space Models Using Unconstrained Multiple Shooting (I)
Decuyper, Jan	Vrije Universiteit Brussel
Runacres, Mark C	Vrije Universiteit Brussel
Schoukens, Johan	Vrije Universiteit Brussel
Tiels, Koen	Eindhoven University of Technology
Keywords: Nonlinear system identification Abstract: A persisting challenge in nonlinear dynamical modelling is parameter inference from data. Provided that an appropriate model structure was selected, the identification problem is profoundly affected by a choice of initialisation. A particular challenge that may arise is initialisation within a region of the parameter space where the model is not contractive. Exploring such regions is not feasible using the conventional optimisation tools for they require a bounded evaluation of the cost. This work proposes an unconstrained multiple shooting technique, able to mitigate stability issues during the optimisation of nonlinear state-space models. The technique is illustrated on simulation results of a Van der Pol oscillator and benchmark results on a Bouc-Wen hysteretic system.

VI111-07
Application of System Identification	Regular Session
Chair: Jampana, Phanindra	Indian Institute of Technology Hyderabad
Co-Chair: Petlenkov, Eduard	Tallinn University of Technology
Paper VI111-07.1
PDF · Video · Assessment Criteria for the Mechanical Loads of Wind Turbines Applied to the Example of Active Power Control (I)
Clemens, Christian	University of Applied Sciences Berlin (HTW), Department of Engin
Gauterin, Eckhard	HTW Berlin
Pöschke, Florian	University of Applied Sciences Berlin (HTW), Control Engineering
Schulte, Horst	HTW Berlin
Keywords: Experiment design Abstract: Assessment criteria for design of wind turbines controller are discussed since conventional control performance criteria are not sufficient to evaluate the mechanical loads as dependency of the controller type and settings. This will be presented and discussed using the example of the active power control of wind turbines. In contrast to the nominal operation of wind turbines divided into power optimization in the partial and power limitation in the full load region, the power output is guided by an external power reference signal. The reference signal may be delivered either directly by higher-level load frequency controller of the power system or by the wind farm controller. In both cases the external variation of the power to be delivered has an enormous influence on the dynamics and mechanical loads of the wind turbine. To quantify these loads that occur during power tracking operation the Damage Equivalent Load amplitude as appropriated load assessment criteria is described and prepared for control design.
Paper VI111-07.2
PDF · Video · Simulation of RF Noise Propagation to Relativistic Electron Beam Properties in a Linear Accelerator
Maalberg, Andrei	Helmholtz-Zentrum Dresden-Rossendorf
Kuntzsch, Michael	Helmholtz-Zentrum Dresden-Rossendorf
Petlenkov, Eduard	Tallinn University of Technology
Keywords: Frequency domain identification Abstract: The control system of the superconducting electron linear accelerator ELBE is planned to be upgraded by a beam-based feedback. As the design of the feedback algorithm enters its preliminary stage, the problem of analyzing the contribution of various disturbances to the development of the electron beam instabilities becomes highly relevant. In this paper we exploit the radio frequency (RF) phase and amplitude noise data measured at ELBE to create a behavioral model in Simulink. By modeling the interaction between a RF electromagnetic field and an electron bunch traversing a bunch compressor we analyze how the addition of RF noise impacts the electron beam properties, such as energy, duration and arrival time.
Paper VI111-07.3
PDF · Video · Sparsity Constrained Reconstruction for Electrical Impedance Tomography
Theertham, Ganesh Teja	Indian Institute of Technology Hyderabad
Varanasi, Santhosh Kumar	University of Alberta
Jampana, Phanindra	Indian Institute of Technology Hyderabad
Keywords: Mechanical and aerospace estimation, Errors in variables identification Abstract: Electrical Impedance Tomography (EIT) can be used to study the hydrodynamic characteristics in multiphase flows such as gas holdup in bubble columns, air core in hydrocyclone etc. In EIT, the main objective is to estimate the electrical properties (conductivity distribution) of an object in a region of interest based on the surface voltage measurements. The main challenge in such reconstruction (estimation of conductivity distribution) is the low spatial resolution. In this paper, a sparse optimization approach for image reconstruction in EIT is presented. The main idea presented in this article is based on considering the L1 norm on the data term which enhances reconstruction of conductivity distributions with sharp changes near phase boundaries. Further, this method is also robust to outliers in the data. The accuracy of the proposed method is demonstrated with the help of two phantoms and a comparison with the existing methods is also presented.
Paper VI111-07.4
PDF · Video · Integral Resonance Control in Continuous Wave Superconducting Particle Accelerators
Bellandi, Andrea	Deutsches Elektronen-Synchrotron (DESY)
Branlard, Julien	DESY
Eichler, Annika	DESY
Pfeiffer, Sven	DESY Hamburg
Keywords: Time series modelling Abstract: Superconducting accelerating cavities for continuous wave low-current particle accelerators requires a tight resonance control to optimize the RF power costs and to minimize the beam delivery downtime. When the detuning produced by radiation pressure becomes comparable to the RF bandwidth, the monotonic instability starts to affect the cavity operation. When this instability is triggered by external vibrations or drifts, the accelerating field amplitude drops rapidly, and the beam acceleration has to be stopped. Past experiments showed that using an integral control of the piezoelectric tuners installed on the cavity prevents the adverse effects of the monotonic instability. This paper derives theoretically why an integral controller is an effective way to counteract the monotonic instability. To perform the study a linearized state-space model of the cavity is derived. Simulations and experiments in a superconducting test facility indicate that the use of this kind of control has the additional benefit of bringing the cavities to the resonance condition automatically.

VI111-08
Bayesian Methods	Regular Session
Chair: Hjalmarsson, Håkan	KTH
Co-Chair: Iannelli, Andrea	ETH Zurich
Paper VI111-08.1
PDF · Video · A Novel Robust Kalman Filter with Non-Stationary Heavy-Tailed Measurement Noise
Jia, Guangle	Harbin Engineering University
Huang, Yulong	Harbin Engineering University
Bai, Mingming	Harbin Engineering University
Zhang, Yonggang	Harbin Engineering University
Keywords: Bayesian methods, Filtering and smoothing Abstract: A novel robust Kalman filter based on Gaussian-Student's t mixture (GSTM) distribution is proposed to address the filtering problem of a linear system with non-stationary heavy-tailed measurement noise. The mixing probability is recursively estimated by using its previous estimates as prior information, and the state vector, the auxiliary parameter, the Bernoulli random variable and the mixing probability are jointly estimated utilizing the variational Bayesian method. The excellent performance of the proposed robust Kalman filter, compared with the existing state-of-the-art filters, is illustrated by a target tracking simulation results under the case of non-stationary heavy-tailed measurement noise.
Paper VI111-08.2
PDF · Video · Stochastic Input Design Problems for the Frequency Response in Bayesian Identification
Zheng, Man	Kyoto University
Ohta, Yoshito	Kyoto University
Keywords: Bayesian methods, Frequency domain identification, Input and excitation design Abstract: Recently, the research of identification input design for Bayesian methods has been actively investigated. Either the problem is formulated as a non-convex problem with difficulty in solving or relaxed as a convex problem with a price of some conservativeness. In this contribution, a new minimum power input design problem is formulated by viewing the input as a stochastic process. We seek the minimum energy input with variance constraints over a frequency band. By exploiting the generalized Kalman-Yakubovich-Popov lemma, the stochastic consideration facilitates the input design problem to be presented as a convex problem whose decision variables are a finite number of autocorrelation coefficients. We obtain the autocorrelation coefficients of the desired stochastic input signal by solving the convex problem and extend them by the maximum entropy extension. Then, a specific identification input is sampled from the obtained stochastic process. Simulations results demonstrate the effectiveness of the proposed method.
Paper VI111-08.3
PDF · Video · Cascade Control: Data-Driven Tuning Approach Based on Bayesian Optimization
Khosravi, Mohammad	ETH Zurich
Behrunani, Varsha	ETH Zurich. Automatic Control Laboratory
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Rupenyan, Alisa	ETH Zurich
Lygeros, John	ETH Zurich
Keywords: Bayesian methods, Learning for control, Fault detection and diagnosis Abstract: Cascaded controller tuning is a multi-step iterative procedure that needs to be performed routinely upon maintenance and modification of mechanical systems. An automated data-driven method for cascaded controller tuning based on Bayesian optimization is proposed. The method is tested on a linear axis drive, modeled using a combination of first principles model and system identification. A custom cost function based on performance indicators derived from system data at different candidate configurations of controller parameters is modeled by a Gaussian process. It is further optimized by minimization of an acquisition function which serves as a sampling criterion to determine the subsequent candidate configuration for experimental trial and improvement of the cost model iteratively, until a minimum according to a termination criterion is found. This results in a data-efficient procedure that can be easily adapted to varying loads or mechanical modifications of the system. The method is further compared to several classical methods for auto-tuning, and demonstrates higher performance according to the defined data-driven performance indicators. The influence of the training data on a cost prior on the number of iterations required to reach optimum is studied, demonstrating the efficiency of the Bayesian optimization tuning method.
Paper VI111-08.4
PDF · Video · Parameter Identification for Digital Fabrication: A Gaussian Process Learning Approach
Stürz, Yvonne Rebecca	University of California Berkeley
Khosravi, Mohammad	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Bayesian methods, Learning for control, Nonlinear system identification Abstract: Tensioned cable nets can be used as supporting structures for the efficient construction of lightweight building elements, such as thin concrete shell structures. To guarantee important mechanical properties of the latter, the tolerances on deviations of the tensioned cable net geometry from the desired target form are very tight. Therefore, the form needs to be readjusted on the construction site. In order to employ model-based optimization techniques, the precise identification of important uncertain model parameters of the cable net system is required. This paper proposes the use of Gaussian process regression to learn the function that maps the cable net geometry to the uncertain parameters. In contrast to previously proposed methods, this approach requires only a single form measurement for the identification of the cable net model parameters. This is beneficial since measurements of the cable net form on the construction site are very expensive. For the training of the Gaussian processes, simulated data is efficiently computed via convex programming. The effectiveness of the proposed method and the impact of the precise identification of the parameters on the form of the cable net are demonstrated in numerical experiments on a quarter-scale prototype of a roof structure.
Paper VI111-08.5
PDF · Video · Robust Gaussian Process Regression with G-Confluent Likelihood
Lindfors, Martin	Linköping University
Chen, Tianshi	The Chinese University of Hong Kong, Shenzhen, China
Keywords: Bayesian methods, Machine learning Abstract: For robust Gaussian process regression problems where the measurements are contaminated by outliers, a likelihood/measurement noise model with heavy-tailed distributions should be used to improve the prediction performance. In this paper, we propose to use a G-confluent distribution as the measurement noise model and a coordinate ascent variational inference method to infer the overall statistical model. In contrast with the commonly used Student's t distribution, the G-confluent distribution can also be written as a Gaussian scale mixture, but its inverse scale follows a Beta distribution rather than a Gamma distribution, and its main advantage is that it is more flexible for modeling outliers while being equally suitable for variational inference. Numerical simulations based on benchmark data show that the G-confluent distribution performs better than or as well as the Student's t distribution.
Paper VI111-08.6
PDF · Video · Nonparametric Models for Hammerstein-Wiener and Wiener-Hammerstein System Identification
Risuleo, Riccardo Sven	KTH Royal Institute of Technology
Hjalmarsson, Håkan	KTH
Keywords: Bayesian methods, Nonlinear system identification, Nonparametric methods Abstract: We propose a framework for modeling structured nonlinear systems using nonparametric Gaussian processes. In particular, we introduce a two-layer stochastic model of latent interconnected Gaussian processes suitable for modeling Hammerstein-Wiener and Wiener-Hammerstein cascades. The posterior distribution of the latent processes is intractable because of the nonlinear interactions in the model; hence, we propose a Markov Chain Monte Carlo method consisting of a Gibbs sampler where each step is implemented using elliptical-slice sampling. We present the results on two example nonlinear systems showing that they can effectively be modeled and identified using the proposed nonparametric modeling approach.
Paper VI111-08.7
PDF · Video · Regularized System Identification: A Hierarchical Bayesian Approach
Khosravi, Mohammad	ETH Zurich
Iannelli, Andrea	ETH Zurich
Yin, Mingzhou	ETH Zurich
Parsi, Anilkumar	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Bayesian methods, Nonparametric methods, Machine learning Abstract: In this paper, the hierarchical Bayesian method for regularized system identification is introduced. To this end, a hyperprior distribution is considered for the regularization matrix and then, the impulse response and the regularization matrix are jointly estimated based on a maximum a posteriori (MAP) approach. Toward introducing a suitable hyperprior, we decompose the regularization matrix using Cholesky decomposition and reduce the estimation problem to the cone of upper triangular matrices with positive diagonal entries. Following this, the hyperprior is introduced on a designed sub-cone of this set. The method differs from the current trend in regularized system identification from various aspect, e.g., the estimation is performed by solving a single stage problem. The MAP estimation problem reduces to a multi-convex optimization problem and a sequential convex programming algorithm is introduced for solving this problem. Consequently, the proposed method is a computationally efficient strategy specially when the regularization matrix has a large size. The method is numerically verified on benchmark examples. Owing to the employed full Bayesian approach, the estimation method shows a satisfactory bias-variance trade-off.
Paper VI111-08.8
PDF · Video · Low-Complexity Identification by Sparse Hyperparameter Estimation
Khosravi, Mohammad	ETH Zurich
Yin, Mingzhou	ETH Zurich
Iannelli, Andrea	ETH Zurich
Parsi, Anilkumar	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Bayesian methods, Nonparametric methods, Machine learning Abstract: This paper presents a novel kernel-based system identification method, which promotes low complexity of the model in terms of the McMillan degree of the system. The regularization matrix is characterized as a linear combination of pre-selected rank-one matrices with unknown hyperparameter coefficients, and the hyperparameters are derived using a maximum a posteriori estimation approach. Each basis matrix is the optimal regularization matrix for a first-order system. With this basis matrix selection, the McMillan degree of the identified model is upper-bounded by the rank of the regularization matrix, which in turn is equal to the cardinality of the hyperparameters. For this reason, a sparsity-promoting prior is chosen for hyperparameter tuning. The resulting optimization problem has a difference of convex program form which can be efficiently solved. The advantages of the proposed method are that the identified model has a low-complexity structure and that an improved bias-variance trade-off is achieved. Numerical results confirm that the proposed method achieves a better bias-variance trade-off as well as a better fit to the model compared to both the empirical Bayes method and the atomic-norm regularization.
Paper VI111-08.9
PDF · Video · A Two-Stage Algorithm for Estimation of Unknown Parameters Using Nonlinear Measurements
Stepanov, O.A.	Concern CSRI Elektropribor, JSC; University ITMO
Nosov, Aleksei	Concern CSRI Elektropribor, JSC; University ITMO
Keywords: Bayesian methods, Particle filtering/Monte Carlo methods, Filtering and smoothing Abstract: A suboptimal two-stage algorithm has been proposed to solve nonlinear estimation problems consist in comparison of measured and reference samples. The new algorithm consists of preliminary processing of measurements, subsampling and simplification of the errors model in nonlinear algorithm. A significant increase in computational performance determines the novelty of the presented algorithm. The effective application of the two-stage suboptimal algorithm is illustrated by an example of gravity-aided navigation.
Paper VI111-08.10
PDF · Video · Process Monitoring with Sparse Bayesian Model for Industrial Methanol Distillation
Luo, Lin	Liaoning Shihua University
Xie, Lei	Zhejiang University
Su, Hongye	Zhejiang University
Zeng, Jiusun	China Jiliang University
Keywords: Fault detection and diagnosis, Bayesian methods Abstract: Following the intuition that not all latent variables in probabilistic principal component analysis method shifts simultaneously, this paper proposes a spike-and-slab regularization technique for nonlinear fault detection and isolation. Different from the existing probabilistic latent variable models, a spike-and-slab prior is introduced to downweight the irrelevant information of latent variables for the discriminative model. The resulting latent subspace supported by regularization parameters is not only sensitive to the informative variables, but it also eliminates the influence of the non-informative ones. The feasibility and efficiency of the proposed approach will be tested on an industrial methanol distillation dataset. Moreover, the performance will be compared with conventional probabilistic latent variables methods.
Paper VI111-08.11
PDF · Video · Probabilistic H2-Norm Estimation Via Gaussian Process System Identification
Persson, Daniel	University of Stuttgart
Koch, Anne	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Nonparametric methods, Bayesian methods, Identification for control Abstract: We present a method for data-based estimation of the H2-norm of a linear time-invariant system from input-output data in a probabilistic setting by employing the recent advances in Gaussian process system identification using stable-spline kernels. Advantages of this starting point include that the norm can be estimated for the continuous-time system and over infinite horizon, even though only a finite number of measurements are available. We approximate the H2-norm distribution as Gaussian, whose expectation can even be obtained analytically, while we use a numerical scheme based on Gaussian process quadrature for the variance. Not only do we utilize the posterior variance of the Gaussian process to derive an error estimate for the H2-norm, but also to tune the estimation by optimizing the input sequence. The performance of the developed scheme is thoroughly evaluated in simulation.
Paper VI111-08.12
PDF · Video · System Identification and Control of a Polymer Reactor
Münker, Tobias	University of Siegen
Kampmann, Geritt	University of Siegen
Schüssler, Max	University of Siegen
Nelles, Oliver	University of Siegen
Keywords: Identification for control, Nonlinear system identification, Bayesian methods Abstract: In a polymer production process, a special reactor is used to adjust the viscosity, i.e., chain length of the polymer. This reactor has several control variables mainly in manually control. For future automatic control concepts, such a reactor is modeled from data with a linear (regularized FIR) and a nonlinear state space model (LMSSN). A model predictive control approach is presented in simulation.
Paper VI111-08.13
PDF · Video · Controllability Gramian of Nonlinear Gaussian Process State Space Models with Application to Model Sparsification
Kashima, Kenji	Kyoto University
Imai, Misaki	Kyoto University
Keywords: Learning for control, Bayesian methods, Stochastic system identification Abstract: For linear control systems, the so-called controllability Gramian has played an important role to quantify how effectively the dynamical states can be driven to a target one by a suitable driving input. On the other hand, thanks to the availability of Big Data, the Gaussian process state space model, a data-driven probabilistic modeling framework, has attracted much attention in recent years. In this paper, we newly introduce the concept of the controllability Gramian for nonlinear dynamics represented by the Gaussian process state space model, aiming at better understanding of this new modeling framework. Then, its effective calculation method and application to model sparsification are investigated.
Paper VI111-08.14
PDF · Video · On Gaussian Process Based Koopman Operators
Lian, Yingzhao	EPFL
Jones, Colin N.	Ecole Polytechnique Federale De Lausanne (EPFL)
Keywords: Learning for control, Nonlinear system identification, Bayesian methods Abstract: Enabling analysis of non-linear systems in linear form, the Koopman operator has been shown to be a powerful tool for system identification and controller design. However, current data-driven methods cannot provide quantification of model uncertainty given the learnt model. This work proposes a probabilistic Koopman operator model based on Gaussian processes which extends the author’s previous results and gives a quantification of model uncertainty. The proposed probabilistic model enables efficient propagation of uncertainty in feature space which allows efficient stochastic/robust controller design. The proposed probabilistic model is tested by learning stable nonlinear dynamics generating hand-written characters and by robust controller design of a bilinear DC motor.
Paper VI111-08.15
PDF · Video · A Kriging-Based Interacting Particle Kalman Filter for the Simultaneous Estimation of Temperature and Emissivity in Infra-Red Imaging
Toullier, Thibaud	Inria
Dumoulin, Jean	IFSTTAR
Mevel, Laurent	INRIA
Keywords: LPV system identification, Particle filtering/Monte Carlo methods, Bayesian methods Abstract: Temperature estimation through infrared thermography is facing the lack of knowledge of the observed material's emissivity. The derivation of the physical equations lead to an ill-posed problem. A new Kriged Interacting Particle Kalman Filter is proposed. A state space model relates the measurements to the temperature and the Kalman filter equations yield a filter tracking the temperature over time. Moreover, a particle filter associated to Kriging prediction is interacting with a bank of Kalman filters to estimate the time-varying parameters of the system. The efficiency of the algorithm is tested on a simulated sequence of infrared thermal images.
Paper VI111-08.16
PDF · Video · On Semiseparable Kernels and Efficient Computation of Regularized System Identification and Function Estimation
Chen, Tianshi	The Chinese University of Hong Kong, Shenzhen, China
Andersen, Martin S.	Technical University of Denmark
Keywords: Nonparametric methods, Bayesian methods Abstract: A long-standing problem for kernel-based regularization methods is their high computational complexity O(N^3), where N is the number of data points. In this paper, we show that for semiseparable kernels and some typical input signals, their computational complexity can be lowered to O(Nq2), where q is the output kernel’s semiseparability rank that only depends on the chosen kernel and the input signal.

VI111-09
Classification, Estimation, and Filtering	Regular Session
Chair: Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Co-Chair: Nair, Girish N.	University of Melbourne
Paper VI111-09.1
PDF · Video · Multi-Point Search Based Identification under Severe Numerical Conditions
Sun, Lianming	The University of Kitakyushu
Uto, Ryoka	The University of Kitakyushu
Liu, Xinyu	The University of Kitakyushu
Sano, Akira	Keio University
Keywords: Closed loop identification, Estimation and filtering Abstract: It is necessary to perform the system identification under severe numerical conditions in many practical applications. When less external test signals are available for parameter estimation from experimental data, the identification performance often suffers from numerical problems in the optimization procedure due to the less independent informative components, the influence of complicated noise, or the local minima problem. In this paper, a multi-point search based identification algorithm is investigated for system identification under severe numerical conditions. It introduces the output over-sampling scheme to collect the experimental input-output data, and extracts the information in time and space domains to complement information criterion for numerical optimization. Furthermore, the multi-point search is utilized to decrease the influence of local minima. The numerical simulation examples illustrate that the identification performance has been improved in the proposed algorithm.
Paper VI111-09.2
PDF · Video · Position and Speed Estimation of PMSMs Using Gaussian Processes
Mayer, Jana	Karlsruhe Institute of Technology
Basarur, Ajit	Karlsruhe Institute of Technology
Petrova, Mariana	Karlsruhe Institute of Technology
Sordon, Fabian	Karlsruhe Institute of Technology
Zea, Antonio	Karlsruhe Institute of Technology
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Experiment design, Machine learning, Estimation and filtering Abstract: In this paper, we present a novel low-cost technique to estimate both the position and the speed of a permanent magnet synchronous motor (PMSM) by sensing its stray magnetic field. At an optimal radial and axial distance, a low-cost magnetoresistive sensor is placed outside at the back of the PMSM. The magnetic field values are recorded for one complete rotor revolution at a resolution of less than a degree for different speeds of operation. Gaussian Processes (GPs) are employed to find a mapping function between the magnetic field values of the permanent magnet and the absolute angular positions. Then, by using the learned GP as a measurement function with an Extended Kalman Filter (EKF), both the angular position and speed of a PMSM can be estimated efficiently. Furthermore, we observe that the magnetic field depends not only on the position but also on the angular speed. To address this, we extend the GP to incorporate multivariate inputs. In order to take the periodicity of the data into account, we employ a periodic kernel for the GP. Additionally, a linear basis function model (LBFM) is introduced to incorporate more training points while maintaining the same computational cost. The GP and LBFM approaches are evaluated with data from a real PMSM experiment setup, and the accuracy of the position and speed state estimation is verified against a high-resolution optical encoder used as ground truth.
Paper VI111-09.3
PDF · Video · On the Stable Cholesky Factorization-Based Method for the Maximum Correntropy Criterion Kalman Filtering
Kulikova, Maria V.	Instituto Superior Técnico, Universidade De Lisboa
Keywords: Filtering and smoothing, Estimation and filtering, Bayesian methods Abstract: This paper continues the research devoted to the design of numerically stable square-root implementations for the maximum correntropy criterion Kalman filtering (MCC-KF). In contrast to the previously obtained results, here we reveal the first robust (with respect to round-off errors) method within the Cholesky factorization-based approach. The method is formulated in terms of square-root factors of the covariance matrices, i.e. it belongs to the covariance-type filtering methodology. Additionally, a numerically stable orthogonal transformation is utilized at each iterate of the algorithm for accurate propagation of the Cholesky factors involved. The results of numerical experiments illustrate a superior performance of the novel MCC-KF implementation compared to both the conventional algorithm and its previously published Cholesky-based variant.
Paper VI111-09.4
PDF · Video · An Adaptive Radiometric Meter with Variable Measurement Time for Monitoring of Coal Jigs Operation
Joostberens, Jaroslaw	Silesian University of Technology
Cierpisz, Stanislaw	Institute of Innovative Technologies EMAG
Keywords: Filtering and smoothing, Estimation and filtering, Errors in variables identification Abstract: The authors discuss the problem of how to monitor the coal/water pulsating bed in a jig with the use of a radiation density meter. The dynamic measurement error of changes in density depends on the time of measurement; its optimal value can be found for a given shape of density changes. An alternative method of the signal filtration is proposed using variable time of measurement during a cycle of pulsations as a function of the time derivative of the density changes. The shape of the density changes during one cycle varies slowly from a cycle to a cycle. This is why the time derivative of the density determined during one cycle can be used in the subsequent cycle to adapt periodically the algorithm generating the variable times of measurement during each cycle. The above time derivative can be calculated from the polynomial fit of stochastic data measured during the previous cycle. In this case, the dynamic error of the measurement MSE can be reduced significantly compared to the optimal constant time of the measurement. This methodology of signal filtration was applied in the simulation model and the results of simulation were compared with field measurements taken with the use of a conventional radiometric density meter.
Paper VI111-09.5
PDF · Video · Robust Hoo Estimation of Retarded State-Multiplicative Systems
Gershon, Eli	Tel Aviv Univ
Keywords: Filtering and smoothing, Estimation and filtering, Synthesis of stochastic systems Abstract: Linear, discrete-time systems with state-multiplicative noise and delayed states are considered. The problem of robust Hoo general-type filtering is solved for these systems when the uncertainty in their deterministic parameters is of the polytopic-type. The obtained vertex-dependant solution is based on a modified Finsler lemma which leads to a simple set of LMIs condition. The included numerical example demonstrates the tractability and solvability of the proposed method.
Paper VI111-09.6
PDF · Video · Performance Assessment and Design of Quadratic Alarm Filters
Roohi, Mohammad	University of Alberta
Chen, Tongwen	University of Alberta
Keywords: Filtering and smoothing, Fault detection and diagnosis Abstract: Alarm filtering is a structurally simple, easy to implement, and effective method to improve industrial alarm systems. Owing to these advantages, alarm filters are widely used in industrial applications. Linear and quadratic are the main types of alarm filters. Although a linear filter can detect mean changes, it can not be used to detect variation changes. However, a quadratic filter can be used to detect both types of changes. Although this remarkable feature of quadratic filters has been addressed in the literature, no explicit performance analysis is performed yet. So, deriving an analytical solution for quadratic filters is of paramount importance. To this aim, we propose an analytical method for performance assessment and design of quadratic filters. On the other side, in industrial applications, many process variables are acquired. So one challenge is to identify the process variable that provides the best alarm performance after filtering. We will derive an analytical solution to this problem. Furthermore, we will prove that this optimal solution is a function of the statistical feature of historical data and alarm filter structure.
Paper VI111-09.7
PDF · Video · Algorithms for Integrated Processing of Marine Gravimeter Data and GNSS Measurements
Stepanov, O.A.	Concern CSRI Elektropribor, JSC; University ITMO
Koshaev, Dmitry	Concern CSRI Elektropribor, JSC; University ITMO
Motorin, Andrei V.	Concern CSRI Elektropribor, JSC; University ITMO
Krasnov, Anton	Concern CSRI Elektropribor, JSC; University ITMO
Sokolov, Alexander	Concern CSRI Elektropribor, JSC; University ITMO
Keywords: Filtering and smoothing, Nonlinear system identification, Software for system identification Abstract: Efficiency of using global navigation satellite system (GNSS) measurements for determining gravity anomalies (GA) at sea by solving filtering and smoothing problems based on GNSS and gravimeter data is studied. The GA, ship heaving, errors of GNSS and gravimeter measurements are presented as stochastic processes. The analysis is based on the standard deviations of the GA estimation errors, calculated at different heaving parameters and in different modes of GNSS data processing.
Paper VI111-09.8
PDF · Video · Granger Causality of Gaussian Signals from Noisy or Filtered Measurements
Ahmadi, Salman	University of Melbourne
Nair, Girish N.	University of Melbourne
Weyer, Erik	University of Melbourne
Keywords: Time series modelling Abstract: This paper investigates the assessment of Granger causality (GC) between jointly Gaussian signals based on noisy or filtered measurements. To do so, a recent rank condition for inferring GC between jointly Gaussian stochastic processes is exploited. Sufficient conditions are derived under which GC can be reliably inferred from the second order moments of the noisy or filtered measurements. This approach does not require a model of the underlying Gaussian system to be identified. The noise signals are not required to be Gaussian or independent, and the filters may be noncausal or nonminimum-phase, as long as they are stable.
Paper VI111-09.9
PDF · Video · Sparse Representation of Feedback Filters in Delta-Sigma Modulators
Nagahara, Masaaki	The University of Kitakyushu
Yamamoto, Yutaka	Kyoto Univ
Keywords: Filtering and smoothing, Quantized systems, Networked embedded control systems Abstract: In this paper, we propose sparse representation of FIR (Finite Impulse Response) feedback filters in delta-sigma modulators. The filter has a sparse structure, that is, only a few coefficients are non-zero, that stabilizes the feedback modulator, and minimizes the maximum magnitude of the noise transfer function at low frequencies. The optimization is described as an L1 minimization with linear matrix inequalities (LMIs), based on the generalized KYP (Kalman-Yakubovich-Popov) lemma. A design example is shown to illustrate the effectiveness of the proposed method.
Paper VI111-09.10
PDF · Video · Sparse ℓ1 and ℓ2 Center Classifiers
Calafiore, Giuseppe	Politecnico Di Torino
Fracastoro, Giulia	Politecnico Di Torino
Keywords: Machine learning Abstract: The nearest-centroid classifier is a simple linear-time classifier based on computing the centroids of the data classes in the training phase, and then assigning a new datum to the class corresponding to its nearest centroid. Thanks to its very low computational cost, the nearest-centroid classifier is still widely used in machine learning, despite the development of many other more sophisticated classification methods. In this paper, we propose two sparse variants of the nearest-centroid classifier, based respectively on ℓ1 and ℓ2 distance criteria. The proposed sparse classifiers perform simultaneous classification and feature selection, by detecting the features that are most relevant for the classification purpose. We show that training of the proposed sparse models, with both distance criteria, can be performed exactly (i.e., the globally optimal set of features is selected) and at a quasi-linear computational cost. The experimental results show that the proposed methods are competitive in accuracy with state-of-the-art feature selection techniques, while having a significantly lower computational cost.
Paper VI111-09.11
PDF · Video · Granger Causality Based Hierarchical Time Series Clustering for State Estimation
Tan, Sin Yong	Iowa State University
Saha, Homagni	Iowa State University
Jacoby, Margarite	University of Colorado, Boulder
Florita, Anthony R.	National Renewable Energy Laboratory
Henze, Gregor P.	University of Colorado Boulder
Sarkar, Soumik	Iowa State University
Keywords: Time series modelling, Machine learning, Quantized systems Abstract: Clustering is an unsupervised learning technique that is useful when working with a large volume of unlabeled data. Complex dynamical systems in real life often entail data streaming from a large number of sources. Although it is desirable to use all source variables to form accurate state estimates, it is often impractical due to large computational power requirements, and sufficiently robust algorithms to handle these cases are not common. We propose a hierarchical time series clustering technique based on symbolic dynamic filtering and Granger causality, which serves as a dimensionality reduction and noise-rejection tool. Our process forms a hierarchy of variables in the multivariate time series with clustering of relevant variables at each level, thus separating out noise and less relevant variables. A new distance metric based on Granger causality is proposed and used for the time series clustering, as well as validated on empirical data sets. Experimental results from occupancy detection and building temperature estimation tasks show fidelity to the empirical data sets while maintaining state-prediction accuracy with substantially reduced data dimensionality.

VI111-10
Estimation, Identification, and Discretization of Continuous-Time Systems	Regular Session
Chair: Hirche, Sandra	Technical University of Munich
Co-Chair: Oliveira, Vilma A.	Universidade De Sao Paulo
Paper VI111-10.1
PDF · Video · A Modified Non-Adaptive OSG-SOGI Filter for Estimation of a Biased Sinusoidal Signal with Global Convergence Properties
Fedele, Giuseppe	Università Della Calabria
Pin, Gilberto	University of Padua
Parisini, Thomas	Imperial College & Univ. of Trieste
Keywords: Continuous time system estimation Abstract: This paper presents an algorithm for estimating the parameters of a biased sinusoidal signal. The proposed method uses the output signals of a second order generalized integrator without adaptation on its resonant frequency to derive a linear regression equation where the unknown parameters are a nonlinear combination of bias and frequency of the input signal. The global stability of the method is proven. Remarkably, the proposed method represents the minimum-order estimator known for the problem under consideration, being implementable by a 4th-order adaptive system. Simulation results and comparisons with existing methods show the accurate estimation capability of the proposed approach.
Paper VI111-10.2
PDF · Video · Identification of Continuous-Time Systems Utilising Kautz Basis Functions from Sampled-Data
Coronel Mendez, María de los Angeles	Universidad Técnica Federico Santa María
Carvajal, Rodrigo	Universidad Tecnica Federico Santa Maria
Aguero, Juan C.	Universidad Santa Maria
Keywords: Continuous time system estimation Abstract: In this paper we address the problem of identifying a continuous-time deterministic system utilising sampled-data with instantaneous sampling. We develop an identification algorithm based on Maximum Likelihood. The exact discrete-time model is obtained for two cases: i) known continuous-time model structure and ii) using Kautz basis functions to approximate the continuous-time transfer function. The contribution of this paper is threefold: i) we show that, in general, the discretisation of continuous-time deterministic systems leads to several local optima in the likelihood function, phenomenon termed as aliasing, ii) we discretise Kautz basis functions and obtain a recursive algorithm for constructing their equivalent discrete-time transfer functions, and iii) we show that the utilisation of Kautz basis functions to approximate the true continuous-time deterministic system results in convex log-likelihood functions. We illustrate the benefits of our proposal via numerical examples.
Paper VI111-10.3
PDF · Video · Adaptive Identification of Nonlinear Time-Delay Systems Using Output Measurements
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Orlov, Yury	CICESE
Keywords: Continuous time system estimation Abstract: A novel adaptive identifier is developed for nonlinear time-delay systems composed of linear, Lipschitz and non-Lipschitz components. To begin with, an identifier is designed for uncertain systems with a priori known delay values, and then it is generalized for systems with unknown delay values. The algorithm ensures the asymptotic parameter estimation and state observation by using gradient algorithms. The unknown delays and plant parameters are estimated by using a special equivalent extension of the plant equation. The algorithms stability is presented by solvability of linear matrix inequalities.
Paper VI111-10.4
PDF · Video · Estimating the Membrane Properties of Vestibular Type II Hair Cells Using Continuous-Time System Identification
Pan, Siqi	University of Newcastle
Welsh, James	University of Newcastle
Brichta, Alan	University of Newcastle
Drury, Hannah	University of Newcastle
Stoddard, Jeremy Grant	University of Newcastle
Keywords: Continuous time system estimation Abstract: In this paper we apply a continuous-time system identification method, known as the Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC), to the problem of estimating membrane properties of vestibular Type II hair cells. Due to the non-ideal characteristics of the experimental system, additional parameters, other than those of the membrane are required to be estimated. The SRIVC algorithm is modified to allow known poles and zeros to be forced into the estimator. This modified algorithm is then applied to the identification of the membrane properties of vestibular Type II hair cells, yielding results commensurate with typically accepted values.
Paper VI111-10.5
PDF · Video · Unknown System Dynamics Estimator for Nonlinear Uncertain Systems (I)
Yang, Jun	Kunming University of Science and Technology
Na, Jing	University of Bristol
Yu, Haoyong	National University of Singapore
Gao, Guanbin	Kunming University of Science & Technology
Wang, Xiaodong	Kunming University of Science and Technology
Keywords: Continuous time system estimation, Bounded error identification, Identification for control Abstract: For feedback control designs, one of the fundamental problems is to handle the unknown system dynamics. In this paper, an alternative unknown system dynamics estimator (USDE) with low-pass filter operations is presented based on an invariant manifold method, in which we only need to set a scalar, the filter parameter. The convergence performance and robustness of this USDE are analysed in both the time-domain and frequency-domain. To circumvent the sensitiveness to the measurement noise, a further enhanced USDE (EUSDE) with two-layer of low-pass filters is constructed. With the proposed estimators, all time-varying components, such as unmodeled dynamics, nonlinearities and external disturbances, can be viewed as a lumped unknown system dynamics term and then effectively estimated even in the presence to fair measurement noise. The function of these estimators is the same as the well-known disturbance observer (DOB) and extended state observer (ESO). Hence, they can be easily incorporated into control schemes. Numerical simulation results are presented to show the effectiveness of the proposed estimation schemes.
Paper VI111-10.6
PDF · Video · Nonlinear Observer Design for Systems with Sampled Measurements: An LPV Approach
Boukal, Yassine	Université Polytechnique Hauts-De-France,
Zerrougui, Mohamed	Aix Marseille University
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Outbib, Rachid	University of Aix-Marseille - LIS
Keywords: Continuous time system estimation, Estimation and filtering Abstract: The aim of this work is to propose a design methodology of observers for a class of Lipschitz nonlinear dynamical systems with sampled measurements by using the differential mean value theorem (DMVT) which allows us to transform the nonlinear part of the estimation error dynamics into a linear parameter varying (LPV) system. The designed observer must ensure the stability of the estimation error subject to a sampled measurements. An LMI-based minimization problem is provided to ensure the stability and the existence of the observer using Lyapunov theory. Thus, the measurements sampling period is included in the LMI as a decision parameter. Indeed, this allows to widen the sampling period as much as possible, which helps optimization of energy consumption while guaranteeing the convergence of the observer. Finally, to illustrate the performance of the proposed methodology, a numerical example is presented.
Paper VI111-10.7
PDF · Video · Enforcing Stability through Ellipsoidal Inner Approximations in the Indirect Approach for Continuous-Time System Identification
González, Rodrigo A.	KTH Royal Institute of Technology
Welsh, James	University of Newcastle
Rojas, Cristian R.	KTH Royal Institute of Technology
Keywords: Continuous time system estimation, Estimation and filtering, Stochastic system identification Abstract: Recently, a new indirect approach method for continuous-time system identification has been proposed that provides complete freedom on the number of poles and zeros of the linear and time-invariant continuous-time model structure. However, this procedure has reliability issues, as it may deliver unstable estimates even if the initialisation model and true system are stable. In this paper, we propose a method to overcome this problem. By generating ellipsoids that contain parameter vectors whose coefficients yield stable polynomials, we introduce a convex constraint in the indirect prediction error method formulation, and show that the proposed method enjoys optimal asymptotic properties while being robust in small and noisy data set scenarios. The effectiveness of the novel method is tested through extensive simulations.
Paper VI111-10.8
PDF · Video · Analysis of the Parameter Estimate Error When Algebraic Differentiators Are Used in the Presence of Disturbances
Othmane, Amine	Université Paris-Saclay; Saarland University
Rudolph, Joachim	Saarland University
Mounier, Hugues	CNRS SUPELEC Université Paris
Keywords: Continuous time system estimation, Filtering and smoothing Abstract: The use of algebraic differentiators in the context of asymptotic continuous-time parameter estimation is discussed. The estimation problem is analyzed within a least squares optimization context. Bounds for the error stemming from high frequency disturbances and the approximation of the derivatives are derived. It is shown that with higher frequencies the error stemming from the disturbances decreases and that the filter parameters can be used to adjust the convergence of this error to zero. An observer with assignable error dynamics for the online estimation is also proposed. A simulation is carried out to evaluate the results and compare the proposed observer with the recursive solution of the least squares problem.
Paper VI111-10.9
PDF · Video · State Estimation for a Locally Unobservable Parameter-Varying System: One Gradient-Based and One Switched Solutions
Aranovskiy, Stanislav	CentraleSupelec - IETR
Efimov, Denis	Inria
Sokolov, Dmitry	Université De Lorraine
Wang, Jian	Hangzhou Dianzi University
Ryadchikov, Igor	Kuban State University
Bobtsov, Alexey	ITMO University
Keywords: Continuous time system estimation, Mechanical and aerospace estimation Abstract: This work is motivated by a case study of a mechanical system where a sensor bias yields loose of observability for certain values of time-varying parameters. Two solutions are proposed: a nonlinear gradient-based observer that requires the persistency of excitation of the system trajectories and a switched observer that imposes an average dwell-time requirement. For both observers, asymptotic convergence of the estimates is proven. The theoretical results are supported by illustrative numerical simulations.
Paper VI111-10.10
PDF · Video · Finite-Time Frequency Estimator for Harmonic Signal
Bobtsov, Alexey	ITMO University
Vediakova, Anastasiia	Saint Petersburg State University
Nikolaev, Nikolay	ITMO University
Slita, Olga	ITMO University
Pyrkin, Anton	ITMO University
Vedyakov, Alexey	ITMO University
Keywords: Continuous time system estimation, Nonlinear system identification Abstract: This paper is devoted to a frequency estimation of a pure sinusoidal signal in finite-time. The parameterization is based on applying delay operators to a measurable signal. The result is the first-order linear regression model with one parameter, which depends on the signal frequency. The proposed method of finite-time estimation consists of two steps. On the first step, the standard gradient descent method is used to estimate the regression model parameter. On the next step using algebraic equations, finite-time frequency estimate is found. The described method does not require measuring or calculating derivatives of the input signal and uses one integrator for the gradient method and another one for the finite-time estimation. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.
Paper VI111-10.11
PDF · Video · Coefficients and Delay Estimation of the General Form of Fractional Order Systems Using Non-Ideal Step Inputs
Hashemniya, Fatemeh	Faculty of Electrical Engineering, K. N. Toosi University of Tec
Tavakoli-Kakhki, Mahsan	K.N. Toosi University of Technology
Azarmi, Roohallah	Eindhoven University of Technology
Keywords: Continuous time system estimation, Recursive identification, Identification for control Abstract: This paper proposes a novel method for the simultaneous estimation of the coefficients and the delay term of a delayed fractional order system. Because of the practicality aspect of the non-ideal step inputs, such inputs are used in this paper for the first time to identify a fractional order system. To this end, the proposed identification procedure is separately described for two types of fractional order systems, i.e., including both non-delayed and delayed systems. For the non-delayed system, a fractional order integral approach is developed, and for the delayed system, a filtering approach is investigated to make the delay term to be explicitly appeared in the parameters vector. In simulation results, some illustrative examples, covering both non-delayed and delayed systems, are given to demonstrate the validity of the proposed method.
Paper VI111-10.12
PDF · Video · Using Multivariate Polynomials to Obtain DC-DC Converter Voltage Gain
Magossi, Rafael Fernando Quirino	Centro Federal De Educação Tecnológica Celso Suckow Da Fonseca,
Fuzato, Guilherme	Federal Institute of Education, Science and Technology of São Pa
Silva de Castro, Daniel	University of São Paulo
Quadros Machado, Ricardo	USP
Oliveira, Vilma A.	Universidade De Sao Paulo
Keywords: Experiment design, Grey box modelling, Continuous time system estimation Abstract: In this paper, a data driven approach is used to obtain the static gain of dc--dc power converters in terms of the duty cycle and a set of linear coefficients. A known number of measurements, dependent on the dc--dc converter topology, are used to built-in a rational function obtained by linear coefficients. This solution shows how to use measurements to determine a function to represent the static gain of dc--dc power converters in the continuous-conduction mode (CCM). To validate the proposed approach, PSIM simulations, as well as experimental results are presented. The analysis was performed with a Interleaved Boost with Voltage Multiplier (IBVM) converter. Finally, the proposed approach is shown to be an alternative to the classical scanning methods or to the conventional solution of differential equations.
Paper VI111-10.13
PDF · Video · Parameter Estimation in Input Matrix under Gain Constraints in Specified Frequency Ranges
Sato, Masayuki	Japan Aerospace Exploration Agency
Keywords: Grey box modelling, Frequency domain identification, Continuous time system estimation Abstract: This paper addresses parameter estimation problem of Continuous-/Discrete-Time (CT/DT) Linear Time-Invariant (LTI) systems, whose gain properties should satisfy given constraints in a priori specified frequencies, using measured data. The following are supposed in our problem: i) only input matrix has parameters to be estimated; ii) the state and the input are both measured, and the derivative of the state is also measured in CT case, and iii) the gain constraints in specified frequency ranges are given beforehand. Under these suppositions, a formulation to minimize the difference between the measured state derivative and the expected state derivative (in CT case) or the difference between the measured one-step-ahead state and the expected one-step-ahead state (in DT case) in Euclidean norm with the supposed gain constraints satisfied is given in terms of Linear Matrix Inequality (LMI). The effectiveness of the proposed method is demonstrated by an academic example in DT case as well as flight data obtained by JAXA's airplane in CT case.
Paper VI111-10.14
PDF · Video · Minimum Phase Properties of Systems with a New Signal Reconstruction Method
Ou, Minghui	Chongqing University
Liang, Shan	Chongqing University
Zhang, Hao	College of Automation, Chongqing University
Liu, Tong	Chongqing University
Liang, Jing	College of Automation，chongqing University
Keywords: Input and excitation design, Continuous time system estimation, Stability and stabilization of hybrid systems Abstract: The Minimum Phase (MP) properties of linear control systems can be reflected by its zero stability. The stability of zeros affects the system control performance. When a continuous-time system is discretized to a discrete-time system, the discretization process may render continuous-time system models have nonminimum phase. This paper analyses the MP properties of system and deduces a new stable condition of the zeros when continuous-time system is discretized by Forward Triangle Sample and Hold (FTSH) for sufficiently small sampling periods. Finally, two numerical examples have verified our results.
Paper VI111-10.15
PDF · Video · Machine Learning for Receding Horizon Observer Design: Application to Traffic Density Estimation
Georges, Didier	Grenoble Institute of Engineering and Management - Univ. Grenobl
Keywords: Machine learning, Continuous time system estimation Abstract: This paper is devoted to the application of a simple machine learning technique for the design of a receding horizon state observer. The proposed approach is based on a neural network trained to learn the inverse problem consisting in deriving the current system state from past measurements and inputs. The training data is obtained from simple integrations of the system dynamics to be observed. The approach is here applied to the problem of estimating the car density on a highway online. A comparison with the solution of an receding horizon observer based on an adjoint method and used as reference demonstrates the effectiveness of the proposed approach.
Paper VI111-10.16
PDF · Video · Robust Sampling Time Designs for Parametric Uncertain Systems
Wang, Ke	University of Strathclyde
Yue, Hong	University of Strathclyde
Keywords: Model formulation, experiment design, Identification and validation, Developments in measurement, signal processing Abstract: Robust experimental design (RED) of sampling time scheduling has been discussed for parametric uncertain systems. Four RED methods, i.e., the pseudo-Bayesian design, the maximin design, the expectation-variance design, and the online experimental redesign, are investigated under the framework of model-based optimal experimental design (OED). Both the D-optimal and the E-optimal criteria are used as performance metrics. Two numerical procedures, the Powell's method and the semi-definite programming (SDP), are employed to obtain the optimum solution for REDs. The robustness performance of the four REDs are compared using a benchmark enzyme reaction system. In comparison to a typical uniform sampling strategy, the sampling time profiles from REDs are more focused on regions where the dynamic system has higher parametric sensitivities, indicating choice of informative data for parameter identification. The designed sampling strategies are also assessed by bootstrap parameter estimation with randomly generated initial points, where the difference between REDs can be observed.
Paper VI111-10.17
PDF · Video · Consistent Discretization of a Class of Predefined-Time Stable Systems
Jiménez-Rodríguez, Esteban	CINVESTAV - Unidad Guadalajara
Aldana-López, Rodrigo	Universidad De Zaragoza
Sanchez-Torres, Juan Diego	ITESO
Gómez-Gutiérrez, David	Intel Coporation
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Keywords: Digital implementation, Stability of nonlinear systems, Application of nonlinear analysis and design Abstract: As the main contribution, this document provides a consistent discretization of a class of fixed-time stable systems, namely predefined-time stable systems. In the unperturbed case, the proposed approach allows obtaining not only a consistent but exact discretization of the considered class of predefined-time stable systems, whereas in the perturbed case, the consistent discretization preserves the predefined-time stability property. All the results are validated through simulations and compared with the conventional explicit Euler scheme, highlighting the advantages of this proposal.

VI111-11
Fault Detection and Diagnosis	Regular Session
Chair: Patton, Ron J.	Univ. of Hull
Co-Chair: Ding, Steven X.	Univ of Duisburg-Essen
Paper VI111-11.1
PDF · Video · Multiple Multiplicative Actuator Fault Detectability Analysis Based on Invariant Sets for Discrete-Time LPV Systems
Min, Bo	Tsinghua University
Xu, Feng	Tsinghua Univerisity
Tan, Junbo	Tsinghua University
Wang, Xueqian	Tsinghua University
Liang, Bin	Tsinghua University
Keywords: Fault detection and diagnosis Abstract: This paper proposes a generalized minimum detectable fault (MDF) computation method based on the set-separation condition between the healthy and faulty residual sets for discrete-time linear parameter varying (LPV) systems with bounded inputs and uncertainties. First, we equivalently transform the multiple multiplicative actuator faults into the form of multiple additive actuator faults, which is benecial to simplify the problem. Then, by considering the 1-norm of the fault vector, we define the generalized MDF in the case of multiple additive actuator faults, which can be computed via solving a simple linear programming (LP) problem. Moreover, an analysis of the effect of the input vector on the magnitude of the generalized MDF is made. Since the proposed generalized MDF computation method is robust by considering the bounds of inputs and uncertainties, robust fault detection (FD) can be guaranteed whenever the sum of the magnitudes of all occurred faults is larger than the magnitude of the generalized MDF. At the end of this paper, a numerical example is used to illustrate the effectiveness of the proposed method.
Paper VI111-11.2
PDF · Video · On Real-Time Fatigue Damage Prediction for Steam Turbine
Xu, Bo	University of Jinan
Sun, Yongjian	University of Jinan
Keywords: Fault detection and diagnosis Abstract: This paper presents a real-time prediction method for fatigue damage of steam turbine. The temperature data and thermal stress data of the key parts are extracted by calculating the temperature field and the stress field. The composite stress is calculated according to the fourth strength theory, and the measured stress data are normalized. Support vector regression model is established, input and output data are trained and predicted. The relationship between stress and damage function is analyzed and fitted, and the framework of the real time fatigue damage prediction system is established. In the end, the effectiveness of the method is verified by simulation experiment.
Paper VI111-11.3
PDF · Video · Probabilistic Robust Parity Relation Based Fault Detection Using Biased Minimax Probability Machine
Ma, Yujia	Huazhong University of Science and Technology
Wan, Yiming	Huazhong University of Science and Technology
Zhong, Maiying	Shandong University of Science and Technology
Keywords: Fault detection and diagnosis Abstract: This paper proposes a probabilistic robust parity relation based approach to fault detection of stochastic linear systems. Instead of assuming exact knowledge of disturbance distribution, the uncertainty of distribution information is taken into account by considering an ambiguity set of disturbance distributions. The biased minimax probability machine scheme is exploited to formulate an integrated design of the parity vector/matrix and the detection threshold. It maximizes the worst-case fault detection rate (FDR) with respect to selected reference faults, while ensuring a predefined worst-case false alarm rate. Firstly, a scalar residual design is derived in an analytical form. The analysis of its FDR in the presence of an arbitrary fault shows its limitation due to using a single reference fault. This issue is further addressed by proposing a vector residual design with a systematic method to select multiple reference faults. The efficacy of the proposed approach is illustrated by a simulation example.
Paper VI111-11.4
PDF · Video · Distributionally Robust Fault Detection by Using Kernel Density Estimation
Xue, Ting	University of Duisburg-Essen
Zhong, Maiying	Shandong University of Science and Technology
Luo, Lijia	Zhejiang University of Technology
Li, Linlin	University of Science and Technology Beijing
Ding, Steven X.	Univ of Duisburg-Essen
Keywords: Fault detection and diagnosis Abstract: In this paper, a method of distributionally robust fault detection (FD) is proposed for stochastic linear discrete-time systems by using the kernel density estimation (KDE) technique. For this purpose, an H2 optimization-based fault detection filter is constructed for residual generation. Towards maximizing the fault detection rate (FDR) for a prescribed false alarm rate (FAR), the residual evaluation issue regarding the design of residual evaluation function and threshold is formulated as a distributionally robust optimization problem, wherein the so-called confidence sets are constituted to model the ambiguity of distribution knowledge of residuals in fault-free and faulty cases. A KDE based solution, robust to the estimation errors in probability distribution of residual caused by the finite number of samples, is further developed to address the targeting problem such that the residual evaluation function, threshold as well as the lower bound of FDR can be achieved simultaneously. A case study on a vehicle lateral control system demonstrates the applicability of the proposed FD method.
Paper VI111-11.5
PDF · Video · Fault Detection and Identification for Nonlinear MIMO Systems Using Derivative Estimation
Lomakin, Alexander	Universität Erlangen-Nürnberg
Deutscher, Joachim	Universität Ulm
Keywords: Fault detection and diagnosis Abstract: In this paper a method for fault detection and identification of affine input nonlinear systems is presented, which is based on derivative estimation with orthonormal Jacobi polynomials. A systematic approach is presented to derive a residual and a differential algebraic expression of the fault from the system description, which solely depends on measurable input and output signals as well as on their time derivatives. For this, a systematic algorithm is provided, which can be directly implemented in computer algebra packages. Furthermore, arbitrary disturbances are taken into account, by making use of a disturbance decoupling. Fault detection and identification is then achieved by polynomial approximation of the determined fault or residual expression. The results are illustrated for a faulty point-mass satellite model.
Paper VI111-11.6
PDF · Video · Robust Anomaly Detection Based on a Dynamical Observer for Continuous Linear Roesser Systems
Alikhani, Hamid	K.N. Toosi University of Technology
Meskin, Nader	Qatar University
Aliyari Shoorehdeli, Mahdi	K.N. Toosi University of Technology
Keywords: Fault detection and diagnosis Abstract: Monitoring of industrial systems for anomalies such as faults and cyber-attacks as unknown and extremely undesirable inputs in the presence of other inputs (like disturbances) is an important issue for ensuring the safety and the reliability of their operation. In this study, a robust anomaly detection filter is proposed for continuous linear Roesser systems using dynamic observer framework. Sufficient conditions for the existence of the observer and its sensitivity to anomaly as well as its robustness to disturbances are addressed via linear matrix inequalities (LMIs). The mentioned sensitivity and robustness are based on the H_- and H_infty performance indices, respectively. Finally, the performance of the proposed observer is demonstrated through a numerical example.
Paper VI111-11.7
PDF · Video · A Novel Probabilistic Fault Detection Scheme with Adjustable Reliability Estimates
Wang, Changren	Tsinghua University
Shang, Chao	Tsinghua University
Huang, Dexian	Tsinghua University
Yu, Bin	Hengli Petrochemical Co., Ltd
Keywords: Fault detection and diagnosis Abstract: We propose a novel probabilistic fault detection scheme with adjustable reliability estimates. Our scheme consists of two phase, the first is the modelling phase, where a probabilistic fault detection design is devised, while the second is the validation phase, where reliability estimates of the design are adjusted online according to new operation records of the plant and the validated reliability. The modelling phase is based on two methods: residual generation, such as parity space, which is an important tool in fault detection problem, and scenario approach, which is a seminal trick to transfer intractable optimization problem into approximate tractable optimization problem and ensure reliability guarantees. The validation phase leverages the state-of-art posteriori probabilistic bounds of convex scenario programs with validation tests. Such a holistic design-and-validate scheme will can help technicians to make better decision. The efficacy of the proposed approach is illustrated on a simulated case study
Paper VI111-11.8
PDF · Video · A Model-Based Fault-Detection Strategy in DC/AC Conversion
Pyrkin, Anton	ITMO University
Cisneros, Rafael	FREEDM-NCSU
Campos-Delgado, Daniel U.	UASLP
Bobtsov, Alexey	ITMO University
Somov, Sergey	ITMO University
Keywords: Fault detection and diagnosis, Adaptive observer design, Estimation and filtering Abstract: An open-circuit fault-detection strategy is here proposed for single-phase DC/AC conversion. The power converter under consideration consists of an H-bridge and a capacitor with parallel resistance and current source in its DC side-these last two stand for the unknown system load and energy injection from renewable resources, respectively. An inductor filter is also included as a coupling element to the AC network. When an open-circuit fault occurs in the H-bridge, the resulting AC output waveform is asymmetric, and induces DC and harmonic components to the network. Hence, by using an additive fault modeling, the fault signature can be expressed by a constant term f_dc and a fluctuating signal. The sign of f_dc allows to determine the pair of faulty switches in the H-bridge. In this work, an DREM-based identification scheme is proposed to estimate f_dc. Through the sign of its estimate, it is possible to detect the pair of faulty switches. To assess our approaches, simulation results are included.
Paper VI111-11.9
PDF · Video · Robust Actuator Fault Diagnosis Algorithm for Autonomous Hexacopter UAVs
González Rot, Antonio	Southern Denmark University
Hasan, Agus	University of Southern Denmark
Manoonpong, Poramate	University of Southern Denmark
Keywords: Fault detection and diagnosis, Adaptive observer design, Mechanical and aerospace estimation Abstract: This paper presents a robust actuator fault diagnosis algorithm for hexacopter Unmanned Aerial Vehicles (UAVs). The algorithm, based on Adaptive eXogenous Kalman Filter (AXKF), consists of two-stage operations: (i) a nonlinear observer and (ii) a linearized adaptive Kalman filter. To this end, we provide a sufficient condition for the nonlinear observer and recursive formulas for the linearized adaptive Kalman filter. The algorithm is tested for actuator fault diagnosis of a hexacopter UAV. Simulation results show that the proposed cascaded algorithm is able to accurately estimate the magnitude of the actuator fault.
Paper VI111-11.10
PDF · Video · Distributed H−/L∞ Fault Detection Observer Design for Linear Systems
Han, Weixin	Northwestern Polytechnical University
Trentelman, Harry L.	Univ. of Groningen
Xu, Bin	Nanyang Technological University
Keywords: Fault detection and diagnosis, Distributed control and estimation, Sensor networks Abstract: This paper studies the distributed fault detection problem for linear time-invariant (LTI) systems with distributed measurement output. A distributed H−/L∞ fault detection observer (DFDO) design method is proposed to detect actuator faults of the monitored system in the presence of a bounded process disturbances. The DFDO consists of a network of local fault detection observers, which communicate with their neighbors as prescribed by a given network graph. By using finite-frequency H− performance, the residual in fault detection is sensitive to fault in the interested frequency-domain. The residual is robust against effects of the external process disturbance by L∞ analysis. A systematic algorithm for DFDO design is addressed and the residual thresholds are calculated in our distributed fault detection scheme. Finally, we use a numerical simulation to demonstrate the effectiveness of the proposed distributed fault detection approach.
Paper VI111-11.11
PDF · Video · Intermittent Fault Detection for Nonlinear Stochastic Systems
Niu, Yichun	China University of Petroleum
Sheng, Li	China University of Petroleum (East China)
Gao, Ming	China University of Petroleum (East China)
Zhou, Donghua	Shandong Univ. of Science and Technology
Keywords: Fault detection and diagnosis, Estimation and filtering Abstract: In this paper, the problem of intermittent fault detection is investigated for nonlinear stochastic systems. The moving horizon estimation with dynamic weight matrices is proposed, where the weight matrices are adjusted by an unreliability index of prior estimate to avoid the smearing effects of intermittent faults. Based on the particle swarm optimization algorithm, the nonlinear optimization problem is solved and the approximate estimate is derived. Finally, the feasibility and effectiveness of the proposed algorithm are validated by a numerical example.
Paper VI111-11.12
PDF · Video · Asymmetrical Load Mitigation of Wind Turbine Pitch Actuator Faults Using Unknown Input-Based Fault-Tolerant Control (I)
Liu, Yanhua	University of Hull
Patton, Ron J.	Univ. of Hull
Shi, Shuo	University of Hull
Keywords: Fault detection and diagnosis, Estimation and filtering Abstract: Offshore wind turbines suffer from asymmetrical blade loading, resulting in enhanced structural fatigue. Individual pitch control (IPC) is an effective method to achieve blade load mitigation, accompanied by enhancing the pitch movements and thus increased the probability of pitch actuator faults. The occurrence of faults will deteriorate the IPC load mitigation performance, which requires fault-tolerant control (FTC). IPC is itself analogous to the FTC problem because the action of rotor bending can be considered as a fault effect. Therefore, the work thus proposes a "co-design" strategy, constituting a combination of IPC-based asymmetrical load mitigation combined with FTC acting at the pitch system level. The FTC uses the well-known fault estimation and compensation strategy. A Proportional-Integral PI-based IPC strategy for blade mitigation is proposed in which the robust fault estimation is achieved using a robust unknown input observer (UIO). The performance of two pitch controllers (baseline pitch controller, PI-based IPC) are compared in the presence of pitch actuator faults (including low pressure & loss of effectiveness). The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system.
Paper VI111-11.13
PDF · Video · Damage Identification for the Tree-Like Network through Frequency-Domain Modeling
Ni, Xiangyu	University of Notre Dame
Goodwine, Bill	University of Notre Dame
Keywords: Fault detection and diagnosis, Frequency domain identification, Multi-agent systems Abstract: In this paper, we propose a method to identify the damaged component and quantify its damage amount in a large network given its overall frequency response. The identification procedure takes advantage of our previous work which exactly models the frequency response of that large network when it is damaged. As a result, the test shows that our method works well when some noise present in the frequency response measurement. In addition, the effects brought by a damaged component which is located deep inside that large network are also discussed.
Paper VI111-11.14
PDF · Video · A Sensor-To-Sensor Model-Based Change Detection Approach for Quadcopters
Ho, Du	Linköping University
Hendeby, Gustaf	Linköpings Universitet
Enqvist, Martin	Linköping University
Keywords: Fault detection and diagnosis, Grey box modelling, Channel estimation/equalisation Abstract: This paper addresses the problem of change detection for a quadcopter in the presence of wind disturbances. Different aspects of the quadcopter dynamics and various flight conditions have been investigated. First, the wind is modeled using the Dryden wind model as a sum of a low-frequent and a turbulent part. Since the closed-loop control can compensate for system changes and disturbances and the effect of the wind disturbance is significant, the residuals obtained from a standard simulation model can be misleading. Instead, a sensor-to-sensor submodel of the quadcopter is selected to detect a change in the payload using the Instrumental Variables (IV) cost function. It is shown that the mass variation can be detected using the IV cost function in different flight scenarios.
Paper VI111-11.15
PDF · Video · On the Choice of Multiple Flat Outputs for Fault Detection and Isolation of a Flat System
Rammal, Rim	University of Bordeaux
Airimitoaie, Tudor-Bogdan	Univ. Bordeaux
Cazaurang, Franck	Univ. Bordeaux I
Levine, Jean	Ecole Des Mines, CAS
Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Keywords: Fault detection and diagnosis, Identifiability, Filtering and smoothing Abstract: This paper presents a rigorous definition of the isolability of a fault in a flat system whose flat outputs are measured by sensors that are subject to faults. In particular, if only one sensor or actuator is faulty at a time, we show that the isolation of faults can be achieved if a pair of flat outputs satisfies some independence condition. A detailed characterization of this condition is presented. Finally, the pertinence of the isolability concept is demonstrated on the example of a three tank system.
Paper VI111-11.16
PDF · Video · Robust Fault Detection and Isolation of Discrete-Time LPV Systems Combining Set-Theoretic UIO and Invariant Sets
Tan, Junbo	Tsinghua University
Xu, Feng	Tsinghua Univerisity
Yang, Jun	Tsinghua University
Wang, Xueqian	Tsinghua University
Liang, Bin	Tsinghua University
Keywords: Fault detection and diagnosis, LPV system identification, Stability and stabilization of hybrid systems Abstract: This paper proposes a mixed active/passive robust fault detection and isolation (FDI) method for discrete-time linear paramter varying (LPV) systems based on set-theoretic unknown input observers (SUIO) and invariant sets. The robustness against system uncertainties (i.e., process disturbances, measurement noises and so on) in FDI of LPV systems can be guaranteed by actively decoupling or passively bounding their effect on residual signal. Furthermore, the quadratic H1 stability condition of the LPV-form state-estimation-error dynamics is established based on a group of linear matrix inequalities (LMIs). Under the precondition of stability, a family of residual sets are constructed to establish set-separation guaranteed fault isolation (FI) conditions using invariant sets off-line. As long as the occurred faults satisfy the guaranteed FI conditions, they can be isolated from each other. At the end, a numerical example is used to illustrate the effectiveness of the proposed method.
Paper VI111-11.17
PDF · Video · Improved Process Diagnosis Using Fault Contribution Plots from Sparse Autoencoders
Hallgrímsson, ásgeir Daniel	Technical University of Denmark
Niemann, Henrik	Technical University of Denmark
Lind, Morten	Technical University of Denmark
Keywords: Fault detection and diagnosis, Machine learning, Grey box modelling Abstract: Development of model-based fault diagnosis methods is a challenge when industrial systems are large and exhibit complex process behavior. Latent projection (LP), a statistical method that extract features of data via dimensionality reduction, is an alternative approach to diagnosis as it can be formulated to not rely on process knowledge. However, LP methods may perform poorly at identifying abnormal process variables due a "fault smearing" effect - variables unaffected by a fault are unintentionally characterized as being abnormal. The effect occurs because data compression permits faulty and non-faulty variables to interact. This paper presents an autoencoder (AE), a nonlinear LP method based on neural networks, as a monitoring method of a simulated nonlinear triple tank process (TTP). Simulated process data was used to train the AE to generate a monitoring statistic representing the condition of the TTP. Sparsity was introduced in the AE to reduce variable interactivity. The AE's ability to detect a fault was demonstrated. The individual contributions of process variables to the AE's monitoring statistic were analyzed to reveal the process variables that were no longer consistent with normal operating conditions. The key result in this study was that sparsity reduced fault smearing onto unaffected variables and increased the contributions of actual faulty variables.
Paper VI111-11.18
PDF · Video · Tension Monitoring of Toothed Belt Drives Using Interval-Based Spectral Features
Fehsenfeld, Moritz	Leibniz University Hannover
Johannes, Kühn	Lenze Automation GmbH
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Fault detection and diagnosis, Machine learning, Time series modelling Abstract: Toothed belt drives are used in manifold automation applications. But only if the belt tension is properly adjusted, optimal working conditions are ensured. A loss of efficiency or even breakdowns might be the consequences otherwise. For this reason, tension monitoring reduces operation costs and may prevent failures. In order to meet industrial requirements, the monitoring is supposed to rely on standard sensor data. From this data, features are extracted in time and frequency domain which are passed on to a random forest. For further improvement, a segmentation of the frequency spectrum is performed beforehand. In this way, interval-based spectral features can be extracted to capture small distinctive parts in the frequency domain. For this purpose, two different segmentation procedures are compared in a random forest regression. A belt drive powered by a 1.9 kW synchronous servomotor is used to evaluate the proposed approaches in two different industrial scenarios. The experimental results show that both segmentation methods enhance the performance of a tree-based regression and offer a reliable tension prediction.
Paper VI111-11.19
PDF · Video · Actuation Failure Detection in Fixed-Wing Aircraft Combining a Pair of Two-Stage Kalman Filters
de Angelis Cordeiro, Rafael	Instituto Superior Técnico
Azinheira, José Raúl	Instituto Superior Técnico - Technical Univ of Lisbon
Moutinho, Alexandra	IDMEC/LAETA, Instituto Superior Técnico, Universidade De Lisboa
Keywords: Fault detection and diagnosis, Mechanical and aerospace estimation Abstract: Actuation failure is one of the causes of loss of control in-flight accidents. Aircraft usually have multiple redundant actuators to mitigate failures, and Failure Detection and Isolation Systems (FDIS) are used to diagnose failures and reconfigure software/hardware to enhance safety. However, the large number of redundant actuators interferes with the FDIS. To detect and isolate failures in fixed-wing aircraft with redundant actuators, this work proposes the combined use of two different strategies of the Two-Stage Kalman Filter. A Supervisory Loop is included using heuristics and statistics to diagnose the actuators, and a Feed-Forward Differential is implemented to improve the isolation process without interfering with the aircraft flight. The solution is evaluated in the detection of an aileron failure in a Boeing 747 simulator.
Paper VI111-11.20
PDF · Video · Sensor Fault Identification in Nonlinear Dynamic Systems
Zhirabok, Alexey N.	Far Eastern Federal Univ
Zuev, Alexander	Far Eastern Federal University
Shumsky, Alexey	Far Eastern Federal University
Keywords: Fault detection and diagnosis, Nonlinear system identification Abstract: The problem of sensor fault diagnosis in technical systems described by nonlinear dynamic models is considered. To address the problem, sliding mode observers are used. The suggested approach for constructing sliding mode observers is based on the reduced order model of the initial system. This allows to reduce complexity of sliding mode observers and relax the limitations imposed on the initial system.
Paper VI111-11.21
PDF · Video · A Jump-Markov Regularized Particle Filter for the Estimation of Ambiguous Sensor Faults
Iglesis, Enzo	ONERA
Dahia, Karim	ONERA
Piet-Lahanier, Helene	ONERA
Merlinge, Nicolas	ONERA
Horri, Nadjim	University of Coventry
Brusey, James	Coventry University
Keywords: Fault detection and diagnosis, Particle filtering/Monte Carlo methods, Diagnosis of discrete event and hybrid systems Abstract: Sensor or actuator faults occurring on a Unmanned Aerial Vehicle (UAV) can compromise the system integrity. Fault diagnosis methods is then becoming a required feature for those systems. In this paper, the focus is on fault estimation for a fixed-wing UAVs in the presence of simultaneous sensor faults. The altitude measurements of a UAV are commonly obtained from the combination of two different types of sensors: a Global Navigation Satellite System (GNSS) receiver and a barometer. Both sensors are subject to additive abrupt faults. To deal with the multimodal nature of the faulty modes, a Jump-Markov Regularized Particle Filter (JMRPF) is proposed in this paper to estimate the barometric altitude and GNSS altitude measurement faults, including the case when both faults occur simultaneously. This method is based on a regularization step that improves the robustness thanks to the approximation of the conditional density by a kernel mixture. In addition, the new jump strategy estimates the correct failure mode in 100% of the 100 simulations performed in this paper. This approach is compared with an Interacting Multiple Model Kalman Filter (IMM-KF) and the results show that the JMRPF outperforms the IMM-KF approach, particularly in the ambiguous case when both sensors are simultaneously subject to additive abrupt faults.
Paper VI111-11.22
PDF · Video · Sensitivity Analysis of Bias in Satellite Sea Surface Temperature Measurements
Eichhorn, Mike	Technische Universität Ilmenau
Shardt, Yuri A.W.	Technical University of Ilmenau
Gradone, Joseph	Teledyne Webb Research
Allsup, Ben	Teledyne Webb Research
Keywords: Fault detection and diagnosis, Particle filtering/Monte Carlo methods, Randomized methods Abstract: The satellite sea surface temperature (SST) measurement is based on the detection of ocean radiation using microwave or infrared wavelengths within the electromagnetic spectrum. The radiance of individual wavelengths can be converted into brightness temperatures for using in SST determination. The calibration and validation of the determined SST data require reference measurements from in-situ observations. These in-situ observations are from various platforms such as ships, drifters, floats and mooring buoys and require a high measurement accuracy. This paper presents an investigation about the possibility of using a glider as possible in-situ platform. A glider is a type of autonomous underwater vehicle (AUV) which can log oceanographic data over a period of up to one year by following predetermined routes. In contrast to buoys, a glider allows a targeted investigation of regional anomalies in SST circulations. To assess the quality of SST observations from a glider, logged data from a glider mission in the Atlantic Ocean from 2018 to 2019 and corresponding satellite SST data were used. The influence of variables (e.g. measurement depth, latitude, view zenith angle, local solar time) of the bias between satellite and glider SST data was investigated using sensitivity analysis. A new and efficient distribution-based method for global sensitivity analyzes, called PAWN, was used successfully. Interested readers will find information about its operation principle and the usage for passive observations where only ``given-data'' are available.
Paper VI111-11.23
PDF · Video · Distributed Detection and Isolation of Covert Cyber Attacks for a Class of Interconnected Systems
Al-Dabbagh, Ahmad	Imperial College London
Barboni, Angelo	Imperial College London
Parisini, Thomas	Imperial College & Univ. of Trieste
Keywords: Fault detection and diagnosis, Secure networked control systems Abstract: This paper deals with a topology for a class of interconnected systems, referred to as a highly interconnected system, consisting of interconnected plants and local controllers. We address the respective cyber attack surfaces as well as a design approach for detection and isolation of covert cyber attacks. For each pair of plant and controller, a cyber attack is implemented by a malicious agent, and its detection and isolation are achieved by associating the controller with two observers. These observers estimate the states of the plant, and compare the estimated states to determine if a neighbouring plant is under a covert cyber attack. The paper presents the modelling of the topology, the analysis of the covertness of cyber attacks, the design approach for the detection and isolation as well as a required existence condition. Simulation results are provided for the application of the design approach to interconnected pendula systems that are subject to a covert cyber attack.
Paper VI111-11.24
PDF · Video · Distributed Fault Diagnosis for a Class of Time-Varying Systems Over Sensor Networks with Stochastic Protocol
Liu, Yuxia	China University of Petroleum (East China)
Sheng, Li	China University of Petroleum (East China)
Gao, Ming	China University of Petroleum (East China)
Keywords: Fault detection and diagnosis, Sensor networks, Estimation and filtering Abstract: This paper is concerned with the distributed fault diagnosis problem for a class of time-varying systems over sensor networks with nonlinearity and uncertainty. For the purpose of solving the problem of data conflict, the stochastic protocol is used to determine which node has the right to send data to the estimator at a certain transmission time. The aim of this paper is to design a set of distributed estimators to detect, isolate and estimate fault signals. The upper bound of estimation error covariance is obtained by solving two recursive matrix equations and the upper bound can be minimized by designing appropriate estimator gain at each step. Finally, a numerical example is provided to show the effectiveness of the proposed design scheme.
Paper VI111-11.25
PDF · Video · A Preventive Maintenance Strategy for an Actuator Using Markov Chains
Alina, Pricopie	Dunarea De Jos University of Galati
Frangu, Laurentiu	Dunarea De Jos University of Galati
Vilanova, Ramon	Universitat Autònoma De Barcelona
Caraman, Sergiu	Dunarea De Jos University
Keywords: Fault detection and diagnosis, Stochastic system identification, Synthesis of stochastic systems Abstract: This paper deals with a proactive maintenance strategy used to increase the reliability of equipment. A predicting schedule of the renewal interventions will be proposed so as to ensure optimal maintenance for the equipment. Hence, the goal is to find the optimal time which is the most profitable to carry out the equipment renewal operations. The deterioration process is modeled by Markov chains, which is capable to provide information about the tendency of the equipment state. For the optimization of the maintenance a preventive strategy based on the average maintenance cost was used. The minimum maintenance average cost corresponds to the optimal time when it is most efficient to stop the equipment operation and to renew it.
Paper VI111-11.26
PDF · Video · A Novel Fault Diagnosis Method Based on Stacked LSTM
Zhang, Qingqing	University of Electronic Science and Technology of China
Zhang, Jiyang	University of Electronic Science and Technology of China
Zou, Jianxiao	School of Automation Engineering, University of Electronic Scien
Shicai, Fan	University of Electronic Science and Technology of China
Keywords: Fault detection and diagnosis, Time series modelling, Machine learning Abstract: Fault diagnosis is essential to ensure the operation security and economic efficiency of the chemical system. Many fault diagnosis methods have been designed for the chemical process, but most of them ignore the temporal correlation in the sequential observation signals of the chemical process. A novel deep learning method based on Stacked Long Short-Term Memory (LSTM) neural network is proposed, which can effectively model sequential data and detect the abnormal values. The proposed method is also able to fully exploit the long-term dependencies information in raw data and adaptively extract the representative features. The dataset of Tennessee Eastman (TE) process is utilized to verify the practicability and superiority of the proposed method. Extensive experimental results show that the fault detection and diagnosis model we proposed has an excellent performance when compared with several state-of-the-art baseline methods.
Paper VI111-11.27
PDF · Video · Mixed Stochastic Process Modelling for Accelerated Degradation Testing
Li, Yang	Nanjing University of Aeronautics and Astronautics
Liu, Yue	China North Vehicle Research Institute
Zio, Enrico	Ecole Centrale Paris, Supelec and Politecnico Di Milano
Lu, Ningyun	Nanjing University of Aeronautics and Astronautics
Wang, Xiuli	Nanjing University of Aeronautics and Astronautics
Jiang, Bin	Nanjing University of Aeronautics and Astronautics
Keywords: Fault detection and diagnosis, Time series modelling, Mechanical and aerospace estimation Abstract: Accelerated degradation testing (ADT) is used to efficiently assess the reliability and lifetime of a high reliable products under normal stress. In general, it is common in practice to build stochastic models of degradation under a single failure mechanism based on the ADT data. However, in real applications, multi-failure mechanisms may influence the degradation process. Motivated by this, a mixed stochastic process model for ADT is proposed in this paper. The mixed stochastic process combines two singlestochastic processes with weights determined by a quantitative method that establishes the relationship with accelerated stress. After the unknown parameter estimation, the proposed model under normal stress level can be obtained. The results show that the proposed model can be used for ADT modeling under multi-failure mechanisms.
Paper VI111-11.28
PDF · Video · Condition Monitoring of Electric-Cam Mechanisms Based on Model-Of-Signals of the Drive Current Higher-Order Differences
Barbieri, Matteo	Alma Mater Studiorum - University of Bologna
Diversi, Roberto	University of Bologna
Tilli, Andrea	University of Bologna
Keywords: Fault detection and diagnosis, Time series modelling, Recursive identification Abstract: Condition monitoring of electric motor driven mechanisms is of great importance in industrial machines. The knowledge of the actual health state of such components permits to address maintenance policies which results in better exploitation of their actual operational life span and consequently in maintenance cost reduction. In this paper, we exploit the way electric cams are implemented on the vast majority of PLC/Motion controllers to develop a suitable condition monitoring procedure. This technique relies on computing the higher-order differences of the current absorbed by slave motors to get signals that do not depend on a priori knowledge of the cam trajectory and of the mechanism nominal model. Subsequently, we will use these data in the Model-of-Signals framework, to gather information on the mechanism's health condition, which in turn can be used to perform predictive maintenance policies. The differenced signal is modelled as an ARMA process and the model capabilities in condition monitoring are then shown in simulation and experimental application. Besides, this framework allows exploiting the edge-computing capabilities of the machinery controllers by implementing recursive estimation algorithms.
Paper VI111-11.29
PDF · Video · A Timed Model for Discrete Event System Identification and Fault Detection
de Souza, Ryan Pitanga Cleto	Federal University of Rio De Janeiro
Moreira, Marcos Vicente	Univ. Fed. Rio De Janeiro
Lesage, Jean-Jacques	ENS De Cachan
Keywords: Closed loop identification, Fault detection and diagnosis, Diagnosis of discrete event and hybrid systems Abstract: We present in this paper a timed discrete event model for system identification with the aim of fault detection, called Timed Automaton with Outputs and Conditional Transitions (TAOCT). The TAOCT is an extension of a recent untimed model proposed in the literature, called Deterministic Automaton with Outputs and Conditional Transitions (DAOCT). Differently from the DAOCT, where only the logical behavior of the discrete event system is considered, the TAOCT takes into account information about the time that the events are observed, and, for this reason, it can be used for the detection of faults that cannot be detected by using untimed models, such as faults that lead the fault detector to deadlocks. The TAOCT represents the fault-free system behavior, and a fault is detected when the observed behavior is different from the behavior predicted by the model, considering both logical and timing information. A practical example is used to illustrate the results of the paper.
Paper VI111-11.30
PDF · Video · Design of Hypervelocity-Impact Damage Assessment Technique Based on Variational Bayesian
Zhang, Haonan	University of Electronic Science and Technology of China
Yin, Chun	University of ElectronicScience and Technology of China, Chengdu6
Huang, Xuegang	China Aerodynamics Research & Development Center
Dadras, Sara	Utah State University
Chen, Kai	University of Electronic Science and Technology of China
Dadras, Soudeh	UC Merced
Zhu, Bing	Beihang University
Keywords: Mechanical and aerospace estimation, Bayesian methods, Fault detection and diagnosis Abstract: In this paper, a damage assessment framework based on the infrared technology is proposed to assess the damage of the spacecraft. This framework mainly contains three steps. Firstly, a damage reconstruction model based on sparse model is proposed to reconstruct the damage image of different layers. To estimate the parameter of the model, variational Bayesian is used for calculating the parameters. Secondly, a damage extraction method is used to eliminate noise in the images. At the same time, this procedure can effectively make the weak subsurface damage more clear. Finally, in order to compare the location of surface and subsurface damage, image fusion method is used to achieve damage fusion. In the experiment, the proposed framework is used for the Whipple shield detection, both images and evaluation parameters show the effectiveness and high-accuracy of the new model.
Paper VI111-11.31
PDF · Video · GMM-Based Automatic Defect Recognition Algorithm for Pressure Vessels Defect Detection through ECPT
Yang, Xiao	University of Electronic Science and Technology of China
Huang, Xuegang	China Aerodynamics Research & Development Center
Yin, Chun	University of ElectronicScience and Technology of China, Chengdu6
Cheng, Yu-hua	University of Electronic Science and Technology of China
Dadras, Sara	Utah State University
Keywords: Mechanical and aerospace estimation, Fault detection and diagnosis, Stochastic hybrid systems Abstract: In order to realize the automatic identification of pressure vessel defects, an improved adaptive defect recognition feature extraction algorithm through ECPT (Eddy current pulsed thermography) is proposed. The proposed feature extraction algorithm consists of five elements: thermal image data segmentation, variable interval search, probability density function modeling, data classification, and reconstructed image acquisition. The combination of data block selection and variable interval search can reduce the double counting. And the KG-EM (Kmeans-GMM-EM) algorithm is proposed to obtain the Gaussian mixture model corresponding to the classification, and thus the corresponding probability is obtained to classify the TTRs (Transient Thermal Response). The reconstructed thermal image is obtained by the classified TTRs. This method can extract the main information of the image accurately and efficiently. Experimental results are provided to demonstrate their effectiveness.
Paper VI111-11.32
PDF · Video · Health-Aware LPV Model Predictive Control of Wind Turbines (I)
Boutros, Khoury	UPC
Nejjari, Fatiha	Universitat Politecnica De Catalunya
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Keywords: Supervisory control and automata, Fault detection and diagnosis Abstract: Wind turbines components are subject to considerable stresses and fatigue due to extreme environmental conditions to which are exposed, especially those located offshore. Interest in the integration of control with life estimation of components has increased in recent years. The integration of a systems health management module with MPC control provides the wind turbine a mechanism to operate safely and optimize the tradeoff between components life and energy production. In this paper, a health-aware LPV model predictive control approach for wind turbines is proposed. The proposed controller establish a trade-off between the economic objective based on maximizing the energy production but at the same time maximizing the remaining useful life. The controller uses an LPV model for dealing with the non-linearity of the wind turbine model. The proposed approach is tested on a well-known wind turbine case study.
Paper VI111-11.33
PDF · Video · Interpretable Deep Learning for Monitoring Combustion Instability
Gangopadhyay, Tryambak	Iowa State University
Tan, Sin Yong	Iowa State University
Locurto, Anthony	Iowa State University
Michael, James B.	Iowa State University
Sarkar, Soumik	Iowa State University
Keywords: Machine learning, Fault detection and diagnosis, Mechanical and aerospace estimation Abstract: Transitions from stable to unstable states occurring in dynamical systems can be sudden leading to catastrophic failure and huge revenue loss. For detecting these transitions during operation, it is of utmost importance to develop an accurate data-driven framework that is robust enough to classify stable and unstable scenarios. In this paper, we propose deep learning frameworks that show remarkable accuracy in the classification task of combustion instability on carefully designed diverse training and test sets. We train our model with data from a laboratory-scale combustion system showing stable and unstable states. The dataset is multimodal with correlated data of hi-speed video and acoustic signals. We develop a labeling mechanism for sequences by implementing Kullback–Leibler Divergence on the time-series data. We develop deep learning frameworks using 3D Convolutional Neural Network and Long Short Term Memory network for this classification task. To go beyond the accuracy and to gain insights into the predictions, we incorporate attention mechanism across the time-steps. This aids in understanding the time-periods which contribute significantly to the prediction outcome. We validate the insights from a domain knowledge perspective. By exploring inside the accurate black-box models, this framework can be used for the development of better detection frameworks in different dynamical systems.
Paper VI111-11.34
PDF · Video · Memoryless Cumulative Sign Detector for Stealthy CPS Sensor Attacks
Bonczek, Paul	University of Virginia
Bezzo, Nicola	University of Virginia
Keywords: Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Modeling, supervision, control and diagnosis of automotive systems, Autonomous Vehicles Abstract: Stealthy false data injection attacks on cyber-physical systems introduce erroneous measurements onto sensors with the intent to degrade system performance. An intelligent attacker can design stealthy attacks with knowledge of the system model and noise characteristics to evade detection from state-of-the-art fault detectors by remaining within detection thresholds. However, during these hidden attacks, an attacker with the intention of hijacking a system will leave traces of non-random behavior that contradict with the expectation of the system model. Given these premises, in this paper we propose a run-time monitor called Cumulative Sign (CUSIGN) detector, for identifying stealthy falsified measurements by identifying if measurements are no longer behaving in a random manner. Specifically, our proposed CUSIGN monitor considers the changes in sign of the measurement residuals and their expected occurrence in order to detect if a sensor could be compromised. Moreover, our detector is designed to be a memoryless procedure, eliminating the need to store large sequences of data for attack detection. We characterize the detection capabilities of the proposed CUSIGN technique following the well-known chi2 failure detection scheme. Additionally, we show the advantage of augmenting CUSIGN to the model-based Cumulative Sum (CUSUM) detector, which provides magnitude bounds on attacks, for enhanced detection of sensor spoofing attacks. Our approach is validated with simulations on an unmanned ground vehicle (UGV) during a navigation case study.

VI111-12
Identification for Control	Regular Session
Chair: Tanaka, Hideyuki	Hiroshima University
Co-Chair: Mitrishkin, Yuri	M.V. Lomonosov Moscow State University
Paper VI111-12.1
PDF · Video · Model Error Modelling Using a Stochastic Embedding Approach with Gaussian Mixture Models for FIR Systems
Orellana Prato, Rafael Angel	Universidad Técnica Federico Santa Maria
Carvajal, Rodrigo	Universidad Tecnica Federico Santa Maria
Aguero, Juan C.	Universidad Santa Maria
Goodwin, Graham C.	University of Newcastle
Keywords: Identification for control Abstract: In this paper a Maximum Likelihood estimation algorithm for error-model modelling using a stochastic embedding approach is developed. The error-model distribution is approximated by a finite Gaussian mixture. An Expectation-Maximization based algorithm is proposed to estimate the nominal model and the distribution of the parameters of the error-model by using the data from independent experiments. The benefits of our proposal are illustrated via numerical simulations.
Paper VI111-12.2
PDF · Video · Identification of Ill-Conditioned Systems Using Output Rotation
Friman, Mats	Neles
Keywords: Identification for control Abstract: A new method for identification of ill-conditioned systems is suggested. Our aim is to provide a solution that is practical and functional in the sense that no initial knowledge about process is needed, light-weight tools can be used for identification (e.g. simple ARX models with standard least-squares regression), and model structures with minimal number of parameters and states are used. The main idea is to employ principal component analysis (PCA) to rotate the outputs before identifying the process in directions important for control.
Paper VI111-12.3
PDF · Video · The Plasma Shape Control System in the Tokamak with the Artificial Neural Network As a Plasma Equilibrium Reconstruction Algorithm
Prokhorov, Artem	Lomonosov Moscow State University
Mitrishkin, Yuri	M.V. Lomonosov Moscow State University
Korenev, Pavel	V.A. Trapeznikov Institute of Control Sciences
Patrov, Mikhail	Ioffe Physical Technical Institute of the Russian Academy of Sci
Keywords: Identification for control, Closed loop identification, Experiment design Abstract: The problem of accurate plasma shape control is significant, both for modern tokamaks, for example for the Globus-M/M2 spherical tokamak, and for future thermonuclear tokamak-reactors using magnetic plasma confinement. The article presents the new results of design and modeling the plasma shape control system for the Globus-M/M2 spherical tokamak with the pre-trained neural network as a plasma equilibrium reconstruction algorithm, which is included in the feedback of the system. To collect the necessary data for training the neural network the developed magnetic plasma evolutionary code was used.
Paper VI111-12.4
PDF · Video · EM-Based Identification of Static Errors-In-Variables Systems Utilizing Gaussian Mixture Models
Cedeño, Angel L.	Universidad Técnica Federico Santa María
Orellana Prato, Rafael Angel	Universidad Técnica Federico Santa Maria
Carvajal, Rodrigo	Universidad Tecnica Federico Santa Maria
Aguero, Juan C.	Universidad Santa Maria
Keywords: Errors in variables identification Abstract: In this paper we address the problem of identifying a static errors-in-variables system. Our proposal is based on the Expectation-Maximization algorithm, in which we consider that the distribution of the noise-free input is approximated by a finite Gaussian mixture. This approach allows us to estimate the static system parameters, the input and output noise variances, and the Gaussian mixture parameters. We show the benefits of our proposal via numerical simulations.
Paper VI111-12.5
PDF · Video · A Data-Driven Immersion Technique for Linearization of Discrete-Time Nonlinear Systems
Wang, Zheming	Université Catholique De Louvain
Jungers, Raphaël M.	Université Catholique De Louvain
Keywords: Identification for control, Nonlinear system identification, Time series modelling Abstract: This paper proposes a data-driven immersion approach to obtain linear equivalents or approximations of discrete-time nonlinear systems. Exact linearization can only be achieved for very particular classes of systems. In general cases, we aim to obtain a finite-time linear approximation. Our approach only takes a finite set of trajectories and hence an analytic model is not required. The mismatch between the approximate linear model and the original system is concretely discussed with formal bounds. We also provide a Koopman-operator interpretation of this technique, which shows a link between system immersibility and the Koopman operator theory. Several numerical examples are taken to show the capabilities of the proposed immersion approach. Comparison is also made with other Koopman-based lifting approaches which use radial basis functions and monomials.
Paper VI111-12.6
PDF · Video · Identification of a Class of Hybrid Dynamical Systems
Massaroli, Stefano	The University of Tokyo
Califano, Federico	University of Twente
Faragasso, Angela	The Univeristy of Tokyo
Risiglione, Mattia	ETH Zurich
Yamashita, Atsushi	The University of Tokyo
Asama, Hajime	The University of Tokyo
Keywords: Recursive identification, Identification for control, Discrete event modeling and simulation Abstract: This paper presents a novel identification procedure for a class of hybrid dynamical systems. In particular, we consider hybrid dynamical systems which are single flowed and single jumped and whose flow and jump maps linearly depend on two sets of unknown parameters. A systematic way to determine whether the system is flowing or jumping is introduced and used to identify the unknown parameters by employing a linear recursive estimator. Simulations have been performed to prove the validity of the proposed methodology. Results proved the efficiency and accuracy of the developed identification procedure.
Paper VI111-12.7
PDF · Video · Efficient Iterative Solvers in the Least Squares Method
Stotsky, Alexander A.	Chalmers University of Technology
Keywords: Recursive identification, Identification for control, Time series modelling Abstract: Fast convergent, accurate, computationally efficient, parallelizable, and robust matrix inversion and parameter estimation algorithms are required in many time-critical and accuracy-critical applications such as system identification, signal and image processing, network and big data analysis, machine learning and in many others. This paper introduces new composite power series expansion with optionally chosen rates (which can be calculated simultaneously on parallel units with different computational capacities) for further convergence rate improvement of high order Newton-Schulz iteration. New expansion was integrated into the Richardson iteration and resulted in significant convergence rate improvement. The improvement is quantified via explicit transient models for estimation errors and by simulations. In addition, the recursive and computationally efficient version of the combination of Richardson iteration and Newton-Schulz iteration with composite expansion is developed for simultaneous calculations. Moreover, unified factorization is developed in this paper in the form of tool-kit for power series expansion, which results in a new family of computationally efficient Newton-Schulz algorithms.
Paper VI111-12.8
PDF · Video · An Estimation Method of Innovations Model in Closed-Loop Environment with Lower Horizons
Ikeda, Kenji	Tokushima University
Tanaka, Hideyuki	Hiroshima University
Keywords: Subspace methods, Closed loop identification, Identification for control Abstract: This paper proposes an estimation method of the innovations model in closed loop environment by using the estimate of the innovations process. The estimate of the innovations process from the finite interval of data has a bias, so are the estimate of the proposed method. However, it is analyzed that the bias can be reduced. The Kalman gain and the covariance of the innovations process are estimated by using a semi-definite programming problem previously proposed by the authors. Numerical simulation illustrates the proposed method gives better performance than Closed-Loop MOESP and PBSID when the data length is large and the past horizon is selected low.
Paper VI111-12.9
PDF · Video · MPC Closed-Loop Identification without Excitation
Zhu, Yun	Zhejiang University
Yan, Wengang	Zhejiang University
Zhu, Yucai	Zhejiang University
Keywords: Closed loop identification, Identification for control, Identifiability Abstract: This paper presents a method of closed-loop identification for multivariable systems without external excitation. The method is specially designed for model predictive control (MPC) systems. Without using external excitation (test signals), the method ensures the informativity of the closed-loop data and, at the same time, improve the control performance during the test period. The purpose of the study is to reduce the cost of identification test. The basic idea is to switch the input weighting matrix in the MPC controller which leads to the informativity of the data-set. A preliminary test is carried out in order to find a new input weighting matrix which improve the control performance; then a switching scheme is developed based on the two weighting matrixes. Traditional simulation based model validation no longer works in closed-loop identification without excitation, and model error bounds on the frequency responses can be used instead. The effectiveness of the proposed method is demonstrated by a simulation study.

VI111-13
Linear Systems Identification	Regular Session
Chair: Mevel, Laurent	INRIA
Co-Chair: Ushirobira, Rosane	Inria
Paper VI111-13.1
PDF · Video · Identification of Noisy Input-Output FIR Models with Colored Output Noise
Barbieri, Matteo	Alma Mater Studiorum - University of Bologna
Diversi, Roberto	University of Bologna
Keywords: Errors in variables identification Abstract: This paper deals with the identification of FIR models corrupted by white input noise and colored output noise. An identification algorithm that exploits the properties of both the dynamic Frisch scheme and the high-order Yule-Walker (HOYW) equations is proposed. It is shown how the HOYW equations allow defining a selection criterion for identifying the input noise variance (and then the FIR coefficients) within the Frisch locus of solutions. The proposed approach does not require any a priori knowledge about the input and output noise variances. The algorithm performance is assessed by means of Monte Carlo simulations.
Paper VI111-13.2
PDF · Video · The Frisch Scheme for EIV System Identification: Time and Frequency Domain Formulations
Soverini, Umberto	University of Bologna
Soderstrom, Torsten	Uppsala University
Keywords: Errors in variables identification, Frequency domain identification Abstract: Several estimation methods have been proposed for identifying errors-in-variables systems, where both input and output measurements are corrupted by noise. One of the more interesting approaches is the Frisch scheme. The method can be applied using either time or frequency domain representations. This paper investigates the general mathematical and geometrical aspects of the Frisch scheme, illustrating the analogies and the differences between the time and frequency domain formulations.
Paper VI111-13.3
PDF · Video · Blind Identification of Two-Channel FIR Systems: A Frequency Domain Approach
Soverini, Umberto	University of Bologna
Soderstrom, Torsten	Uppsala University
Keywords: Errors in variables identification, Frequency domain identification, Channel estimation/equalisation Abstract: This paper describes a new approach for the blind identification of a two-channel FIR system from a finite number of output measurements, in the presence of additive and uncorrelated white noise. The proposed approach is based on frequency domain data and, as a major novelty, it enables the estimation to be frequency selective. The features of the proposed method are analyzed by means of Monte Carlo simulations. The benefits of filtering the data and using only part of the frequency domain is highlighted by means of a numerical example.
Paper VI111-13.4
PDF · Video · Decoupling of Discrete-Time Dynamical Systems through Input-Output Blending
Baar, Tamas	Hungarian Academy of Sciences, Institute for Computer Science An
Bauer, Peter	Institute for Computer Science and Control
Luspay, Tamás	Institiute for Computer Science and Control
Keywords: Subspace methods Abstract: This paper presents a subsystem decoupling method for Linear Time Invariant Discrete-time systems. The aim is to control a selected subsystem, while not affecting the remaining dynamics. The paper extends earlier continuous time results to discrete time systems over a finite frequency interval. Decoupling is achieved by suitable input and output blend vectors, such that they maximize the sensitivity of the selected subsystem, while at the same time they minimize the transfer through the undesired dynamics. The proposed algorithm is based on an optimization problem involving Linear Matrix Inequalities, where the H minus index of the controlled subsystem is maximized, while the transfer through the dynamics to be decoupled is minimized by a sparsity like criteria. The present approach has the advantage that it is directly applicable to stable and unstable subsystems also. Numerical examples demonstrate the effectiveness of the method.
Paper VI111-13.5
PDF · Video · Existence and Uniqueness of Solution for Discontinuous Conewise Linear Systems
Şahan, Gökhan	Izmir Institute of Technology
Keywords: Subspace methods, Stability and stabilization of hybrid systems Abstract: In this study, we give necessary and sufficient conditions for well posedness of Conewise Linear Systems in 3-dimensional space where the vector field is allowed to be discontinuous. The conditions are stated using the subspaces derived from subsystem matrices and the results are compared with the existing conditions given in the literature. We show that even we don’t have a fixed structure on system matrices as in bimodal systems, similar subspaces and numbers again determines well posedness.
Paper VI111-13.6
PDF · Video · Variance Computation for System Matrices and Transfer Function from Input/output Subspace System Identification
Gres, Szymon	INRIA
Döhler, Michael	Inria
Mevel, Laurent	INRIA
Keywords: Subspace methods, Vibration and modal analysis Abstract: The transfer function of a linear system is defined in terms of the quadruplet of matrices (A,B,C,D) that can be identified from input and output measurements. Similarly these matrices determine the state space evolution for the considered dynamical system. Estimation of the quadruplet has been well studied in the literature from both theoretical and practical points of view. Nonetheless, the uncertainty quantification of their estimation errors has been mainly discussed from a theoretical viewpoint. For several output-only and input/output subspace methods, the variance of the (A,C) matrices can be effectively obtained with recently developed first-order perturbation-based schemes. This paper addresses the estimation of the (B,D) matrices, and the remaining problem of the effective variance computation of their estimates and the resulting transfer function. The proposed schemes are validated on a simulation of a mechanical system.
Paper VI111-13.7
PDF · Video · Laguerre-Domain Modelling and Identification of Linear Discrete-Time Delay Systems
Bro, Viktor	Uppsala University
Medvedev, Alexander	Uppsala University
Ushirobira, Rosane	Inria
Keywords: Frequency domain identification, Filtering and smoothing, Channel estimation/equalisation Abstract: A closed-form Laguerre-domain representation of discrete linear time-invariant systems with constant input time delay is derived. It is shown to be useful in a l_2 to l_2 system identification setup (with l_2 denoting square-summables signals) often arising in biomedical applications, where the experimental protocol does not allow for persistent excitation of the system dynamics. The utility of the proposed system representation is demonstrated on a problem of drug kinetics estimation from clinical data.

VI111-14
Learning for Modeling, Identification, and Control	Regular Session
Chair: Matschek, Janine	Otto-von-Guericke-Universität Magdeburg
Co-Chair: Borrelli, Francesco	University of California
Paper VI111-14.1
PDF · Video · Online Gradient Descent for Linear Dynamical Systems
Nonhoff, Marko	Leibniz University Hannover
Muller, Matthias A.	Leibniz University Hannover
Keywords: Learning for control Abstract: In this paper, online convex optimization is applied to the problem of controlling linear dynamical systems. An algorithm similar to online gradient descent, which can handle time-varying and unknown cost functions, is proposed. Then, performance guarantees are derived in terms of regret analysis. We show that the proposed control scheme achieves sublinear regret if the variation of the cost functions is sublinear. In addition, as a special case, the system converges to the optimal equilibrium if the cost functions are invariant after some finite time. Finally, the performance of the resulting closed loop is illustrated by numerical simulations.
Paper VI111-14.2
PDF · Video · Data-Driven Surrogate Models for LTI Systems Via Saddle-Point Dynamics
Martin, Tim	University of Stuttgart
Koch, Anne	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Learning for control, Bounded error identification, Identification for control Abstract: For the analysis, simulation, and controller design of large-scale systems, a surrogate model is mostly required. The surrogate model should have small complexity while it approximates precisely the system behaviour with a bound on the error. A standard approach to compute a reduced model is given by modelling the system and applying model order reduction techniques. Contrary, we propose a data-driven approach. Hence, we derive a surrogate model of the input-output behaviour of LTI systems without knowledge of a model. Moreover, a bound on the maximal error between the system and the surrogate model is obtained. We analyse the stability and convergence of the presented schemes and we apply them on a benchmark system from the model-order-reduction literature.
Paper VI111-14.3
PDF · Video · Structured Exploration in the Finite Horizon Linear Quadratic Dual Control Problem
Iannelli, Andrea	ETH Zurich
Khosravi, Mohammad	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Learning for control, Identification for control, Experiment design Abstract: This paper presents a novel approach to synthesize dual controllers for unknown linear time-invariant systems with the tasks of optimizing a quadratic cost while reducing the uncertainty. To this end, a synthesis problem is defined where the feedback law has to simultaneously gain knowledge of the system and robustly optimize the cost. By framing the problem in a finite horizon setting, the trade-offs arising when the tasks include both identification and control are formally captured in the optimization problem. Results show that efficient exploration strategies are achieved when the structure of the problem is exploited.
Paper VI111-14.4
PDF · Video · Learning Non-Parametric Models with Guarantees: A Smooth Lipschitz Regression Approach
Maddalena, Emilio Tanowe	école Polytechnique Fédérale De Lausanne
Jones, Colin N.	Ecole Polytechnique Federale De Lausanne (EPFL)
Keywords: Learning for control, Machine learning, Bounded error identification Abstract: We propose a non-parametric regression methodology that enforces the regressor to be fully consistent with the sample set and the ground-truth regularity assumptions. As opposed to the Nonlinear Set Membership technique, this constraint guarantees the attainment of everywhere differentiable surrogate models, which are more suitable to optimization-based controllers that heavily rely on gradient computations. The presented approach is named Smooth Lipschitz Regression (SLR) and provides error bounds on the prediction error at unseen points in the space. A numerical example is given to show the effectiveness of this method when compared to the other alternatives in a Model Predictive Control setting.
Paper VI111-14.5
PDF · Video · Constrained Gaussian Process Learning for Model Predictive Control
Matschek, Janine	Otto-von-Guericke-Universität Magdeburg
Himmel, Andreas	Otto Von Guericke University Magdeburg
Sundmacher, Kai	Max Planck Institute for Dynamics of Complex Technical Systems
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Learning for control, Machine learning, Grey box modelling Abstract: Many control tasks can be formulated as tracking problems of a known or unknown reference signal. Examples are motion compensation in collaborative robotics, the synchronisation of oscillations for power systems or the reference tracking of recipes in chemical process operation. Both the tracking performance and the stability of the closed-loop system depend strongly on two factors: Firstly, they depend on whether the future reference signal required for tracking is known, and secondly, whether the system can track the reference at all. This paper shows how to use machine learning, i.e. Gaussian processes, to learn a reference from (noisy) data while guaranteeing trackability of the modified desired reference predictions within the framework of model predictive control. Guarantees are provided by adjusting the hyperparameters via a constrained optimisation. Two specific scenarios, i.e. asymptotically constant and periodic references, are discussed.
Paper VI111-14.6
PDF · Video · On the Synthesis of Control Policies from Example Datasets
Gagliardi, Davide	University College Dublin
Russo, Giovanni	University of Salerno
Keywords: Learning for control, Machine learning, Nonparametric methods Abstract: A framework that is becoming particularly appealing to design control algorithms is that of devising the control policy from examples (or demonstrations). At their roots these control from demonstration techniques, which are gaining considerable attention under the label of Inverse Reinforcement Learning (IRL), rely on Inverse Optimal Control and Optimization. Today, IRL/control is recognized as an appealing framework to learn policies from success stories and potential applications include planning and preferences/prescriptions learning. There is then no surprise that, over the years, a number of techniques have been developed to address the problem of devising control policies from demonstrations, mainly in the context of Markov Decision Processes (MDPs). In this extended abstract we introduce an approach to synthesize control policies from examples. This approach formalizes the control problem as an optimization problem where the Kullback-Leibler Divergence between an ideal probability density function (pdf, obtained from e.g. demonstrations) and the pdf modeling the system/plant is minimized. A key technical novelty of our results lies in the fact that we explicitly embed actuation constraints in our formulation, thus solving an optimization problem where the Kullback-Leibler Divergence is minimized subject to constraints on the control variable. One of the main advantages of our results over classic Inverse Reinforcement Learning (Inverse Control) approaches is that policies can be synthesized from data without requiring that the system is a MDP. Moreover, by embedding actuation constraints into the problem formulation and by solving the resulting optimization, we can export the policy that has been learned on other systems that have different actuation capabilities. As an additional contribution, we devise from our theoretical results an algorithmic procedure. The key reference applications over which the algorithm was tested involved an autonomous driving use case and full results will be presented at the conference.
Paper VI111-14.7
PDF · Video · Modeling of Dynamical Systems Via Successive Graph Approximations
Nair, Siddharth	University of California, Berkeley
Bujarbaruah, Monimoy	UC Berkeley
Borrelli, Francesco	University of California
Keywords: Learning for control, Nonparametric methods, Identification for control Abstract: A non-parametric technique for modeling of systems with unknown nonlinear Lipschitz dynamics is presented. The key idea is to successively utilize measurements to approximate the graph of the state-update function of the system dynamics using envelopes described by quadratic constraints. The proposed approach is then used for computing outer approximations of the state-update function using convex optimization. We highlight the efficacy of the proposed approach via a detailed numerical example.
Paper VI111-14.8
PDF · Video · GP3: A Sampling-Based Analysis Framework for Gaussian Processes
Lederer, Armin	Technical University of Munich
Kessler, Markus	Technical University of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Machine learning, Learning for control, Bayesian methods Abstract: Although machine learning is increasingly applied in control approaches, only few methods guarantee certifiable safety, which is necessary for real world applications. These approaches typically rely on well-understood learning algorithms, which allow formal theoretical analysis. Gaussian process regression is a prominent example among those methods, which attracts growing attention due to its strong Bayesian foundations. Even though many problems regarding the analysis of Gaussian processes have a similar structure, specific approaches are typically tailored for them individually, without strong focus on computational efficiency. Thereby, the practical applicability and performance of these approaches is limited. In order to overcome this issue, we propose a novel framework called GP3, general purpose computation on graphics processing units for Gaussian processes, which allows to solve many of the existing problems efficiently. By employing interval analysis, local Lipschitz constants are computed in order to extend properties verified on a grid to continuous state spaces. Since the computation is completely parallelizable, the computational benefits of GPU processing are exploited in combination with multi-resolution sampling in order to allow high resolution analysis.
Paper VI111-14.9
PDF · Video · Active Learning for Linear Parameter-Varying System Identification
Chin, Robert	The University of Melbourne & University of Birmingham
Maass, Alejandro I.	The University of Melbourne
Ulapane, Nalika	University of Melbourne
Manzie, Chris	The University of Melbourne
Shames, Iman	University of Melbourne
Nesic, Dragan	Univ of Melbourne
Rowe, Jonathan	University of Birmingham
Nakada, Hayato	Toyota Motor Corporation
Keywords: LPV system identification, Experiment design, Machine learning Abstract: Active learning is proposed for selection of the next operating points in the design of experiments, for identifying linear parameter-varying systems. We extend existing approaches found in literature to multiple-input multiple-output systems with a multivariate scheduling parameter. Our approach is based on exploiting the probabilistic features of Gaussian process regression to quantify the overall model uncertainty across locally identified models. This results in a flexible framework which accommodates for various techniques to be applied for estimation of local linear models and their corresponding uncertainty. We perform active learning in application to the identification of a diesel engine air-path model, and demonstrate that measures of model uncertainty can be successfully reduced using the proposed framework.
Paper VI111-14.10
PDF · Video · Sparse Gaussian Mixture Model Clustering Via Simultaneous Perturbation Stochastic Approximation
Boiarov, Andrei	Saint Petersburg State University
Granichin, Oleg	Saint Petersburg State University
Keywords: Machine learning, Randomized methods Abstract: In this paper the problem of a multidimensional optimization in unsupervised learning and clustering is studied under significant uncertainties in the data model and measurements of penalty functions. We propose a modified version of SPSA-based algorithm which maintains stability under conditions such as a sparse Gaussian mixture model. This data model is important because it can be effectively used to evaluate the noise model in many practical systems. The proposed algorithm is robust to external disturbances and is able to process data sequentially, ``on the fly''. In this paper provides a study of this algorithm and its mathematical justification. The behavior of the algorithm is illustrated by examples of its use for clustering in various difficult conditions.
Paper VI111-14.11
PDF · Video · Nonparametric Identification of Linear Time-Varying Systems Using Gaussian Process Regression
Hallemans, Noël	Vrije Universiteit Brussel
Lataire, John	Vrije Universiteit Brussel
Pintelon, Rik	Vrije Universiteit Brussel
Keywords: Frequency domain identification, Machine learning, Nonparametric methods Abstract: Linear time-varying systems are a class of systems, the dynamics of which evolve in time. This results in a time-varying transfer function where each frequency has a time-varying gain. In classical identification techniques, basis functions are employed to fit these time-varying gains. In this paper a new method based on Gaussian process regression is presented. The advantage of the proposed method is a more convenient model structure and model order selection.
Paper VI111-14.12
PDF · Video · Confidence Regions for Predictions of Online Learning-Based Control
Capone, Alexandre	Technical University of Munich
Lederer, Armin	Technical University of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Machine learning, Stochastic system identification, Particle filtering/Monte Carlo methods Abstract: Although machine learning techniques are increasingly employed in control tasks, few methods exist to predict the behavior of closed-loop learning-based systems. In this paper, we introduce a method for computing confidence regions of closed-loop system trajectories under an online learning-based control law. We employ a sampling-based approximation and exploit system properties to prove that the computed confidence regions are correct with high probability. In a numerical simulation, we show that the proposed approach accurately predicts correct confidence regions.
Paper VI111-14.13
PDF · Video · A Study on Majority-Voting Classifiers with Guarantees on the Probability of Error
Carè, Algo	University of Brescia, Italy
Campi, Marco	University of Brescia
Ramponi, Federico Alessandro	Università Degli Studi Di Brescia
Garatti, Simone	Politecnico Di Milano
Cobbenhagen, Roy	Eindhoven University of Technology
Keywords: Machine learning, Multi-agent systems, Randomized methods Abstract: The Guaranteed Error Machine (GEM) is a classification algorithm that allows the user to set a-priori (i.e., before data are observed) an upper bound on the probability of error. Due to its strong statistical guarantees, GEM is of particular interest for safety critical applications in control engineering. Empirical studies have suggested that a pool of GEM classifiers can be combined in a majority voting scheme to boost the individual performances. In this paper, we investigate the possibility of keeping the probability of error under control in the absence of extra validation or test sets. In particular, we consider situations where the classifiers in the pool may have different guarantees on the probability of error, for which we propose a data-dependent weighted majority voting scheme. The preliminary results presented in this paper are very general and apply in principle to any weighted majority voting scheme involving individual classifiers that come with statistical guarantees, in the spirit of Probably Approximately Correct (PAC) learning.

VI111-15
Modeling, Identification and Control of Dynamic Networks	Regular Session
Chair: Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Co-Chair: Liu, Guoping	University of South Wales
Paper VI111-15.1
PDF · Video · Identification of Complex Network Topologies through Delayed Mutual Information
Toupance, Pierre-Alain	Univ. Grenoble Alpes, Grenoble INP, LCIS
Lefevre, Laurent	Univ. Grenoble Alpes
Chopard, Bastien	CUI, University of Geneva
Keywords: Dynamic Networks, Distributed control and estimation, Stochastic system identification Abstract: The definitions of delayed mutual information and multi-information are recalled. It is shown how the delayed mutual information may be used to reconstruct the interaction topology resulting from some unknown scale-free graph with its associated local dynamics. Delayed mutual information is also used to solve the community detection problem. A probabilistic voter model defined on a scale-free graph is used throughout the paper as an illustrative example.
Paper VI111-15.2
PDF · Video · Design of Prediction-Based Estimator for Time-Varying Networks Subject to Communication Delays and Missing Data
Hu, Jun	Harbin Institute of Technology
Liu, Guoping	University of South Wales
Keywords: Dynamic Networks, Estimation and filtering, Control and estimation with data loss Abstract: This paper is concerned with the robust optimal estimation problem based on the prediction compensation mechanism for dynamical networks with time-varying parameters, where communication delays and degraded measurements are considered. The missing measurements are characterized by some random variables governed by Bernoulli distribution, where each sensor having individual missing probability is reflected. During the signal transmissions through the communication networks, the network-induced communication delays commonly exist among the adjacent nodes transmissions and a prediction updating method is given to compensate the caused impacts. Accordingly, a time-varying state estimator with hybrid compensation scheme is constructed such that, for both the communication delays and missing measurements, a minimized upper bound matrix with regards to the estimation error covariance matrix is found and an explicit estimator parameter matrix is designed at each sampling step accordingly. Finally, the comparative simulations are given to validate the advantages of main results.
Paper VI111-15.3
PDF · Video · Network Topology Impact on the Identification of Dynamic Network Models with Application to Autonomous Vehicle Platooning
Araujo Pimentel, Guilherme	Pontifícia Universidade Católica Do Rio Grande Do Sul
de Vasconcelos, Rafael	Pontifícia Universidade Católica Do Rio Grande Do Sul
Salton, Aurelio Tergolina	Universidade Federal Do Rio Grande Do Sul (UFRGS)
Bazanella, Alexandre S.	Univ. Federal Do Rio Grande Do Sul
Keywords: Dynamic Networks, Identification for control, Identifiability Abstract: The interconnection of complex devices in network structures has been a challenging topic in the system identification research domain. This study presents the model identification of autonomous vehicles in platoon formation, which can be cast as a dynamic network. The paper presents the comparison between two network structures: (i) a vehicle-based network, which considers the interconnection between the vehicles based only on the velocity measurements, and (ii) a sensor-based network that considers the available sensor, i.e. the velocity and the relative distance measurements. The comparison is based on the difference between the identified transfer functions and the true ones, and the analysis of the identified air resistance coefficient variances. In addition, the paper presents the identifiability requirements for both network topologies. Simulation results show that for the same data set the variance of the identified parameters can be almost five times smaller if the system is represented as a sensor-based network, but some conditions to guarantee the identifiability of this network structure must be fulfilled.
Paper VI111-15.4
PDF · Video · Desynchronization in Oscillatory Networks Based on Yakubovich Oscillatority
Plotnikov, Sergei	Institute for Problems of Mechanical Engineering, Russian Academ
Fradkov, Alexander L.	Russian Academy of Sciences
Keywords: Dynamic Networks, Multi-agent systems, Consensus Abstract: The desynchronization problems in oscillatory networks is considered. A new desynchronization notion is introduced and desynchronization conditions are provided. The desynchronization notion is formulated in terms of Yakubovich oscillatority of the auxiliary synchronization error system. As an example, the network of diffusively coupled FitzHugh-Nagumo systems with undirected graph is considered. The simple inequality guaranteeing network desynchronization is derived. The simulation results confirm the validity of the obtained analytical results.
Paper VI111-15.5
PDF · Video · Sparse Estimation of Laplacian Eigenvalues in Multiagent Networks
Hayhoe, Mikhail	University of Pennsylvania
Barreras, Jorge Francisco	University of Pennsylvania
Preciado, Victor M.	University of Pennsylvania
Keywords: Identification for control, Multi-agent systems, Identifiability Abstract: We propose a method to efficiently estimate the Laplacian eigenvalues of an arbitrary, unknown network of interacting dynamical agents. The inputs to our estimation algorithm are measurements about the evolution of a collection of agents (potentially one) during a finite time horizon; notably, we do not require knowledge of which agents are contributing to our measurements. We propose a scalable algorithm to exactly recover a subset of the Laplacian eigenvalues from these measurements. These eigenvalues correspond directly to those Laplacian modes that are observable from our measurements. We show how our technique can be applied to networks of multiagent systems with arbitrary dynamics in both continuous- and discrete-time. Finally, we illustrate our results with numerical simulations.
Paper VI111-15.6
PDF · Video · Finite-Sample Analysis for Decentralized Cooperative Multi-Agent Reinforcement Learning from Batch Data
Zhang, Kaiqing	University of Illinois at Urbana-Champaign (UIUC)
Yang, Zhuoran	Princeton
Liu, Han	Northwestern University
Zhang, Tong	The Hong Kong University of Science and Technology
Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Keywords: Machine learning, Consensus and Reinforcement learning control, Multi-agent systems Abstract: In contrast to its great empirical success, theoretical understanding of multi-agent reinforcement learning (MARL) remains largely underdeveloped. As an initial attempt, we provide a finite-sample analysis for decentralized cooperative MARL with networked agents. In particular, we consider a team of cooperative agents connected by a time-varying communication network, with no central controller coordinating them. The goal for each agent is to maximize the long-term return associated with the team-average reward, by communicating only with its neighbors over the network. A batch MARL algorithm is developed for this setting, which can be implemented in a decentralized fashion. We then quantify the estimation errors of the action-value functions obtained from our algorithm, establishing their dependence on the function class, the number of samples in each iteration, and the number of iterations. This work appears to be the first finite-sample analysis for decentralized cooperative MARL from batch data.
Paper VI111-15.7
PDF · Video · Online Observability of Boolean Control Networks
Wu, Guisen	Southwest University
Liyun, Dai	Southwest University
Zhiming, Liu	Southwest University
Chen, Taolue	Birkbeck, University of London
Pang, Jun	University of Luxembourg
Keywords: Identifiability, Nonlinear system identification, Identification for control Abstract: Observabililty is an important topic of Boolean control networks (BCNs). In this paper, we propose a new type of observability named online observability to present the sufficient and necessary condition of determining the initial states of BCNs, when their initial states cannot be reset. And we design an algorithm to decide whether a BCN has the online observability. Moreover, we prove that a BCN is identifiable iff it satisfies the controllability and the online observability, which reveals the essence of identification problem of BCNs.

VI111-16
Nonlinear System Identification	Regular Session
Chair: Okuda, Hiroyuki	Nagoya University
Co-Chair: Enqvist, Martin	Linköping University
Paper VI111-16.1
PDF · Video · Nonlinear Grey-Box Identification with Inflow Decoupling in Gravity Sewers
Balla, Krisztian Mark	Aalborg University
Kallesøe, Carsten Skovmose	Grundfos
Schou, Christian	Grundfos Management A/S
Bendtsen, Jan Dimon	Aalborg Univ
Keywords: Grey box modelling, Identification for control, Nonlinear system identification Abstract: Knowing where wastewater is flowing in sewer networks is essential to optimize system operation. Unfortunately, flow in gravity-driven sewers is subject to transport delays and typically disturbed by significant domestic, ground, and rain inflows. In this work, we utilize a lumped-parameter hydrodynamic model with a bi-linear structure for identifying these delays, decouple disturbances and to predict the discharged flow. We use pumped inlet and discharged dry-weather flow data to estimate the model parameters. Under mild assumptions on the domestic and groundwater inflows, i.e. disturbances, we show that decoupling these inflows from the total discharge is possible. A numerical case study on an EPA Storm Water Management Model and experimental results on a real network demonstrate the proposed method.
Paper VI111-16.2
PDF · Video · An Alternating Optimization Method for Switched Linear Systems Identification
Bianchi, Federico	Politecnico Di Milano
Falsone, Alessandro	Politecnico Di Milano
Piroddi, Luigi	Politecnico Di Milano
Prandini, Maria	Politecnico Di Milano
Keywords: Hybrid and distributed system identification Abstract: The identification of switched systems involves solving a mixed-integer optimization problem to determine the parameters of each mode dynamics (continuous part) and assign the data samples to the modes (discrete part), so as to minimize a cost criterion measuring the quality of the model on a set of input/output data collected from the system. Oftentimes, some a priori information on the switching mechanism is available, e.g., in the form of a minimum dwell time. This information can be encoded in a suitable constraint and included in the optimization problem, but this introduces a coupling between the discrete and continuous optimization variables that makes the problem harder to solve. In this paper, we propose an iterative approach to the identification of switched systems that alternates a minimization step with respect to the continuous parameters of the modes, and a minimization step with respect to the discrete variables defining the sample-mode mapping. Constraints originating from prior knowledge on the switching mechanism are taken into account after the (unconstrained) discrete optimization step through a post-processing phase. These three phases are repeated until a stopping criterion is met. A comparative numerical analysis of the proposed method shows its improved performance with respect to competitive approaches in the literature.
Paper VI111-16.3
PDF · Video · Identification of Markov Jump Autoregressive Processes from Large Noisy Data Sets
Hojjatinia, Sarah	The Pennsylvania State University
Lagoa, Constantino M.	Pennsylvania State Univ
Keywords: Hybrid and distributed system identification, Identification for control Abstract: This paper introduces a novel methodology for the identification of switching dynamics for switched autoregressive linear models. Switching behavior is assumed to follow a Markov model. The system's outputs are contaminated by possibly large values of measurement noise. Although the procedure provided can handle other noise distributions, for simplicity, it is assumed that the distribution is Normal with unknown variance. Given noisy input-output data, we aim at identifying switched system coefficients, parameters of the noise distribution, dynamics of switching and probability transition matrix of Markovian model. System dynamics are estimated using previous results which exploit algebraic constraints that system trajectories have to satisfy. Switching dynamics are computed with solving a maximum likelihood estimation problem. The efficiency of proposed approach is shown with several academic examples. Although the noise to output ratio can be high, the method is shown to be effective in the situations where a large number of measurements is available.
Paper VI111-16.4
PDF · Video · Joint Identification and Control in Hybrid Linear Systems
Somarakis, Christoforos	Palo Alto Research Center
Matei, Ion	Palo Alto Research Center
Zhenirovskyy, Maksym	PARC
de Kleer, Johan	PARC
Chowdhury, Souma	University at Buffalo
Rai, Rahul	Buffalo-SUNY
Keywords: Hybrid and distributed system identification, Identification for control, Learning for control Abstract: We propose a theoretical framework for joint system identification and control on a class of stochastic linear systems. We investigate optimization algorithms for inferring endogenous and environmental parameters from data, part of which are used for control purposes. A number of non-trivial interplays among stability and performance, as well as computational challenges and fundamental limits in identification rate emerge. Our results are validated via simulation example on a quadcopter control problem.
Paper VI111-16.5
PDF · Video · Model Structure Identification of Hybrid Dynamical Systems Based on Unsupervised Clustering and Variable Selection
Nguyen, Duc An	Nagoya University
Nwadiuto, Jude	Nagoya University
Okuda, Hiroyuki	Nagoya University
Suzuki, Tatsuya	Nagoya Univ
Keywords: Hybrid and distributed system identification, Nonlinear system identification, Identification for control Abstract: This paper presents a systematic identification process for the hybrid dynamical system (HDS) estimating not only the coefficients but also the structure of the model. Generally speaking, the system identification is used for the HDS system that the model structure, the number of modes, and the explanatory variables of the model are unknown. In the proposed method, a quantitative index to evaluate the number of modes is deployed and the optimal number of modes is determined from the measurement. Model selection method is also introduced to determine the explanatory variables in each mode in a systematic manner. Two of piece-wise linear models which are well known as the HDS models are used for the targeting system to identify, and the validity of the proposed method is demonstrated. Finally, the result of system identification in comparison with the conventional system identification method for HDS is discussed.
Paper VI111-16.6
PDF · Video · A Bias-Correction Approach for the Identification of Piecewise Affine Output-Error Models
Mejari, Manas	IDSIA Dalle Molle Institute for Artificial Intelligence
Breschi, Valentina	Politecnico Di Milano
Naik, Vihangkumar Vinaykumar	IMT School for Advanced Studies Lucca, Italy
Piga, Dario	SUPSI-USI
Keywords: Hybrid and distributed system identification, Nonlinear system identification, Recursive identification Abstract: The paper presents an algorithm for the identification of PieceWise Affine Output-Error (PWA-OE) models, which involves the estimation of the parameters defining affine submodels as well as a partition of the regressor space. For the estimation of affine submodel parameters, a bias-correction scheme is presented to correct the bias in the least squares estimates which is caused by the output-error noise structure. The obtained bias-corrected estimates are proven to be consistent under suitable assumptions. The bias-correction method is then combined with a recursive estimation algorithm for clustering the regressors. These clusters are used to compute a partition of the regressor space by employing linear multi-category discrimination. The effectiveness of the proposed methodology is demonstrated via a simulation case study.
Paper VI111-16.7
PDF · Video · Data Informativity for the Identification of Particular Parallel Hammerstein Systems
Colin, Kévin	Ecole Centrale De Lyon
Bombois, Xavier	Ecole Centrale De Lyon
Bako, Laurent	Ecole Centrale De Lyon
Morelli, Federico	Laboratoire Ampère, Ecole Centrale De Lyon
Keywords: Identifiability, Nonlinear system identification Abstract: To obtain a consistent estimate when performing an identification with Prediction Error, it is important that the excitation yields informative data with respect to the chosen model structure. While the characterization of this property seems to be a mature research area in the linear case, the same cannot be said for nonlinear systems. In this work, we study the data informativity for a particular type of Hammerstein systems for two commonly-used excitations: white Gaussian noise and multisine. The real life example of the MEMS gyroscope is considered.
Paper VI111-16.8
PDF · Video · Asymptotic Prediction Error Variance for Feedforward Neural Networks
Malmström, Magnus	Linköping University
Skog, Isaac	KTH
Axehill, Daniel	Linköping University
Gustafsson, Fredrik	Linköping University
Keywords: Identification for control, Machine learning, Nonlinear system identification Abstract: The prediction uncertainty of a neural network is considered from a classical system identification point of view. To know this uncertainty is extremely important when using a network in decision and feedback applications. The asymptotic covariance of the internal parameters in the network due to noise in the observed dependent variables (output) and model class mismatch, i.e., the true system cannot be exactly described by the model class, is first surveyed. This is then applied to the prediction step of the network to get a closed form expression for the asymptotic, in training data information, prediction variance. Another interpretation of this expression is as the non-asymptotic Cramér-Rao Lower Bound. To approximate this expression, only the gradients and residuals, already computed in the gradient descent algorithms commonly used to train neural networks, are needed. Using a toy example, it is illustrated how the uncertainty in the output of a neural network can be estimated.
Paper VI111-16.9
PDF · Video · Data-Based Identifiability and Observability Assessment for Nonlinear Control Systems Using the Profile Likelihood Method
Schmitt, Thomas	Technische Universität Darmstadt
Ritter, Bastian	Technische Universität Darmstadt
Keywords: Identifiability, Nonlinear system identification, Identification for control Abstract: This paper introduces the profile likelihood method in order to assess simultaneously the parameter identifiability and the state observability for nonlinear dynamic state-space models with constant parameters. While a formal definition of a parameter’s identifiability has been used before, the novel idea is to investigate also the state’s observability by the identifiability of its initial value. Using the profile likelihood, both qualitative as well as quantitative statements are drawn from the analysis based on the nonlinear model and (possibly noisy) sensor data. A simplified wind turbine model is presented and used as an application example for the profile likelihood approach in order to investigate the model’s usability for state and parameter estimation. It is shown that the critical model parameters and initial states are identifiable in principle. The analysis with more complex models and realistic data reveals the limitations when assumptions are deliberately violated in order to meet reality.
Paper VI111-16.10
PDF · Video · A Polytopic Box Particle Filter for State Estimation of Non Linear Discrete-Time Systems
Gatto, Thomas	ONERA
Meyer, Luc	Univ Paris Saclay
Piet-Lahanier, Helene	ONERA
Keywords: Nonlinear system identification, Bounded error identification, Particle filtering/Monte Carlo methods Abstract: The development of Particle Filters has made possible state estimation of dynamic systems presenting non-linear dynamics and potential multi-modalities. However, the efficiency of these approaches depends tightly of the required number of particles which may prove very high to approximate large range of uncertainty on the process or the measurements. To overcome this issue, the Box-Particle Filter (BPF) combines the versatility of the Particle Filter and the robustness of set-membership algorithms. The particles are replaced by boxes which represent in a compact way large variations of the estimates. Although this filter presents various advantages and requires a small number of boxes to estimate the state, the resulting estimates may prove pessimistic, as the uncertainty description as unions of axis-aligned intervals can be rather rough and doesn't account for potential dependencies between the resulting estimate components. In the proposed paper, a new version of the BPF is proposed. Boxes are replaced by polytopes (multidimensional polygons) in the filter algorithm, so that they can adapt to represent state components dependency. This modification tends to ameliorate the estimation precision (i.e. the size of the final set that includes the true state decreases) while keeping the number of required polyhedrons small. Several examples illustrate the benefits of such an approach.
Paper VI111-16.11
PDF · Video · State-Space Kernelized Closed-Loop Identification of Nonlinear Systems
Shakib, Mohammad Fahim	Eindhoven University of Technology
Tóth, Roland	Eindhoven University of Technology
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Pavlov, Alexey	Norwegian University of Science and Technology
van de Wouw, Nathan	Eindhoven Univ of Technology
Keywords: Nonlinear system identification, Closed loop identification, Nonparametric methods Abstract: In this paper, we propose a non-parametric state-space identification approach for open-loop and closed-loop discrete-time nonlinear systems with multiple inputs and multiple outputs. Employing a least squares support vector machine (LS-SVM) approach in a reproducing kernel Hilbert space framework, a nonlinear auto-regressive model with exogenous terms is identified to provide a non-parametric estimate of the innovation noise sequence. Subsequently, this estimate is used to obtain a compatible non-parametric estimate of the state sequence in an unknown basis using kernel canonical correlation analysis. Finally, the estimate of the state sequence is used together with the estimated innovation noise sequence to find a non-parametric state-space model, again using a LS-SVM approach. The performance of the approach is analyzed in a simulation study with a nonlinear system operating both in open loop and closed loop. The identification approach can be viewed as a nonlinear counterpart of consistent subspace identification techniques for linear time-invariant systems operating in closed loop.
Paper VI111-16.12
PDF · Video · Consistent Parameter Estimators for Second-Order Modulus Systems with Non-Additive Disturbances
Ljungberg, Fredrik	Linköping University
Enqvist, Martin	Linköping University
Keywords: Nonlinear system identification, Grey box modelling Abstract: This work deals with a class of nonlinear regression models called second-order modulus models. It is shown that the possibility of obtaining consistent parameter estimators for these models depends on how process disturbances enter the system. Two scenarios where consistency can be achieved for instrumental variable estimators despite non-additive system disturbances are demonstrated, both in theory and by simulation examples.
Paper VI111-16.13
PDF · Video · An Algebraic Approach to Efficient Identification of a Class of Wiener Systems
Ozbay, Bengisu	Northeastern University
Sznaier, Mario	Northeastern University
Camps, Octavia I.	Northeastern University
Keywords: Nonlinear system identification, Hybrid and distributed system identification Abstract: This paper considers the problem of identifying the linear portion of a Wiener system, for the case of a known, but non-invertible output non-linearity. It is well known that this scenario, common in many practical applications, leads to problems that are generically NP-hard in the number of experiments. Thus, existing techniques scale poorly and are typically limited to relatively few points. The main result of this paper shows that this difficulty can be circumvented by considering an algebraic motivated approach. Specifically, we show that the problem is equivalent to identification of a switched linear system generated from the observed data. In turn, this problem can be solved by recasting it as the problem of finding the vanishing ideal of an arrangement of subspaces, a task that reduces to finding the null space of an embedded data matrix constructed from the observed data.
Paper VI111-16.14
PDF · Video · Identification of Nonlinear Systems and Optimality Analysis in Sobolev Spaces
Novara, Carlo	Politecnico Di Torino
Nicolì, Angelo	Politecnico Di Torino
Calafiore, Giuseppe	Politecnico Di Torino
Keywords: Nonlinear system identification, Identification for control Abstract: In this paper, we propose a novel approach for the identification from data of an unknown nonlinear function together with its derivatives. This approach can be useful, for instance, in the context of nonlinear system identification for obtaining models that are more reliable than the traditional ones, based on plain function approximation. Indeed, models identified by accounting for the derivatives can provide a better performance in several tasks, such as multi-step prediction, simulation, and control design. We also develop an optimality analysis, showing that models derived using this approach enjoy suitable optimality properties in Sobolev spaces. We finally demonstrate the effectiveness of the approach with a numerical example.
Paper VI111-16.15
PDF · Video · Koopman Operator Methods for Global Phase Space Exploration of Equivariant Dynamical Systems
Sinha, Subhrajit	Pacific Northwest National Laboratory
Nandanoori, Sai Pushpak	Pacific Northwest National Laboratory
Yeung, Enoch	Brigham Young University
Keywords: Nonlinear system identification, Identification for control, Continuous time system estimation Abstract: In this paper, we develop the Koopman operator theory for dynamical systems with symmetry. In particular, we investigate how the Koopman operator and eigenfunctions behave under the action of the symmetry group of the underlying dynamical system. Further, exploring the underlying symmetry, we propose an algorithm to construct a global Koopman operator from local Koopman operators. In particular, we show, by exploiting the symmetry, data from all the invariant sets are not required for constructing the global Koopman operator; that is, local knowledge of the system is enough to infer the global dynamics.
Paper VI111-16.16
PDF · Video · Estimating Koopman Invariant Subspaces of Excited Systems Using Artificial Neural Networks
Bonnert, Marcel	Technische Universität Darmstadt
Konigorski, Ulrich	Technische Universität Darmstadt
Keywords: Nonlinear system identification, Identification for control, Machine learning Abstract: In recent years, the Koopman operator was the topic of many extensive investigations in the nonlinear system identification community. Especially, when dealing with nonlinear systems no straight forward method is available to identify systems of this class. In modern data science a standard method is using artificial neural networks to extract models from data. This method is mainly used when there is a certain function behind the measured data, but little other information is available. This paper combines the Koopman framework and artificial neural networks to achieve a linear model for nonlinear systems. The structure of the network is similar to an autoencoder. The input part is the encoder which itself consists of two different parts. The first part propagates the measurements directly to the middle part. The second encoder introduces the state-space lifting which characterizes the Koopman framework. The middle layer of the network represents an estimation of a linear state-space system that acts on a Koopman operator invariant subspace. After this layer, the extended state-space must be decoded so that the outputs of the Koopman linear system are functions of the true states. The method is evaluated with a single pendulum and a nonlinear yeast glycolysis model. Additionally, we show the advantage of considering inputs as true inputs rather than additional states.
Paper VI111-16.17
PDF · Video · Local Linear Model Tree with Optimized Structure
Hu, Xiaoyan	Loughborough University
Gong, Yu	Loughborough University
Zhao, Dezong	Loughborough University
Gu, Wen	Loughborough University
Keywords: Nonlinear system identification, Machine learning, Grey box modelling Abstract: This paper investigates the local linear model tree (LOLIMOT) with optimized structure. The performance of the LOLIMOT model depends on how the neurons are constructed. In the typical LOLIMOT model, the number of neurons is initially set as one and starts to increase by repeatedly splitting an existing neuron into two equal ones until the required performance is achieved. Because the equal split of a neuron is not optimal, a large model size is often necessary for required performance, leading to high complexity and strong overfitting. In this paper, we propose a gradient-decent-search-based algorithm to optimally split an existing neuron into two new ones. Based on both numerical data and simulated engine data, through the evaluation of optimized structure, the effectiveness of proposed method has been verified.
Paper VI111-16.18
PDF · Video · Learning Koopman Operator under Dissipativity Constraints
Hara, Keita	Keio University
Inoue, Masaki	Keio University
Sebe, Noboru	Kyushu Inst. of Tech
Keywords: Nonlinear system identification, Machine learning, Identification for control Abstract: This paper addresses a learning problem for nonlinear dynamical systems with incorporating any specified dissipativity property. The nonlinear systems are described by the Koopman operator, which is a linear operator defined on the infinite-dimensional lifted state space. The problem of learning the Koopman operator under specified quadratic dissipativity constraints is formulated and addressed. The learning problem is in a class of the non-convex optimization problem due to nonlinear constraints and is numerically intractable. By applying the change of variable technique and the convex overbounding approximation, the problem is reduced to sequential convex optimization and is solved in a numerically efficient manner. Finally, a numerical simulation is given, where high modeling accuracy achieved by the proposed approach including the specified dissipativity is demonstrated.
Paper VI111-16.19
PDF · Video · Deep Learning and System Identfication
Ljung, Lennart	Linköping University
Andersson, Carl	Uppsala University
Tiels, Koen	Eindhoven University of Technology
Schön, Thomas Bo	Uppsala University
Keywords: Nonlinear system identification, Machine learning, Software for system identification Abstract: Deep learning is a topic of considerable interest today. Since it deals with estimating -- or learning -- models, there are connections to the area of System Identification developed in the Automatic Control community. Such connections are explored and exploited in this contribution. It is stressed that common deep nets such as feedforward and cascadeforward nets are nonlinear ARX (NARX) models, and can thus be easily incorporated in System Identification code and practice. The case of LSTM nets is an example of NonLinear State-Space (NLSS) models. It performs worse than the cascadeforwardnet for a standard benchmark example.
Paper VI111-16.20
PDF · Video · Extending Regularized Least Squares Support Vector Machines for Order Selection of Dynamical Takagi-Sugeno Models
Kahl, Matthias	University of Kassel
Kroll, Andreas	University of Kassel
Keywords: Nonlinear system identification, Nonparametric methods, LPV system identification Abstract: In this paper, the problem of order selection for nonlinear dynamical Takagi-Sugeno (TS) fuzzy models is adressed. It is solved by reformulating the TS model in its Linear Parameter Varying (LPV) form and applying an extension of a recently proposed Regularized Least Squares Support Vector Machine (R-LSSVM) technique for LPV models. For that, a nonparametric formulation of the TS identification problem is proposed which uses data-dependent basis functions. By doing so, the partition of unity of the TS model is preserved and the scheduling dependencies of the model are obtained in a nonparametric manner. For the local order selection, a regularization approach is used which forces the coefficient functions of insignificant values of the lagged input and output towards zero.
Paper VI111-16.21
PDF · Video · Valve Stiction Model Estimation in Closed-Loop Operation
Xiong, Man	Zhejiang University
Zhu, Yucai	Zhejiang University
Keywords: Nonlinear system identification, Recursive identification, Closed loop identification Abstract: The estimation of valve stiction model is studied. In industrial applications, valve outputs are often not available, the stiction nonlinear block appears before a linear dynamic block which is operation in a closed-loop system. By parameterizing the valve stiction model as a form of cubic splines, an identification method is proposed using a relaxation iteration scheme. Parameter estimation for the linear part is accomplished through a two-stage procedure. Firstly, an unbiased estimation is obtained by the high-order ARX (AutoRegressive eXogenous) model. Then the ARX model is reduced to a Box-Jenkins model. The consistency of the method is established. Simulation data sets and real operation data sets are used to illustrate the method.
Paper VI111-16.22
PDF · Video · Learning Stable Nonparametric Dynamical Systems with Gaussian Process Regression
Xiao, Wenxin	Technical University of Munich
Lederer, Armin	Technical University of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Nonparametric methods, Machine learning, Nonlinear system identification Abstract: Modelling real world systems involving humans such as biological processes for disease treatment or human behavior for robotic rehabilitation is a challenging problem because labeled training data is sparse and expensive, while high prediction accuracy is required from models of these dynamical systems. Due to the high nonlinearity of problems in this area, data-driven approaches gain increasing attention for identifying nonparametric models. In order to increase the prediction performance of these models, abstract prior knowledge such as stability should be included in the learning approach. One of the key challenges is to ensure sufficient exibility of the models, which is typically limited by the usage of parametric Lyapunov functions to guarantee stability. Therefore, we derive an approach to learn a nonparametric Lyapunov function based on Gaussian process regression from data. Furthermore, we learn a nonparametric Gaussian process state space model from the data and show that it is capable of reproducing observed data exactly. We prove that stabilization of the nominal model based on the nonparametric control Lyapunov function does not modify the behavior of the nominal model at training samples. The flexibility and efficiency of our approach is demonstrated on the benchmark problem of learning handwriting motions from a real world dataset, where our approach achieves almost exact reproduction of the training data.
Paper VI111-16.23
PDF · Video · On Considering the Output in Space-Filling Test Signal Designs for the Identification of Dynamic Takagi-Sugeno Models
Gringard, Matthias	University of Kassel
Kroll, Andreas	University of Kassel
Keywords: Input and excitation design, Experiment design, Nonlinear system identification Abstract: The model-based design of test signals for the identification of dynamical Takagi-Sugeno (TS) fuzzy models is addressed. The multi-model structure is exploited to reduce computational cost. Space-filling designs usually only address the input but the nonlinear behavior of dynamic systems depends on the lagged output in general. This is considered as an additional constraint regarding the test signal design. This contribution investigates whether a control input can be calculated exploiting the local structure and whether considering the output in space-filling designs yields identified models of higher quality.
Paper VI111-16.24
PDF · Video · Parameter Estimation of Nonlinearly Parameterized Regressions: Application to System Identification and Adaptive Control
Ortega, Romeo	Supelec
Gromov, Vladislav	ITMO University
Nuño, Emmanuel	University of Guadalajara
Pyrkin, Anton	ITMO University
Romero Velazquez, José Guadalupe	ITAM
Keywords: Nonparametric methods, Nonlinear adaptive control, Identification for control Abstract: We propose a solution to the problem of parameter estimation of nonlinearly parameterized regressions - continuous or discrete time - and apply it for system identification and adaptive control. We restrict our attention to parameterizations that can be factorized as the product of two functions, a measurable one and a nonlinear function of the parameters to be estimated. Another feature of the proposed estimator is that parameter convergence is ensured without a persistency of excitation assumption. It is assumed that, after a coordinate change, some of the elements of the transformed function satisfy a monotonicity condition. The proposed estimators are applied to design identifiers and adaptive controllers for nonlinearly parameterized systems, which are traditionally tackled using overparameterization and assuming persistency of excitation.
Paper VI111-16.25
PDF · Video · A New Form of Rate Independence for Hysteresis Systems
Ikhouane, Faycal	Universitat Politecnica De Catalunya
Keywords: Grey box modelling Abstract: In mathematical texts hysteresis is defined as a rate independent phenomenon, and many mathematical models of hysteresis exhibit this rate independence property. However, experiments suggest that this property is only an approximation of the hysteresis behaviour when the excitation is slow enough. Using a generalized form of the hysteretic Duhem model, we show that, although this model is not rate independent, it still satisfies a new form of rate independence. We also explore the relationship between this new form and the usual property of rate independence.
Paper VI111-16.26
PDF · Video · Parameter Varying Mode Decoupling for LPV Systems
Baar, Tamas	Hungarian Academy of Sciences, Institute for Computer Science An
Luspay, Tamás	Institiute for Computer Science and Control
Bauer, Peter	Institute for Computer Science and Control
Keywords: LPV system identification, Subspace methods Abstract: The paper presents the design of parameter varying input and output transformations for Linear Parameter Varying systems, which make possible the control of a selected subsystem. In order to achieve the desired decoupling the inputs and outputs of the plant are blended together, and so the MIMO control problem is reduced to a SISO one. The new input of the blended system will only interact with the selected subsystem, while the response of the undesired dynamical part is suppressed in the single output. Decoupling is achieved over the whole parameter range, and no further dynamics are introduced. Linear Matrix Inequality methods form the basis of the proposed approach, where the minimum sensitivity is maximized for the subsystem to be controlled, while the H infinity norm of the subsystem to be decoupled is minimized. The method is evaluated on a flexible wing aircraft model.
Paper VI111-16.27
PDF · Video · Parameters Adaptive Identification of Bouc-Wen Hysteresis
Karabutov, Nikolay	MIREA - Russian Technological University
Shmyrin, Anatoly	Lipetsk State Technical University
Keywords: Modeling of manufacturing operations Abstract: The method of structural identification of nonlinear dynamic systems is designed. It is based on the analysis of the dynamic structures offered in work. The method of construction structures is described. Structures are defined on the special informational set. The concept structurally identifiability of nonlinear dynamic system is introduced. The algorithm of structural identification is offered. The algorithm of structural identification in the conditions of uncertainty is offered.
Paper VI111-16.28
PDF · Video · KBERG: A MatLab Toolbox for Nonlinear Kernel-Based Regularization and System Identification
Mazzoleni, Mirko	University of Bergamo
Scandella, Matteo	University of Bergamo
Previdi, Fabio	Universita' Degli Studi Di Bergamo
Keywords: Software for system identification Abstract: We present KBERG, a MatLab package for nonlinear Kernel-BasEd ReGularization and system identification. The toolbox provides a complete environment for running experiments on simulated and experimental data from both static and dynamical systems. The whole identification procedure is supported: (i) data generation, (ii) excitation signals design; (iii) kernel-based estimation and (iv) evaluation of the results. One of the main differences of the proposed package with respect to existing frameworks lies in the possibility to separately define experiments, algorithms and test, then combining them as desired by the user. Once these three quantities are defined, the user can simply run all the computations with only a command, waiting for results to be analyzed. As additional noticeable feature, the toolbox fully supports the manifold regularization rationale, in addition to the standard Tikhonov one, and the possibility to compute different (but equivalent) types of solutions other than the standard one.
Paper VI111-16.29
PDF · Video · Linear Time-Periodic System Identification with Grouped Atomic Norm Regularization
Yin, Mingzhou	ETH Zurich
Iannelli, Andrea	ETH Zurich
Khosravi, Mohammad	ETH Zurich
Parsi, Anilkumar	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Nonparametric methods, LPV system identification Abstract: This paper proposes a new methodology in linear time-periodic (LTP) system identification. In contrast to previous methods that totally separate dynamics at different tag times for identification, the method focuses on imposing appropriate structural constraints on the linear time-invariant (LTI) reformulation of LTP systems. This method adopts a periodically-switched truncated infinite impulse response model for LTP systems, where the structural constraints are interpreted as the requirement to place the poles of the non-truncated models at the same locations for all sub-models. This constraint is imposed by combining the atomic norm regularization framework for LTI systems with the group lasso technique in regression. As a result, the estimated system is both uniform and low-order, which is hard to achieve with other existing estimators. Monte Carlo simulation shows that the grouped atomic norm method does not only show better results compared to other regularized methods, but also outperforms the subspace identification method under high noise levels in terms of model fitting.
Paper VI111-16.30
PDF · Video · On the Vanishing and Exploding Gradient Problem in Gated Recurrent Units
Rehmer, Alexander	University of Kassel
Kroll, Andreas	University of Kassel
Keywords: Machine learning, Nonlinear system identification Abstract: Recurrent Neural Networks are applied in areas such as speech recognition, natural language and video processing, and the identification of nonlinear state space models. Conventional Recurrent Neural Networks, e.g. the Elman Network, are hard to train. A more recently developed class of recurrent neural networks, so-called gated recurrent units, outperform their counterparts on virtually every task. Previous explanation attempts have not been able to explain this phenomenon in its entirety. This paper aims to provide additional insights into the differences between RNNs and gated recurrent units in order to explain the superior perfomance of gated recurrent units.
Paper VI111-16.31
PDF · Video · A Fast Quasi-Newton-Type Method for Large-Scale Stochastic Optimisation
Wills, Adrian	University of Newcastle
Schön, Thomas Bo	Uppsala University
Jidling, Carl	Uppsala University
Keywords: Machine learning, Nonlinear system identification, Stochastic system identification Abstract: In recent years there has been an increased interest in stochastic adaptations of limited memory quasi-Newton methods, which compared to pure gradient-based routines can improve the convergence by incorporating second-order information. In this work we propose a direct least-squares approach conceptually similar to the limited memory quasi-Newton methods, but that computes the search direction in a slightly different way. This is achieved in a fast and numerically robust manner by maintaining a Cholesky factor of low dimension. The performance is demonstrated on real-world benchmark problems which shows improved results in comparison with already established methods.
Paper VI111-16.32
PDF · Video · An Empirical Assessment of the Universality of ANNs to Predict Oscillatory Time Series
Dercole, Fabio	Politecnico Di Milano
Sangiorgio, Matteo	Politecnico Di Milano
Schmirander, Yunus	Politecnico Di Milano
Keywords: Machine learning, Time series modelling, Nonlinear system identification Abstract: Artificial neural networks (ANNs) are universal function approximators, therefore suitable to be trained as predictors of oscillatory time series. Though several ANN architectures have been tested to predict both synthetic and real-world time series, the universality of their predictive power remained unexplored. Here we empirically test this universality across five well-known chaotic oscillators, limiting the analysis to the simplest architecture, namely multi-layer feed-forward ANN trained to predict one sampling step ahead. To compare different predictors, data are sampled according to their frequency content and the ANN structure scales with the characteristic dimensions of the oscillator. Moreover, the quality of recursive multi-step-ahead predictions are compared in terms of the system's (largest) Lyapunov exponent (LLE), i.e., the predictive power is measured in terms of the number of Lyapunov times (LT, the LLE inverse) predicted within a prescribed (relative) error. The results confirm the rather uniform predictive power of the proposed ANN architecture.

VI111-17
Particle Filtering/Monte Carlo Methods	Regular Session
Chair: Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Co-Chair: Imsland, Lars	Norwegian University of Science and Technology
Paper VI111-17.1
PDF · Video · Bayesian Fill Volume Estimation Based on Point Level Sensor Signals
Zumsande, Johannes	Leibniz University Hannover
Kortmann, Karl-Philipp	Leibniz University Hannover
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Particle filtering/Monte Carlo methods, Bayesian methods, Stochastic system identification Abstract: In dry bulk and fluid processing, the composites are usually stored in hoppers, tanks, or other containers. Due to the economic advantages, binary point level sensors, which detect fill level exceeding, are widely used for process monitoring and control. In this paper, we propose different filters for estimating the probability distribution of the fill volume based on a time-variant measurement distribution and a stochastic physical model with white process noise. A filter based on the model prediction with separated measurement update and two Bayesian particle filters are proposed and compared with a simulated ground truth. The performance measures are the root-mean-square error, the precision of the 95% and 75% credible intervals, and the average value of the estimated probability density function at the simulated fill volumes.
Paper VI111-17.2
PDF · Video · Auxiliary-Filter-Free Incompressible Particle Flow Filtering Using Direct Estimation of the Log-Density Gradient with Target Tracking Examples
Choe, Yeongkwon	Seoul National University
Park, Chan Gook	Seoul National Univ
Keywords: Particle filtering/Monte Carlo methods, Estimation and filtering, Mechanical and aerospace estimation Abstract: This paper presents an incompressible particle flow filtering method that does not require an auxiliary filter by estimating log-density gradients directly from particles. Particle flow filter (PFF) is likely to avoid particle impoverishment and degeneracy problems that occur in particle filters because particles themselves move toward desired density to perform measurement updates. There are various implementation forms for PFF depending on the assumptions made about the flow. This paper deals with PFF using incompressible flow. Incompressible PFF requires the log-density gradient to calculate the flow. The well-known gradient estimation method for incompressible PFF is a finite difference method collaborating with k nearest neighbors(kNN) method. Since this method requires the prior knowledge about the prior density value in each particle, it is necessary to use an auxiliary filter or a density estimation technique. As a result, the performance of an auxiliary filter or a density estimation technique can directly affect the PFF performance, and the finite difference method is more likely to be inaccurate than directly estimating the log-density gradient. Therefore, this paper presents a PFF structure applying least-squares log-density gradient (LSLDG) method that estimates the log-density gradient directly from particles. In order to verify the performance of the presented structure, this paper performs both single and multiple target tracking simulations. Simulation results demonstrate that the presented structure has a relatively good estimation performance and works more robustly for various situations.
Paper VI111-17.3
PDF · Video · Sampling Variance Update Method in Monte Carlo Model Predictive Control
Nakatani, Shintaro	University of Tsukuba
Date, Hisashi	University of Tsukuba
Keywords: Particle filtering/Monte Carlo methods, Randomized methods Abstract: This study describes the influence of user parameters on control performance in a Monte-Carlo model predictive control (MCMPC). MCMPC based on Monte-Carlo sampling depends significantly on the characteristics of sampling distribution. We quantified the effect of user determinable parameters on control performance using the relationship between the algorithm of MCMPC and convergence to the optimal solution. In particular, we investigated the limitations associated with the variance of sampling distribution causing a trade-off relationship with the convergence speed and accuracy of estimation. To overcome this limitation, we proposed two variance updating methods and new MCMPC algorithm. Furthermore, the effectiveness of the numerical simulation was verified.
Paper VI111-17.4
PDF · Video · Optimal Reduction of Dirac Mixture Densities on the 2-Sphere
Frisch, Daniel	KIT
Li, Kailai	Karlsruhe Institute of Technology (KIT)
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Particle filtering/Monte Carlo methods, Stochastic system identification, Estimation and filtering Abstract: This paper is concerned with optimal approximation of a given Dirac mixture density on the S2 manifold, i.e., a set of weighted samples located on the unit sphere, by an equally weighted Dirac mixture with a reduced number of components. The sample locations of the approximating density are calculated by minimizing a smooth global distance measure, a generalization of the well-known Cramér-von Mises Distance. First, the Localized Cumulative Density (LCD) together with the von Mises-Fisher kernel provides a continuous characterization of Dirac mixtures on the S2 manifold. Second, the L2 norm of the difference of two LCDs is a unique and symmetric distance between the corresponding Dirac mixtures. Thereby we integrate over all possible kernel sizes instead of choosing one specific kernel size. The resulting approximation method facilitates various efficient nonlinear sample-based state estimation methods.
Paper VI111-17.5
PDF · Video · Probability Density Function Control for Stochastic Nonlinear Systems Using Monte Carlo Simulation
Zhang, Qichun	University of Bradford
Wang, Hong	Pcific Northwest National Laboratory
Keywords: Particle filtering/Monte Carlo methods, Synthesis of stochastic systems Abstract: This paper presents an implementable framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

VI112
Systems and Signals - Adaptive and Learning Systems
VI112-01 Active Disturbance Rejection Control: Data-Driven Mechanisms, Analysis and Engineering Practice   Open Invited Session, 12 papers
VI112-02 History of Adaptive Control   Open Invited Session, 5 papers
VI112-03 Iterative Learning Control and Repetitive Control   Open Invited Session, 21 papers
VI112-04 Adaptive Observers and Control   Regular Session, 5 papers
VI112-05 Consensus and Reinforcement Learning Control   Regular Session, 9 papers
VI112-06 Extremum Seeking and Model-Free Adaptive Control   Regular Session, 7 papers
VI112-07 Nonlinear Adaptive Control   Regular Session, 11 papers

VI112-01
Active Disturbance Rejection Control: Data-Driven Mechanisms, Analysis and Engineering Practice	Open Invited Session
Chair: Tan, Ying	The Univ of Melbourne
Co-Chair: Xue, Wenchao	Chinese Academy of Sciences, Beijing 100190,
Organizer: Xue, Wenchao	Chinese Academy of Sciences, Beijing 100190,
Organizer: Gao, Zhiqiang	Cleveland State Univ
Organizer: Tan, Ying	The Univ of Melbourne
Organizer: Hou, Zhongsheng	Beijing Jiaotong Univ
Organizer: Sira-Ramirez, Hebertt	CINVESTAV-IPN
Paper VI112-01.1
PDF · Video · The Combination of Q-Learning Based Tuning Method and Active Disturbance Rejection Control for SISO Systems with Several Practical Factors (I)
Chen, Sen	Chinese Academy of Sciences
Bai, Wenyan	Chinese Academy of Sciences
Chen, Zhixiang	Rocket Force University of Engineering
Zhao, Zhiliang	Shaanxi Normal University
Keywords: Learning for control, Nonlinear adaptive control, Adaptive observer design Abstract: The paper studies the control design and parameter tuning for SISO systems with several practical factors, including nonlinear uncertainty, time delay, input saturation and measurement noise. An active disturbance rejection control design is proposed to actively compensate for the above nonlinear factors. Moreover, an automatic tuning method based on Q-learning is proposed, which is featured with model-free and data-driven properties. By the tentative actions in the proposed Q-learning algorithm, the optimized control parameters can be obtained.
Paper VI112-01.2
PDF · Video · Servo Velocity Control Using a P+ADOB Controller (I)
Luna Pineda, Jose Luis	CINVESTAV
Asiain De la Luz, Erick	Centro De Investigación Y De Estudios Avanzados Del IPN
Garrido-Moctezuma, Rubén Alejandro	Centro De Investigacion Y De Estudios Avanzados Del I.P.N
Keywords: Adaptive observer design, Experiment design Abstract: This paper describes preliminary results on a Proportional plus Adaptive Disturbance Observer (P+ADOB) controller applied to velocity regulation tasks in a servo system. Adaptation law is obtained to estimate the servo system input gain, which is subsequently employed in the design of a Disturbance Observer. Compared with previous approaches, this feature relaxes the assumption on exact knowledge on the input gain, and only upper and lower bounds on this term are assumed known. A stability proof assuming constant disturbances allows concluding that the estimate of the input gain is bounded, and the velocity tracking error converges to zero. Real-time experiments illustrate the performance of the proposed controller.
Paper VI112-01.3
PDF · Video · Error Analysis of ADRC Linear Extended State Observer for the System with Measurement Noise (I)
Song, Jia	Beihang University, Beijing
Zhao, Mingfei	Beihang University
Gao, Ke	School of Astronautics, Beihang University, Beijing
Su, Jiangcheng	Beihang University
Keywords: Adaptive observer design, Filtering and smoothing, Frequency domain identification Abstract: The Active Disturbance Rejection Control (ADRC) method, which is not dependent upon the accurate system model and has strong robustness for adjusting to disturbances, is widely used in many fields. As the core of the ADRC method, the performance of the Extended State Observer (ESO) is of great importance to the controller. In practical applications, the observer will inevitably receive the influence of measurement noise, but the research on the extent of impact is less. This article takes into account observing errors caused by measurement noise, deriving and analyzing their impact on Linear Extended State Observer (LESO) performance firstly. According to the theoretical derivation and simulation analysis, an improved controller is designed, which can effectively suppress the effect of noise on the actuator and system output.
Paper VI112-01.4
PDF · Video · Friction Compensation and Limit Cycle Suppression at Low Velocities Based on Extended State Observer (I)
Piao, Minnan	Nankai University
Wang, Ying	Science and Technology on Space Physics Laboratory
Sun, Mingwei	Nankai University
Chen, Zengqiang	Nankai University
Keywords: Adaptive observer design, Mechanical and aerospace estimation Abstract: This paper investigates the extended state observer (ESO) based friction compensation at low velocities with only the position measurement. ESO is an effective model-free friction compensation technique and thus is employed in this paper. Based on the describing function analysis, it is revealed that the higher the observer bandwidth is, the larger the velocity feedback gain should be to suppress the limit cycle. However, the available damping provided by the derivative control is restricted when the signal-to-noise ratio of the velocity is low. Under such a condition, the observer bandwidth cannot be high and the friction compensation performance is thus limited. To solve this conflict, a switching control law based on the ESO is proposed to compensate the friction in a fast manner and suppress the limit cycle simultaneously. The switching strategy aims to determine when the disturbance compensation should be added in the control signal to eliminate the friction induced oscillations without making the system response become sluggish. Such an idea is enlightened by the fact that nonlinear modifications to the integral action are always needed in practice. Hardware experiments are performed on a brushless DC motor to validate the effectiveness of the proposed compensation scheme.
Paper VI112-01.5
PDF · Video · Half-Gain Tuning for Active Disturbance Rejection Control (I)
Herbst, Gernot	Siemens AG
Hempel, Arne-Jens	Technische Universität Chemnitz
Göhrt, Thomas	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Adaptive observer design, Estimation and filtering Abstract: A new tuning rule is introduced for linear active disturbance rejection control (ADRC), which results in similar closed-loop dynamics as the commonly employed bandwidth parameterization design, but with lower feedback gains. In this manner the noise sensitivity of the controller is reduced, paving the way for using ADRC in more noise-affected applications. It is proved that the proposed tuning gains, while rooted in the analytical solution of an algebraic Riccati equation, can always be obtained from a bandwidth parameterization design by simply halving the gains. This establishes a link between optimal control and pole placement design.
Paper VI112-01.6
PDF · Video · New Tuning Methods of Both PID and ADRC for MIMO Coupled Nonlinear Uncertain Systems (I)
Zhong, Sheng	Chinese Academy of Sciences
Huang, Yi	Institute of Systems Science, Chinese Academy of Sciences
Guo, Lei	Chinese Academy of Sciences
Keywords: Nonlinear adaptive control, Adaptive observer design Abstract: This paper proposes a new and simple design method for both the famous proportional-integral-derivative (PID) control and the active disturbance rejection control (ADRC) of multi-input multi-output (MIMO) coupled nonlinear uncertain systems. Firstly, a quantitative lower bound to the bandwidth of the parallel extended state observers (ESOs) of ADRC is given, which is not necessarily of high gain. Then, inspired by an inherent but less noticed relationship between PID and ADRC, a new and concrete PID tuning rule is introduced, which can achieve both the strong robust decoupling control and good tracking performance of the MIMO closed-loop systems. Finally, the theoretical results, which reveal that why and how both PID control and ADRC can effectively deal with decoupling problem for MIMO coupled nonlinear uncertain systems, are verified by simulations.
Paper VI112-01.7
PDF · Video · Model-Based Feed-Forward Control for Time-Varying Systems with an Example for SRF Cavities (I)
Pfeiffer, Sven	DESY Hamburg
Eichler, Annika	DESY
Schlarb, Holger	DESY
Keywords: Time series modelling, Model reference adaptive control Abstract: To derive feed-forward signals the impulse response matrix has to be inverted. While for time-invariant systems this matrix has a Toeplitz structure, this is not the case for time-variant systems. Thus, the derivation of the inverse scales cubically with the length of the signal horizon. This paper presents an efficient way to calculate the inverse impulse response matrix based on the description as linear fractional transformation. With this the calculation effort scales only linearly with the horizon. The feed-forward signal generation is applied in this paper for superconducting accelerating structures. The superconducting accelerating cavities are operated in pulsed mode. Each cavity is fed by a 1.3,GHz radio frequency signal with high power. Model-based feed-forward control is essential here to relief the feedback controller and with this to minimize the power consumption and therefore heating of different components. To derive a model-based feed-forward signal, first, a reasonable reference signal is to be chosen, which is done here based on physical properties of the cavities, then the efficient inversion of the impulse response matrix is applied. Experimentally results from the European X-ray free-electron laser are presented.
Paper VI112-01.8
PDF · Video · Flatness Based ADRC Control of Lagrangian Systems: A Moving Crane (I)
Sira-Ramirez, Hebertt J.	CINVESTAV-IPN
Gao, Zhiqiang	Cleveland State Univ
Keywords: Nonlinear adaptive control Abstract: A procedure is described for direct tangent linearization, around a given equilibrium point, of non-linear multivariable Lagrangian systems, in terms of second order variational expansions of the Lagrangian function. When the linearized model is controllable (i.e., it exhibits the flatness property), we present an Active Disturbance Rejection Control (ADRC) scheme, valid for stabilization and flat output reference trajectory tracking tasks designed on the basis of the incremental system. The linear approach requires only generalized incremental position measurements, with no explicit need for incremental velocity observers. The ADRC controller is cast in terms of equivalent classical linear compensation networks. A moving crane example is presented which illustrates, through digital computer simulations, the effectiveness of the proposed control scheme.
Paper VI112-01.9
PDF · Video · Disturbance Observer Based Control Design Via Active Disturbance Rejection Control: A PMSM Example (I)
Aguilar-Orduña, Mario Andrés	CINVESTAV
Zurita-Bustamante, Eric William	CINVESTAV
Sira-Ramirez, Hebertt J.	CINVESTAV-IPN
Gao, Zhiqiang	Cleveland State Univ
Keywords: Nonlinear adaptive control Abstract: A new Disturbance Observer Based (DOB) controller design procedure is here obtained via a reinterpretation of the disturbance estimation scheme, present in the Extended State Observer (ESO) based Active Disturbance Rejection (ADR) control scheme. If the reinterpreted disturbance estimation process is explicitly used, now, in combination with an ADR controller, the overall total disturbance effects are substantially diminished in the feedback loop, beyond that achievable by ESO-based ADR control alone. The context is that of nonlinear differentially flat systems, simplified to Kronecker chains of integrations. A Permanent Magnet Synchronous Motor (PMSM) example is examined and its performance is assessed from an experimental setting.
Paper VI112-01.10
PDF · Video · Anti-Windup Disturbance Rejection Control Design for Sampled Systems with Output Delay and Asymmetric Actuator Saturation Constraint (I)
Geng, Xinpeng	Dalian University of Technology
Wang, Zhencai	Dalian University of Technology
Hao, Shoulin	Dalian University of Technology
Liu, Tao	Dalian University of Technology (DLUT)
Nagy, Zoltan K.	Loughborough Univ
Keywords: Adaptive observer design, Estimation and filtering Abstract: A novel anti-windup disturbance rejection control design is proposed for industrial sampled systems with output delay and asymmetric actuator saturation constraint. To deal with the asymmetric actuator saturation constraint as often encountered in engineering practice, the input constraint is equivalently transformed into a symmetric actuator saturation constraint for the convenience of control design. Based on the equivalent system description, a model-based extended state observer (MESO) is designed to simultaneously estimate the system state and disturbance, which becomes an anti-windup compensator when the actuator saturation occurs. In order to compensate for the delay mismatch in MESO, a generalized predictor is utilized to estimate the undelayed system output. Accordingly, a pole placement approach is given to design the feedback controller. A set-point pre-filter is designed to ensure no steady-state output tracking error, in terms of a desired transfer function for the set-point tracking. Based on the delay-dependent sector condition and generalized free-weighting-matrix (GFWM), a suffcient condition guaranteeing the stability of the closed-loop system is established in terms of linear matrix inequalities (LMIs). An illustrative example from the literature is used to demonstrate the effectiveness and advantage of the proposed control method.
Paper VI112-01.11
PDF · Video · Active Disturbance Rejection Control for Wheeled Mobile Robots with Parametric Uncertainties (I)
Zhu, Yicheng	Shanghai Jiao Tong University
Huang, Yao	Shanghai Jiao Tong University
Su, Jianbo	Shanghai Jiaotong Univ
Pu, Cuiping	Kunming University
Keywords: Disturbance rejection, Robust control, Lagrangian and Hamiltonian systems, Application of nonlinear analysis and design Abstract: In this paper, an efficient controller design method is proposed based on active disturbance rejection control (ADRC) scheme for stabilization problem of wheeled mobile robots with parametric uncertainties, which can make the system converge quickly. By using the extended state observer (ESO), both the system states and the unknown parametric uncertainties could be estimated. In addition, the input-state scaling technique is used to transform the system into two decoupled subsystems. Based on the decoupled subsystems, a switching controller and ADRC are designed. Simulation results show that the proposed scheme can stabilize the wheeled mobile robot system asymptotically despite the presence of parametric uncertainties.
Paper VI112-01.12
PDF · Video · Discrete Reduced-Order Active Disturbance Rejection Control for Marine Engines Using Variable Sampling Rate Control Scheme under Limited Bandwidth (I)
Wang, Runzhi	Harbin Engineering University
Li, Xuemin	Harbin Engineering University
Ma, Xiuzhen	College of Power and Energy Engineering, Harbin Engineering Univ
Keywords: Control architectures in marine systems, Nonlinear and optimal marine system control Abstract: In this paper, the reduced-order active disturbance rejection control (RADRC) is studied for marine engine speed control. The benefits of using RADRC are demonstrated by bode diagram method with the transfer function between input disturbance and system output. Discrete RADRC and active disturbance rejection control (ADRC) are designed for marine engine speed control by adopting variable sampling rate control method. The proposed method is assessed by experiment on a hard-in-loop (HIL) engine test platform. Except the step-response indexes, ADRC and RADRC are compared in more indexes. The results demonstrate that RADRC has superiority during the sudden load varying process. For steady-state, a single smaller observer bandwidth in RADRC can make a good compromise for a wide range engine speed. It also has been found that the index of total variation (TV) in control input for RADRC is inferior to the ADRC. Overall, RADRC is a promising method for marine engine speed control.

VI112-02
History of Adaptive Control	Open Invited Session
Chair: Fradkov, Alexander L.	Russian Academy of Sciences
Co-Chair: Polyak, Boris T.	Moscow Inst. of Control Sciences
Organizer: Fradkov, Alexander L.	Russian Academy of Sciences
Organizer: Giri, Fouad	University of Caen Normandie
Paper VI112-02.1
PDF · Video · Speed-Gradient Method in Adaptive Control and Identification. Historical Overview (I)
Andrievsky, Boris	Inst. for Problems of Mechanical Engineering of the RAS
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Plotnikov, Sergei	Institute for Problems of Mechanical Engineering, Russian Academ
Keywords: Nonlinear adaptive control, Nonlinear system identification, Model reference adaptive control Abstract: The paper provides a historical overview of the Speed-gradient method and its applications to adaptive control and identification problems since mid-1970-th, when the method was originated, till the present days. It is demonstrated that it is an efficient and a useful tool for solving a wide range of engineering problems.
Paper VI112-02.2
PDF · Video · Adaptive and Robust Control in the USSR (I)
Fradkov, Alexander L.	Russian Academy of Sciences
Polyak, Boris T.	Moscow Inst. of Control Sciences
Keywords: Nonlinear adaptive control, Machine learning, Extremum seeking and model free adaptive control Abstract: Control theory in the USSR after WW2 achieved serios successes in such fields as optimal control, absolute stability, delay systems, pulse and relay control. Later there was a huge peak of breakthrough research on adaptation, learning and pattern recognition, starting at 1960th. Next approach to control under uncertainty relates to robustness; the results here are also deep and pioneering. The contributions to all these fields were due to Feldbaum, Aizerman, Lerner, Tsypkin, Yakubovich and their coauthors and colleagues. We try to survey the main stages of this fascinating competition.
Paper VI112-02.3
PDF · Video · Centennary of Yakov Zalmanovich Tsypkin's Birth (I)
Polyak, Boris T.	Moscow Inst. of Control Sciences
Keywords: Nonlinear adaptive control, Estimation and filtering, Identification for control Abstract: The paper is devoted to the memory of Yakov Zalmanovich Tsypkin and his ``life in feedback control''.
Paper VI112-02.4
PDF · Video · Notes on Yakubovich’s Method of Recursive Objective Inequalities and Its Application in Adaptive Control and Robotics (I)
Gusev, Sergei V.	St. Petersburg State Univ
Bondarko, Vladimir A.	St. Petersburg State Univ
Keywords: Learning for control, Nonlinear adaptive control, Identification for control Abstract: The purpose of the paper is to introduce to the control community the brilliant but little-known part of Yakubovich's academic heritage - the method of recurrent objective inequalities. This method was successfully used by V.A.Yakubovich and his followers in pattern recognition, adaptive control and robotics. The paper deals with the last two topics. The most of surveyed results were published in Russian. A 1975 video about experiments with the first Soviet self-learning robot will be shown.
Paper VI112-02.5
PDF · Video · Early History of Machine Learning (I)
Fradkov, Alexander L.	Russian Academy of Sciences
Keywords: Reinforcement learning control, Knowledge-based control Abstract: Machine learning belongs to the crossroad of cybernetics (control science) and computer science. It is attracting recently an overwhelming interest, both of professionals and of the general public. In the talk a brief overview of the historical development of the machine learning field with a focus on the development of mathematical apparatus in its first decades is provided. A number of little-known facts published in hard to reach sources are presented.

VI112-03
Iterative Learning Control and Repetitive Control	Open Invited Session
Chair: Oomen, Tom	Eindhoven University of Technology
Co-Chair: Tan, Ying	The Univ of Melbourne
Organizer: Oomen, Tom	Eindhoven University of Technology
Organizer: Chu, Bing	University of Southampton
Organizer: Barton, Kira	University of Michigan
Organizer: Tan, Ying	The Univ of Melbourne
Paper VI112-03.1
PDF · Video · Iterative Bias Estimation for an Ultra-Wideband Localization System (I)
van der Heijden, Bas	Delft University of Technology
Ledergerber, Anton	ETH
Gill, Rajan Joshua	ETH
D'Andrea, Raffaello	ETH Zurich
Keywords: Adaptive observer design, Iterative and Repetitive learning control, Bayesian methods Abstract: An iterative bias estimation framework is presented that mitigates position-dependent ranging errors often present in ultra-wideband localization systems. State estimation and control are integrated, such that the positioning accuracy improves over iterations. The framework is experimentally evaluated on a quadcopter platform, resulting in improvements in the tracking performance with respect to ground truth, and also smoothing the overall flight by significantly reducing unwanted oscillations; see https://youtu.be/J-htfbzf40U for a video.
Paper VI112-03.2
PDF · Video · Output Feedback Based Iterative Learning Control with Finite Frequency Range Specifications Via a Heuristic Approach for Batch Processes with Polytopic Uncertainties (I)
Hao, Shoulin	Dalian University of Technology
Liu, Tao	Dalian University of Technology (DLUT)
Paszke, Wojciech	University of Zielona Gora
Tao, Hongfeng	Jiangnan University
Keywords: Iterative and Repetitive learning control, Learning for control Abstract: For robust control and iterative optimization of industrial batch processes with polytopic uncertainties, this paper proposes a robust output feedback based iterative learning control (ILC) design in terms of finite frequency range stability specifications. Robust stability conditions for the closed-loop ILC system along both time and batch directions are first established based on the generalized Kalman-Yakubovich-Popov lemma and linear repetitive system theory. To facilitate the ILC controller design with respect to process uncertainties described in a polytopic form, extended sufficient conditions for the system stability are then derived in terms of matrix inequalities. Correspondingly, a two-stage heuristic approach is developed to iteratively compute feasible ILC controller gains for implementation. An illustrative example is given to demonstrate the effectiveness of the proposed control design.
Paper VI112-03.3
PDF · Video · A Model-Free Loop-Shaping Method Based on Iterative Learning Control (I)
Shih, Li-Wei	National Taiwan University
Chen, Cheng-Wei	National Taiwan University
Keywords: Learning for control, Iterative and Repetitive learning control Abstract: Many techniques have been developed for the loop-shaping method in control design. While most loop-shaping methods apply a model of the open-loop controlled plant, the resulting performance depends on the accuracy of the dynamical model. The aim of this paper is to develop a model-free loop-shaping technique. The core idea is to convert the model matching problem to a trajectory tracking problem. To achieve the desired loop gain, we need to determine the control input such that the system output tracks the impulse response of the loop gain function. In this paper, a model-free iterative learning control (ILC) algorithm is applied to solve this tracking problem. Once the ILC converges, the feedback controller that meets the desired loop gain can then be constructed. This method does not require the model of the controlled plant, hence it provides better performance of loop-shaping control design. The proposed method is validated through numerical simulation on a 3-rd order plant.
Paper VI112-03.4
PDF · Video · An ILC Approach to Feed-Forward Friction Compensation (I)
Norrlof, Mikael	Linköping University
Gunnarsson, Svante	Linkoping University
Keywords: Iterative and Repetitive learning control, Nonlinear system identification, Grey box modelling Abstract: An iterative, learning based, feed-forward method for compensation of friction in industrial robots is studied. The method is put into an ILC framework by using a two step procedure proposed in literature. The friction compensation method is based on a black-box friction model which is learned from operational data, and this can be seen as the first step in the method. In the second step the learned model is used for compensation of the friction using the reference joint velocity as input. The approach is supported by simulation experiments.
Paper VI112-03.5
PDF · Video · Improving Mechanical Ventilation for Patient Care through Repetitive Control (I)
Reinders, Joey	Eindhoven University of Technology & Demcon Advanced Mechatronic
Verkade, Ruben	Demcon
Hunnekens, Bram	Eindhoven University of Technology
van de Wouw, Nathan	Eindhoven Univ of Technology
Oomen, Tom	Eindhoven University of Technology
Keywords: Iterative and Repetitive learning control Abstract: Mechanical ventilators sustain life of patients that are unable to breathe (sufficiently) on their own. The aim of this paper is to improve pressure tracking performance of mechanical ventilators for a wide variety of sedated patients. This is achieved by utilizing the repetitive nature of sedated ventilation through repetitive control. A systematic design procedure of a repetitive controller for mechanical ventilation is presented. Thereafter, the controller is implemented in an experimental setup showing superior tracking performance for a variety of patients.
Paper VI112-03.6
PDF · Video · Iterative Learning Control and Gaussian Process Regression for Hydraulic Cushion Control (I)
Trojaola, Ignacio	Ikerlan Technology Research Centre
Elorza, Iker	Ikerlan
Irigoyen, Eloy	University of the Basque Country (UPV/EHU)
Pujana-Arrese, Aron	IKERLAN IK4
Calleja, Carlos	IKERLAN
Keywords: Iterative and Repetitive learning control, Nonlinear system identification Abstract: In this paper, we investigate on extending a feed-forward control scheme for the force control circuit of a hydraulic cushion with Gaussian Process nonlinear regression and Iterative Learning Control. Gaussian Processes allow the possibility of estimating the unknown proportional valve nonlinearities and provide uncertainty measurements of the predictions. However, the system must realize a high precision tracking control which is not achievable if any uncertainty remains in the estimation. Therefore, an extra feed-forward signal based on Iterative Learning Control is used to obtain a precise and fast force reference tracking performance. The design of the Iterative Learning Control is based on an inverted linearized model in which a fourth-order low-pass filter is included to attenuate the unknown valve dynamics. The low-pass filter is split up into two second-order low-pass filters, one of which is applied in the positive, the other in the negative, direction of time, resulting in zero-phase filtering. Simulation results show that Gaussian Process regression allows the possibility of using feed-forward control and that the force tracking performance is improved by introducing Iterative Learning Control.
Paper VI112-03.7
PDF · Video · Supervised Output Regulation Via Iterative Learning Control for Rejecting Unknown Periodic Disturbances (I)
Kocan, Oktay	Mr
Astolfi, Daniele	CNRS - Univ Lyon 1
Poussot-Vassal, Charles	Onera
Manecy, Augustin	Onera
Keywords: Iterative and Repetitive learning control, Learning for control, Filtering and smoothing Abstract: The internal model principle (IMP) in linear robust output regulation theory states that a dynamical controller needs to incorporate a copy of the model generating the periodic signals in order to achieve perfect rejection/tracking, robustly with respect to plant's parameters. On the other hand Iterative Learning Control (ILC) is a data-based approach which not requires any a priori knowledge, and can be used to find the required control action for attenuating periodic disturbances or tracking periodic references. The control signal generated by ILC includes the frequency and amplitude information of the disturbance and can be used to build the internal model needed for a linear output regulator problem. The objective of this work is therefore that of trying to combine the two approaches, that is IMP and ILC, in order to retain the advantages of each methodology. The proposed methodology, denoted as Supervised Output Regulation via Iterative Learning Control (SOR-ILC), allows to address the problem of output regulation in presence of unknown frequencies. The performances of SOR-ILC are validated through numerical simulations in case of complex periodic disturbances and parameter uncertainties.
Paper VI112-03.8
PDF · Video · On Improving Transient Behavior and Steady-State Performance of Model-Free Iterative Learning Control (I)
Zhang, Geng-Hao	National Taiwan University
Chen, Cheng-Wei	National Taiwan University
Keywords: Iterative and Repetitive learning control, Recursive identification, Time series modelling Abstract: A novel model-free iterative learning control algorithm is proposed in this paper to improve both the robustness against output disturbances and the tracking performance in steady-state. For model-free ILC, several methods have been investigated, such as the time-reversal error filtering, the Model-Free Inversion-based Iterative Control (MFIIC), and the Non-Linear Inversion-based Iterative Control (NLIIC). However, the time-reversal error filtering has a conservative learning rate. Other two methods, although with much faster error convergence, have either a high noise sensitivity or a non-optimized steady-state. To improve the performance and robustness of model-free ILC, we apply the time-reversal based ILC and recursively accelerate its error convergence using the online identified learning filter. The effectiveness of the proposed algorithm has been validated by a numerical simulation. The proposed approach not only improves the transient response of the MFIIC, but achieves lower tracking error in steady-state compared to that of the NLIIC.
Paper VI112-03.9
PDF · Video · Iterative Learning Control for Output Tracking of Systems with Unmeasurable States (I)
Li, Xuefang	Sun Yat-Sen University
Shen, Dong	Renmin University of China
Keywords: Iterative and Repetitive learning control Abstract: In this work, a new design framework of adaptive iterative learning control (ILC) approach for a class of uncertain nonlinear systems is presented. By making use of the closed-loop reference model which works as an observer, the developed adaptive ILC method is able to be adopted to deal with the output tracking problem of nonlinear systems without requiring the measurability of system states. In the system, the uncertainties are formed by the product of unknown parameters and state functions that are also unknown as the system states are not available. In order to facilitate the controller design and convergence analysis, the composite energy function (CEF) method is employed, and the accurate tracking task can be realized successfully. The proposed approach extends CEF-based ILC approach sucessfully to output tracking control of nonlinear systems without requiring the system states information and complicated observer design. The effectiveness of the proposed ILC scheme is verified through an illustrative numerical example.
Paper VI112-03.10
PDF · Video · Iterative Learning Control for Switched Systems in the Presence of Input Saturation (I)
Pakshin, Pavel	Arzamas Polytechnic Institute of R.E. Alekseev NSTU
Emelianova, Julia	Arzamas Polytechnic Institute of R.E. Alekseev NSTU
Rogers, Eric	Univ of Southampton
Galkowski, Krzysztof	Univ. of Zielona Gora
Keywords: Iterative and Repetitive learning control, Learning for control, Hybrid and switched systems modeling Abstract: The paper considers iterative learning control for differential and discrete switched linear systems with control input saturation. A new design is developed based on the use of common vector Lyapunov functions. An example demonstrating the features and advantages of the new design is given.
Paper VI112-03.11
PDF · Video · On the Role of Models in Learning Control: Actor-Critic Iterative Learning Control (I)
Poot, Maurice	Eindhoven University of Technology
Portegies, Jim	Eindhoven University of Technology
Oomen, Tom	Eindhoven University of Technology
Keywords: Learning for control, Consensus and Reinforcement learning control, Iterative and Repetitive learning control Abstract: Learning from data of past tasks can substantially improve the accuracy of mechatronic systems. Often, for fast and safe learning a model of the system is required. The aim of this paper is to develop a model-free approach for fast and safe learning for mechatronic systems. The developed actor-critic iterative learning control (ACILC) framework uses a feedforward parameterization with basis functions. These basis functions encode implicit model knowledge and the actor-critic algorithm learns the feedforward parameters without explicitly using a model. Experimental results on a printer setup demonstrate that the developed ACILC framework is capable of achieving the same feedforward signal as preexisting model-based methods without using explicit model knowledge.
Paper VI112-03.12
PDF · Video · Stability of Switched Differential Repetitive Processes and Iterative Learning Control Design (I)
Emelianova, Julia	Arzamas Polytechnic Institute of R.E. Alekseev NSTU
Pakshin, Pavel	Arzamas Polytechnic Institute of R.E. Alekseev NSTU
Emelianov, Mikhail	Arzamas Polytechnic Institute of R.E. Alekseev NSTU
Keywords: Iterative and Repetitive learning control, Stability and stabilization of hybrid systems, Learning for control Abstract: In this paper general stability conditions of differential nonlinear repetitive processes with switching are obtained. The approach is based on the development of a method that uses vector Lyapunov functions and the properties of the counterpart of its divergence. The obtained results are applied to iterative learning control design for switched linear system. An example that demonstrate effectiveness of the new design is given.
Paper VI112-03.13
PDF · Video · New Relaxed Stability and Stabilization Conditions for Differential Linear Repetitive Processes (I)
Maniarski, Robert	University of Zielona Góra
Paszke, Wojciech	University of Zielona Gora
Rogers, Eric	Univ of Southampton
Boski, Marcin	Faculty of Computer, Electrical and Control Engineering Universi
Keywords: Iterative and Repetitive learning control Abstract: The paper develops new results on the stability analysis of differential linear repetitive processes. These processes are a distinct class of two-dimensional (2D) systems that arise in the modelling of physical processes and also the existing systems theory for them can be used to effect in solving control problems for other classes of systems, including iterative learning control design. This paper uses a version of the Kalman-Yakubovich-Popov Lemma to develop relaxed conditions for the stability property in terms of linear matrix inequalities (LMIs). The main result is reduced conservatism in applying tests for the stability property with an extension to state feedback control law design. The numerical example of a metal rolling process is given to support the new results.
Paper VI112-03.14
PDF · Video · Repetitive Control of Nonlinear Systems Via Feedback Linearization: An Application to Robotics (I)
Biagiotti, Luigi	University of Modena and Reggio Emilia
Keywords: Iterative and Repetitive learning control Abstract: In this paper, a novel Repetitive Control (RC) scheme for a class of nonlinear systems is presented and discussed. This work generalizes the approach proposed in Biagiotti et al. (2015) where a RC scheme based on the modification of a B-spline reference trajectory has been presented. Also in this case, the generation of the B-splines based on dynamic filters plays a crucial role in the control scheme since it allows to implement a feedforward action that, coupled with an exact feedback linearization and a stabilizing state feedback, makes the RC robustly asymptotically stable. In this manner, the tracking error at the via-points defining the reference trajectory is nullified even if parametric uncertainties on the system model or exogenous (cyclic) disturbances are present. The application to a two-dof robot manipulator shows the effectiveness of the proposed method and its inherent robustness.
Paper VI112-03.15
PDF · Video · Monotonically Convergent Iterative Learning Control for Piecewise Affine Systems (I)
Strijbosch, Nard	Eindhoven University of Technology
Spiegel, Isaac	University of Michigan
Barton, Kira	University of Michigan
Oomen, Tom	Eindhoven University of Technology
Keywords: Iterative and Repetitive learning control, Learning for control, Hybrid and switched systems modeling Abstract: Piecewise affine (PWA) systems enable modelling of systems that encompass hybrid dynamics and nonlinear effects. The aim of this paper is to develop an ILC framework for PWA systems. A new approach to analyse monotonic convergence is developed for PWA systems. This is achieved by exploiting the incremental l2-gain leading to sufficient LMI conditions guaranteeing monotonic convergence. An example confirms the monotonic convergence property for ILC applied to a mass-spring-damper system with a one-sided spring.
Paper VI112-03.16
PDF · Video · Overcoming Output Constraints in Iterative Learning Control Systems by Reference Adaptation (I)
Meindl, Michael	Hochschule Karlsruhe - Technik Und Wirtschaft
Molinari, Fabio	Technische Universitaet Berlin
Raisch, Joerg	Technische Universitaet Berlin
Seel, Thomas	Technische Universitaet Berlin
Keywords: Iterative and Repetitive learning control, Learning for control Abstract: Iterative Learning Control (ILC) schemes can guarantee properties such as asymptotic stability and monotonic error convergence, but do not, in general, ensure adherence to output constraints. The topic of this paper is the design of a reference-adapting ILC (RAILC) scheme, extending an existing ILC system and capable of complying with output constraints. The underlying idea is to scale the reference at every trial by using a conservative estimate of the output’s progression. Properties as the monotonic convergence above a threshold and the respect of output constraints are formally proven. Numerical simulations and experimental results reinforce our theoretical results.
Paper VI112-03.17
PDF · Video · Gaussian Process Repetitive Control for Suppressing Spatial Disturbances (I)
Mooren, Noud	Eindhoven University of Technology
Witvoet, Gert	TNO
Oomen, Tom	Eindhoven University of Technology
Keywords: Iterative and Repetitive learning control, Learning for control, Machine learning Abstract: Motion systems are often subject to disturbances such as cogging, commutation errors, and imbalances, that vary with velocity and appear periodic in time for constant operating velocities. The aim of this paper is to develop a repetitive controller (RC) for disturbances that are not periodic in the time domain, yet occur due to an identical position-domain disturbance. A new spatial RC framework is developed, allowing to attenuate disturbances that are periodic in the position domain but manifest a-periodic in the time domain. A Gaussian process (GP) based memory is employed with a suitable periodic kernel that can effectively deal with the intermittent observations inherent to the position domain. A mechatronic example confirms the potential of the method.
Paper VI112-03.18
PDF · Video · Switch-Based Iterative Learning Control for Tracking Iteration Varying References (I)
Balta, Efe	University of Michigan
Tilbury, Dawn M.	Univ of Michigan
Barton, Kira	University of Michigan
Keywords: Iterative and Repetitive learning control, Adaptive gain scheduling autotuning control and switching control, Learning for control Abstract: Iterative Learning Control (ILC) is a control strategy that improves the performance of repetitive systems by enabling near-perfect reference tracking. Iteration-invariant reference signals have been a fundamental assumption for most existing ILC developments. This assumption poses limitations on many applications of ILC where the iteration-varying reference is known to the controller a priori. This work presents a switch-based ILC scheme that combines the performance of standard ILC with guarantees on the error for switched reference signals. The proposed controller is formulated and its performance is analyzed. A simulation case study is provided at the end to illustrate the performance.
Paper VI112-03.19
PDF · Video · Efficient Implementation of a Binary Iterative Learning Control
Arnold, Florian	Technische Universität Berlin
Topalovic, Daniel	Technische Universität Berlin
King, Rudibert	Technische Universitaet Berlin
Keywords: Iterative and Repetitive learning control Abstract: Iterative learning control (ILC) is an adequate control approach to handle various types of cyclic control tasks. However, when in each iteration the calculation of the control trajectory requires the solution of a high dimensional constrained quadratic program, the algorithm is bound to be infeasible for real-time applications with very small cycle lengths in the order of milliseconds due to the prohibitively large computational cost. In this contribution, an approach is presented to reduce the computational burden to solve an optimization-based iterative learning control that is restricted to a binary domain by orders of magnitude. The method is suitable for control trajectories that contain only few 1’s, but a large number of 0’s in each iteration for a specific class of problems, e.g., for cyclic firing synchronization of combustion tubes such is required. The presented setup is tested experimentally at an acoustic mock-up of an annular pulse detonation combustor to determine an appropriate fire synchronization. More specifically, it is used to adjust the firing pattern of multiple simulated combustion tubes in order to reduce pressure fluctuations measured downstream in an annular plenum, which is a prerequisite to apply such a new thermodynamically efficient combustion process in a real gas turbine.
Paper VI112-03.20
PDF · Video · Disturbance Observer Based Repetitive Control System with Non-Minimal State Space Realization and Anti-Windup Mechanism
Wang, Liuping	RMIT University
Freeman, Christopher Thomas	University of Southampton
Rogers, Eric	Univ of Southampton
Young, Peter	Lancaster University
Keywords: Iterative and Repetitive learning control Abstract: This paper develops a disturbance observer-based repetitive control system using a non-minimal state-space realization in which all state variables are chosen to correspond to the system's input and output variables and their past values. To enable the repetitive control system to follow a periodic reference signal or reject a disturbance signal of the same nature, a disturbance observer is used to estimate an input disturbance that contains the same frequency characteristics. This new approach differs from previously published design in repetitive control because it separates the design procedure into two simple tasks: first, stabilization by the design of a non-minimal state feedback control; and second, to independently incorporate the periodic modes via the estimation of the disturbance. Moreover, because this design ensures the stability of the disturbance observer, its implementation contains an anti-windup mechanism when the control signal reaches its maximum or minimum value. Without the complication of an observer for the state variables, the detection of a disturbance occurs earlier and the repetitive controller acts much faster than in the case of minimal state controller incorporating an observer. This leads to considerable performance improvement, with excellent disturbance rejection achieved with smaller control signal variations.
Paper VI112-03.21
PDF · Video · Application of the Dynamic Iterative Learning Control to the Heteropolar Active Magnetic Bearing
Hladowski, Lukasz	University of Zielona Gora
Mystkowski, Arkadiusz	Bialystok University of Technology
Galkowski, Krzysztof	Univ. of Zielona Gora
Rogers, Eric	Univ of Southampton
Chu, Bing	University of Southampton
Keywords: Regulation (linear case), Linear systems, Time-invariant systems Abstract: Heteroplanar active magnetic bearings have numerous applications, where one example is a high-temperature gas-cooled reactors. Rotor imbalance, however, may cause problems for critical parts of the system in the form of repetitive periodic vibrations. This is known problem and periodic component extraction is widely used in active magnetic bearing unbalance control laws. More recently, iterative learning control has been considered as an alternative and this paper gives new results on this approach. In particular, a new control law in the 2D systems setting is developed and the results of a simulation based study using the model of a test rig are given, where such a study is an essential step prior to experimental validation.

VI112-04
Adaptive Observers and Control	Regular Session
Chair: Chen, Songlin	Harbin Institute of Technology
Co-Chair: Bullinger, Eric	Otto-von-Guericke-Universität Magdeburg
Paper VI112-04.1
PDF · Video · Optimal Model-Based Sensor Placement & Adaptive Monitoring of an Oil Spill
Hodgson, Zak	University of Sheffield
Esnaola, Iñaki	University of Sheffield
Jones, Bryn L.	University of Sheffield
Keywords: Adaptive control of multi-agent systems, Multi-agent systems, Control under computation constraints Abstract: This paper presents a model based adaptive monitoring method for the estimation of flow tracers, with application to mapping, prediction and observation of oil spills in the immediate aftermath of an incident. Autonomous agents are guided to optimal sensing locations via the solution of a PDE constrained optimisation problem, obtained using the adjoint method. The proposed method employs a dynamic model of the combined ocean and oil dynamics, with states that are updated in real-time using a Kalman filter that fuses agent-based measurements with a reduced-order model of the ocean circulation dynamics. In turn, the updated predictions from the fluid model are used to identify and update the reduced order model, in a process of continuous feedback. The proposed method exhibits a 30% oil presence mapping and prediction improvement compared to standard industrial oil observation sensor guidance and model use.
Paper VI112-04.2
PDF · Video · Transforming Time-Delay System Observers to Adaptive Observers
Ahmed-Ali, Tarek	Université De Caen Normandie
Zhang, Qinghua	INRIA
Giri, Fouad	University of Caen Normandie
Liu, Xingwen	Southwest University for Nationalities of China
Keywords: Adaptive observer design Abstract: For joint estimation of states and parameters in time varying time-delay systems (TDS) involving both distributed and lumped time-delays, a general approach is proposed in this paper to transforming existing (non adaptive) observers to adaptive observers. In addition to the convergence conditions of the considered existing observers, a persistent excitation condition is introduced in order to ensure the convergence of parameter estimation. In contrast to implicitly formulated convergence conditions, which are usually assumed jointly for both state and parameter estimations in most TDS adaptive observers, the persistent excitation condition in the proposed approach is explicitly formulated and decoupled from the conditions initially assumed for state estimation.
Paper VI112-04.3
PDF · Video · Fixed-Time Estimators of Derivatives of Unknown Maps (I)
Wang, Libin	Harbin Institute of Technology
Chen, Songlin	Harbin Institute of Technology
Krstic, Miroslav	Univ. of California at San Diego
Zhao, Hui	Harbin Institute of Technology
Keywords: Adaptive observer design Abstract: A systematic and generalized asymptotic derivative estimator design method is first presented for unknown maps by adding a sinusoidal excitation signal to the argument of the map. Then, based on the proposed asymptotic derivative estimator approach and based on the existing design methods for both finite-time and fixed-time state observers, finite-time and fixed-time derivative estimators are designed. The sufficient conditions for finite-time and fixed-time input-to-state stable of the finite-time and fixed-time derivative estimators are given respectively when a bounded disturbance input exists.
Paper VI112-04.4
PDF · Video · A Robust Sensorless Controller-Observer Strategy for PMSMs with Unknown Resistance and Mechanical Model
Bosso, Alessandro	Alma Mater Studiorum - University of Bologna
Tilli, Andrea	University of Bologna
Conficoni, Christian	Alma Mater Studiorum Bologna
Keywords: Adaptive observer design, Closed loop identification, Continuous time system estimation Abstract: In this work, we present a mixed sensorless strategy for Permanent Magnet Synchronous Machines, combining a torque/current controller and an observer for position, speed, flux, and stator resistance. The proposed co-design is motivated by the need for an appropriate signal injection technique to guarantee full state observability. Neither the typical constant or slowly-varying speed assumptions, nor a priori mechanical model information are required. Instead, the rotor speed is modeled as an unknown input disturbance with constant (unknown) sign and uniformly non-zero magnitude. With the proposed architecture, we show that the torque tracking and signal injection tasks can be achieved and asymptotically decoupled. Because of these features, we refer to this strategy as a sensorless controller-observer with no mechanical model. Employing a gradient descent resistance/back-EMF estimation, combined with the unit circle formalism to describe the rotor position, we prove regional practical asymptotic stability of the overall scheme. In particular, the domain of attraction can be arbitrarily large, without including a lower-dimensional manifold. The effectiveness of this design is further validated with numerical simulations, related to a challenging application of UAV propellers control.
Paper VI112-04.5
PDF · Video · Mixed Fractional Order Adaptive Control: Theory and Applications
Duarte-Mermoud, Manuel	Univ of Chile
Barzaga Martell, Lisbel	Univesity of Chile
Ceballos Benavides, Gustavo	Universidad San Sebastián
Keywords: Model reference adaptive control Abstract: In this paper we study the adaptive control problem of integer order plants using fractional order adaptive laws in the controller. The study is based on a general methodology recently developed to establish boundeness and asymptotic behavior of solutions to multiorder systems (set of differential equations with different derivation orders) having multiple time-varying delays. Also it is based on recent results for fractional order systems under the perspective of the so called "Error Models". The method relies on vector Lyapunov-like functions and on comparison arguments. Boundedness and convergence of the solutions are theoretically analyzed and applications to fractional adaptive schemes are presented towards the end of the paper, including numerical simulations to verify the analytical results.

VI112-05
Consensus and Reinforcement Learning Control	Regular Session
Chair: Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Co-Chair: Stankovic, Milos S.	University of Belgrade
Paper VI112-05.1
PDF · Video · A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning
Suttle, Wesley	Stony Brook University
Yang, Zhuoran	Princeton
Zhang, Kaiqing	University of Illinois at Urbana-Champaign (UIUC)
Wang, Zhaoran	Northwestern University
Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Liu, Ji	Stony Brook University
Keywords: Consensus and Reinforcement learning control, Adaptive control of multi-agent systems Abstract: This paper extends off-policy reinforcement learning to the multi-agent case in which a set of networked agents communicating with their neighbors according to a time-varying graph collaboratively evaluates and improves a target policy while following a distinct behavior policy. To this end, the paper develops a multi-agent version of emphatic temporal difference learning for off-policy policy evaluation, and proves convergence under linear function approximation. The paper then leverages this result, in conjunction with a novel multi-agent off-policy policy gradient theorem and recent work in both multi-agent on-policy and single-agent off-policy actor-critic methods, to develop and give convergence guarantees for a new multi-agent off-policy actor-critic algorithm. An empirical validation of these theoretical results is given.
Paper VI112-05.2
PDF · Video · Deep Decentralized Reinforcement Learning for Cooperative Control
Koepf, Florian	Karlsruhe Institute of Technology (KIT)
Tesfazgi, Samuel	Technical University Munich
Flad, Michael	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Consensus and Reinforcement learning control, Adaptive control of multi-agent systems, Learning for control Abstract: In order to collaborate efficiently with unknown partners in cooperative control settings, adaptation of the partners based on online experience is required. The rather general and widely applicable control setting where each cooperation partner might strive for individual goals while the control laws and objectives of the partners are unknown entails various challenges such as the non-stationarity of the environment, the multi-agent credit assignment problem, the alter-exploration problem and the coordination problem. We propose new, modular deep decentralized Multi-Agent Reinforcement Learning mechanisms to account for these challenges. Therefore, our method uses a time-dependent prioritization of samples, incorporates a model of the system dynamics and utilizes variable, accountability-driven learning rates and simulated, artificial experiences in order to guide the learning process. The effectiveness of our method is demonstrated by means of a simulated nonlinear cooperative control task.
Paper VI112-05.3
PDF · Video · Distributed Gradient Temporal Difference Off-Policy Learning with Eligibility Traces: Weak Convergence
Stankovic, Milos S.	University of Belgrade
Beko, Marko	COPELABS, Universidade Lusofona De Humanidades E Tecnologias, Li
Stankovic, Srdjan	University of Belgrade
Keywords: Consensus and Reinforcement learning control, Distributed control and estimation, Multi-agent systems Abstract: In this paper we propose two novel distributed algorithms for multi-agent off-policy learning of linear approximation of the value function in Markov decision processes. The algorithms differ in the way of how distributed consensus iterations are incorporated in a basic, recently proposed, single agent scheme. The proposed completely decentralized off-policy learning schemes subsume local eligibility traces, and allow applications in which all the agents may have different behavior policies while evaluating a single target policy. Under nonrestrictive assumptions on the time-varying network topology and the individual state-visiting distributions of the agents, we prove that the parameter estimates of the algorithms weakly converge to a consensus. The variance reduction properties of the proposed algorithms are demonstrated. We also formulate specific guidelines on how to design the network weights and topology. The results are illustrated using simulations.
Paper VI112-05.4
PDF · Video · Actuation Strategy of a Virtual Skydiver Derived by Reinforcement Learning
Clarke, Anna	Technion Israel Institute of Technology
Gutman, Per-Olof	Technion - Israel Institute of Technology
Keywords: Consensus and Reinforcement learning control, Learning for control, Experiment design Abstract: An innovative approach of training motor skills involved in human body flight is proposed. Body flight is the art of maneuvering during the free fall stage of skydiving. The key idea is gradually constructing the movement patterns which are the combinations of body degrees-of-freedom that are activated synchronously and proportionally as a single unit, and turning this process into a coaching strategy. The proposed method is iterative: at each skill level an optimal movement pattern is constructed from the basic elements of the current movement repertoire. The free-fall maneuvers of each learning stage can be executed using any one of the basic elements. The construction has two stages: 1. tracking the desired maneuver while the body is actuated by each one of the basic patterns; 2. finding an optimal combination of these patterns to form a new way of body actuation. This hierarchical design resolves stage 2 by Reinforcement Learning with pure exploration and a minimal number of episodes. The method was tested in a Skydiver Simulator and resulted in deriving a movement pattern that showed a superior performance of the studied maneuver. The states and the reward of the Reinforcement Learning algorithm were converted into motor learning aids.
Paper VI112-05.5
PDF · Video · Model-Free Control Design for Loop Heat Pipes Using Deep Deterministic Policy Gradient
Gellrich, Thomas	FZI Research Center for Information Technology
Min, Yi	FZI Research Center for Information Technology
Schwab, Stefan	FZI - Research Center for Information Technology
Hohmann, Soeren	KIT
Keywords: Consensus and Reinforcement learning control, Learning for control, Extremum seeking and model free adaptive control Abstract: In this paper, a model-free adaptive control design for loop heat pipes (LHPs) based on the reinforcement learning (RL) method of deep deterministic policy gradient (DDPG) is presented. An LHP as a heat transport system combines complex, thermodynamic processes, which are not yet fully described in a dynamic control model over the entire LHP operating range for model-based control design. However, RL methods provide the controller with the ability to improve its control performance without a model by analyzing and rewarding the performance online. The aim of an LHP controller is to keep the LHP operating temperature as close as possible to the fixed setpoint temperature by additional heating, while the amount of heat to be transported and the temperature of the heat sink change over time. A validated numerical simulation of the LHP provides a safe, dynamic environment for the training of the learning controller. In comparison with the commonly used PI controller with a single temperature feedback, the control performance of the learning controller observing the same temperature achieves similar control results. Furthermore, multiple observations are easily incorporated into a model-free learning controller, whereby the additional feedback of further temperature measurements ensures an improved performance over the entire operating range.
Paper VI112-05.6
PDF · Video · Reinforcement Learning and Trajectory Planning Based on Model Approximation with Neural Networks Applied to Transition Problems
Pritzkoleit, Max	TU Dresden
Knoll, Carsten	Technische Universität Dresden
Röbenack, Klaus	TU Dresden
Keywords: Consensus and Reinforcement learning control, Learning for control, Nonlinear system identification Abstract: In this paper we use a multilayer neural network to approximate the dynamics of nonlinear (mechanical) control systems. Furthermore, these neural network models are combined with offline trajectory planning, to form a model-based reinforcement learning (RL) algorithm, suitable for transition problems of nonlinear dynamical systems. We evaluate the algorithm on the swing-up of the cart-pole benchmark system and observe a significant performance gain in terms of data efficiency compared to a state-of-the-art model-free RL method (Deep Deterministic Policy Gradient (DDPG)). Additionally, we present first experimental results on a cart-triple-pole system test bench. For a simple transition problem, the proposed algorithm shows a good controller performance.
Paper VI112-05.7
PDF · Video · Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction
Okawa, Yoshihiro	Fujitsu Laboratories Ltd
Sasaki, Tomotake	Fujitsu Laboratories Ltd
Iwane, Hidenao	Reading Skill Test, Inc
Keywords: Consensus and Reinforcement learning control, Nonlinear adaptive control, Learning for control Abstract: In reinforcement learning (RL) algorithms, exploratory control inputs are used during learning to acquire knowledge for decision making and control, while the true dynamics of a controlled object is unknown. However, this exploring property sometimes causes undesired situations by violating constraints regarding the state of the controlled object. In this paper, we propose an automatic exploration process adjustment method for safe RL in continuous state and action spaces utilizing a linear nominal model of the controlled object. Specifically, our proposed method automatically selects whether the exploratory input is used or not at each time depending on the state and its predicted value as well as adjusts the variance-covariance matrix of a normal distribution used in the Gaussian policy for exploration. We also show that our exploration process adjustment method theoretically guarantees the satisfaction of the constraints with the pre-specified probability, that is, the satisfaction of a joint chance constraint at every time. Finally, we illustrate the validity and the effectiveness of our method through numerical simulation.
Paper VI112-05.8
PDF · Video · Online Output-Feedback Optimal Control of Linear Systems Based on Data-Driven Adaptive Learning
Zhao, Jun	Kunming University of Science and Technology
Na, Jing	University of Bristol
Gao, Guanbin	Kunming University of Science & Technology
Han, Shichang	Kunming University of Science and Technology
Chen, Qiang	Zhejiang University of Technology
Wang, Shubo	Qingdao University
Keywords: Consensus and Reinforcement learning control, Nonlinear adaptive control, Neural and fuzzy adaptive control Abstract: This paper proposes a new approach to solve the output-feedback optimal control for linear systems. A modified algebraic Riccati equation (MARE) is constructed by investigating the corresponding relationship with the state-feedback optimal control. To solve the derived MARE, an online data-driven adaptive learning is designed, where the vectorization operation and Kronecker’s product are applied to reformulate the output Lyapunov function. Consequently, only the measurable system input and output are used to derive the solution of the MARE. In this case, the output-feedback optimal control solution can be obtained in an online manner without resorting to the unknown system states. Simulation results are provided to demonstrate the efficacy of the suggested method.
Paper VI112-05.9
PDF · Video · Learning Optimal Switching Feedback Controllers from Data
Ferrarotti, Laura	IMT School for Advanced Studies, Lucca
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Consensus and Reinforcement learning control, Optimal control of hybrid systems, Machine learning Abstract: In this paper we present a data-driven approach for synthesizing optimal switching controllers directly from experimental data, without the need of a global model of the dynamics of the process. The set of controllers and the switching law are learned by using a coordinate descent strategy: for a fixed switching law, the controllers are sequentially optimized by using stochastic gradient descent iterations, while for fixed controllers the switching law is iteratively refined by unsupervised learning. We report examples showing that the approach performs well when applied to control processes characterized by hybrid or nonlinear dynamics, outperforming control laws that are single-mode (no switching) or multi-mode but with the switching law defined a priori.

VI112-06
Extremum Seeking and Model-Free Adaptive Control	Regular Session
Chair: Ebenbauer, Christian	University of Stuttgart
Co-Chair: Marconi, Lorenzo	Univ. Di Bologna
Paper VI112-06.1
PDF · Video · Discrete-Step, Quasi-Newton Extremum Seeking Control for Multivariate Real-Time Optimization (I)
Lange, Andreas	Technische Universitaet Berlin
King, Rudibert	Technische Universitaet Berlin
Keywords: Extremum seeking and model free adaptive control Abstract: Extremum seeking control is a well known approach for multivariate real-time optimization of dynamic systems. In classical extremum seeking control schemes, the estimated gradient of the process's steady-state map is continuously integrated towards a local optimum. Gradient estimation can be done by a combination of low- and high-/bandpass filters. Advanced approaches have been developed that use extended Kalman Filters, which allow for a joined estimation of the multidimensional gradient. Within this work, a discrete-step real-time optimization scheme is investigated that is derived from the prevalent quasi-Newton method of numerical optimization. Gradient estimation is implemented by the identification of a local linear dynamic model. A significantly faster convergence to the optimum compared to classical extremum seeking is shown for an academic Hammerstein example and for the optimization of the power consumption within a multistage compressor simulation.
Paper VI112-06.2
PDF · Video · Real-Time Efficient Operation of Decatizing Processes Via a Geometric-Based Extremum Seeking Control
Ferro, Fabiana Federica	University of Padova
Lionello, Michele	University of Padova
Rampazzo, Mirco	Universita Degli Studi Di Padova
Beghi, Alessandro	Università Di Padova
Guay, Martin	Queen's Univ
Keywords: Extremum seeking and model free adaptive control Abstract: Finishing is one of the fundamental steps of textile production and still, nowadays, it largely depends on empirical knowledge. Aim of finishing processes is to impart the required functional properties to the fabric and, in particular, decatizing is the process that lends the fabrics dimensional stability, enhances the luster, and improves the so-called ‘fabric hand’, corresponding to the sense of touching a textile. In order to properly treat the textile while minimizing the process energy consumption, suitable decatizing operating conditions, such as air temperature and humidity in the steaming section, have to be set. In this paper, because of the limited knowledge of certain process parameters and the difficulty of developing, implementing, and using effective a-priori process models, the problem of determining the set-points for the main controlled process variables is formulated as a constrained optimization problem and this is faced by means of a model-free approach. More precisely, we consider a constrained Extremum Seeking Control scheme, using a geometric approach. In this preliminary study, first, we develop a Matlab-based simulation environment for the textile decatizing process and then we exploit it to design and test the ESC scheme. The in silico results confirm the effectiveness of the proposed approach.
Paper VI112-06.3
PDF · Video · Extremum Seeking Control Based on the Super-Twisting Algorithm
Torres, Ixbalank	Universidad De Guanajuato
Lopez-Caamal, Fernando	Universidad De Guanajuato
Hernández-Escoto, Héctor	University of Guanajuato
Vargas, Alejandro	Instituto De Ingenieria UNAM
Keywords: Real-time optimal control, Robust control applications, Sliding mode control Abstract: This article addresses the problem of extremum seeking of a continuous-time dynamical system with a single input and a single output. First, a super-twisting-based gradient-based optimization algorithm is proposed to compute the input that leads to the extremum value of an unknown, convex objective function. Since the algorithm requires the input-output gradient of the system's response, a super-twisting based differentiator is proposed to compute the gradient using the measured output and the controlled input. Feasibility of the extremum seeking controller is demonstrated via closed-loop simulations over a microalgae production photobioreactor.
Paper VI112-06.4
PDF · Video · An Extremum Seeking Approach to Search and Rescue Operations in Avalanches Using ARVA
Azzollini, Ilario Antonio	University of Bologna
Mimmo, Nicola	University of Bologna
Marconi, Lorenzo	Univ. Di Bologna
Keywords: Extremum seeking and model free adaptive control Abstract: Search and rescue operations in avalanches can greatly benefit from the support of unmanned aerial vehicles, which could safely and autonomously fly above the snow surface to estimate the position of the victim. This work relies upon the Appareil de Recherche de Victimes (ARVA), which consists of a transmitter and a receiver. The transmitter is worn by the victim and produces an electromagnetic field that can be sensed by the receiver, integrated on the drone. A receiver able to sense the complete 3D electromagnetic field has been developed, whose model and properties are presented in this work. The main contribution of this work is the development of a control algorithm able to drive the ARVA-equipped drone as close as possible to the victim location.
Paper VI112-06.5
PDF · Video · Dither Signals Optimization in Constrained Multi-Agent Extremum Seeking Control
Silva, Thiago L.	Norwegian University of Science and Technology
Pavlov, Alexey	Norwegian University of Science and Technology
Keywords: Extremum seeking and model free adaptive control, Multi-agent systems Abstract: In this paper we consider the problem of optimization of a multi-agent system with constraints through perturbations-based extremum seeking control. We demonstrate that for such systems, effects of dither signals applied to individual agents can sum up to significant perturbations in the outputs at the overall system level despite the fact that individual dither signals can be small. These perturbations are especially detrimental in constrained outputs. To resolve this challenge, we propose a method of dither signals optimization: while maintaining persistent perturbations of individual agents, dither signals are coordinated between the agents to minimize their summed effect in constrained outputs. This problem is formulated as a computationally feasible mathematical programming problem that can be solved numerically at each time step. Combined with a constrained steady-state optimizer and a least squares-based gradient estimator, this method provides better performance than a similar perturbation-based extremum seeking scheme without dither optimization. This is demonstrated with an example on oil production optimization from a system of multiple gas-lifted wells with a total water processing constraint.
Paper VI112-06.6
PDF · Video · Quantized Measurements in Q-Learning Based Model-Free Optimal Control
Tiistola, Sini Päivikki	Tampere University
Ritala, Risto	Tampere University of Technology, Dept of Automation Science And
Vilkko, Matti Kalervo	Tampere University
Keywords: Extremum seeking and model free adaptive control, Quantized systems, Machine learning Abstract: Quantization noise is present in many real-time applications due to the resolution of analog-to-digital conversions. This can lead to error in policies that are learned by model-free Q-learning. A method for quantization error reduction for Q-learning algorithms is developed using the sample time and an exploration noise that is added to the control input. The method is illustrated with discrete-time policy and value iteration algorithms using both a simulated environment and a real-time physical system.
Paper VI112-06.7
PDF · Video · Discrete-Time Repetitive Control for Multi-Harmonic Reference Trajectories with Arbitrary Frequency
Marko, Lukas	Vienna University of Technology
Saxinger, Martin	Vienna University of Technology
Bittner, Matthias	Vienna University of Technology
Steinboeck, Andreas	Vienna University of Technology
Kugi, Andreas	Vienna University of Technology
Keywords: Iterative and Repetitive learning control, Extremum seeking and model free adaptive control Abstract: In this work, a repetitive control approach for the tracking of harmonic reference trajectories in the presence of actuator backlash and sticking friction is presented. A spatial Fourier series formulation is utilized to obtain a learning law which is independent of the desired reference frequency. Subsequently, discrete-time averaging is employed, which results in a simple convergence criterion for the closed-loop system. Furthermore, all updates are calculated in a time-recursive manner, which avoids the necessity of large data windows and allows for a discrete-time implementation with a uniform sampling time. Finally, experimental results of a fully assembled spindle drive are presented. This demonstrates the effectiveness of the proposed control scheme as well as its suitability as an add-on strategy in existing positioning devices.

VI112-07
Nonlinear Adaptive Control	Regular Session
Chair: Bobtsov, Alexey	ITMO University
Co-Chair: Limon, Daniel	Universidad De Sevilla
Paper VI112-07.1
PDF · Video · Adaptive Full State Observer for Nonsalient PMSM with Noised Measurements of the Current and Voltage
Pyrkin, Anton	ITMO University
Vedyakov, Alexey	ITMO University
Bobtsov, Alexey	ITMO University
Bazylev, Dmitry	ITMO University
Sinetova, Madina	ITMO University
Ovcharov, Alexey	ITMO University
Antipov, Vladislav	ITMO University
Keywords: Adaptive observer design, Nonlinear system identification, Identification for control Abstract: An algorithm of adaptive estimation of the magnetic flux for the non-salient permanent magnet synchronous motor (PMSM) for the case when measurable electrical signals are corrupted by a constant offset is presented. A new nonlinear parameterization of the electric drive model based on dynamical regressor extension and mixing (DREM) procedure is proposed. Due to this parameterization the problem of flux estimation is translated to the auxiliary task of identification of unknown constant parameters related to measurement errors. It is proved that when both current and voltage measurements are biased the proposed algorithm ensures convergence of the flux observation error to a bounded set. At the same time the position error converges to zero. The observer provides global exponential convergence if the corresponding regression function satisfies the persistent excitation condition. If the regression function is not square integrable the global asymptotic convergence is ensured. In comparison with known analogues this paper gives a constructive way of the flux reconstruction for a nonsalient PMSM with guaranteed performance (low oscillation, convergence rate regulation) and, from other hand, a straightforwardly easy implementation of the proposed observer to embedded systems.
Paper VI112-07.2
PDF · Video · Iteration-Dependent High-Order Internal Model Based Iterative Learning Control for Discrete-Time Nonlinear Systems with Time-Iteration-Varying Parameter
Yu, Miao	Zhejiang University
Chai, Sheng	Zhejiang University
Keywords: Iterative and Repetitive learning control, Nonlinear adaptive control Abstract: In this paper, an adaptive iterative learning control (AILC) scheme is designed for discrete-time nonlinear systems with random initial condition and time-iteration-varying parameter. The time-iteration-varying parameter is generated by a general iteration-varying high-order internal model (HOIM) with iteration-varying order and coefficients, and the parameter updating law is designed based on least square method. Compared with the existing works based on iteration-invariant HOIM with fixed order and coefficients, our work significantly extends the application scope of HOIM-based ILC. Using the designed HOIM based iterative learning controller, the learning convergence in the iteration domain is guaranteed through rigorous theoretical analysis under Lyapunov theory. Moreover, an illustrative example is given to demonstrate the effectiveness of the proposed method.
Paper VI112-07.3
PDF · Video · Training Neural Networks for Plant Estimation, Control and Disturbance Rejection
Kotzé, Henry	Stellenbosch University
Kamper, Herman	Stellenbosch University
Jordaan, Hendrik Willem	Stellenbosch University
Keywords: Neural and fuzzy adaptive control, Adaptive observer design, Nonlinear adaptive control Abstract: Neural networks are used in control systems to combat difficulties which nonlinear and linear controllers struggle to compensate for, such as environmental and model uncertainties. Neural networks have shown promising results as controllers or estimators of these uncertainties. However, few studies expand on important aspects on using and training a neural network, such as the dataset, input and output pairs, and the training of the different controllers and estimators. In this paper, a dataset used for neural controllers and estimators are presented which contains more complexity than that of the expected test environment. The training of different neural controllers and estimators are presented: estimators for the forward dynamics and disturbances, a feedback controller, a feedback linearisation controller and a disturbance rejection controller. For each neural component, the input and output pairs are presented with results of them performing in a test environment. From these results it was evident that through the use of the proposed dataset and training method the neural networks succeeded in fulfilling its role in the control architectures.
Paper VI112-07.4
PDF · Video · ASPR Based Output Regulation with Adaptive PFC and Feedforward Input Via Kernel Method
Mizumoto, Ikuro	Kumamoto Univ
Akaike, Kota	Kumamoto University
Keywords: Neural and fuzzy adaptive control, Model reference adaptive control, Nonlinear adaptive control Abstract: An adaptive control system design problem based on the almost strictly positive real-ness (ASPR-ness) is dealt with. For ASPR systems, one can easily design a stable adaptive output feedback control system, however, in the case where the system is not ASPR, in order to guarantee the stability of the adaptive system, an parallel feedforward compensator (PFC), which makes the resulting augmented system ASPR, is introduced. In the proposed method, an adaptive PFC design scheme for making the resulting augmented system ASPR and an adaptive feedforward input design scheme for attaining the output tracking are proposed by applying the kernel method for uncertain non-ASPR linear systems. The effectiveness of the proposed method is confirmed through numerical simulations for a simple uncertain system.
Paper VI112-07.5
PDF · Video · Tube-Based Internal Model Control of Minimum-Phase Input-Affine MIMO Systems under Input Constraints
Ben Jemaa, Karim	Ulm University, Robert Bosch GmbH
Reimann, Sven	Robert Bosch GmbH
Kotman, Philipp	Robert Bosch GmbH
Graichen, Knut	Friedrich-Alexander-University Erlangen-Nuremberg
Keywords: Nonlinear adaptive control Abstract: In this paper an optimal control approach based on a combination of inversion-based control and internal model control (IMC) is designed to keep the controlled states of a minimum-phase input-affne MIMO system within predefined tubes while respecting input constraints. This contribution extends recently presented results for the SISO case to nonlinear input-affne MIMO systems. The developed approach uses ideas developed in the design of inversion-based IMC controllers for setpoint tracking and extends them to 'tube tracking'. It shows the interesting result that for input-affine systems the control task of maintaining each controlled state within a tube while minimizing energy consumption and respecting input constraints can be expressed as a convex quadratic optimization problem. This concept allows to handle dynamic systems where the number of control inputs differs from the number of controlled outputs are not equal. The control approach is illustrated by three simulation examples.
Paper VI112-07.6
PDF · Video · Adaptive Stabilization by Delay with Biased Measurements
Efimov, Denis	Inria
Aranovskiy, Stanislav	Centrale Supelec - IETR
Fridman, Emilia	Tel-Aviv Univ
Sokolov, Dmitry	Université De Lorraine
Wang, Jian	Hangzhou Dianzi University
Bobtsov, Alexey	ITMO University
Keywords: Nonlinear adaptive control, Continuous time system estimation, Adaptive observer design Abstract: The problem of output robust adaptive stabilization for a class of Lipschitz nonlinear systems is studied under assumption that the measurements are available with a constant bias. The state reconstruction is avoided by using delayed values of the output in the feedback and adaptation laws. The control and adaptation gains can be selected as a solution of the proposed linear matrix inequalities (LMIs). The efficiency of the presented approach is demonstrated on a nonlinear pendulum through simulations
Paper VI112-07.7
PDF · Video · Real-Time Optimization of Periodic Systems: A Modifier-Adaptation Approach
Mirasierra, Victor	Universidad De Sevilla
Vergara-Dietrich, Jose Dolores	Universidade Tecnológica Federal Do Paraná
Limon, Daniel	Universidad De Sevilla
Keywords: Nonlinear adaptive control, Iterative and Repetitive learning control Abstract: Modifier-Adaptation methodologies have been widely used to overcome plant-model mismatch and control a system to its steady-state optimal setpoint. They use gradient information of the real plant to design modifiers that correct the model, so that the first order necessary conditions for optimality of the model-based problem converge to those of the optimal one. In this paper, we get rid of the hypothesis that the plant optimum needs to be an equilibrium point. Instead, we only require it to be a periodic trajectory. We show the behaviour of the proposed approach by means of a motivating example that highlights the necessity of this formulation in cases where the system changes periodically through time.
Paper VI112-07.8
PDF · Video · Online Adaptive Critic Robust Control of Discrete-Time Nonlinear Systems with Unknown Dynamics
Fu, Hao	China University of Geosciences
Chen, Xin	China University of Geosciences
Wu, Min	China University of Geosciences
Keywords: Nonlinear adaptive control, Model reference adaptive control, Learning for control Abstract: This paper concerns the optimal model reference adaptive control problem for unknown discrete-time nonlinear systems. For such problem, it is challenging to improve online learning efficiency and guaranteeing robustness to the uncertainty. To this end, we develop an online adaptive critic robust control method. In this method, a critic network and a new supervised action network are constructed to not only improve the real-time learning efficiency, but also obtain the optimal control performance. By combining the designed compensation control term, robustness is further guaranteed by compensating the uncertainty. The comparative simulation study is conducted to show the superiority of our developed method.
Paper VI112-07.9
PDF · Video · Fixed-Time Control for a Class of Unknown Nonlinear Affine Systems and Its Applications to a Lithography Machine
Luo, Kehan	University of Electronic Science and Technology of China
Zou, Jianxiao	School of Automation Engineering, University of Electronic Scien
Kong, Linghuan	University of Electronic Science and Technology of China
He, Wei	University of Science and Technology Beijing
Keywords: Nonlinear adaptive control, Neural and fuzzy adaptive control Abstract: The fixed-time control problems of a class of unknown nonlinear affine systems subject to external disturbances, unknown input dead zone and output constraints are considered in this paper. The novel fixed-time adaptive neural networks state feedback controller is designed in this paper. In the control design, the log-type barrier Lyapunov function (BLF) is chosen to handle the system output constraints. Then, neural networks(NNs) are applied to compensate for the adverse impact of unknown input dead zone and approximate unknown system functions. The novel virtual controllers and novel online updating laws of neural network weights are proposed to ensure the fixed-time stability of closed-loop systems. All the signals in closed-loop system are proved to be uniformly bounded with Lyapunov stability theory. Finally, a lithography machine experiment is used to illustrate the effectiveness of the proposed method.
Paper VI112-07.10
PDF · Video · On the Decay Rate for Degenerate Gradient Flows Subject to Persistent Excitation
Prandi, Dario	Université Paris-Saclay, CentraleSupélec, CNRS
Chitour, Yacine	Universit'e Paris-Sud, CNRS, Centralesupelec
Mason, Paolo	L2S CentraleSupélec, CNRS
Keywords: Nonlinear adaptive control, Nonlinear system identification, Input and excitation design Abstract: In this paper, we estimate the worst rate of exponential decay of a class of degenerate gradient flows issued from adaptive control theory. Under a persistent excitation assumption, we provide upper bounds for this rate of decay consistent with previously known lower bounds and analogous stability results for more general classes of persistently excited signals. The strategy of proof consists in relating the worst decay rate to optimal control questions and studying in details their solutions.
Paper VI112-07.11
PDF · Video · On the Line-Search Gradient Methods for Stochastic Optimization
Dvinskikh, Darina	WIAS
Ogaltsov, Aleksandr	Higher School of Economics, Moscow / Antiplagiat Company
Gasnikov, Alexander	Moscow Institute of Physics and Technology
Dvurechensky, Pavel	Weierstrass Institute
Spokoiny, Vladimir	WIAS and HU Berlin
Keywords: Stochastic adaptive control, Nonlinear adaptive control, Machine learning Abstract: We consider several line-search based gradient methods for stochastic optimization: a gradient and accelerated gradient methods for convex optimization and gradient method for non-convex optimization. The methods simultaneously adapt to the unknown Lipschitz constant of the gradient and variance of the stochastic approximation for the gradient. The focus of this paper is to numerically compare such methods with state-of-the-art adaptive methods which are based on a different idea of taking norm of the stochastic gradient to define the stepsize, e.g., AdaGrad and Adam.

VI113
Systems and Signals - Discrete Event and Hybrid Systems
VI113-01 Cyber-Security and Safety of Discrete-Event Systems   Invited Session, 10 papers
VI113-02 Distributed Event-Triggered Control of Multi-Agent Systems   Invited Session, 6 papers
VI113-03 Formal Methods for Hybrid Systems   Open Invited Session, 11 papers
VI113-04 Modelling, Analysis and Control of Hybrid and Switched Systems   Regular Session, 10 papers
VI113-06 Reachability Analysis, Verification , and Abstraction of Hybrid Systems   Regular Session, 6 papers
VI113-07 Stability and Stabilization of Hybrid Systems   Regular Session, 13 papers
VI113-08 Supervisory Control and Analysis of Discrete Event Systems   Regular Session, 16 papers

VI113-01
Cyber-Security and Safety of Discrete-Event Systems	Invited Session
Chair: Cai, Kai	Osaka City University
Co-Chair: Yin, Xiang	Shanghai Jiao Tong University
Organizer: Yin, Xiang	Shanghai Jiao Tong University
Organizer: Cai, Kai	Osaka City University
Paper VI113-01.1
PDF · Video · Incremental Improvements of Heuristic Policies for Average-Reward Markov Decision Processes (I)
Reveliotis, Spyros A.	Georgia Institute of Technology
Ibrahim, Michael	University of Cairo
Keywords: Discrete event modeling and simulation, Learning for control, Queueing systems and performance model                                        Abstract: Within the realm of Discrete Event Systems (DES) theory, the problem of performance optimization for many applications can be modeled as an infinite-horizon, average-reward Markov Decision Process (MDP) with a finite state space. In principle, these MDPs can be solved by various well-developed methods like value iteration, policy iteration and linear programming. But in reality, the tractability of these methods in the context of the aforementioned applications is compromised by the explosive size of the underlying state spaces, a problem that is known as ``the curse of dimensionality''. Hence, the corresponding performance optimization problems are frequently addressed by heuristic control policies. The considered work uses results from (i) the sensitivity analysis of Markov reward processes and (ii) the ranking & selection theory in statistics in order to develop a methodology for assessing the optimality of isolated decisions in the context of any well-defined heuristic control policy for the aforementioned MDPs. It also determines an improved decision when the current one is found to be suboptimal. Hence, when embedded in an iterative scheme, this methodology can support the incremental enhancement of the original heuristic policy in a way that controls, both, the computational and also the representational complexity of the new policy. Finally, an additional important feature of the presented methodology is that it can be executed either in an ``off-line'' mode, using a simulation of the dynamics of the underlying DES, or in an ``on-line'' mode, based on the sample path that is defined by the real-time dynamics of the controlled system.
Paper VI113-01.2
PDF · Video · Verification of Infinite-Step Opacity Using Labeled Petri Nets (I)
Lan, Hao	Southwest Jiaotong University
Tong, Yin	Southwest Jiaotong University
Seatzu, Carla	Univ. of Cagliari
Keywords: Petri nets, Discrete event modeling and simulation, Supervisory control and automata Abstract: Opacity is an important information secure property. A system is said to be infinite-step opaque if the intruder is never able to ascertain that the system is or has been in a secret state at some time, based on its observation of the system evolution. This work aims to verify infinite-step opacity of discrete event systems modeled with labeled Petri nets. Based on the notion of basis reachability graph, a new structure called basis two-way observer is proposed to check infinite-step opacity of a bounded system, which is shown to be more efficient than the standard method based on the reachability graph.
Paper VI113-01.3
PDF · Video · Supervisor Reduction by Hiding Events (I)
Malik, Robi	The University of Waikato
Keywords: Supervisory control and automata, Event-based control Abstract: This paper proposes a method to improve supervisor reduction for discrete event systems by first reducing the number of events. Supervisor reduction is a method to reduce the number of states of an automatically computed supervisor or controller in order to make it more manageable. This paper proposes to complement the most popular supervisor reduction algorithm currently in use by first reducing the supervisor's event set. Experimental results show that this does not only reduce the communication between the supervisor and plant, but also produces a simpler state machine that can be minimised more effectively.
Paper VI113-01.4
PDF · Video · Confidentiality of Cyber-Physical Systems Using Event-Based Cryptography (I)
Lima, Públio M.	Universidade Federal Do Rio De Janeiro
Carvalho, Lilian Kawakami	Universidade Federal Do Rio De Janeiro
Moreira, Marcos Vicente	Univ. Fed. Rio De Janeiro
Keywords: Secure networked control systems, Discrete event modeling and simulation Abstract: One of the most important challenges for the application of cyber-physical systems (CPS) in smart industries is ensuring its security against cyber attacks. In this paper, we consider that the CPS is abstracted as a Discrete-Event System (DES), and we consider cyber attacks where the intruder eavesdrops the sensor communication channel to detect the occurrence of a sequence in the secret behavior of the system. In order to prevent the attacker from getting information from the sensor channel, we introduce a new cryptographic scheme based on events called event-based cryptography. We also define the property of confidentiality of DES, present a necessary and sufficient condition for ensuring this property, and propose a verification test.
Paper VI113-01.5
PDF · Video · Optimal Stabilization of Discrete Event Systems with Guaranteed Worst Cost (I)
Ji, Yiding	Boston University
Yin, Xiang	Shanghai Jiao Tong University
Keywords: Supervisory control and automata, Stochastic control and game theory, Reachability analysis, verification and abstraction of hybrid systems Abstract: This work investigates optimal stabilization with guaranteed worst-case performance of stochastic discrete event systems by supervisory control. We formulate the problem on probabilistic weighted automata. The system is driven to a specified set of target states after a finite number of transitions, thus stabilized. The cost of stabilization is concerned with the accumulative weight of transitions reaching target states. Our goal is to optimize the expected cost of reaching target states, while ensuring that the worst-case individual cost is bounded by a given threshold. Then we transform the supervisory control problem to a two-player stochastic game between the supervisor and the environment, which properly encodes the worst-case requirement. Finally an algorithm is presented to synthesize the optimal supervisor by leveraging results from Markov Decision Processes, which turns out to provably solve the original problem.
Paper VI113-01.6
PDF · Video · Discrete Control of Response for Cybersecurity in Industrial Control (I)
Delaval, Gwenaël	Université Grenoble Alpes
Hore, Ayan	Inria Grenoble
Mocanu, Stephane	GIPSA-Lab, Grenoble-INP
Muller, Lucie	Inria Grenoble
Rutten, Eric	INRIA Rhône Alpes
Keywords: Discrete event modeling and simulation, Supervisory control and automata Abstract: Cybersecurity in Industrial Control Systems (ICS) is a crucial problem, as recent history has shown. A notable characteristic of ICS, compared to Information Technology, is the necessity to take into account the physical process, and its specific dynamics and effects on the environment, when considering cybersecurity issues. Intrusion Detection Systems have been studied extensively. In our work, we address the less classic topic of response mechanisms, and their automation in a self-protection feedback loop. More precisely, we address self-protection seen as resilience, where the functionality of the system is maintained under attacks, be it in a degraded mode. We model this as a Discrete Event Systems supervisory control problem, involving a model of the plant’s possible behaviors, a model of considered attacks, and a formulation of the control objectives. We consider a case study, and perform a prototype implementation and simulation, using the Heptagon/BZR programming language and compiler/code generator, and targeting a multi-PLC experimental platform.
Paper VI113-01.7
PDF · Video · Efficient Failure-Recovering Supervisors (I)
Paape, Nick	Eindhoven University of Technology
van de Mortel-Fronczak, Joanna	Eindhoven University of Technology
Swartjes, Lennart	Vanderlande Industries
Reniers, Michel	TU/e
Keywords: Supervisory control and automata Abstract: Automated systems require controllers which guarantee machine safety and specified functionality even in case of occurring defects. In literature, several methods can be found for formally deriving a supervisor providing such guarantees, including the existence of failure recovery. In this paper, an extension is proposed so that the derived supervisor not only guarantees the existence of failure recovery, but also enforces a shortest path for it. To this end, a two-step procedure is defined for supervisor derivation, in which two algorithms are involved.
Paper VI113-01.8
PDF · Video · Opacity Enforcing Supervisory Control Using Non-Deterministic Supervisors (I)
Xie, Yifan	Shanghai Jiao Tong University
Yin, Xiang	Shanghai Jiao Tong University
Li, Shaoyuan	Shanghai Jiao Tong Univ
Keywords: Supervisory control and automata, Discrete event modeling and simulation, Diagnosis of discrete event and hybrid systems Abstract: In this paper, we investigate the enforcement of opacity via supervisory control in the context of discrete-event systems. A system is said to be opaque if the intruder, which is modeled as a passive observer, can never infer confidentially that the system is at a secret state. The design objective is to synthesize a supervisor such that the closed-loop system is opaque even though the control policy is publicly known. In this paper, we propose to use non-deterministic supervisors to enforce opacity. A non-deterministic supervisor provides a set of control decisions at each instant, and randomly picks a specific control decision from the decision set. Such a non-deterministic control mechanism can enhance the plausible deniability of the controlled system as the online control decision cannot be implicitly inferred from the control policy. We provide an effective approach to synthesize a non-deterministic opacity-enforcing supervisor. Furthermore, we show that non-deterministic supervisors are strictly more powerful than deterministic supervisors in the sense that there may exist a non-deterministic opacity-enforcing supervisor even when deterministic supervisors cannot enforce opacity.
Paper VI113-01.9
PDF · Video · Maximally Permissive Supervisor Control of Timed Discrete-Event Systems under Partial Observation (I)
Yang, Ziteng	Shanghai Jiao Tong University
Yin, Xiang	Shanghai Jiao Tong University
Li, Shaoyuan	Shanghai Jiao Tong Univ
Keywords: Supervisory control and automata, Discrete event modeling and simulation, Diagnosis of discrete event and hybrid systems Abstract: In this paper, we investigate the supervisory control problem for timed discrete-event systems (TDES) under partial observation. In the timed setting, the system consists of both standard logical events and time event, where the former can be disabled directly by the supervisor if it is controllable while the latter can only be preempted by forcing the occurrences of forcible events. We consider a general control mechanism where the supervisor can choose which events to force dynamically online at each instant. The design objective is to synthesize a maximally-permissive supervisor to restrict the behavior of the system such that the closed-loop language is within a safe specification language. Effective procedure is presented to synthesize such a supervisor. To our knowledge, how to synthesize a maximally-permissive partial-observation supervisor for has not been solved for timed DES. We provide a solution to this problem under a general control mechanism.
Paper VI113-01.10
PDF · Video · Towards Probabilistic Intrusion Detection in Supervisory Control of Discrete Event Systems (I)
Meira-Góes, Rômulo	University of Michigan
Keroglou, Christoforos	University of Michigan, Ann Arbor
Lafortune, Stephane	Univ. of Michigan
Keywords: Supervisory control and automata, Discrete event modeling and simulation Abstract: In control systems, sensor deception is a class of attacks where an attacker manipulates sensor readings to cause damage to the system. Our work investigates quantitative measurements to detect this class of attacks in the context of stochastic supervisory control. We introduce the notion of e-safe systems, which is a first step to generalize qualitative intrusion detection conditions to quantitative intrusion detection conditions. We provide sufficient and necessary conditions to verify if a system is e-safe. Moreover, we provide an algorithm that verifies these conditions, which implies that the problem is decidable.

VI113-02
Distributed Event-Triggered Control of Multi-Agent Systems	Invited Session
Chair: He, Wangli	East China University of Science and Technology
Co-Chair: Xu, Wenying	Southeast University
Organizer: He, Wangli	East China University of Science and Technology
Organizer: Tang, Yang	East China University of Science and Technology
Organizer: Han, Qing-Long	Swinburne University of Technology
Paper VI113-02.1
PDF · Video · Event-Triggered Finite-Time Consensus under Directed Graphs (I)
Jin, Xin	East China University of Science and Technology
Zhang, Wenbing	Yangzhou University
Wu, Xiaotai	Anhui Polytechnic University
Tang, Yang	East China University of Science and Technology
Keywords: Multi-agent systems, Consensus, Event-based control Abstract: This paper focuses on deal with thenite-time consensus with event-triggered control strategy for multi-agent systems (MASs). An event-triggered protocol fornite-time consensus is designed using relative measurements. The coordination measurement error is utilized in the triggering condition design for the purpose of removing the prerequisite of topology graph knowledge. Under strongly connected graph assumptions, by utilizing the proposed consensus protocol, all agents can complete consensus and Zeno behaviour will not happen in a settling time. Next, by decomposing the Laplacian matrix in Frobenius norm form, the results are extended to the more general graphs containing a directed spanning tree. At last, a numerical example demonstrates the validity of the algorithm results.
Paper VI113-02.2
PDF · Video · Dynamic Adaptive Event-Triggered Scheme for General Linear Multi-Agent Systems (I)
Xu, Wenying	Southeast University, Nanjing
Ho, Daniel W. C.	City Univ. of Hong Kong
He, Wangli	East China University of Science and Technology
Keywords: Consensus, Control under communication constraints, Distributed control and estimation Abstract: This paper proposes a novel dynamic adaptive event-triggered scheme to deal with consensus problems in a class of general linear multi-agent systems. Firstly, a fully distributed event-triggered consensus protocol is proposed by assigning a time-varying coupling weight for each edge. Then by introducing an additional internal dynamic variable, a dynamic adaptive event condition is skillfully constructed and Zeno behavior is also successfully excluded. Based on this, the asymptotic consensus is eventually achieved and the frequency of communication among agents is significantly reduced. Finally, one simulation example is provided to verify the effectiveness of the proposed scheme.
Paper VI113-02.3
PDF · Video · Co-Design of Sampling Pattern and Control in Self-Triggered Model Predictive Control for Sampled-Data Systems (I)
Cui, Di	Northwestern Polytechnical University
Li, Huiping	Northwestern Polytechnical University
Keywords: Event-based control, Model predictive control of hybrid systems, Control over networks Abstract: This paper studies the event-triggered model predictive control (MPC) problem for networked control systems with input constraints, where the control is of the sampled data form. A novel self-triggered MPC (STMPC) method which enables the optimal design of sampling pattern and control law is proposed to reduce the conservatism of separate design of trigger and control law in existing approaches. The conditions on ensuring algorithm feasibility and closed-loop system stability are developed. In addition, an upper bound of the closed-loop system performance is derived which provides performance guarantee for the designed STMPC. Finally, simulation results are presented to verify the effectiveness of the proposed STMPC method.
Paper VI113-02.4
PDF · Video · Risk Assessment of Multi-Area Interconnected Power System under Gas Station Network Attacked (I)
Li, Xue	Shanghai University
Zhang, Zhourong	Shanghai Key Laboratory of Power Station Automation Technology,
Du, Dajun	Queen's University Belfast
Dong, Jing	Shanghai Key Laboratory of Power Station Automation Technology,
Wang, Yu-Long	Shanghai University
Keywords: Secure networked control systems, Control over networks Abstract: This paper mainly investigates the risk assessment of multi-area interconnected power system with probabilistic optimal power flow (POPF) for charging load of plug-in hybrid electric vehicle (PHEV) under gas station network attacked. Firstly, the PHEV charging model is developed by analyzing the change of PHEV operation mode after running out of gasoline. Secondly, in a multi-region interconnected power system, a line overload risk index is established to evaluate the impact of PHEV charging on the tie-line powers with the gas station network unavailable, and POPF considering PHEVs, wind and photovoltaic generation is employed to reduce the risk of system operation. Finally, the method is tested on IEEE 118-bus system to analyze the impacts of PHEV charging on tie-line powers and the entire system under gas station network attacked, and the economy and safety of system operation are evaluated before and after optimization.
Paper VI113-02.5
PDF · Video · Resilient Distributed Event-Triggered Control of Vehicle Platooning under DoS Attacks (I)
Xiao, Shunyuan	Nanjing University of Science and Technology
Ge, Xiaohua	Swinburne University of Technology
Han, Qing-Long	Swinburne University of Technology
Cao, Zhenwei	Swinburne University
Zhang, Yijun	Nanjing University of Science and Technology
Wang, Honghai	College of Information Science and Engineering, NortheasternUniv
Keywords: Secure networked control systems, Control under communication constraints, Networked embedded control systems Abstract: This paper is concerned with resilient distributed event-triggered control of a platoon of automatic vehicles under DoS attacks. First, an event-triggered transmission mechanism resilient to energy-limited DoS attacks is proposed to save the possible communication resources within inter-vehicle communication channels. A consensus-based distributed control strategy, which acts on each vehicle in the platoon, is developed to account for the information cooperation of leading and following vehicles under the proposed resilient event-triggered data transmission mechanism. Second, an attack-tolerant performance index with certain resilience level is put forward in such a way to achieve resilience evaluation of the vehicular platoon system. Third, sufficient conditions are derived for ensuring the asymptotic stability of the resulting vehicular platoon system while preserving the prescribed resilience performance requirement. Furthermore, a co-design approach to the distributed platoon controller as well as the resilient event triggering condition is presented. Finally, a case study under a predecessor-leader following topology is given to demonstrate the effectiveness of the obtained results.
Paper VI113-02.6
PDF · Video · Quantized Consensus of Linear Multi-Agent Systems under an Event-Triggered Strategy (I)
Luo, Tinghui	East China University of Science and Technology
He, Wangli	East China University of Science and Technology
Xu, Wenying	City University of Hong Kong
Keywords: Consensus, Event-based control, Quantized systems Abstract: This paper addresses a quantized consensus problem of general linear multi-agent systems in a symmetric network under an event-triggered scheme. Firstly, a distributed event-triggered strategy is developed with a dynamic threshold to reduce the unnecessary control update. Then, based on absolute quantized state measurements, a distributed controller is proposed and then a consensus criterion is derived, which ensures bounded consensus of linear multi-agent systems. The Zeno behavior is also successfully excluded. Finally, a numerical simulation is presented to validate theoretical results.

VI113-03
Formal Methods for Hybrid Systems	Open Invited Session
Chair: Sanfelice, Ricardo	University of California Santa Cruz
Co-Chair: Prabhakar, Pavithra	Kansas State University
Organizer: Liu, Jun	University of Waterloo
Organizer: Prabhakar, Pavithra	Kansas State University
Organizer: Sanfelice, Ricardo	University of California Santa Cruz
Paper VI113-03.1
PDF · Video · Abstraction of Monotone Systems Based on Feedback Controllers (I)
Sinyakov, Vladimir	CNRS
Girard, Antoine	CNRS
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: In this paper, we consider the problem of computation of efficient symbolic abstractions for a certain subclass of continuous-time monotone control systems. The new abstraction algorithm utilizes the properties of such systems to build symbolic models with the same number of states but fewer transitions in comparison to the one produced by the standard algorithm. At the same time, the new abstract system is at least as controllable as the standard one. The proposed algorithm is based on the solution of a region-to-region control synthesis problem. This solution is formally obtained using the theory of viscosity solutions of the dynamic programming equation and the theory of differential equations with discontinuous right-hand side. In the new abstraction algorithm, the symbolic controls are essentially the feedback controllers that solve this control synthesis problem. The improvement in the number of transitions is achieved by reducing the number of successors for each symbolic control. The approach is illustrated by an example that compares the two abstraction algorithms.
Paper VI113-03.2
PDF · Video · Interval Reachability Analysis Using Second-Order Sensitivity (I)
Meyer, Pierre-Jean	University of California, Berkeley
Arcak, Murat	UC Berkeley
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: We propose a new approach to compute an interval over-approximation of the finite time reachable set for a large class of nonlinear systems. This approach relies on the notions of sensitivity matrices, which are the partial derivatives representing the variations of the system trajectories in response to variations of the initial states. Using interval arithmetics, we first over-approximate the possible values of the second-order sensitivity at the final time of the reachability problem. Then we exploit these bounds and the evaluation of the first-order sensitivity matrices at a few sampled initial states to obtain an over-approximation of the first-order sensitivity, which is in turn used to over-approximate the reachable set of the initial system. Unlike existing methods relying only on the first-order sensitivity matrix, this new approach provides guaranteed over-approximations of the first-order sensitivity and can also provide such over-approximations with an arbitrary precision by increasing the number of samples.
Paper VI113-03.3
PDF · Video · Continuous and Discrete Abstractions for Planning, Applied to Ship Docking (I)
Meyer, Pierre-Jean	University of California, Berkeley
Yin, He	University of California, Berkeley
Brodtkorb, Astrid H	Norwegian University of Science and Technology
Arcak, Murat	UC Berkeley
Soerensen, Asgeir	Norwegian University of Science and Technology
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: We propose a hierarchical control framework for the synthesis of correct-by-construction controllers for nonlinear control-affine systems with respect to reach-avoid-stay specifications. We first create a low-dimensional continuous abstraction of the system and use Sum-of-Squares (SOS) programming to obtain a low-level controller ensuring a bounded error between the two models. We then create a discrete abstraction of the continuous abstraction and use formal methods to synthesize a controller satisfying the specifications shrunk by the obtained error bound. Combining both controllers finally solves the main control problem on the initial system. This two-step framework allows the discrete abstraction methods to deal with higher-dimensional systems which may be computationally expensive without the prior continuous abstraction. The main novelty of the proposed SOS continuous abstraction is that it allows the error between abstract and concrete models to explicitly depend on the control input of the abstract model, which offers more freedom in the choice of the continuous abstraction model and provides lower error bounds than when only the states of both models are considered. This approach is illustrated on the docking problem of a marine vessel.
Paper VI113-03.4
PDF · Video · Lazy Safety Controller Synthesis with Multi-Scale Adaptive-Sampling Abstractions of Nonlinear Systems (I)
Ivanova, Elena	CNRS, CentraleSupelec, Université Paris-Sud, Université Paris-Sa
Girard, Antoine	CNRS
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: In this paper, we present an abstraction-based approach to safety controller synthesis for continuous-time nonlinear systems. To reduce the computational burden associated with symbolic control approaches, we develop a lazy controller synthesis algorithm, which uses the incremental forward exploration of the symbolic dynamics, allowing us to restrict the controller synthesis computations to reachable states only. We propose using this algorithm with novel multi-scale abstractions, which also use adaptive time sampling. Transition duration is constrained by intervals that must contain the reachable set, which enables better control of the symbolic transitions as opposed to using transitions of predetermined duration. Implementation of the algorithm and controller refinement are discussed. We provide a simple example to illustrate these benefits of the approach.
Paper VI113-03.5
PDF · Video · On Symbolic Control Design of Nonlinear Systems with Dynamic Regular Language Specifications (I)
Masciulli, Tommaso	University of L'Aquila
Pola, Giordano	University of L'Aquila
Keywords: Quantized systems, Supervisory control and automata Abstract: Formal methods are becoming rather popular in the research community working on hybrid systems because they provide a systematic approach to design complex and heterogeneous systems of interest in e.g. industrial world. In this paper we consider a control problem where the plant is a nonlinear system, the controller is a finite state machine, easily implementable in digital devices, and the specification is a regular language and, it is dynamic. The motivation for considering dynamic specifications comes from some relevant and concrete applications where environment, external to the plant, may change in time and therefore designed controllers need to timely reconfigure to properly deal with new scenario. We propose an approach to reduce on–line computations for controller reconfiguration which exhibits gain in terms of time computational complexity. The results we present are based on the use of symbolic models and on regular language theory.
Paper VI113-03.6
PDF · Video · A Necessary Condition on Chain Reachable Robustness of Dynamical Systems (I)
Fitzsimmons, Maxwell	University of Waterloo
Liu, Jun	University of Waterloo
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: It is ``folklore'' that the solution to a set reachability problem for a dynamical system is only noncomputable because of non-robustness reasons. A robustness condition that can be imposed on a dynamical system is the requirement of the chain reachable set to equal the closure of the reachable set. We claim that this condition necessarily imposes strong conditions on the dynamical system. For instance, if the space is connected and compact and we are computing a chain reachable robust single valued function f then f cannot have an unstable fixed point or unstable periodic cycle.
Paper VI113-03.7
PDF · Video · Compositional Construction of Control Barrier Functions for Networks of Continuous-Time Stochastic Systems (I)
Nejati, Ameneh	Technical University of Munich (TUM)
Soudjani, Sadegh	Newcastle University
Zamani, Majid	University of Colorado Boulder
Keywords: Control of networks, Synthesis of stochastic systems, Stochastic hybrid systems Abstract: In this paper, we propose a compositional framework for the construction of control barrier functions for networks of continuous-time stochastic control systems. The proposed scheme is based on a notion of so-called pseudo-barrier functions computed for subsystems, using which one can synthesize state-feedback controllers for interconnected systems enforcing safety specifications over a finite-time horizon. Particularly, we first leverage sufficient small-gain type conditions to compositionally construct control barrier functions for interconnected systems based on the corresponding pseudo-barrier functions computed for subsystems. Then, using the constructed control barrier functions, we quantify upper bounds on exit probabilities - the probability that an interconnected system reaches certain unsafe regions - in a finite-time horizon. We employ a systematic technique based on the sum-of-squares optimization program to search for pseudo-barrier functions of subsystems while synthesizing safety controllers. We demonstrate our proposed results by applying them to a temperature regulation in a network of 1000 rooms.
Paper VI113-03.8
PDF · Video · Compositional Construction of Control Barrier Certificates for Large-Scale Interconnected Stochastic Systems (I)
Anand, Mahathi	Ludwig Maximilian University of Munich
Lavaei, Abolfazl	Ludwig Maximilian University of Munich (LMU)
Zamani, Majid	University of Colorado Boulder
Keywords: Synthesis of stochastic systems, Control of networks, Stochastic hybrid systems Abstract: This paper proposes a compositional approach for constructing control barrier certificates of large-scale interconnected discrete-time stochastic control systems. The proposed compositional methodology is based on a notion of control sub-barrier certificates enabling one to construct control barrier certificates of interconnected systems by leveraging some small-gain type conditions. The main goal is to synthesize control policies satisfying safety properties for interconnected systems utilizing those control sub-barrier certificates of subsystems while providing upper bounds on the probability that interconnected systems reach unsafe regions in finite-time horizons. A sum-of-squares optimization problem is formulated for searching control sub-barrier certificates and corresponding local control policies satisfying safety specifications. The proposed compositional approaches are illustrated on a temperature regulation in a circular building containing 1000 rooms by compositionally synthesizing safety controllers to maintain the temperature of each room in a comfort zone in a bounded-time horizon.
Paper VI113-03.9
PDF · Video · Compositional Synthesis of Symbolic Models for Infinite Networks (I)
Swikir, Abdalla	Technical University of Munich
Noroozi, Navid	Otto Von Guericke University Magdeburg
Zamani, Majid	University of Colorado Boulder
Keywords: Quantized systems, Control of networks, Multi-agent systems Abstract: In this paper, we provide a compositional method for the construction of symbolic models (a.k.a. finite abstractions) for infinite networks of discrete-time control systems. The concrete infinite network and its symbolic model are related by a so-called alternating simulation function which allows one to quantify the mismatch between the output behavior of the infinite interconnection of concrete subsystems and that of their symbolic models. We show that such an alternating simulation function can be obtained compositionally by assuming some small-gain type conditions and composing so-called local alternating simulation functions constructed for subsystems. Assuming certain stability property of concrete subsystems, we also provide a technique to synthesize their symbolic models together with their corresponding local alternating simulation functions. Finally, we apply our results to a traffic network divided into infinitely many cells.
Paper VI113-03.10
PDF · Video · Optimization-Based Motion Planning and Runtime Monitoring for Robotic Agent with Space and Time Tolerances (I)
Lin, Zhenyu	University of Maryland, College Park
Baras, John S.	Univ. of Maryland
Keywords: Optimal control of hybrid systems, Event-based control, Model predictive control of hybrid systems Abstract: We present an optimization-based approach for robot planning, monitoring and self-correction problems under signal temporal logic specifications (STL). The STL specifications are translated into mixed-integer linear constraints, and we generate the reference trajectory by solving a mixed-integer-linear-programming (MILP) to maximize the overall space and time tolerances. During runtime execution, a prediction module is constantly evaluating the robustness degree of the predicted trajectory, and a self-correction module based on event- triggered model predictive control (MPC) has been designed to predict and correct possible future violations of the specifications. Simulation results show that with our approach, the robotic agent is able to generate a path that satisfies the STL specifications while maximizing space and time tolerances, and able to make corrections when there are possible violations of the specifications during runtime execution.
Paper VI113-03.11
PDF · Video · Reachability-Based Human-In-The-Loop Control with Uncertain Specifications
Gao, Yulong	The Royal Institute of Technology (KTH)
Jiang, Frank J.	KTH Royal Institute of Technology
Ren, Xiaoqiang	Shanghai University
Xie, Lihua	Nanyang Technological University
Johansson, Karl H.	Royal Institute of Technology
Keywords: Networked robotic systems, Networked embedded control systems, Control over networks Abstract: We propose a shared autonomy approach for implementing human operator decisions onto an automated system during multi-objective missions, while guaranteeing safety and mission completion. A mission is specified as a set of linear temporal logic (LTL) formulae. Then, using a novel correspondence between LTL and reachability analysis, we synthesize a set of controllers for assisting the human operator to complete the mission, while guaranteeing that the system maintains specified spatial and temporal properties. We assume the human operator's exact preference of how to complete the mission is unknown. Instead, we use a data-driven approach to infer and update the automated system's internal belief of which specified objective the human intends to complete. If, while the human is operating the system, she provides inputs that violate any of the invariances prescribed by the LTL formula, our verified controller will use its internal belief of the human operator's intended objective to guide the operator back on track. Moreover, we show that as long as the specifications are initially feasible, our controller will stay feasible and can guide the human to complete the mission despite some unexpected human errors. We illustrate our approach with a simple, but practical, experimental setup where a remote operator is parking a vehicle in a parking lot with multiple parking options. In these experiments, we show that our approach is able to infer the human operator's preference over parking spots in real-time and guarantee that the human will park in the spot safely.

VI113-04
Modelling, Analysis and Control of Hybrid and Switched Systems	Regular Session
Chair: Sanfelice, Ricardo	University of California Santa Cruz
Co-Chair: Pepe, Pierdomenico	University of L'Aquila
Paper VI113-04.1
PDF · Video · Index-2 Hybrid DAE: A Case Study with Well-Posedness and Numerical Analysis
Rocca, Alexandre	Inria Grenoble, Uga, Ljk
Acary, Vincent	INRIA Grenoble
Brogliato, Bernard	UR Rhone-Alpes
Keywords: Hybrid and switched systems modeling Abstract: In this work, we study differential algebraic equations with constraints defined in a piecewise manner using a conditional statement. Such models classically appear in systems where constraints can evolve in a very small time frame compared to the observed time scale. The use of conditional statements or hybrid automata is a powerful way to describe such systems and are, in general, well suited to simulation with event driven numerical schemes. However, such methods are often subject to chattering at mode switch in presence of sliding modes, or can result in Zeno behaviours. In contrast, the representation of such systems using differential inclusions and method from non-smooth dynamics are often closer to the physical theory but may be harder to interpret. Associated time-stepping numerical methods have been extensively used in mechanical modelling with success and then extended to other fields such as electronics and system biology. In a similar manner to the previous application of non-smooth methods to the simulation of piecewise linear ODEs, non-smooth event-capturing numerical schemes are applied to piecewise linear DAEs. In particular, the detailed study of a 2-D dynamical system of index-2 with a switching constraint using set-valued operators, is presented.
Paper VI113-04.2
PDF · Video · Enhancing Low-Rank Solutions in Semidefinite Relaxations of Boolean Quadratic Problems
Cerone, Vito	Politecnico Di Torino
Fosson, Sophie Marie	Politecnico Di Torino
Regruto, Diego	Politecnico Di Torino
Keywords: Hybrid and switched systems modeling Abstract: Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR’s) are proposed in the literature to approximate the solution, which recasts the problem into convex optimization. Nevertheless, SDR’s do not guarantee the extraction of the correct binary minimizer. In this paper, we present a novel approach to enhance the binary solution recovery. The key of the proposed method is the exploitation of known information on the eigenvalues of the desired solution. As the proposed approach yields a non-convex program, we develop and analyze an iterative descent strategy, whose practical effectiveness is shown via numerical results.
Paper VI113-04.3
PDF · Video · ISS Small-Gain Theorem for Networked Discrete-Time Switching Systems
Pepe, Pierdomenico	University of L'Aquila
Keywords: Hybrid and switched systems modeling, Control of networks, Stability and stabilization of hybrid systems Abstract: In this paper it is proved that a discrete-time switching system, equipped with a given switches digraph, is input-to-state stable, provided that there exist multiple Lyapunov functions (one for each mode) for each subsystem in the network, satisfying suitable standard inequalities, and provided that a set of suitable vector small-gain conditions are satisfied. The small-gain theorem here provided for the input-to-state stability takes into account the switches digraph. That is, the less is the number of edges in the switches digraph, the less is the number of involved Lyapunov inequalities and small-gain conditions which, if satisfied, guarantee the input-to-state stability of the entire switching system under study. The multiple Lyapunov functions for the entire system, guaranteeing the input-to-state stability, are determined by the multiple Lyapunov functions for each subsystem in the family. To the author's best knowledge, this is the first paper in the literature concerning small-gain theorems for the input-to-state stability of nonlinear discrete-time switching systems with given switches digraphs.
Paper VI113-04.4
PDF · Video · An Adaptive Hybrid Control Algorithm for Sender-Receiver Clock Synchronization
Guarro, Marcello	University of California, Santa Cruz
Sanfelice, Ricardo	University of California Santa Cruz
Keywords: Hybrid and switched systems modeling, Control over networks, Sensor networks Abstract: This paper presents an innovative hybrid systems approach to the sender-receiver synchronization of timers. Via the hybrid systems framework, we unite the traditional sender-receiver algorithm for clock synchronization with an, online, adaptive strategy to achieve synchronization of the clock rates to exponentially synchronize a pair of clocks connected over a network. Following the conventions of the algorithm, clock measurements of the nodes are given at periodic time instants, and each node uses these measurements to achieve synchronization. For this purpose, we introduce a hybrid system model of a network with continuous and impulsive dynamics that captures the sender-receiver algorithm as a state-feedback controller to synchronize the network clocks. Moreover, we provide sufficient design conditions that ensure attractivity of the synchronization set.
Paper VI113-04.5
PDF · Video · An Algebraic Approach for Discrete Dynamic Reconstruction for Switched Bilinear Systems
Motchon, Koffi M. Djidula	Université De Reims Champagne Ardenne, CReSTIC EA 3804
Rajaoarisoa, Lala	Institut Mines Télecom. Mines De Douai
Pekpe, Komi Midzodzi	University Lille 1
Etienne, Lucien	IMT Lille-Douai
Lecoeuche, Stéphane	IMT Lille Douai
Keywords: Hybrid and switched systems modeling, Nonlinear system identification, Continuous time system estimation Abstract: Estimation of the switching signal of continuous-time switched bilinear systems from input-output measurements is addressed in this paper. First, the uniqueness problem of the switching signal reconstruction from the input-output data is studied in terms of distinguishability analysis of the operating modes. In this context, a numerically verifiable condition for the operating modes distinguishability is established. This condition also provides a characterization of regularly persistent control inputs ensuring the unique determination of the switching signal. For these class of control inputs, an algorithm is then provided for the estimation problem. The proposed approach is based on a compatibility test between the input-output measurements and the dynamical behaviour of the modes.
Paper VI113-04.6
PDF · Video · Adaptive Cruise Control with Timed Automata
Kara, Mustafa Yavuz	Middle East Technical University
Aydin Gol, Ebru	Middle East Technical University
Keywords: Hybrid and switched systems modeling, Reachability analysis, verification and abstraction of hybrid systems, Supervisory control and automata Abstract: An adaptive cruise control (ACC) system maintains the vehicle at the given target speed when there is no leading vehicle in the sensor range. On the other hand, in the presence of a leading vehicle, the system maintains a safe distance between the vehicles while driving as close as possible to the target speed. For such an automated system, besides meeting safety requirements, it is also important to provide a comfortable drive. In this paper, we develop a formal model for adaptive cruise control system based on timed automata and express specifications in temporal logics. The proposed model supports different acceleration levels. Parametric constraints govern the transitions to the states associated with acceleration levels. The proposed parameter optimization methods generate parameter valuations for particular driving styles while guaranteeing safety and the specifications over the target speed. Therefore, the resulting system is guaranteed to satisfy the requirements while the driver comfort is optimized. The models and the synthesis approach are illustrated with examples.
Paper VI113-04.7
PDF · Video · Indirect Model Reference Adaptive Control of Piecewise Affine Systems with Concurrent Learning
Liu, Tong	Technische Universität München
Buss, Martin	Technische Universitaet Muenchen
Keywords: Hybrid and switched systems modeling, Stability and stabilization of hybrid systems, Adaptive gain scheduling autotuning control and switching control Abstract: In this paper, we propose a concurrent learning-based indirect model reference adaptive control approach for multivariable piecewise affine systems as an enhancement of our previous work. The main advantage of the concurrent learning-based approach is that the linear independence condition of the recorded data suffices for the convergence of the estimated system parameters. The classical persistent excitation assumption of the input signal is not required. Moreover, it is proved that the closed-loop system is stable even when the system enters the sliding mode. The numerical example shows that the concurrent learning-based approach exhibits better tracking performance and achieves parameter convergence when compared with our previously proposed approach.
Paper VI113-04.8
PDF · Video · New Results on Stabilization of Stochastic Switching Systems Subject to Partly Available Semi-Markov Kernel
Ning, Zepeng	Harbin Institute of Technology
Cai, Bo	Harbin Institute of Technology
Zhang, Ruixian	Harbin Institute of Technology
Zhang, Lixian	Harbin Institute of Technology
Keywords: Hybrid and switched systems modeling, Synthesis of stochastic systems, Stochastic hybrid systems Abstract: This paper investigates the stabilization issue for a class of discrete-time stochastic switching systems. The switching behavior is dominated by a semi-Markov process with finite sojourn time. Allowing for the fact that it is often difficult to get complete semi-Markov kernel (SMK) in practice, the elements in SMK of the model under study are considered to be partly accessible, which is more general than both semi-Markov model with complete SMK and Markov model with unknown transition probabilities. Sufficient stability condition is derived for the underlying system without any a priori knowledge, based on which a stabilization criterion is presented such that the closed-loop stochastic switching systems can be mean-square stable. In the end, the validity of the theoretical results is testified by a numerical example.
Paper VI113-04.9
PDF · Video · Structural Controllability of Switching Max-Plus Linear Systems
Gupta, Abhimanyu	Delft University of Technology
van den Boom, Ton J. J.	Delft Univ. of Tech
van der Woude, Jacob	Delft University of Technology
De Schutter, Bart	Delft University of Technology
Keywords: Max-plus algebra, Stability and stabilization of hybrid systems, Hybrid and switched systems modeling Abstract: We introduce a framework for studying controllability properties of discrete-event systems modelled as switching max-plus linear systems. In this framework, we generalise the notion of structural controllability to include the switching phenomenon. Such models provide an additional discrete input to change the synchronisation and/or ordering constraints of the system. In this paper, we solve the problem of assigning the throughput of the system by suitable controller configurations. In particular, we formulate structural conditions for the existence of controllers achieving stable stationary behaviour. We also classify the achievable throughput under different controller configurations.
Paper VI113-04.10
PDF · Video · Modeling DC-DC Converters from Measurements of Their Harmonic Transfer Function
Lefteriu, Sanda	IMT Lille Douai
Keywords: Power systems, Time-varying systems, Infinite-dimensional systems Abstract: Power converters rely on semiconductor devices (transistors and/or diodes) acting as switches opening and closing periodically, hence they can be analyzed as periodic switched linear systems. The periodic behavior makes it possible to model them via the Harmonic Transfer Function (HTF). The HTF contains an infinite number of transfer functions, relating to each harmonic, but for converters operating in continuous current mode, a limited number of harmonics yields satisfactory results. This extended abstract aims at recovering a state-space model in a system identification sense from frequency-domain measurements that are physically realizable. After analyzing the open-loop response to a range of small-signal inputs with the FFT, the measurements of the HTF are obtained. This data set is used in the Loewner framework to create a descriptor-form continuous model. The advantage of the Loewner framework is that the quantities involved can be expressed in terms of generalized controllability and observability matrices. Hence, the similarity transformation is the extended observability matrix, and an optimization problem can be set up and solved iteratively for recovering the Fourier coefficients of the converter's state-space matrices and, consequently, the full description of the periodic system.

VI113-06
Reachability Analysis, Verification , and Abstraction of Hybrid Systems	Regular Session
Chair: Wisniewski, Rafal	Aalborg University
Co-Chair: Sigalotti, Mario	Inria
Paper VI113-06.1
PDF · Video · Reachable Sets for a 3D Accidentally Symmetric Molecule
Boscain, Ugo V.	DR2, CNRS, CMAP, Ecole Polytechnique
Pozzoli, Eugenio	INRIA, LJLL, Sorbonne Université
Sigalotti, Mario	Inria
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: In this paper we study the controllability properties of the quantum rotational dynamics of a 3D symmetric molecule, with electric dipole moment not collinear to the symmetry axis of the molecule (that is, an accidentally symmetric-top). We control the dynamics with three orthogonally polarized electric fields. When the dipole has a nonzero component along the symmetry axis, it is known that the dynamics is approximately controllable. We focus here our attention to the case where the dipole moment and the symmetry axis are orthogonal (that is, an orthogonal accidentally symmetric-top), providing a description of the reachable sets.
Paper VI113-06.2
PDF · Video · Safety Verification for Impulsive Systems
Feketa, Petro	Christian-Albrechts-University Kiel
Bogomolov, Sergiy	Australian National University
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: Reachability analysis, verification and abstraction of hybrid systems Abstract: The problem of safety verification for a subclass of hybrid systems, namely for impulsive systems with fixed moments of jumps is considered. Sufficient conditions are derived for the safety of impulsive systems whose continuous dynamics may steer the state outside the safe region. For this purpose auxiliary barrier certificates with nonlinear rates are introduced and equipped with appropriate dwell-time conditions which restrict the upper bound for the inter-jump interval in order to ensure the desired safety property. The proposed approach is demonstrated by performing safety verification of linear and nonlinear impulsive systems.
Paper VI113-06.3
PDF · Video · Reach-Set Estimation for DAE Systems under Uncertainty and Disturbances Using Trajectory Sensitivity and Logarithmic Norm
Geng, Sijia	University of Michigan
Hiskens, Ian A.	University of Michigan
Keywords: Reachability analysis, verification and abstraction of hybrid systems, Bounded error identification, Continuous time system estimation Abstract: Trajectory sensitivity analysis is useful for analyzing the dynamic behaviour of differential-algebraic equation (DAE) systems under uncertain initial conditions and/or parameters. However, the approximate trajectories obtained using trajectory sensitivities are not accompanied by explicit error bounds. In this paper, we provide an efficient method to obtain a numerical error bound for the first-order trajectory approximation. This approach uses second-order trajectory sensitivities. A theoretical result quantifying the excursion of trajectories induced by uncertain initial conditions and external disturbances is derived based on the logarithmic norm, and is extended to DAE systems. Although this result itself provides a guaranteed over-approximation of the reach-set of nonlinear DAE systems, by combining this result with the efficient bound obtained from trajectory sensitivities, we are able to provide a much less conservative reach-set estimate for systems under uncertain initial conditions and/or parameters, and external disturbances.
Paper VI113-06.4
PDF · Video · Compositional Construction of Finite MDPs for Continuous-Time Stochastic Systems: A Dissipativity Approach (I)
Nejati, Ameneh	Technical University of Munich (TUM)
Zamani, Majid	University of Colorado Boulder
Keywords: Reachability analysis, verification and abstraction of hybrid systems, Control of networks, Synthesis of stochastic systems Abstract: This paper provides a compositional scheme based on dissipativity approaches for constructing finite abstractions of continuous-time continuous-space stochastic control systems. The proposed framework enjoys the structure of the interconnection topology and employs a notion of stochastic storage functions, that describe joint dissipativity-type properties of subsystems and their abstractions. By utilizing those stochastic storage functions, one can establish a relation between continuous-time continuous-space stochastic systems and their finite counterparts while quantifying probabilistic distances between their output trajectories. Consequently, one can employ the finite system as a suitable substitution of the continuous-time one in the controller design process with a guaranteed error bound. In this respect, we first leverage dissipativity-type compositional conditions for the compositional quantification of the distance between the interconnection of continuous-time continuous-space stochastic systems and that of their discrete-time (finite or infinite) abstractions. We then consider a specific class of stochastic affine systems and construct their finite abstractions together with their corresponding stochastic storage functions. We illustrate the effectiveness of the proposed techniques by applying them to a physical case study.
Paper VI113-06.5
PDF · Video · Symbolic Supervisory Control of Periodic Event-Triggered Control Systems
Ren, Wei	KTH Royal Institute of Technology
Dimarogonas, Dimos V.	KTH Royal Institute of Technology
Keywords: Reachability analysis, verification and abstraction of hybrid systems, Discrete event modeling and simulation, Supervisory control and automata Abstract: This paper studies supervisory control of periodic event-triggered control (PETC) systems based on the construction of symbolic abstractions. To this end, we first construct symbolic abstractions for PETC systems, and establish feedback refinement relation from the PETC system to its symbolic models. Here, the constructed symbolic models are represented by the form of discrete event systems (DESs), including extended finite state machines, finite state machines, and classic DESs. With the constructed symbolic models, we study the supervisory control of PETC systems to achieve the desired specification. Since the constructed symbolic models are nondeterministic, we first transfer the symbolic models into deterministic versions, and then verify the existence of the supervisor. Finally, the obtained results are illustrated via a numerical example.
Paper VI113-06.6
PDF · Video · Anomaly Detection of Markov Processes with Evolution Equation and Moments
Wisniewski, Rafal	Aalborg University
Bujorianu, Luminita-Manuela	University of Strathclyde
Keywords: Reachability analysis, verification and abstraction of hybrid systems, Fault detection and diagnosis, Synthesis of stochastic systems Abstract: Our departure point is the evolution equation of a Markov process. It describes the changes in the transition probability as time passes. We compare the transition probability for a priori model with the actual transition probability of the observed process to detect a mismatch between the expected and the measured data. To translate this idea into an algorithm, we characterize the involved measures by their moments. Specifically, a linear dynamic system is put forward that describes the evolution of moments. As the last result, we define a moment divergence as the means of computing the distance between two sequences of moments. We see the work as a step towards merging model-driven and data-driven concepts in control engineering. To elucidate the concepts introduced, we have incorporated several simple examples.

VI113-07
Stability and Stabilization of Hybrid Systems	Regular Session
Chair: Teel, Andrew R.	Univ. of California at Santa Barbara
Co-Chair: Liberzon, Daniel	Univ. of Illinois at Urbana-Champaign
Paper VI113-07.1
PDF · Video · Average Dwell-Time Conditions for Input-To-State Stability of Impulsive Systems
Bachmann, Patrick	University of Kaiserslautern
Bajcinca, Naim	University of Kaiserslautern
Keywords: Stability and stabilization of hybrid systems Abstract: This paper provides sufficient conditions for input-to-state stability of impulsive control systems on Banach spaces. The derived conditions determine average dwell-time constraints for a candidate Lyapunov function parametrized by a class of nonlinear rate functions in order to guarantee the ISS property. Thereby, we consider a generalized case with unstable continuous flow maps and assume the jumps, rather than the continuous flow to induce a stabilizing influence on the system dynamics of the impulsive system. Compared to some well-known related and recent results in the literature, such as fixed dwell-time conditions, the obtained conditions are more general, while offering a higher flexibility in the choice of candidate Lyapunov functions.
Paper VI113-07.2
PDF · Video · A Lyapunov-Razumikhin Condition of ISS for Switched Time-Delay Systems under Average Dwell Time Commutation
Zhang, Junfeng	Hangzhou Dianzi University
Efimov, Denis	Inria
Keywords: Stability and stabilization of hybrid systems Abstract: A condition of ISS is proposed for nonlinear time-delay systems based on the Lyapunov-Razumikhin theory, which allows the rate of convergence to be evaluated. Then, this condition is used for ISS analysis of switched nonlinear time-delay systems with average dwell time switching. Finally, one example is given to verify the effectiveness of theoreticalndings.
Paper VI113-07.3
PDF · Video · Quasi-Integral-Input-To-State Stability for Switched Nonlinear Systems
Russo, Antonio	Università Della Campania
Liu, Shenyu	University of California, San Diego
Liberzon, Daniel	Univ. of Illinois at Urbana-Champaign
Cavallo, Alberto	University of Campania Luigi Vanvitelli
Keywords: Stability and stabilization of hybrid systems Abstract: In this paper we introduce and give sufficient conditions for the quasi-iISS property for switched nonlinear system under dwell-time switching signals. Unlike previous works, our dwell-time bound does not rely on the knowledge of the state but it relies only on the system initial condition and the bound on the input energy. We prove, through a counterexample, that knowledge of the system initial state and bound on input energy is necessary for the estimation of a dwell-time that guarantees quasi-iISS for the switched system. An illustrative example is also included.
Paper VI113-07.4
PDF · Video · Stability of Uncertain Piecewise-Affine Systems with Parametric Dependence
Massioni, Paolo	INSA De Lyon
Bako, Laurent	Ecole Centrale De Lyon
Scorletti, Gerard	Ecole Centrale De Lyon
Keywords: Stability and stabilization of hybrid systems Abstract: This paper proposes a numerical approach to the stability analysis for a class of piecewise-affine systems with (possibly time-varying) parameter-dependent cells and dynamics. This class of model aims at allowing a better modelling of time-varying or parameter-varying nonlinearities of physical phenomena such as dry friction. We form the stability certification problem as the one of finding a Lyapunov function that is parameterised as a polynomial function of the variable parameter. The application of the well-known Lyapunov stability together with the use of the generalised S-procedure reduces the problem to checking whether a certain set of matrices has the sum-of-squares property. The latter can be solved using well-documented numerical solvers, and we provide two examples of successful applications at the end of the paper.
Paper VI113-07.5
PDF · Video · Lie-Algebraic Criterion for Stability of Switched Differential-Algebraic Equations
Harivanam, Phani	Indian Institute of Technology Bombay
Pal, Debasattam	Indian Institute of Technology Bombay
Keywords: Stability and stabilization of hybrid systems Abstract: In this paper, we prove a Lie algebraic result for stability of switched DAEs with a common descriptor matrix (common E matrix). We first show that if a switched DAE with a common descriptor matrix is asymptotically stable, then it is also globally uniformly exponentially stable. We then show that switched DAEs with common descriptor matrix and consistent block upper triangular structure is globally uniformly exponentially stable if and only if the switched DAEs corresponding to the diagonal blocks are globally uniformly exponentially stable. Finally, we show that a switched DAE with common descriptor matrix, stable and impulse free DAE subsystems, is globally uniformly exponentially stable (GUES) if there exists an invertible matrix N such that the Lie algebra generated by NE,NA_i is solvable.
Paper VI113-07.6
PDF · Video · A Semi-Global Hybrid Sensorless Observer for Permanent Magnet Synchronous Machines with Unknown Mechanical Model
Bosso, Alessandro	Alma Mater Studiorum - University of Bologna
Azzollini, Ilario Antonio	University of Bologna
Tilli, Andrea	University of Bologna
Keywords: Stability and stabilization of hybrid systems, Adaptive observer design Abstract: In this paper, we present a hybrid sensorless observer for Permanent Magnet Synchronous Machines, with no a priori knowledge of the mechanical dynamics and without the typical assumption of constant or slowly-varying speed. Instead, we impose the rotor speed to have a constant (unknown) sign and a non-zero magnitude at all times. For the design of the proposed scheme, we adopt meaningful Lie group formalism to describe the rotor position as an element of the unit circle. This choice, however, leads to a non-contractible state space, and therefore it introduces topological constraints that complicate the achievement of global/semi-global and robust results. In this respect, we show that the proposed observer, which augments a recent continuous-time solution, achieves semi-global practical asymptotic stability by periodically resetting the estimates. As highlighted in the simulation results, the novel hybrid strategy leads to improved transient performance, notably without any modification of the gains employed in the continuous-time version. These features motivate to augment the observer with a discrete-time identifier, leading to significantly faster rotor flux reconstruction.
Paper VI113-07.7
PDF · Video · Lyapunov Characterizations of Input-To-State Stability for Discrete-Time Switched Systems Via Finite-Step Lyapunov Functions
Sharifi, Maryam	Tehran University
Noroozi, Navid	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Stability and stabilization of hybrid systems, Control over networks Abstract: This paper addresses Lyapunov characterizations of input-to-state stability for nonlinear switched discrete-time systems via finite-step Lyapunov functions with respect to closed sets. The use of finite-step Lyapunov functions permits not-necessarily input-to-state stable systems in the systems family, while input-to-state stability of the resulting switched system is ensured. The result is generally presented for systems under arbitrary switching. It additionally covers the case of constrained switchings. We illustrate the effectiveness of our results by application to networked control systems with periodic scheduling policies under a priori known and dwell time-based switching mechanism.
Paper VI113-07.8
PDF · Video · Stability of Charge-Pump Phase-Locked Loops: The Hold-In and Pull-In Ranges
Kuznetsov, Nikolay	Saint-Petersburg State Univ
Matveev, Alexey S.	St.Petersburg Univ
Yuldashev, Marat	Saint Petersburg State University
Yuldashev, Renat	St. Petersburg State University
Bianchi, Giovanni	Advantest Europe GMBH
Keywords: Stability and stabilization of hybrid systems, Dynamic Networks, Nonlinear system identification Abstract: The problem of design and analysis of synchronization control circuits is a challenging task for many applications: satellite navigation, digital communication, wireless networks, and others. In this article the Charge-Pump Phase-Locked Loop (CP-PLL) electronic circuit, which is used for frequency synthesis and clock generation in computer architectures, is studied. Analysis of CP-PLL is not trivial: full mathematical model, rigorous definitions, and analysis still remain open issues in many respects. This article is devoted to development of a mathematical model, taking into account engineering aspects of the circuit, interpretation of core engineering problems, definition in relation to mathematical model, and rigorous analysis.
Paper VI113-07.9
PDF · Video · Lyapunov-Based Singular Perturbation Results in the Framework of Hybrid Systems
Wang, Xue-Fang	Dalian University of Technology
Liu, Kun-Zhi	Dalian University of Technology
Sun, Xi-Ming	Dalian University of Technology
Teel, Andrew R.	Univ. of California at Santa Barbara
Keywords: Stability and stabilization of hybrid systems, Hybrid and switched systems modeling Abstract: Stability properties of singularly perturbed hybrid systems are investigated via Lyapunov functions with assistance from the invariance principle. Both continuously differentiable Lyapunov functions and non-smooth Lyapunov functions are considered. In each case, under appropriate assumptions, uniform asymptotic stability and uniform global asymptotic stability are established. An estimate of the basin of attraction is given for the former property. Two examples are given to illustrate the proposed theoretical results based on continuously differentiable Lyapunov functions. In addition, one example for switched learning inclusions with unstable modes is given to show the effectiveness of the results obtained based on non-smooth Lyapunov functions.
Paper VI113-07.10
PDF · Video · On the Stability of Discrete-Time Linear Switched Systems in Block Companion Form
De Iuliis, Vittorio	Università Degli Studi Dell'Aquila
D'Innocenzo, Alessandro	Università Degli Studi Di L'Aquila
Germani, Alfredo	University of L'Aquila
Manes, Costanzo	Università Dell'Aquila
Keywords: Stability and stabilization of hybrid systems, Hybrid and switched systems modeling Abstract: Inspired by some insightful results on the delay-independent stability of discrete-time systems with time-varying delays, in this work we study the arbitrary switching stability for some classes of discrete-time switched systems whose dynamic matrices are in block companion form. We start from the special family of block companion matrices whose first block-row is made of permutations of nonnegative matrices, deriving a simple necessary and sufficient condition for its arbitrary switching stability. Then we relax both these assumptions, at the expense of introducing some conservatism. Some consequences on the computation of the Joint Spectral Radius for the aforementioned families of matrices are illustrated.
Paper VI113-07.11
PDF · Video · Omega-Limit Sets and Robust Stability for Switched Systems with Distinct Equilibria
Baradaran Hosseini, Matina	University of California, Santa Barbara
Teel, Andrew R.	Univ. of California at Santa Barbara
Keywords: Stability and stabilization of hybrid systems, Hybrid and switched systems modeling Abstract: This work characterizes the asymptotic behavior that results from switching among a family of asymptotically stable systems with distinct equilibria when the switching frequency satisfies an average dwell-time constraint with a small average rate. The asymptotic characterization is in terms of the omega limit set of an associated ideal hybrid system containing an average dwell-time automaton with the rate parameter set equal to zero. This set is globally asymptotically stable for the ideal system. The actual switched system, together with small disturbances, constitutes a small perturbation of this ideal system, resulting in semi-global, practical asymptotic stability.
Paper VI113-07.12
PDF · Video · Output-Feedback Stabilization for Descriptor Markovian Jump Systems with Generally Uncertain Transition Rates
Park, In Seok	Pohang University of Science and Technology
Park, Chan-eun	POSTECH
Park, PooGyeon	Pohang Univ. of Sci. & Tech
Keywords: Stability and stabilization of hybrid systems, Stochastic hybrid systems Abstract: This paper presents a dynamic output-feedback stabilization problem of descriptor Markovian jump systems with generally uncertain transition rates. First, a new necessary and sufficient condition to relax inequalities including generally uncertain transition rates is introduced. For the closed-loop systems with a dynamic output-feedback controller, the stabilization criterion is achieved as non-convex matrix inequalities. For the obtained criterion, this paper gives an improved necessary and sufficient condition in terms of linear matrix inequalities under completely known transition rates. Then, the proposed condition is extended for the descriptor Markovian jump systems with generally uncertain transition rates. To show the validity of the proposed control, a numerical example is given.
Paper VI113-07.13
PDF · Video · A Positive Real Lemma for Singular Hybrid System
Park, Chan-eun	POSTECH
Park, In Seok	Pohang University of Science and Technology
Kwon, Nam Kyu	Yeungnam University
Park, PooGyeon	Pohang Univ. of Sci. & Tech
Keywords: Stochastic hybrid systems, Stability and stabilization of hybrid systems Abstract: This paper introduces a positive real lemma for continuous-time singular hybrid systems. The necessary and sufficient condition of stochastic admissibility and strictly passivity for the singular hybrid systems is obtained in terms of linear matrix inequalities. The sufficient condition is driven by using mode-dependent Lyapunov function. In this step, two slack variables are inserted to make the proposed condition be necessary and sufficient condition in terms of strict linear matrix inequalities. Then, to prove the necessary condition, the positive real lemma for the hybrid system is proposed. Since the admissible singular system can be reformulated into stable normal system, the positive real lemma for the hybrid system holds. Thus, we give a necessary condition by constructing the solution of the proposed lemma from that of the hybrid systems.

VI113-08
Supervisory Control and Analysis of Discrete Event Systems	Regular Session
Chair: Giua, Alessandro	University of Cagliari, Italy
Co-Chair: Moor, Thomas	Friedrich-Alexander Universität Erlangen-Nürnberg
Paper VI113-08.1
PDF · Video · Controlled Microparticle Separation Using Whispering Gallery Mode Forces
Chang, Yuhe	Boston University
Svitelskiy, Oleksiy	Gorden College
Ekinci, Kamil	Boston University
Andersson, Sean	Boston University
Keywords: Discrete event modeling and simulation, Distributed control and estimation, Filtering and smoothing Abstract: There is a wide variety of applications that require sorting and separation of micro-particles from a large cluster of similar objects. Existing methods can distinguish micro-particles by their bulk properties, such as their size, density, and electric polarizability. These methods, however, are not selective with respect to the individual geometry of the particles. In this work, we focus on the use of a resonance effect between a microparticle and an evanescent light field known as the Whispering Gallery Mode (WGM) force. The WGM force is highly sensitive to the radius of the particle and is both controllable and tunable. In this paper, we explore through simulation the design of a WGM-based device for micro-particle separation. In this device, particles flow in through an inlet and are carried over two actuation regions given by waveguides carrying laser light to generate the evanescent field. Particles are observed by a camera, allowing for feedback control on the power of the lasers. While the basic control structure is simple, there are several challenges, including unknown disturbances to the fluid flow, limited laser power, and uni-directional control over each actuation region. We combine Expectation Maximization with Kalman filtering to both estimate the unknown disturbance and filter the measurements into a position estimate. We then develop simple hybrid controllers and compare them to the ideal setting (without any constraints) based on a Linear–Quadratic–Gaussian (LQG) control approach.
Paper VI113-08.2
PDF · Video · Distributed Multirobot Path Planning in Unknown Maps Using Petri Net Models
Mahulea, Cristian	University of Zaragoza
Montijano, Eduardo	Universidad De Zaragoza
Kloetzer, Marius	Technical University of Iasi
Keywords: Discrete event modeling and simulation, Petri nets, Multi-agent systems Abstract: This paper considers the path planning problem in multirobot systems with an unknown environment. The robots' mission is given as a Boolean formula on the final states. We assume that the robots have partial knowledge of the environment and they are able to estimate the environment using a recursive Bayes estimator. Furthermore, they communicate between them if they are at a distance smaller than a given threshold in order to improve their own estimation. Each robot will solve an optimization problem based on the Petri net model of the environment and it will move accordingly. We provide an algorithm to be iterated by each robot and we evaluate the results by simulation.
Paper VI113-08.3
PDF · Video · Queueing Network Realization of an Epidemiological Model for Efficient Evaluation of Computer Transmitted Infections
Wu, Neng Eva	Binghamton Univ
Montague, Joshua	State University of New York at Binghamton
Van Ornam, Drake	Binghamton University
Sarailoo, Morteza	Binghamton University
Bay, John S.	State University of New York at Binghamton
Keywords: Discrete event modeling and simulation, Queueing systems and performance model                                       , Secure networked control systems Abstract: This paper reexamines an epidemiological model with 4 population groups (vigilant/non-vigilant susceptible/infectious) built to study the effect of user vigilance on computer transmitted infections (CTIs) in computer networks. The model serves as an example through which a model conversion process is delineated, which aims at enhancing computational efficiency in the evaluation of the global prevalence of CTIs. More specifically, the conventional node-centric networked Markov chain (NCMC) is remodeled as a population-centric Markov chain (PCMC) to reduce the state-space size from an exponential to a polynomial function of the number of computing nodes N in a strongly connected network, where external attack and internal spread processes are aggregated. The PCMC is then realized as a closed queueing network of 4 M/M/N/N queueing nodes, corresponding to the 4 population groups. The results of evaluating the evolution of mean populations for the 4-population network of up to 150,000 computing nodes show that the queueing network realization slows the growth of computational complexity from exponential to linear with respect to the network size without resorting to mean field approximations. The paper briefly discusses on how the queueing network framework can accommodate node-centric Markov chains (NCMCs) of arbitrary directed networks of heterogeneous nodes, and its potential to significantly reduce the complexity in the evaluation of mean population dynamics for the more general class of large networks.
Paper VI113-08.4
PDF · Video · On Opacity Verification for Discrete-Event Systems
Masopust, Tomas	Czech Academy of Sciences and Palacky University in Olomouc
Balun, Jiří	Palacký University in Olomouc
Keywords: Discrete event modeling and simulation, Supervisory control and automata, Diagnosis of discrete event and hybrid systems Abstract: Opacity is an information flow property characterizing whether a system reveals its secret to an intruder. Verification of opacity for discrete-event systems modeled by automata is in general a hard problem. We discuss the question whether there are structural restrictions on the system models for which the opacity verification is tractable. We consider two kinds of automata models: (i) acyclic automata, and (ii) automata where all cycles are only in the form of self-loops. In some sense, these models are the simplest models of (deadlock-free) systems. Although the expressivity of such systems is weaker than the expressivity of linear temporal logic, we show that the opacity verification for these systems is still hard.
Paper VI113-08.5
PDF · Video · Communication Policies in Heterogeneous Multi-Agent Systems in Partially Known Environments under Temporal Logic Specifications
Keroglou, Christoforos	University of Michigan, Ann Arbor
Dimarogonas, Dimos V.	KTH Royal Institute of Technology
Keywords: Discrete event modeling and simulation, Supervisory control and automata, Multi-agent systems Abstract: In this paper, we explore communication protocols between two or more agents in an initially partially known environment.We assume two types of agents (A and B), where an agent of Type A constitutes an information source (e.g., a mobile sensor) with its own local objective expressed in temporal logic, and an agent of Type B constitutes an agent that accomplishes its own mission (e.g., search and rescue mission) also expressed in temporal logic. An agent of Type B requests information from an agent of Type A to update its knowledge about the environment. In this work, we develop an algorithm that is able to verify if a communication protocol exists, for any possible initial plan executed by an agent of Type B.
Paper VI113-08.6
PDF · Video · Structural Characterization of Controllability in Timed Continuous Petri Nets Using Invariant Subspaces
Arzola, César	Universidad De Zaragoza
Vazquez, Carlos Renato	ITESM Campus Guadalajara
Silva, Manuel	Universidad De Zaragoza
Ramirez-Trevino, Antonio	CINVESTAV-IPN
Keywords: Petri nets, Hybrid and switched systems modeling, Reachability analysis, verification and abstraction of hybrid systems Abstract: This work deals with the controllability analysis in Timed Continuous Petri Nets (TCPNs) under infinite server semantics, a fluid relaxation that can model highly populated Discrete Event Systems. Here, the full rank-controllability property is defined, ensuring that the TCPN is controllable over the equilibrium markings in each of the regions of its reachability space. This allows forcing the TCPN systems to work at interesting operation points such as maximum production states, safety regions, to mention a few. Herein two structural conditions for full rank-controllability, one necessary and the other sufficient, are introduced, avoiding the enumeration of all the configurations required in other approaches. Finally, based on this, a polynomial algorithm to test the full rank-controllability is provided.
Paper VI113-08.7
PDF · Video · A Monte-Carlo Tree Search Based Tracking Control Approach for Timed Petri Nets
Fritz, Raphael	University of Kaiserslautern
Krebs, Nico	University of Kaiserslautern
Zhang, Ping	Univ of Kaiserslautern
Keywords: Petri nets, Particle filtering/Monte Carlo methods Abstract: In this paper, an approach for the tracking control problem for discrete event systems modeled by timed Petri nets (TPN) is proposed. The approach applies the Monte-Carlo Tree Search to the tracking control problem for TPN to find a firing sequence from an initial marking to the desired destination marking that minimizes the required duration. The proposed tracking control method randomly searches a small part of the reachability graph and incrementally constructs a search tree to find the optimal solution. This reduces the computational effort and allows the approach to solve the tracking control problem for larger systems. The approach has capabilities for deadlock avoidance and can be applied to a wide range of control problems like reachability analysis, fault-tolerant control and scheduling problems.
Paper VI113-08.8
PDF · Video · Regulation Control in Interpreted Petri Nets under Partial Observation
Jiménez-Ochoa, Italia	CINVESTAV
Guevara-Lozano, Daniel	CINVESTAV
Vazquez, Carlos Renato	ITESM Campus Guadalajara
Ramirez-Trevino, Antonio	CINVESTAV-IPN
Keywords: Petri nets, Supervisory control and automata, Event-based control Abstract: This paper addresses the regulation control problem for discrete event systems (DES) under partial information. In this approach, the system to be controlled, named the plant, and the required behavior, named the specification, are both represented as Petri nets (PNs) with input and output symbols. The goal is to synthesize a controller that indicates input symbols to the plant in order to reach an state where the output is equal to that of the specification. To achieve this goal, the only information available to the controller is the plant output, i.e., the controller does not know the exact state of the plant. In this work, a control methodology is proposed to synthesize regulation controllers under this setting.
Paper VI113-08.9
PDF · Video · Simulation with Qualitative Models in Reduced Tensor Representations
Müller-Eping, Thorsten	Fraunhofer Institute for Solar Energy Systems - ISE
Lichtenberg, Gerwald	Hamburg University of Applied Sciences
Keywords: Quantized systems, Supervisory control and automata, Stochastic system identification Abstract: The paper proposes simulation algorithms for a new tensor representation of qualitative models based on stochastic automata. We show that storing the transition probabilities of the stochastic automaton in tensor formats will help to break the curse of dimensionality, i.e. to overcome the storage complexity problem of the automaton that occurs due to the exponential growth in the quantity of automata transitions when the number of input, state and output signals of the underlying discrete-time system is high. In addition, we present the application of a modern tensor optimization method for the completion of qualitative models identified by data-driven black-box approaches and thus suffering from the problem of unobserved sets of training data.
Paper VI113-08.10
PDF · Video · Maximal Permissiveness of Modular Supervisory Control Via Multilevel Structuring
Komenda, Jan	Academy of Sciences of Czech Republic
Masopust, Tomas	Czech Academy of Sciences and Palacky University in Olomouc
van Schuppen, Jan H.	Van Schuppen Control Research
Keywords: Supervisory control and automata Abstract: Modular supervisory control is motivated by the gain in complexity of control synthesis of supervisors. Sufficient conditions for maximal permissiveness of supervisors include mutual controllability and mutual normality. In this paper, we show how these conditions can be weakened. Namely, we can relax the requirement that the conditions hold for all pairs of components by putting the tuples of plants that do not satisfy the given condition for maximal permissiveness into different groups on an intermediate level of abstraction.
Paper VI113-08.11
PDF · Video · An Efficient Algorithm for the Computation of the Controllability Prefix of *-Languages (I)
Moor, Thomas	Friedrich-Alexander Universität Erlangen-Nürnberg
Schmidt, Klaus Werner	Middle East Technical University
Schmuck, Anne-Kathrin	Max Planck Institute for Software Systems
Keywords: Supervisory control and automata Abstract: Given a plant and a specification, both represented as formal languages, the controllability prefix is defined as the set of event sequences from which on a supervisor can control the plant according to the specification. The controllability prefix was first introduced in the context of omega-languages, where it plays a crucial role in the solution of the supervisory controller synthesis problem. In the present paper, we address the controllability prefix for *-languages. In our discussion, we (a) present a novel characterisation of the supremal controllable and relatively closed sublanguage in terms the controllability prefix; we (b) derive a fixpoint characterisation of winning states from a game theoretic interpretation of a specific state feedback synthesis problem; and (c) we establish a one-to-one correspondence between winning states and the controllability prefix. In summary, we obtain an efficient algorithm for the computation of the controllability prefix.
Paper VI113-08.12
PDF · Video · On-Line Synthesis of Permissive Supervisors for Partially Observed Discrete Event Systems under scLTL Constraints (I)
Sakakibara, Ami	Osaka University
Ushio, Toshimitsu	Osaka Univ
Keywords: Supervisory control and automata Abstract: We consider a supervisory control problem of a discrete event system (DES) under partial observation, where a control specification is given by a fragment of linear temporal logic. We design an on-line supervisor that dynamically computes its control action with the complete information of the product automaton of the DES and an acceptor for the specification. The concepts of controllability and observability are defined by means of a ranking function defined on the product automaton, which decreases its value if an accepting state of the product automaton is being approached. The proposed on-line control scheme leverages the ranking function and an energy function, which represents a time-varying permissiveness level. As a result, the on-line supervisor achieves the specification, being aware of the tradeoff between its permissiveness and acceptance of the specification, if the product automaton is controllable and observable.
Paper VI113-08.13
PDF · Video · Instant Detectability of Discrete-Event Systems
Zhang, Kuize	KTH Royal Institute of Technology
Giua, Alessandro	University of Cagliari, Italy
Keywords: Supervisory control and automata, Diagnosis of discrete event and hybrid systems Abstract: Detectability is a basic property that describes whether an observer can use the current and past values of an observed output sequence produced by a system to reconstruct its current state. We consider particular properties called instant strong detectability and instant weak detectability, where the former implies that for each possible infinite observed output sequence each prefix of the output sequence allows reconstructing the current state, the latter implies that some infinite observed output sequence (if it exists) satisfies that each of its prefixes allows reconstructing the current state. For discrete-event systems modeled by finite-state automata, we give a linear-time verification algorithm for the former in the size of an automaton, and also give a polynomial-time verification algorithm for the latter.
Paper VI113-08.14
PDF · Video · Control of Timed Discrete Event Systems with Ticked Linear Temporal Logic Constraints (I)
Kinugawa, Takuma	Osaka University
Hashimoto, Kazumune	Keio University
Ushio, Toshimitsu	Osaka Univ
Keywords: Supervisory control and automata, Discrete event modeling and simulation Abstract: This paper presents a novel method of synthesizing a controller of a timed discrete event system(TDES), introducing a novel linear temporal logic(LTL), called ticked LTLf. The ticked LTLf is given as an extension to LTLf, where the semantics is defined over a finite execution sequence. Differently from the standard LTLf, the formula is defined as a variant of metric temporal logic formula, where the temporal properties are described by counting the number of tick in the execution sequence of the TDES. Moreover, we provide a scheme that encodes the problem into a suitable one that can be solved by an integer linear programming (ILP). The effectiveness of the proposed approach is illustrated through a numerical example of a path planning.
Paper VI113-08.15
PDF · Video · A Reactive Synthesis Approach to Supervisory Control of Terminating Processes (I)
Schmuck, Anne-Kathrin	Max Planck Institute for Software Systems
Moor, Thomas	Friedrich-Alexander Universität Erlangen-Nürnberg
Schmidt, Klaus Werner	Middle East Technical University
Keywords: Supervisory control and automata, Event-based control Abstract: This paper establishes a connection between supervisory control theory (SCT) and reactive synthesis (RS) in the situation where both the plant and the specification are modeled by *-languages, i.e., formal languages over finite words. In particular, we show that the deterministic finite automaton G typically used in SCT to construct a maximally permissive supervisor f for a plant language L w.r.t. a specification language E, can be interpreted as a two-player game which allows to solve the considered synthesis problem by a two-nested fixed-point algorithm in the mu-calculus over G. The resulting game turns out to be a cooperative Büchi-type game which allows for a maximally permissive solution in the particular context of SCT. This is surprising, as classical Büchi games do not have this property.
Paper VI113-08.16
PDF · Video · Enforcing Opacity in Modular Systems
Zinck, Graeme	Mount Allison University
Ricker, Laurie	Mount Allison University
Marchand, Herve	IRISA/INRIA Rennes
Loïc, Hélouët	INRIA
Keywords: Supervisory control and automata, Multi-agent systems Abstract: In discrete-event systems, the opacity of a secret ensures that some behaviors or states cannot be inferred with certainty from partial observation of the system. Enforcing opacity in a discrete-event system, encoded by a finite labelled transition system (LTS), is a way to avoid information leakage. Checking opacity is decidable but costly (EXPTIME in the worst cases). This paper addresses opacity for modular systems in which every module, represented by an LTS, has to protect its own secret (a set of secret states) w.r.t. a local attacker. Once the system is composed, we assume a coalition between the attackers that share their local view (called the global attacker). Assuming the global attacker can observe all interactions between modules, we provide a reduced-complexity opacity verification technique and an algorithm for constructing local controllers that enforces opacity for each secret separately.

VI114
Systems and Signals - Stochastic Systems
VI114-02 Stochastic Systems, Stochastic Control and Adaptive Control, Numerical Methods, Deep Learning and Data Science   Invited Session, 12 papers
VI114-03 Stochastic Control and Game Theory   Regular Session, 8 papers
VI114-04 Stochastic Systems Estimation and Filtering   Regular Session, 22 papers
VI114-05 Stochastic System Identification   Regular Session, 5 papers

VI114-02
Stochastic Systems, Stochastic Control and Adaptive Control, Numerical Methods, Deep Learning and Data Science	Invited Session
Chair: Pasik-Duncan, Bozenna	Univ. of Kansas
Co-Chair: Baras, John S.	Univ. of Maryland
Organizer: Pasik-Duncan, Bozenna	Univ. of Kansas
Paper VI114-02.1
PDF · Video · Series Solution of Stochastic Dynamic Programming Equations (I)
Krener, Arthur J	Naval Postgraduate School
Keywords: Stochastic control and game theory Abstract: In this paper we consider discrete time stochastic optimal control problems over infinite and finite time horizons. We show that for a large class of such problems the Taylor polynomials of the solutions to the associated Dynamic Programming Equations can be computed degree by degree.
Paper VI114-02.2
PDF · Video · Filterless Least-Squares Based Adaptive Stochastic Continuous-Time Nonlinear Control (I)
Li, Wuquan	Ludong University
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Stochastic system identification, Synthesis of stochastic systems Abstract: In continuous-time system identification and adaptive control, the least-squares parameter estimation algorithm has always been used with regressor filtering, in order to avoid using time-derivatives of the measured state. Filtering adds to the dynamic order of the identifier and affects its performance. We solve the problem of filterless least-squares-based adaptive control for stochastic strict-feedback nonlinear systems with an unknown parameter in the drift term. The novel ingredient in our least-squares identification is that the update law for the parameter estimate is not a simple integrator but it also incorporates a feedthrough effect, namely, the parameter estimator is of relative degree zero (rather than one) relative to the update function. The feedthrough in the update law is a carefully designed nonlinear function, which incorporates the integration with respect to state (and not time) of the regressor function, the purpose of which is to eliminate the need for time-filtering of the regressor. Our backstepping design of the control law compensates the adverse effect of the noise (the Hessian nonlinear term, involving the diffusion nonlinearity, in the Lyapunov analysis) on the least-squares estimator. Such a controller also enables a construction of an single overall Lyapunov function, quadratic in the parameter error and quartic in the transformed state, to guarantee that the equilibrium at the origin of the closed-loop system is globally stable in probability and the states are regulated to zero almost surely.
Paper VI114-02.3
PDF · Video · Ergodic Linear-Quadratic Control for a Two Dimensional Stochastic System Driven by a Continuous Non-Gaussian Noise (I)
Duncan, Tyrone E.	Univ. of Kansas
Pasik-Duncan, Bozenna	Univ. of Kansas
Keywords: Stochastic control and game theory, Stochastic system identification, Learning for control Abstract: In this paper an infinite time horizon (ergodic) quadratic cost control problem for a linear two dimensional stochastic system with a two dimensional Rosenblatt noise process is solved by providing an explicit expression to determine the optimal feedback. The system has some symmetry properties that allow for an explicit determination of an optimal control. The controls are the family of constant linear feedbacks which is known to be the natural family of controls for a Brownian motion noise to determine optimality. This family of constant linear feedback controls allows for practical implementation of the optimal control. Rosenblatt processes are continuous, non-Gaussian processes that have a long range dependence and a useful stochastic calculus and they are generated by double Wiener-It^o integrals with singular kernels. The long range dependence property of the Rosenblatt processes is a natural generalization from an important subfamily of (Gaussian) fractional Brownian motions. Long range dependent processes have been identified empirically in a significant variety of physical phenomena. An expression is obtained to determine explicitly the optimal ergodic control. The ergodic control result in this paper seems to be the first explicit ergodic control result for a multidimensional control system with a continuous, non-Gaussian noise. Furthermore it seems to be the first solution for a multi-dimensional game problem with a Rosenblatt noise.
Paper VI114-02.4
PDF · Video · Distributed Planning in Mean-Field-Type Games (I)
Tembine, Hamidou	New York University
Keywords: Stochastic control and game theory Abstract: In this paper we study the problem of designing a collection of terminal payoff of mean-field type by interacting decision-makers to a specified terminal measure. We solve in a semi-explicit way a class of distributed planning in mean-field-type games with different objective functionals. We establish some relationships between the proposed framework, optimal transport theory, and distributed control of dynamical systems.
Paper VI114-02.5
PDF · Video · PID Control of Nonlinear Stochastic Systems with Structural Uncertainties (I)
Zhang, Jinke	Chinese Academy of Sciences
Guo, Lei	Chinese Academy of Sciences
Keywords: Stochastic adaptive control, Nonlinear adaptive control, Synthesis of stochastic systems Abstract: It is widely known that the classical PID (proportional-integral-derivative) controller still plays a dominating role in engineering control systems, and that most of the theoretical studies on PID control focus on linear deterministic systems. In this paper, we will extend the authors recent theoretical investigation by considering additional uncertainties in the input channel, and try to establish a theoretical foundation on the PID control for a class of high-dimensional nonlinear stochastic systems with structural uncertainties consisting of dynamics uncertainty, diffusion uncertainty and input channel uncertainty. We will construct a three dimensional parameter set based on the available information, so that under the classical PID control, the closed-loop control system can be globally stabilized with regulation error tending to zero in the mean square sense, as long as the three PID parameters are chosen from this set. We will further show that global stabilization and asymptotic regulation of a class of multi-agent uncertain nonlinear stochastic systems can also be achieved by uncoupled PID controllers of the agents.
Paper VI114-02.6
PDF · Video · Prescribed-Time Mean-Square Nonlinear Stochastic Stabilization (I)
Li, Wuquan	Ludong University
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Synthesis of stochastic systems, Stochastic control and game theory Abstract: We solve the prescribed-time mean-square stabilization problem, providing the first feedback solution to a stochastic null-controllability problem for strict-feedback nonlinear systems with stochastic disturbances. Our non-scaling backstepping design scheme's key novel design ingredient is that, rather than employing ``blowing up" time-varying scaling of the backstepping coordinate transformation, we introduce, instead, a damping in the backstepping target systems which grows unbounded as time approaches the terminal time. With this approach, even for deterministic systems, a simpler controller results and the control effort is reduced compared to previous designs. We achieve prescribed-time stabilization in the mean-square sense.
Paper VI114-02.7
PDF · Video · Minimal Feedback Optimal Control of Linear-Quadratic-Gaussian Systems: No Communication Is Also a Communication (I)
Maity, Dipankar	Georgia Institute of Technology
Baras, John S.	Univ. of Maryland
Keywords: Control under communication constraints, Control over networks, Stochastic control and game theory Abstract: We consider a linear-quadratic-Gaussian optimal control problem where the sensor and the controller are remotely connected over a communication channel. The communication of the measurement from the sensor to the controller requires a certain cost which is augmented with the quadratic control cost. We formulate a control and communication co-design problem where we solve for the joint optimal pair of controller and transmitter. We emphasize on the fact that absence of measurement communication at any time instance also conveys certain information to the controller, and such implicit information should be taken into account while designing a controller. We decompose the problem into two subproblems to construct the optimal controller and the optimal transmitter. While the optimal controller can be constructed by solving a certain Riccati equation, the optimal transmitter can be found solving a certain dynamic programming problem. We first characterize a sub-optimal solution for this dynamic program and then design an iterative algorithm to further improve the sub-optimal solution.
Paper VI114-02.8
PDF · Video · Conversion of Certain Stochastic Control Problems into Deterministic Control Problems (I)
McEneaney, William	Univ of California, San Diego
Dower, Peter M.	University of Melbourne
Keywords: Stochastic control and game theory Abstract: A class of nonlinear, stochastic staticization control problems (including minimization problems with smooth, convex, coercive payoffs) driven by diffusion dynamics with constant diffusion coefficient is considered. A fundamental solution form is obtained where the same solution can be used for a limited variety of terminal costs without re-solution of the problem. One may convert this fundamental solution form from a stochastic control problem form to a deterministic control problem form. This yields an equivalence between certain second-order (in space) Hamilton-Jacobi partial differential equations (HJ PDEs) and associated first-order HJ PDEs. This reformulation has substantial numerical implications.
Paper VI114-02.9
PDF · Video · Convergence of Stochastic Vector Quantization and Learning Vector Quantization with Bregman Divergences (I)
Mavridis, Christos	University of Maryland
Baras, John S.	Univ. of Maryland
Keywords: Machine learning, Bayesian methods, Stochastic system identification Abstract: Stochastic vector quantization methods have been extensively studied in supervised and unsupervised learning problems as online, data-driven, interpretable, robust, and fast to train and evaluate algorithms. Being prototype-based methods, they depend on a dissimilarity measure, which is both necessary and sufficient to belong to the family of Bregman divergences, if the mean value is used as the representative of the cluster. In this work, we investigate the convergence properties of stochastic vector quantization (VQ) and its supervised counterpart, Learning Vector Quantization (LVQ), using Bregman divergences. We employ the theory of stochastic approximation to study the conditions on the initialization and the Bregman divergence generating functions, under which, the algorithms converge to desired configurations. These results formally support the use of Bregman divergences, such as the Kullback-Leibler divergence, in vector quantization algorithms.
Paper VI114-02.10
PDF · Video · Strong Solution Existence for a Class of Degenerate Stochastic Differential Equations (I)
McEneaney, William	Univ of California, San Diego
Kaise, Hidehiro	Nagoya University
Dower, Peter M.	University of Melbourne
Zhao, Ruobing	UCSD
Keywords: Stochastic control and game theory Abstract: Existence and uniqueness results for stochastic differential equations (SDEs) under exceptionally weak conditions are well known in the case where the diffusion coefficient is nondegenerate. Here, existence of a strong solution is obtained in the case of degenerate SDEs in a class that is motivated by diffusion representations for solution of Schrodinger initial value problems. In such examples, the dimension of the range of the diffusion coefficient is exactly half that of the state. In addition to the degeneracy, two types of discontinuities and singularities in the drift are allowed, where these are motivated by the structure of the Coulomb potential. The first type consists of discontinuities that may occur on a possibly high-dimensional manifold (up to codimension one). The second consists of singularities that may occur on a lower-dimensional manifold (up to codimension two).
Paper VI114-02.11
PDF · Video · Security of Control Systems with Erroneous Observations (I)
Kim, Jaewon	Texas A&M University
Kumar, P. R.	Texas A&M University
Keywords: Secure networked control systems Abstract: We address the problem of security of stochastic control systems when observation measurements used to close the control loop may be erroneous, due to a malicious adversary who has intercepted the associated sensors or the communication network. We show how the method of dynamic watermarking can be employed to secure such a system. This is a method of defense based on stochastic considerations, relying on the inability of the attacker to separate the ambient noise present in the system from a deliberatively superimposed random watermark. We present the results of experiments against several attacks, and show the capability of this method to detect attacks in all the tested cases. The experiments are conducted on a prototypical process control system consisting of two coupled water tanks. Keywords: Security, Malicious Sensors, Cyber Physical Systems, Dynamic Watermarking.
Paper VI114-02.12
PDF · Video · Machine Learning Model to Characterize Seizure Development in Traumatic Brain Injury Patients (I)
La Rocca, Marianna	University of Southern California
Garner, Rachael	University of Southern California
Duncan, Dominique	University of Southern California
Keywords: Machine learning, Stochastic system identification, Stochastic adaptive control Abstract: Traumatic brain injury (TBI) occurs in 69 million people annually and many patients go on to develop disabling disorders such as post-traumatic epilepsy (PTE). This work focuses on data modeling and analysis for TBI patients who develop seizures. We investigated and analyzed MRI scans using voxel-based morphometry (VBM) to characterize gray level intensity differences between TBI patients who developed seizures and TBI patients who have not developed seizures. We used MRI scans from the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy, which aims to identify epileptogenic biomarkers through an international project involving multiple species, modalities, and research institutions. Using the VBM approach, statistically significant voxel changes were identified between the two clinical groups in different brain regions. Stochastic modeling and statistical analysis of the data in terms of interesting, confounding factors (age and total intracranial volume) and residual variability applied to each voxel independently, are presented. Statistical inference is used to test hypotheses that are expressed as functions of the General Linear Model estimated regression parameters. In addition, we used significant voxels to train a Neural Network (NN) classifier and evaluate the informative power of the proposed approach. The NN was able to distinguish the two clinical groups with an Area Under the receiver operating characteristics Curve of 62%.

VI114-03
Stochastic Control and Game Theory	Regular Session
Chair: Huang, Minyi	Carleton University
Co-Chair: Cetinkaya, Ahmet	National Institute of Informatics
Paper VI114-03.1
PDF · Video · Fixed Points of Set-Based Bellman Operator
Li, Sarah H.Q.	University of Washington
Adjé, Assalé	Université De Perpignan Via-Domitia
Garoche, Pierre-Loic	ONERA Toulouse
Acikmese, Behcet	University of Washington
Keywords: Stochastic control and game theory Abstract: Motivated by uncertain parameters encountered in Markov decision processes (MDPs), we study the effect of parameter uncertainty on Bellman operator-based methods. Specifically, we consider a family of MDPs where the cost parameters are from a given compact set. We then define a Bellman operator acting on an input set of value functions to produce a new set of value functions as the output under all possible variations in the cost parameters. Finally we prove the existence of a fixed point of this set-based Bellman operator by proving that it is a contractive operator on a complete metric space.
Paper VI114-03.2
PDF · Video · Mean Field Stackelberg Games: State Feedback Equilibrium
Huang, Minyi	Carleton University
Yang, Xuwei	Carleton University
Keywords: Stochastic control and game theory, Complex system management Abstract: We study mean field Stackelberg games between a major player (the leader) and a large population of minor players (the followers). By treating the mean field as part of the dynamics of the major player and a representative minor player, we Markovianize the decision problems and employ dynamic programming to determine the equilibrium strategy in a state feedback form. We show that for linear quadratic (LQ) models, the feedback equilibrium strategy is time consistent. We further give the explicit solution in a discrete-time LQ model.
Paper VI114-03.3
PDF · Video · Mean-Field Type Quantum Filter for a Quantum Ising Type System
Ohki, Kentaro	Kyoto University
Keywords: Stochastic control and game theory, Filtering and smoothing, Estimation and filtering Abstract: Mean-field games or mean-field type control problems are one of distributed control schemes that reduce the computational burden. In this paper, a quantum version of mean-field game settings is developed and the mean-field type quantum filter is derived for quantum Ising models.
Paper VI114-03.4
PDF · Video · Mixed H2/Hoo State-Feedback Control of Continuous-Time Markov Jump Systems with Partial Observations of the Markov Chain
Marcorin de Oliveira, André	UNIFESP
Costa, Oswaldo Luiz V.	Univ. of Sao Paulo
Keywords: Stochastic control and game theory, Optimal control of hybrid systems, Stochastic hybrid systems Abstract: We study the mixed H2/Hoo state-feedback control of continuous-time Markov jump linear systems considering that the Markov chain is not observable, with the only information available to the controller coming from the output of a fault-detection and isolation device. We present sufficient design conditions given in terms of linear matrix inequalities so that the closed-loop system is stable and its H2 and Hoo norms are bounded. We present an illustrative example in which we investigate the behavior of the proposed algorithm.
Paper VI114-03.5
PDF · Video · Gain-Scheduled Hinf Controller Synthesis for LPV Systems Subject to Multiplicative Noise
Levano, Elmer	Federal University of Technology -- Paraná
Oliveira, Ricardo C. L. F.	University of Campinas
Vargas, Alessandro N.	Univ. Tec. Federal Do Parana, UTFPR
Keywords: Stochastic control and game theory, Stochastic adaptive control, Adaptive gain scheduling autotuning control and switching control Abstract: This paper proposes LMI conditions to design parameter-dependent (i.e. gain-scheduled) state-feedback controllers that ensure closed-loop stability with guaranteed Hinf performance for both continuous and discrete-time LPV systems with state multiplicative noise. The state-space matrices and the multiplicative noise matrix are considered polytopic and independent. The time-varying parameters can be considered time-invariant, arbitrarily fast or with bounded rates of variation. The advantages of the proposed technique are illustrated by numerical examples borrowed from the literature.
Paper VI114-03.6
PDF · Video · Conditions of Almost Sure Boundedness and Practical Asymptotic Stability of Continuous-Time Stochastic Systems
Hoshino, Kenta	Kyoto University
Nishimura, Yuki	Kagoshima University
Keywords: Stochastic control and game theory, Synthesis of stochastic systems Abstract: This paper investigates the boundedness conditions of solutions of stochastic differential equations in the almost sure sense. Boundedness is one of the most fundamental properties in a lot of control problems. In general, it is hard to investigate almost sure boundedness of solutions of stochastic differential equations, unlike deterministic systems. However, for a class of systems, the almost sure boundedness can be investigated. This paper deals with conditions for the almost sure boundedness of stochastic systems, which is based on boundary properties of one-dimensional diffusion processes. Moreover, based on the boundedness, we show the characterization of a kind of practical asymptotic stability of one-dimensional stochastic systems in the almost sure sense. The presented results are validated through a numerical example.
Paper VI114-03.7
PDF · Video · An Impossibility Result Concerning Bounded Average-Moment Control of Linear Stochastic Systems
Cetinkaya, Ahmet	National Institute of Informatics
Kishida, Masako	National Institute of Informatics
Keywords: Stochastic control and game theory, Synthesis of stochastic systems, Control over networks Abstract: It is known that strictly unstable linear systems that are subject to nonvanishing additive stochastic noise with unbounded supports cannot be stabilized by using deterministically bounded control inputs. In this paper, we explore similar impossibility results for scenarios where the expected value of the squared control input norm is subject to constraints and the support of the noise distribution is not necessarily unbounded. Specifically, we consider the stabilization problem with control policies that have bounded time-averaged second moments. We obtain values of such average second moment bounds, below which stabilization is not possible and the second moment of the state diverges regardless of the choice of the control policy and the initial state distribution. The results are illustrated with a numerical example.
Paper VI114-03.8
PDF · Video · Stability Analysis for Linear Systems with Time-Varying and Time-Invariant Stochastic Parameters
Ito, Yuji	Toyota Central R&d Labs., Inc
Fujimoto, Kenji	Kyoto University
Keywords: Synthesis of stochastic systems, Stochastic control and game theory Abstract: This paper presents a method to guarantee stability of linear stochastic systems. The systems include both time-varying and time-invariant unknown stochastic parameters simultaneously. For analyzing the stability, such a system is represented by an expanded system that contains only the time-invariant stochastic parameter. This expansion excludes the time-varying parameter from the system, which simplifies the stability analysis. Existing methods on robust stability theory can be thus employed to ensure stability of the expanded system. Guaranteeing stability of the expanded system is a necessary and/or sufficient condition for that of the original system. Consequently, the stability of the original system is evaluated by using linear matrix inequalities.

VI114-04
Stochastic Systems Estimation and Filtering	Regular Session
Chair: King, Rudibert	Technische Universitaet Berlin
Co-Chair: Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Paper VI114-04.1
PDF · Video · A Fundamental Bound on Performance of Non-Intrusive Load Monitoring Algorithms with Application to Smart-Meter Privacy
Farokhi, Farhad	The University of Melbourne
Keywords: Estimation and filtering Abstract: We consider non-intrusive load monitoring by a sophisticated adversary that knows the load profiles of the appliances and wants to determine their start-finish times based on smart-meter readings. We prove that the expected estimation error of non-intrusive load monitoring algorithms is lower bounded by the trace of the inverse of the cross-correlation matrix between the derivatives of the load profiles of the appliances. This is an interesting observation illustrating that the derivatives of the load profiles are more important than the profiles themselves for non-intrusive load monitoring (i.e., small rapidly-changing loads are easier to identify than large, yet slowly-varying ones). This fundamental bound on the performance of non-intrusive load monitoring adversaries is used to develop privacy-preserving policies. Particularly, we devise a load-scheduling policy by maximizing the lower bound on the expected estimation error of non-intrusive load monitoring algorithms.
Paper VI114-04.2
PDF · Video · On the Resilience of a Class of Correntropy-Based State Estimators
Kircher, Alexandre	Laboratoire Ampère, Ecole Centrale De Lyon
Bako, Laurent	Ecole Centrale De Lyon
Blanco, Eric	AMPERE Laboratory
Benallouch, Mohamed	Louis Pasteur Univ
Keywords: Estimation and filtering Abstract: This paper deals with the analysis of a class of offline state estimators for LTI discrete-time systems in the presence of an arbitrary measurement noise which can potentially take any value. The considered class of estimators is defined as the solution of an optimization problem involving a performance function which can be interpreted as a generalization of cost functions used in the Maximum Correntropy Criterion. The conclusion of the analysis is that if the system is observable enough, then the considered class of estimators is resilient, which means that the obtained estimation error is independent from the highest values of the measurement noise. In the case of systems with a bounded process noise, the considered class of estimators provides a bounded estimation error under the appropriate conditions despite not being designed for this scenario.
Paper VI114-04.3
PDF · Video · Identifying Trending Coefficients with an Ensemble Kalman Filter - a Demonstration on a Force Model for Milling (I)
Schwenzer, Max	RWTH Aachen University
Visconti, Giuseppe	RWTH Aachen University
Ay, Muzaffer	RWTH Aachen University
Bergs, Thomas	RWTH Aachen University
Herty, Michael	RWTH Aachen
Abel, Dirk	RWTH-Aachen University
Keywords: Estimation and filtering Abstract: This paper extends the ensemble Kalman filter (EnKF) for inverse problems to identify trending model coefficients. This is done by repeatedly inflating the ensemble while maintaining the mean of the particles. As a benchmark serves a classic EnKF and a recursive least squares (RLS) on the example of identifying a force model in milling, which changes due to the progression of tool wear. For a proper comparison, the true values are simulated and augmented with white Gaussian noise. The results demonstrate the feasibility of the approach for dynamic identification while still achieving good accuracy in the static case. Further, the inflated EnKF shows a remarkably insensitivity on the starting set but a less smooth convergence compared to the classic EnKF.
Paper VI114-04.4
PDF · Video · Extended State Based Kalman Filter for Uncertain Systems with Bias (I)
Zhang, Xiaocheng	Academy of Mathematics and Systems Science, Chinese Academy of S
Xue, Wenchao	Chinese Academy of Sciences, Beijing 100190,
Fang, Haitao	AcademyofMathematicsandSystemsScience, ChineseAcademyofSciences
Li, Shihua	Southeast University
Yang, Jun	Southeast University
Keywords: Estimation and filtering Abstract: This paper addresses the state estimation for a class of stochastic systems with both uncertain dynamics and measurement bias. By using the idea of uncertainty/disturbance estimation, an extended state based Kalman filter algorithm is developed to estimate the original state, the uncertain dynamics and the measurement bias. Furthermore, a necessary and sufficient condition for the observability of augmented system is presented. Also, the stability of the proposed algorithm is analyzed. It is shown that the proposed filter can achieve unbiased estimation of measurement bias, such that the influence of measurement bias is eliminated. Finally, a simulation study is provided to illustrate the effectiveness of proposed method.
Paper VI114-04.5
PDF · Video · Kernel-Based Learning of Orthogonal Functions
Scampicchio, Anna	University of Padova
Pillonetto, Gianluigi	Univ of Padova
Bisiacco, Mauro	Univ of Padova
Keywords: Estimation and filtering, Bayesian methods, Particle filtering/Monte Carlo methods Abstract: The paper deals with the reconstruction of functions from sparse and noisy data in suitable intersections of Hilbert spaces that account for orthogonality constraints. Such problem is becoming more and more relevant in several areas like imaging, dictionary learning, compressed sensing. We propose a new approach where it is interpreted as a particular kernel-based multi-task learning problem, with regularization formulated in a reproducing kernel Hilbert space. Special penalty terms are then designed to induce orthogonality. We show that the problem can be given a Bayesian interpretation. This then permits to overcome nonconvexity through a novel Markov chain Monte Carlo scheme able to recover the posterior of the unknown functions and also to understand from data if the orthogonal constraints really hold.
Paper VI114-04.6
PDF · Video · State Estimation of a Benchmark Two-Tank Problem: A Carleman Linearization Approach
Bhatt, Dhruvi	Sardar Vallabhbhai National Institute of Technology
Sharma, Shambhu N.	National Institute of Technology, Surat, Gujarat
Keywords: Estimation and filtering, Continuous time system estimation Abstract: The two-tank problem is often considered as a challenging benchmark problem of process control, owing to its non-linear nature and non-minimum phase behavior. Non-linearity arises due to the dependence of non-linear outlet flow associated with the tank level. Hence, it is significant to investigate the dynamics of the system. This paper utilizes a novel idea of transforming the non-linear Stochastic Differential Equations (SDEs) to an appropriate form of the SDEs that preserves non-linear effects. In this paper, first, the Carleman linearization technique is explored to arrive at the bi-linearized two-tank SDEs. Then, we utilize the Fokker-Planck equation for the estimation of the bi-linearized two-tank problem. The theoretical results corroborated with numerical simulations highlight the effectiveness of the proposed Carleman linearization-based estimation method in contrast to the benchmark EKF-prediction method, i.e. without observation.
Paper VI114-04.7
PDF · Video · Pose Observation for Second Order Pose Kinematics
Ng, Yonhon	Australian National University
van Goor, Pieter	Australian National University
Mahony, Robert	Australian National University
Keywords: Estimation and filtering, Continuous time system estimation Abstract: This paper proposes an equivariant observer for second order pose estimation of a rigid body. The observer exploits the second order kinematic model and its symmetry group. The observer uses conventional sensors and simple computations that allow it to be run on resource-constrained devices. The observer design is based on the lifted kinematics and we prove its asymptotic convergence property. The performance of the observer is demonstrated in simulation.
Paper VI114-04.8
PDF · Video · State Estimation with Event-Based Inputs Using Stochastic Triggers
Noack, Benjamin	Karlsruhe Institute of Technology (KIT)
Funk, Christopher	Karlsruhe Institute of Technology (KIT)
Radtke, Susanne	KIT – the Research University in the Helmholtz Association
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Estimation and filtering, Distributed control and estimation, Sensor networks Abstract: Event-based communication and state estimation offer the potential to improve resource utilization in networked sensor and control systems significantly. Sensor nodes can trigger transmissions when data are deemed useful for the remote estimation units. To improve the estimation performance, the remote estimator can exploit the implicit information conveyed by the event trigger even if no transmission is triggered. The implicit information is typically incorporated into the measurement update of a remote Kalman filter. In this paper, event-triggered transmissions of input data are investigated that enter the prediction step of the remote estimator. By employing a stochastic trigger, the implicit input information remains Gaussian and can easily be incorporated into the remote Kalman filter. The proposed event-based scheme is evaluated in remote tracking scenarios, where system inputs are transmitted aperiodically.
Paper VI114-04.9
PDF · Video · Boundedness of the Kitanidis Filter for Optimal Robust State Estimation
Zhang, Qinghua	INRIA
Keywords: Estimation and filtering, Fault detection and diagnosis Abstract: The Kitanidis filter is a natural extension of the Kalman filter to systems subject to arbitrary disturbances or unknown inputs. Though the optimality of the Kitanidis filter was founded for general time varying systems more than 30 years ago, its stability analysis is still limited to time invariant systems, to the author's knowledge. In the framework of general time varying systems, this paper establishes upper bounds for the error covariance of the Kitanidis filter and for all the auxiliary variables involved in the filter.
Paper VI114-04.10
PDF · Video · A Comparative Study of Kalman-Like Filters for State Estimation of Turning Aircraft in Presence of Glint Noise
Kulikov, Gennady Yu.	Instituto Superior Tecnico, Universidade De Lisboa
Kulikova, Maria V.	Instituto Superior Técnico, Universidade De Lisboa
Keywords: Estimation and filtering, Filtering and smoothing Abstract: This paper continues the study started by Kulikov and Kulikova on state estimation accuracies of various Kalman-like filtering techniques in target tracking scenarios with non-Gaussian noise in 2018. The cited authors examined a number of methods, which are grounded in the minimum-variance or maximum-correntropy criteria and cover extended-, cubature- and unscented-type Kalman filters, in the well-known turning aircraft scenario with impulsive (shot) noise or mixed-Gaussian one. Despite the success of the maximum-correntropy-based filtering methods reported on estimation of linear discrete-time stochastic systems in literature, those case studies expose the superiority of the cubature and unscented Kalman filters towards various extended Kalman methods designed in the minimum-variance sense or grounded in the maximum-correntropy criterion within the mentioned target tracking scenarios. Here, we extend that examination to the turning aircraft scenario with glint noise, which is simulated by a sum of two zero-mean Gaussian variables with difference covariances. In particular, our study reveals a valued potential of the maximum-correntropy-based accurate continuous-discrete extended Kalman filters devised by the above authors in this glint noise state estimation environment.
Paper VI114-04.11
PDF · Video · Modified Extended Kalman Filtering for Nonlinear Stochastic Differential Algebraic Systems
Bhase, Swapnil S	Homi Bhabha National Institute, Mumbai
Bhushan, Mani	Indian Institute of Technology Bombay
Kadu, Sachin C.	Bhaba Atomic Research Centre (BARC), Mumbai
Mukhopadhyay, Sulekha	Bhabha Atomic Research Center
Keywords: Estimation and filtering, Filtering and smoothing Abstract: The extended Kalman filter (EKF) is one of the most widely used nonlinear filtering technique for a system of differential algebraic equations (DAEs). In this work we propose an alternate EKF approach for state estimation of nonlinear DAE systems that addresses shortcomings of the EKF approaches available in literature (Becerra et al., 2001; Mandela et al. 2010). The proposed approach is based on the idea that since the algebraic equations are assumed to be exact, the error covariance matrix of only the differential states needs to be directly propagated during the prediction step. The error covariance matrix for algebraic states and cross covariance matrix between the errors in differential and algebraic states, which are required to incorporate effect of prior algebraic state estimates on the update step, can be computed from the differential state error covariance matrix alone using the linearized algebraic equations. The update step of the proposed work also follows a similar philosophy and ensures that the covariance update is not approximate. The efficacy of the proposed EKF approach is evaluated using benchmark case studies of a Galvanostatic charge process and a drum boiler.
Paper VI114-04.12
PDF · Video · Hyperspherical Unscented Particle Filter for Nonlinear Orientation Estimation
Li, Kailai	Karlsruhe Institute of Technology (KIT)
Pfaff, Florian	Karlsruhe Institute of Technology
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Estimation and filtering, Filtering and smoothing Abstract: We propose a novel quaternion particle filter for nonlinear SO(3) estimation. For importance sampling, the proposal distribution is designed to incorporate newly observed evidence. For that, the unscented Kalman filtering is performed particle-wise on the tangent plane of the unit quaternion manifold via gnomonic projection/retraction based on hyperspherical geometry. As prior particles are driven towards high-likelihood regions on the manifold, computational efficiency of quaternion particle filtering is significantly improved. The resulting hyperspherical unscented particle filter (HUPF) is evaluated for nonlinear orientation estimation in simulations. Results show that it gives superior tracking performance compared with the conventional particle filter and other existing quaternion filtering schemes relying on parametric modeling.
Paper VI114-04.13
PDF · Video · The Spherical Grid Filter for Nonlinear Estimation on the Unit Sphere
Pfaff, Florian	Karlsruhe Institute of Technology (KIT)
Li, Kailai	Karlsruhe Institute of Technology (KIT)
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Estimation and filtering, Filtering and smoothing, Bayesian methods Abstract: Filters for the unit sphere have to consider its inherent periodic nature. Since the unit sphere is a domain of finite size, suitable grids covering the manifold can be provided. We explain the considerations for the grid generation and provide efficient ways to implement the prediction and update steps of a novel grid filter for this manifold. The filter supports nonlinear system and measurement models in the form of transition densities and likelihoods. In the evaluation, the proposed filter achieves a higher estimation accuracy than competing approaches.
Paper VI114-04.14
PDF · Video · The J-Orthogonal Square-Root Euler-Maruyama-Based Unscented Kalman Filter for Nonlinear Stochastic Systems
Kulikov, Gennady Yu.	Instituto Superior Tecnico, Universidade De Lisboa
Kulikova, Maria V.	Instituto Superior Técnico, Universidade De Lisboa
Keywords: Estimation and filtering, Filtering and smoothing, Continuous time system estimation Abstract: This paper addresses the issue of square-rooting in the Unscented Kalman Filtering (UKF) methods. Since their discovery the UKF is considered to be among the most valued state estimation algorithms because of its outstanding performance in numerous real-world applications. However, the main shortcoming of such a technique is the need for the Cholesky decomposition of predicted and filtering covariances derived in all time and measurement update steps. Such a factorization is time-consuming and highly sensitive to round-off and other errors committed in the course of calculation, which can result in losing the covariance's positivity and, hence, in failing the Cholesky decomposition. The latter problem is usually overcome via square-root filtering implementations, which propagate not the covariance itself but only its square root (Cholesky factor). Unfortunately, negative weights arising in applications of the UKF schemes to large stochastic systems preclude from designing conventional square-root UKF methods. So, we resolve it with a hyperbolic QR factorization used for yielding J-orthogonal square roots. Our novel square-root filter is grounded in the Euler-Maruyama discretization of order 0.5. It is justified theoretically and examined and compared numerically to the conventional (non-square-root) UKF in an aircraft's coordinated turn scenario with ill-conditioned measurements.
Paper VI114-04.15
PDF · Video · Estimation of Physical Parameters Using a New Discrete-Time Derivative Algorithm
Tebaldi, Davide	Univ. of Modena and Reggio Emilia
Morselli, Riccardo	DANA
Zanasi, Roberto	Univ of Modena and Reggio Emilia
Keywords: Estimation and filtering, Nonlinear system identification, Mechanical and aerospace estimation Abstract: The paper presents a parameters estimation procedure for physical systems modeled using the POG (Power-Oriented Graphs) technique. The coefficients defining the constitutive relation for both static and dynamic physical elements within the system can be estimated, as well as the coefficients describing energy conversions taking place either within the same energetic domain or between two different energetic domains. The evolution of the state vector over time is supposed to be known, whereas its first derivative is supposed to be unknown and is obtained by using a new algorithm for computing the discrete-time derivative of a sampled signal, which is effective even in presence of disturbances affecting the signal samples. As long as the unknown parameters appear linearly within the system differential equations, the system is allowed to exhibit any nonlinear function of the state vector and its first derivative. The procedure is finally applied to two different case studies: a linear one and a nonlinear one.
Paper VI114-04.16
PDF · Video · Optimal Transport Based Filtering with Nonlinear State Equality Constraints
Das, Niladri	Texas A&M University
Bhattacharya, Raktim	Texas A&M
Keywords: Estimation and filtering, Particle filtering/Monte Carlo methods, Filtering and smoothing Abstract: In this work we propose a framework to address the issue of state dependent nonlinear equality-constrained state estimation using Bayesian filtering. This framework is constructed specifically for a linear approximation of Bayesian filtering that uses the theory of Optimal Transport. As a part of this framework, we present three traditionally used nonlinear equality constraint-preserving algorithms coupled with the Optimal Transport based filter: the equality-constrained Optimal Transport filter, the projected Optimal Transport filter, and the measurement-augmented Optimal Transport filter. In cases where the nonlinear equality- constraints represent an arbitrary convex manifold, we show that the re-sampling step of Optimal Transport filter, can generate initial samples for filtering, from any probability distribution function defined on this manifold. We show numerical results using our proposed framework.
Paper VI114-04.17
PDF · Video · A Comparative Investigation of Information Loss Due to Variable Quantization on Parameter Estimation of Compound Distribution
Seifullaev, Ruslan	Uppsala University
Knorn, Steffi	Uppsala University
Ahlen, Anders	Uppsala University
Keywords: Estimation and filtering, Quantized systems, Control and estimation with data loss Abstract: In this paper we study the problem of how quantization may affect the maximum likelihood estimation of the parameters of a probability density function representing a compound distribution. We consider and compare three different approaches to design a variable quantizer allowing to guarantee a predefined loss of Fisher information which is used as a measure of the information loss due to quantization. We also propose the approximations which characterize the asymptotic behavior of the loss allowing a significant reduction of the computational complexity.
Paper VI114-04.18
PDF · Video · Probabilistic Bounds on Vehicle Trajectory Prediction Using Scenario Approach
Shen, Xun	Tokyo University of Agriculture and Technology
Zhang, Xingguo	Tokyo University of Agriculture and Technology
Raksincharoensak, Pongsathorn	Tokyo University of Agriculture and Technology
Keywords: Estimation and filtering, Randomized methods, Particle filtering/Monte Carlo methods Abstract: The automotive industry concerns about improving road safety. One of the major challenges is to assess road risk and react accordingly in order to avoid accidents. This requires predicting the evolution of the surrounding vehicle trajectories. However, the prediction involves uncertainties from driver operations and ground situations. It is critical to obtain the vehicle trajectory prediction with probabilistic-guarantee bounds. This contribution paper proposes a novel approach to obtain probabilistic ellipsoidal bounds for vehicle trajectory prediction. The vehicle dynamics model adopts a classical bicycle model. The uncertainty of the future trajectory is from the driver's intend and road condition which can be simplified by setting some parameters of the vehicle dynamics model as a stochastic model. Then, a stochastic optimization problem is formulated to obtain the probabilistic ellipsoidal bounds on the future vehicle trajectories. The proposed approach is validated in a numerical simulation which shows the relationship between the computation complexity and the conservatism of the probabilistic ellipsoidal bounds. The proposed method can be generally used for a physics-based motion method, maneuver-based motion method, and interaction-aware motion method by defining the probability distribution of uncertain variables differently.
Paper VI114-04.19
PDF · Video · Real-Time Estimation of Parameter Maps
Gentsch, Maik	Technische Universität Berlin
King, Rudibert	Technische Universitaet Berlin
Keywords: Estimation and filtering, Recursive identification, Adaptive observer design Abstract: System parameters might have a distinct operating point dependency that is unknown. Nonlinear state observers or Kalman Filters can be applied to estimate such parameters in real-time, revealing the unknown parameter value in the vicinity of the current operating point. Commonly, these methods are prone to forget the revealed dependence continuously when a different operating point is approached. This paper provides a procedure to preserve past estimates and reveal the hidden parameter map during operation of the system. Parameter dependencies are approximated via adjustable interpolants. In particular, ready-to-use formulae for piecewise linear and cubic Hermite interpolants are provided. An existing approach as well as a newly derived approach to embed these interpolants within an Unscented Kalman Filter are presented and discussed. While the first approach utilizes the parameter map estimation directly within the Kalman Filter scheme, the new approach expands the Kalman Filter steps by a recursive map adaption scheme and is thereby far less computationally expensive. Both methods are compared and validated via numeric simulations, where a superior performance is achieved compared to the standard parameter estimation within the Kalman Filter approach.
Paper VI114-04.20
PDF · Video · On the Stability of Kalman Filter with Random Coefficients
Gan, Die	Academy of Mathematics and Systems Science
Liu, Zhixin	Academy of Mathematics and Systems Sciences
Keywords: Estimation and filtering, Stochastic system identification Abstract: Inspired by the random packet dropout problem widely existing in the networked control systems, we investigate the stability of Kalman filter with random coefficients. We present an excitation condition about the regression vectors to establish the Lp-stability and Lp-exponential stability of random Riccati equation. Furthermore, we prove the stability of the error equations of Kalman filter under the excitation condition and some conditions on the system matrix and noises, without relying on any stationarity or independence assumptions about the regressors.
Paper VI114-04.21
PDF · Video · State Estimation in the Presence of Intermittent Actuator Faults
Strandt, Alia	Marquette University
Schneider, Susan	Marquette University
Yaz, Edwin	Marquette University
Keywords: Estimation and filtering, Stochastic system identification, Bayesian methods Abstract: The problem of intermittent, random actuator faults is important in many applications, such as in networked systems, in which there may be intermittent losses of communication between the actuators and the plant. However, state estimation of such systems is rarely addressed, with the majority of the work focusing on fault-tolerant control. In this work, the Kalman filter is modified for state estimation of systems with intermittent actuator faults when the fault rate is known. The proposed estimator is then extended to the case when the actuator fault rate is unknown using the multiple model estimation algorithm. In addition, a sketch of a proof of convergence for this technique is provided. Several simulations involving a DC motor that experiences random actuator faults demonstrate the effectiveness of the proposed techniques.
Paper VI114-04.22
PDF · Video · On the Stratonovich Approach for a Satellite Dynamics
Hirpara, Ravish H.	S.V. National Institute of Technology, Surat
Sharma, Shambhu N.	National Institute of Technology, Surat, Gujarat
Keywords: Estimation and filtering, Stochastic system identification, Nonlinear system identification Abstract: In contrast to a vector non-linear stochastic differential equation (SDE) describing the satellite dynamics under the ‘fluctuating aerodynamic torque’, this paper analyses a second-order fluctuation equation for the radial perturbation about the given orbit. The second-order fluctuation equation for the radial perturbation has found its application for the satellite orbital stability. After accomplishing a phase space formulation, we arrive at the two-dimensional SDE. Most notably, the inaccurate choice of stochastic integral describing the satellite stochastic dynamics will have influence on their estimation, stability and control. For this reason, we develop a noise equation of the satellite dynamics in the Stratonovich setting. The satellite dynamics in the Stratonovich sense can be expressed equivalently in the Itô setting by accounting additional correction terms in the system non-linearity term of the SDE. This paper develops the estimation theory of satellite dynamics via the Stratonovich calculus. The analytic findings are useful to the trajectory estimation of the orbiting satellite under the influence of atmospheric dust perturbations, where the observations are not available.

VI114-05
Stochastic System Identification	Regular Session
Chair: Ikeda, Kenji	Tokushima University
Co-Chair: Straka, Ondrej	University of West Bohemia
Paper VI114-05.1
PDF · Video · Estimation of Parameters of Gaussian Sum Distributed Noises in State-Space Models
Dunik, Jindrich	University of West Bohemia
Kost, Oliver	University of West Bohemia
Straka, Ondrej	University of West Bohemia
Keywords: Stochastic system identification, Estimation and filtering Abstract: The paper deals with the estimation of noise parameters of a linear time-varying system. In particular, the stress is laid on the state-space models, where the state and measurement noises are described by the Gaussian sum probability density functions. The recently introduced measurement difference method for the estimation of higher-order moments of the state and measurement noises is revised and, subsequently, extended for estimation of the parameters of the noise Gaussian sum densities with a special focus on the densities with two-components. The theoretical results are discussed and illustrated in a numerical example.
Paper VI114-05.2
PDF · Video · Identification of Dynamic Textures Using Dynamic Mode Decomposition
Previtali, Davide	University of Bergamo
Valceschini, Nicholas	University of Bergamo
Mazzoleni, Mirko	University of Bergamo
Previdi, Fabio	Universita' Degli Studi Di Bergamo
Keywords: Stochastic system identification, Estimation and filtering Abstract: Dynamic Textures (DTs) are image sequences of moving scenes that present stationary properties in time. In this paper, we apply Dynamic Mode Decomposition (DMD) and Dynamic Mode Decomposition with Control (DMDc) to identify a parametric model of dynamic textures. The identification results are compared with a benchmark method from the dynamic texture literature, both from a mathematical and from a computational complexity point of view. Extensive simulations are carried out to assess the performance of the proposed algorithms with regards to synthesis and denoising purposes, with different types of dynamic textures. Results show that DMD and DMDc present lower error, lower residual noise and lower variance compared to the benchmark approach.
Paper VI114-05.3
PDF · Video · Subspace Identification Algorithm for Stochastic Systems Equipped with Zeros Close to Unit Circle
Tanaka, Hideyuki	Hiroshima University
Ikeda, Kenji	Tokushima University
Keywords: Stochastic system identification, Realization theory, Subspace methods Abstract: In identifying a stochastic system possessing zeros close to the unit circle, the effect of the initial state appears in the estimates. This paper derives a stochastic subspace identification algorithm for such a system. A new stochastic realization algorithm is developed based on the covariance matrices of the state and the white-noise input, by taking the initial state and positive realness into account. A subspace identification algorithm is obtained by applying the realization algorithm to a finite string of data. Numerical simulation results show that the proposed algorithm provides favorable results compared with the conventional ones.
Paper VI114-05.4
PDF · Video · A Computation Approach to Chance Constrained Optimization of Boundary-Value Parabolic Partial Differential Equation Systems
Nida, Kibru Teka	Technical University of Ilmenau
Geletu, Abebe	Ilmenau University of Technology
Li, Pu	Technische Universität Ilmenau
Keywords: Stochastic system identification, Synthesis of stochastic systems, Distributed control and estimation Abstract: This work studies chance constrained optimization of boundary-value parabolic partial differential equations (CCPDE) with random data, where the PDE model is treated as equality constraint and chance constraints are imposed on inequality constraints involving state variables. Since such a CCPDE problem is generally non-smooth, non-convex and difficult to solve directly, we use our recently proposed smoothing approximation method to solve the problem. As a result, the probability function of the chance constraints is approximated in two different ways by a family of differentiable functions. This leads to two smooth parametric optimization problems IA_tau and OA_tau, where the feasible sets of IA_tau are always subsets (inner approximation) and the feasible sets of OA_tau always supersets (outer approximation). The feasible sets of IA_tau (resp. OA_tau) converge asymptotically to the feasible set of the CCPDE. Moreover, any limit point of a sequence of optimal solutions of IA_tau (resp. OA_tau) is a stationary point of CCPDE. The viability of the approximation approach is numerically demonstrated by optimal thermal cancer treatment as a case study.
Paper VI114-05.5
PDF · Video · Synthesis of Stochastic Systems with Partial Information Via Control Barrier Functions
Jahanshahi, Niloofar	Ludwig Maximilian University of Munich
Jagtap, Pushpak	Technical University of Munich, Munich, Germany
Zamani, Majid	University of Colorado Boulder
Keywords: Synthesis of stochastic systems, Identification for control, Continuous time system estimation Abstract: Synthesis of controllers for stochastic control systems ensuring safety constraints has gained considerable attention in the last few years. In this paper, we consider the problem of synthesizing controllers for partially observed stochastic control systems to ensure finite-time safety. Given an estimator with a probabilistic guarantee on the accuracy of the estimations, we provide an approach to compute a controller providing a lower bound on the probability that the trajectories of the stochastic control system remain safe over a finite time-horizon. To obtain such controllers, we utilize a notion of control barrier functions. We also provide an approach to compute a probability bound on estimator accuracy by using a notion of so-called stochastic simulation function. The proposed result is illustrated on a case study.

VI115
Systems and Signals - Networked Systems
VI115-01 Cooperative Control of Unmanned Aerial Vehicles: Reliability and Autonomy   Invited Session, 9 papers
VI115-02 Resilience Analysis, Security Countermeasures and Privacy Protection in Distributed State Estimation   Invited Session, 4 papers
VI115-03 Resilient and Networked Control of Complex Cyber-Physical Systems   Invited Session, 6 papers
VI115-04 Resilient Large-Scale Networks: Spreading and Bifurcation   Invited Session, 6 papers
VI115-05 Control for Next Generation Wireless Networks   Open Invited Session, 9 papers
VI115-06 Distributed Optimization for Learning and Control in Smart Networks   Open Invited Session, 10 papers
VI115-07 Event-Triggered and Self-Triggered Control   Open Invited Session, 19 papers
VI115-08 Social Systems: Dynamics, Games and Control on Networks   Open Invited Session, 13 papers
VI115-09 Consensus   Regular Session, 30 papers
VI115-10 Control under Communication Constraints   Regular Session, 9 papers
VI115-11 Coordination of Multiple Vehicle Systems   Regular Session, 9 papers
VI115-12 Distributed Control and Estimation   Regular Session, 14 papers
VI115-13 Distributed Optimization for Large-Scale Systems   Regular Session, 9 papers
VI115-14 Multi-Agent Systems   Regular Session, 28 papers
VI115-15 Security of Networked Control Systems   Regular Session, 12 papers
VI115-16 Sensor Networks   Regular Session, 7 papers

VI115-01
Cooperative Control of Unmanned Aerial Vehicles: Reliability and Autonomy	Invited Session
Chair: Wang, Xiangke	National University of Defense Technology
Co-Chair: Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Organizer: Wang, Xiangke	National University of Defense Technology
Organizer: Liu, Hao	Beihang University
Organizer: Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Paper VI115-01.1
PDF · Video · Angle-Based Formation Shape Control with Velocity Alignment (I)
Chen, Liangming	University of Groningen
Cao, Ming	University of Groningen
Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Anderson, Brian D. O.	Australian National Univ/NICTA
Li, Chuanjiang	Harbin Institute of Technology
Keywords: Networked robotic systems, Coordination of multiple vehicle systems, Multi-agent systems Abstract: With the rapid development of sensor technology, bearing/angle measurements are becoming cheaper and more reliable, which motivates the study of angle-based formation shape control. This work studies how to achieve angle-based formation control and velocity alignment at the same time, in which all agents can form a desired angle-rigid formation and translate with the same velocity simultaneously. The agents' communication topology for the achievement of velocity alignment is described by a connected graph, while the formation shape is determined by a set of angles that are associated with triangles within the formation and computed using bearing measurements. A simulation example validates the effectiveness of the theoretical results.
Paper VI115-01.2
PDF · Video · Distributed Finite-Time Coordination Control for Networked Euler-Lagrange Systems under Directed Graphs (I)
Xu, Tao	Peking University
Lv, Yuezu	Southeast University
Duan, Zhisheng	Peking University
Keywords: Multi-agent systems, Consensus Abstract: The distributed coordination problems for networked Euler-Lagrange systems are investigated in this paper, where both the distributed synchronization control and the distributed containment control are considered. Compared with the existing traditional asymptotically stable control laws, the desired cooperative control objectives of this paper can be realized in finite time, and the estimate of the settling times are explicitly provided. Another distinct feature of our work is that the communication interactions between neighboring agents are unidirectional, which is more practical in real applications. Finally, some simulation results are shown to validate the feasibility of the theoretical schemes.
Paper VI115-01.3
PDF · Video · Dynamics of Generic Linear Agents Over Signed Networks without Structural Constraints (I)
Shi, Lei	University of Electronic Science and Technology of China
Chen, Hongjian	University of Electronic Science and Technology of China
Cheng, Yuhua	University of Electronic Science and Technology of China
Zheng, Wei Xing	Western Sydney University
Shao, Jinliang	University of Electronic Science and Technology of China
Keywords: Consensus, Multi-agent systems, Control of networks Abstract: Signed networks have been widely used to describe cooperative and competitive interactions in multiagent systems (MASs) so far. Most of the existing dynamics results of MASs on signed networks have a certain constraint on the network topology, that is, the network topology is required to have sufficient connectivity for realizing consensus or bipartite consensus. The highlight of this article is to extend the existing dynamics of MASs to a more general signed network, in which there are no any structural constraints on the topology. This general setting of the network topology unifies most existing models, such as consensus, bipartite consensus, and bipartite containment, which are usually analyzed separately in the same framework using different methods. Relying on a method of constructing cooperative auxiliary digraphs, it is theoretically proved that the agents in closed strong connected components with balanced structure and unbalanced structure gradually reach separately bipartite consensus and consensus, and the agents outside the closed strong connected components gradually enter the convex hull formed by the agents in the closed strong connected components, that is, achieving bipartite containment. Finally, a computer simulation is presented to verify the theoretical discovery.
Paper VI115-01.4
PDF · Video · Fault-Tolerant Control for the Formation of Multiple Unknown Nonlinear Quadrotors Via Reinforcement Learning (I)
Zhao, Wanbing	Beihang University
Liu, Hao	Beihang University
Lewis, Frank L.	Univ of Texas at Arlington
Keywords: Networked robotic systems, Consensus and Reinforcement learning control, Multi-agent systems Abstract: In this paper, the fault-tolerant control problem for the formation of unknown quadrotor team with nonlinearities, couplings, and actuator faults in the dynamics is investigated. A distributed observer is designed to estimate the position references for each quadrotor. A hierarchical control scheme is constructed including a fault-tolerant position controller to achieve the desired formation and a fault-tolerant attitude controller to track the attitude references. Reinforcement learning algorithms are designed to learn the optimal control policies of the position and attitude controllers. Simulation results are given to illustrate the effectiveness of the proposed controller.
Paper VI115-01.5
PDF · Video · Optimal UAV Circumnavigation Control with Input Saturation Based on Information Geometry (I)
Yu, Yangguang	National University of Defense Technology
Wang, Xiangke	National University of Defense Technology
Shen, Lincheng	National University of Defense Technology
Keywords: Extremum seeking and model free adaptive control, Nonlinear adaptive control, Dynamic Networks Abstract: In this paper, we investigate the problem of the optimal circumnavigation around a ground moving target for a fixed-wing unmanned aerial vehicle equipped with a radar. We propose an optimal circumnavigation control law which not only achieves the circumnavigation of a UAV around a moving target, but also maximizes the utilization of the sensor information. Firstly, an optimization criterion re ecting the extent of the sensor information utilization is established based on the Fisher information. Then, based on a neural network, an optimal circumnavigation control law with input saturation is designed. The result is a nearly optimal state feedback controller that has been tuned a priori off-line. Finally, a simulation is presented to demonstrate the validity and correctness of the proposed method.
Paper VI115-01.6
PDF · Video · A Hierarchical Collision Avoidance Architecture for Multiple Fixed-Wing UAVs in an Integrated Airspace (I)
Wang, Yajing	National University of Defense Technology
Wang, Xiangke	National University of Defense Technology
Zhao, Shulong	National University of Defense Technology
Shen, Lincheng	National University of Defense Technology
Keywords: Coordination of multiple vehicle systems, Multi-agent systems Abstract: This paper studies the collision avoidance problem for autonomous multiple fixed-wing UAVs in the complex integrated airspace. By studying and combining the online path planning method, the distributed model predictive control algorithm, and the geometric reactive control approach, a three-layered collision avoidance system integrating conflict detection and resolution procedures is developed for multiple fixed-wing UAVs modeled by unicycle kinematics subject to input constraints. The effectiveness of the proposed methodology is evaluated and validated via test results of comparative simulations under both deterministic and probabilistic sensing conditions.
Paper VI115-01.7
PDF · Video · Consensus for Expressed and Private Opinions under Self-Persuasion (I)
Cheng, Chun	Fudan University
Luo, Yun	Wuhan University
Yu, Changbin (Brad)	Australian National University
Keywords: Multi-agent systems, Dynamic Networks, Consensus Abstract: As recognized in psychological research, there is often a difference between an agent’s expressed opinion and private opinion (or belief). This occurs for different reasons, such as political correctness or peer pressure. The opinion expressed by an agent is the result of pressure to follow the (average) opinions expressed by the group to which the agent belongs, or to follow group norms. The agent’s private opinion is unknown to others, but evolved under the influence of other agents’ expressed opinions. This paper proposes an opinion formation model based on the theory of bounded confidence, and studies the dynamic process of expressed and private opinions in time-varying networks. At the same time, the self-persuasion effect of agents in the dissonance between expressed and private opinions is considered. Here, group pressure establishes the motive force from private opinion to expressed opinion, while self-persuasion establishes the reverse connection. We find that group pressure can effectively reduce the gap of opinions between the group, but does not always promote consensus. Furthermore, the self-persuasion effect of agents can ensure the realization of group consensus.
Paper VI115-01.8
PDF · Video · Coordination Control of Double-Integrator Systems with Time-Varying Weighted Inputs (I)
Greiff, Carl Marcus	Lund University
Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Robertsson, Anders	LTH, Lund University
Keywords: Distributed control and estimation, Coordination of multiple vehicle systems, Networked embedded control systems Abstract: This paper considers coordination control of double-integrator systems and proposes general control laws involving time-varying inputs. The nominal control input is weighted by time-varying (time-dependent or state-dependent) positive definite matrices, providing more freedoms in defining the control tasks. We present sufficient conditions to ensure the asymptotic convergence of double-integrator networked systems in this context, and support the theoretical results by several application examples. This includes distance-based multi-agent formation control and power network systems with unknown inertia matrices.
Paper VI115-01.9
PDF · Video · Finite-Time Distributed Convex Optimization with Zero-Gradient-Sum Algorithms (I)
Wu, Zizhen	Peking University
Li, Zhongkui	Peking University
Keywords: Consensus, Multi-agent systems, Distributed control and estimation Abstract: This article considers the distributed finite-time optimization problem of multi-agent systems within the Zero-Gradient-Sum (ZGS) framework. We employ a distributed algorithm to drive the estimate of each agent to converge to the optimal solution of the global objective function, the sum of the local objectives. In a general case with non-quadratic local functions, we can obtain a finite-time convergence. Furthermore, when all the local cost functions are quadratic, the proposed algorithm can achieve a fixed-time result such that the upper bound of settling time can be estimated regardless of the initial conditions. Considering that the communication network may be affected by some external disturbances, we also extend to consider the case with switching topologies. Finally, the algorithms are demonstrated via an example simulation.

VI115-02
Resilience Analysis, Security Countermeasures and Privacy Protection in Distributed State Estimation	Invited Session
Chair: Yang, Wen	East China University of Science and Techonology
Co-Chair: Zhang, Heng	Huaihai Institute of Technology
Organizer: Yang, Wen	East China University of Science and Techonology
Organizer: Tang, Yang	East China University of Science and Technology
Organizer: Zhang, Heng	Huaihai Institute of Technology
Organizer: Zheng, Minghui	University at Buffalo
Paper VI115-02.1
PDF · Video · Reinforcement Learning Based Anti-Jamming Schedule in Cyber Physical Systems (I)
Gan, Ruimeng	University of Electronic Science and Technology of China
Xiao, Yue	National Key Laboratory of Science and Technology on Communicati
Shao, Jinliang	University of Electronic Science and Technology of China
Zhang, Heng	Huaihai Institute of Technology
Zheng, Wei Xing	Western Sydney University
Keywords: Secure networked control systems, Control and estimation with data loss Abstract: In this paper, the security issue of cyber-physical systems is investigated, where the observation data is transmitted from a sensor to an estimator through wireless channels disturbed by an attacker. The failure of this data transmission occurs, when the sensor accesses the channel that happens to be attacked by the jammer. Since the system performance measured by the estimation error depends on whether the data transmission is a success, the problem of selecting the channel to alleviate the attack eect is studied. Moreover, the state of each channel is time-variant due to various factors, such as path loss and shadowing. Motivated by energy conservation, the problem of selecting the channel with the best state is also considered. With the help of cognitive radio technique, the sensor has the ability of selecting a sequence of channels dynamically. Based on this, the problem of selecting the channel is resolved by means of reinforcement learning to jointly avoid the attack and enjoy the channel with the best state. A corresponding algorithm is presented to obtain the sequence of channels for the sensor, and its eectiveness is proved analytically. Numerical simulations further verify the derived results.
Paper VI115-02.2
PDF · Video · A "Safe Kernel" Approach for Resilient Multi-Dimensional Consensus (I)
Yan, Jiaqi	Nanyang Technological University, Singapore
Mo, Yilin	Tsinghua University
Li, Xiuxian	Nanyang Technological University
Wen, Changyun	Nanyang Technological University
Keywords: Consensus, Secure networked control systems Abstract: This paper considers the resilient multi-dimensional consensus problem in networked systems, where some of the agents might be malicious (or faulty). We propose a multi-dimensional consensus algorithm, where at each time step each healthy agent computes a "safe kernel" based on the information from its neighbors, and modifies its own state towards a point inside the kernel. Assuming that the number of malicious agents is locally (or globally) upper bounded, sufficient conditions on the network topology are presented to guarantee that the benign agents exponentially reach an agreement within the convex hull of their initial states, regardless of the actions of the misbehaving ones. It is also revealed that the graph connectivity and robustness required to achieve the resilient consensus increases linearly with respect to the dimension of the agents’ state, indicating the existence of a trade-off between the low communication cost and system security. Numerical examples are provided in the end to validate the theoretical results.
Paper VI115-02.3
PDF · Video · Intrusion Detection of Industrial Control System Based on Double-Layer One-Class Support Vector Machine (I)
Zhang, Wen-An	Zhejiang University of Technology
Miao, Yinfeng	ZJUT
Wu, Qi	College of Information Engineering, Zhejiang University of Techn
Yu, Li	Zhejiang Univ of Technology
Shi, Xiufang	Zhejiang University of Technology
Keywords: Secure networked control systems Abstract: In this paper, the stealthy attack detection in industrial control system (ICS) is studied, and a new detection method is proposed from the perspective of signal analysis. The method consists of a double-layer one-class support vector machine model (DL-OCSVM), where the first-layer model is the standard OCSVM, and the second-layer model is obtained by incremental learning based on the former. The wavelet decomposition is used to extract the physical characteristics of the ICS. The KKT condition and the adjacent classification interval are adopted to reduce the training samples, improving the learning rate and system scalability. In addition, the designed boundary samples are employed for incremental learning, avoiding overfitting and reducing false positives rate (FPR). The experimental results show that the proposed method has high detection rate and low FPR for stealthy attacks, and is more suitable for precision machining process.
Paper VI115-02.4
PDF · Video · Optimal Online Transmission Schedule for Remote State Estimation Over a Hidden Markovian Channel (I)
Sun, Bowen	Southeast University
Cao, Xianghui	Southeast University
Wang, Le	Southeast University
Sun, Changyin	Southeast University
Keywords: Control and estimation with data loss, Estimation and filtering Abstract: This paper investigates the optimal transmission scheduling problem in remote state estimation systems over an unreliable wireless channel where the channel state evolves as a Markov chain. However, due to inaccurate observations of the channel state, the wireless channel is modeled as a hidden Markov chain. We propose a prediction algorithm based on the Viterbi algorithm to estimate the channel state. To save the wireless sensor's energy, we consider scheduling the transmission of sensor transmissions while balancing between estimation performance and sensor energy expenditure. By jointly considering performance and energy, we formulate the scheduling problem as a Markov decision process. We prove the existence of the optimal transmission policy and derive a threshold structure of the optimal strategy. Finally, the performance of the proposed method is evaluated through simulations.

VI115-03
Resilient and Networked Control of Complex Cyber-Physical Systems	Invited Session
Chair: Zhao, Yu	Northwestern Polytechnical University
Co-Chair: Liu, Hao	Beihang University
Organizer: Wang, Bohui	Nanyang Technological University
Organizer: Zhao, Yu	Northwestern Polytechnical University
Organizer: Shen, Chao	Xi'an Jiaotong University
Organizer: Liu, Hao	Beihang University
Organizer: Zhang, Dong	Northwestern Polytechnical University
Organizer: Liang, Xiaoling	Dalian Maritime University
Organizer: Zhang, Bin	University of South Carolina
Organizer: Zhang, Langwen	South China University of Technology
Paper VI115-03.1
PDF · Video · Control Lyapunov Function Based Finite-Horizon Optimal Control for Repointing of a Spacecraft (I)
Geng, Yuanzhuo	Harbin Institute of Technology
Li, Chuanjiang	Harbin Institute of Technology
Guo, Yanning	Harbin Institute of Technology
Biggs, James Douglas	Politecnico Di Milano
Keywords: Nonlinear adaptive control, Adaptive gain scheduling autotuning control and switching control, Optimal control of hybrid systems Abstract: This paper addresses the problem of optimally repointing the optical axis of a spacecraft to align with the target direction. A new metric defining the repointing error is proposed where the corresponding kinematic equations provide a simple and convenient form for control design. The proposed control integrates a Control Lyapunov Function (CLF) approach with a sliding mode controller which simultaneously guarantees the optimality and robustness of the closed-loop system. Firstly, a CLF based control scheme is used to ensure that the state optimally converges to the sliding surface. Then a fixed-time non-singular terminal sliding mode controller is employed to provide robust convergence to the origin along the sliding surface. The convergence time is finite for any initial states and is thus useful for applications with critical time constraints. The region of attraction and convergence time is analyzed. Finally, numerical investigations are conducted to verify the effectiveness and superiority of the proposed algorithm with respect to the classical CLF method.
Paper VI115-03.2
PDF · Video · Moving Area Tracking Formation Control of Multiple Autonomous Agents (I)
Zhang, Wenfei	Northwestern Polytechnical University
Zhao, Yu	Northwestern Polytechnical University
Keywords: Multi-agent systems Abstract: This paper investigates a moving area tracking formation control (MATFC) problem of multiple autonomous agents, which aims at driving a group of agents to achieve a desired formation configuration and track a moving area. By using local information interaction among agents, a distributed MATFC protocol is proposed for single integrator dynamics. Without requiring the center of the sub-area is bounded, the MATFC problem obtains greater application potential. During the moving process, the formation size can be regulated in real time to adapt the complicated environment through a scaling parameter. By adding a rotation matrix, the spatial orientation of each agent is capable of transforming in different cases. Then, based on the Lyapunov stability theory, it is verified that the objective of MATFC problem can be achieved under the proposed control protocol. Finally, numerical simulation results are shown to further demonstrate the effectiveness of the designed MATFC protocol.
Paper VI115-03.3
PDF · Video · A Probabilistic Time-Constrained Based Heuristic Path Planning Algorithm in Warehouse Multi-AGV Systems (I)
Lian, Yindong	South China University of Technology
Xie, Wei	South China University of Technology
Zhang, Langwen	South China University of Technology
Keywords: Coordination of multiple vehicle systems, Multi-agent systems, Networked robotic systems Abstract: This paper mainly focuses on the path planning algorithm of multi-AGV system in the warehouse environment. We first analyze and model the path network of multiple AGVs based on dynamic stochastic network theory. Then, a probabilistic time constraint is added in the process of the well-known A* heuristic algorithm, and the solution of the time cost is proposed based on probability theory. Furthermore, a multi-AGV conflict avoidance strategy suitable for heuristic planning algorithms is achieved in combination with queuing mechanism. Finally, numerical simulation experiments of the warehouse multi-AGV system are realized and demonstrate the effectiveness of the proposed algorithm.
Paper VI115-03.4
PDF · Video · Distributed Fault Detection of Nonlinear Process Systems with Senor Failures (I)
Zhang, Langwen	South China University of Technology
Xie, Wei	South China University of Technology
Lian, Yindong	South China University of Technology
Keywords: Distributed control and estimation, Fault detection and diagnosis, Filtering and smoothing Abstract: A distributed fault detection scheme is presented in this work to deal with the senor failures in a nonlinear process system. Firstly, a residual generator is derived, in which the fault signal is generated by introducing a residual signal. Then, a distributed extended Kalman Filter (EKF) is designed to estimate the unmeasurable system states. Finally, the proposed distributed EKF is used for the fault detection and isolation in a distributed framework. By applying the distributed fault detection scheme to a completely stirred tank reactor process, it is shown that the proposed scheme has ability to monitor the sensor faults automatically.
Paper VI115-03.5
PDF · Video · Distributed Event-Triggered Consensus of Multi-Agent Systems with Input Delay (I)
Li, Yunhan	Beijing Institute of Technology
Zhang, Pengyu	China Aerospace Science and Technology Corporation
Wang, Chunyan	Beijing Institute of Technology
Wang, Dandan	Beijing Institute of Technology
Wang, Jianan	Beijing Institute of Technology
Keywords: Event-based control, Multi-agent systems, Distributed control and estimation Abstract: This paper investigates distributed event-triggered consensus control for multi-agent systems with input delay. To deal with input delay, the original system is converted to a delay-free system via Artstein-Kwon-Pearson reduction transformation method. Distributed event-triggered protocols are designed to alleviate the communication burden of the agents. The system convergence is validated by using Lyapunov stability analysis and solving linear matrix inequality function. Furthermore, it is proved that the system does not display Zeno behavior under the proposed event-triggering function, and thus, consistent triggering is excluded from the system. A simulation example is given to demonstrate the effectiveness of the control algorithm.
Paper VI115-03.6
PDF · Video · False Data Injection Attacks for Networked Control Systems with Sensor Fault and Actuator Saturation (I)
Geng, Qing	Yanshan University
Liu, Fucai	Yanshan University
Li, Yafeng	Yanshan University
Keywords: Control of networks, Dynamic Networks Abstract: This paper presents the design problem of false data injection (FDI) attacks against the networked predictive control (NPC) strategy, where the sensor fault and actuator saturation are considered. An estimator is designed to estimate system states and sensor fault simultaneously. A predictive controller which can generate a sequence of predictive signals is designed to actively compensate the time-varying delays for the networked control system (NCS). A sufficient condition is derived for stability of the NCS by a switched system theory. Finally, a numerical simulation demonstrates the effectiveness of proposed method for the NCS.

VI115-04
Resilient Large-Scale Networks: Spreading and Bifurcation	Invited Session
Chair: Pare, Philip E.	KTH Royal Institute of Technology
Co-Chair: Johansson, Karl H.	Royal Institute of Technology
Organizer: Pare, Philip E.	KTH Royal Institute of Technology
Organizer: Gracy, Sebin	Royal Institute of Technology, KTH
Organizer: Sandberg, Henrik	KTH Royal Institute of Technology
Organizer: Johansson, Karl H.	Royal Institute of Technology
Paper VI115-04.1
PDF · Video · The Solution of the NIMFA Epidemic Model Around the Epidemic Threshold (I)
Prasse, Bastian	Delft University of Technology
Piet, Van Mieghem	Delft University of Technology
Keywords: Control of networks Abstract: Non-linear differential equations are a common approach to modelling the spread of infectious diseases. Unfortunately, a closed-form solution is not known for the majority of epidemic models, which restricts an in-depth understanding of the evolution of the virus. In this work, we solve the differential equations of the NIMFA epidemic model around the epidemic threshold, provided that the initial viral state is small or proportional to the steady-state. The solution of the NIMFA model around the epidemic threshold is of particular importance for disease control measures that aim to eradicate the infectious disease.
Paper VI115-04.2
PDF · Video · A Network SIS Meta-Population Model with Transportation Flow (I)
Ye, Mengbin	Curtin University
Liu, Ji	Stony Brook University
Cenedese, Carlo	University of Groningen
Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Cao, Ming	University of Groningen
Keywords: Multi-agent systems, Control over networks, Complex system management Abstract: This paper considers a deterministic Susceptible-Infected-Susceptible (SIS) meta-population model for the spread of a disease in a strongly connected network, where each node represents a large population. Individuals can travel between the nodes (populations). We derive a necessary and sufficient condition for the healthy equilibrium to be the unique equilibrium of the system, and then in fact it is asymptotically stable for all initial conditions (a sufficient condition for exponential stability is also given). If the condition is not satisfied, then there additionally exists a unique endemic equilibrium which is exponentially stable for all nonzero initial conditions. We then consider time-delay in the travel between nodes, and further investigate the role of the mobility rate that governs the flow of individuals between nodes in determining the convergence properties. We find that sometimes, increasing mobility helps the system converge to the healthy equilibrium.
Paper VI115-04.3
PDF · Video · Disagreement and Polarization in Two-Party Social Networks (I)
Yi, Yuhao	Rensselaer Polytechnic Institute
Patterson, Stacy	Rensselaer Polytechnic Institute
Keywords: Consensus, Control of networks, Multi-agent systems Abstract: We investigate disagreement and polarization in a social network with two polarizing sources of information. First, we define disagreement and polarization indices in two-party leader-follower models of opinion dynamics. We then give expressions for the indices in terms of a graph Laplacian. The expressions show a relationship between these quantities and the concepts of resistance distance and biharmonic distance. We next study the problem of designing the network so as to minimize disagreement and polarization. We give conditions for optimal disagreement and polarization, and further, we show that a linear combination of disagreement and polarization of the follower nodes is a convex function of the edge weights between followers. We propose algorithms to address some related continuous and discrete optimization problems and also present analytic results for some interesting examples.
Paper VI115-04.4
PDF · Video · On the Stability of the Endemic Equilibrium of a Discrete-Time Networked Epidemic Model (I)
Liu, Fangzhou	Technical University of Munich
Cui, Shaoxuan	Technical University of Munich
Li, Xianwei	Nanyang Technological University
Buss, Martin	Technische Universitaet Muenchen
Keywords: Control over networks Abstract: Networked epidemic models have been widely adopted to describe propagation phenomena. The endemic equilibrium of these models is of great significance in the field of viral marketing, innovation dissemination, and information diffusion. However, its stability conditions have not been fully explored. In this paper, we study the stability of the endemic equilibrium of a networked Susceptible-Infected-Susceptible (SIS) epidemic model with heterogeneous transition rates in a discrete-time manner. We show that the endemic equilibrium, if it exists, is asymptotically stable for any nontrivial initial condition. Under mild assumptions on initial conditions, we further prove that during the spreading process there exists no overshoot with respect to the endemic equilibrium. Finally, we conduct numerical experiments on real-world networks to illustrate our results.
Paper VI115-04.5
PDF · Video · On a Network SIS Model with Opinion Dynamics (I)
Xuan, Weihao	University of Leeds
Ren, Ruijie	University of Leeds
Pare, Philip E.	KTH Royal Institute of Technology
Ye, Mengbin	Curtin University
Ruf, Sebastian	Northeastern University
Liu, Ji	Stony Brook University
Keywords: Multi-agent systems, Dynamic Networks, Consensus Abstract: This paper proposes a network continuous-time susceptible-infected-susceptible (SIS) model coupled with individual opinion dynamics, where the opinion dynamic models an individual's perceived severity of illness or perceived susceptibility. The effects of opinion dynamics on the network SIS model are studied by analyzing the limiting behaviors of the model, equilibria of the system and their stability.
Paper VI115-04.6
PDF · Video · Stability and Phase Transitions of Dynamical Flow Networks with Finite Capacities (I)
Leonardo, Massai	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Control over networks, Multi-agent systems, Dynamic Networks Abstract: We study deterministic continuous-time lossy dynamical flow networks with constant exogenous demands, fixed routing, and finite flow and buffer capacities. In the considered model, when the total net flow in a cell —consisting of the difference between the total flow directed towards it minus the outflow from it— exceeds a certain capacity constraint, then the exceeding part of it leaks out of the system. The ensuing network flow dynamics is a linear saturated system with compact state space that we analyse using tools from monotone systems and contraction theory. Specifically, we prove that there exists a set of equilibria that is globally asymptotically stable. Such equilibrium set reduces to a single globally asymptotically stable equilibrium for generic exogenous demand vectors. Moreover, we show that the critical exogenous demand vectors giving rise to non-unique equilibria correspond to phase transitions in the asymptotic behavior of the dynamical flow network.

VI115-05
Control for Next Generation Wireless Networks	Open Invited Session
Chair: Gatsis, Konstantinos	University of Oxford
Co-Chair: Baumann, Dominik	Max Planck Institute for Intelligent Systems
Organizer: Baumann, Dominik	Max Planck Institute for Intelligent Systems
Organizer: Gatsis, Konstantinos	University of Pennsylvania
Organizer: Johansson, Karl H.	Royal Institute of Technology
Organizer: Trimpe, Sebastian	Max Planck Institute for Intelligent Systems
Paper VI115-05.1
PDF · Video · Stability Analysis for Nonlinear Weakly Hard Real-Time Control Systems (I)
Hertneck, Michael	University of Stuttgart
Linsenmayer, Steffen	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Networked embedded control systems, Control over networks, Control under communication constraints Abstract: This paper considers the stability analysis for nonlinear sampled-data systems with failures in the feedback loop. The failures are caused by shared resources, and modeled by a weakly hard real-time (WHRT) dropout description. The WHRT dropout description restricts the considered dropout sequences with a non-probabilistic, window based constraint, that originates from schedulability analysis. The proposed approach is based on the emulation of a controller for the nonlinear sampled-data system from a continuous-time feedback. The emulation technique is extended and combined with non-monotonic Lyapunov functions and a graph description for the WHRT constraints to guarantee asymptotic stability. The effectiveness of the proposed approach is illustrated with a numerical example from literature.
Paper VI115-05.2
PDF · Video · Predictably Reliable Real-Time Transport Services for Wireless Cyber-Physical Systems (I)
Schmidt, Andreas	Saarland Informatics Campus
Gil Pereira, Pablo	Saarland Informatics Campus
Herfet, Thorsten	Intel Visual Computing Institute, Saarland University
Keywords: Control under communication constraints, Networked embedded control systems, Control over networks Abstract: Cyber-physical systems increasingly leverage wireless networks for distributed control applications. In these systems, control and communication mustfind explicit agreements on the resilience and age-of-information (AoI) provided by the transport services to ensure stability. We present PRRT and its unique features to provide a predictably reliable real-time service that can fulfil these agreements. These features include cross-layer pacing, i.e. allowing an application to adapt to the system's bottleneck to achieve predictably low AoI. Finally, we highlight future directions for the transport service provided by PRRT with respect to its usage in constrained devices, where, e.g., energy demands play an important role.
Paper VI115-05.3
PDF · Video · Learning to Control Over Unknown Wireless Channels (I)
Gatsis, Konstantinos	University of Oxford
Pappas, George J.	Univ of Pennsylvania
Keywords: Learning for control, Control over networks Abstract: Emerging control applications in the Internet-of-Things are increasingly relying on communication networks and wireless channels to close the loop. Traditional model-based approaches, i.e., assuming a known wireless channel model, are focused on analyzing stability and designing appropriate controller structures. Such modeling is challenging as wireless channels are typically unknown a priori and only available through data samples. In this work we aim to design data-based controllers using channel samples and provide high confidence guarantees on the performance of these controllers when deployed over the actual unknown channel. To achieve these results we combine statistical learning (concentration inequalities) with structural properties of our problem (monotonicity with respect to the unknown channel parameters), and also provide sample complexity analysis.
Paper VI115-05.4
PDF · Video · Real-Time Distributed Automation of Road Intersections (I)
Molinari, Fabio	Technische Universitaet Berlin
Katriniok, Alexander	Ford Research & Innovation Center (RIC)
Raisch, Joerg	Technische Universitaet Berlin
Keywords: Coordination of multiple vehicle systems, Distributed control and estimation, Consensus Abstract: The topic of this paper is the design of a fully distributed and real-time capable control scheme for the automation of road intersections. State of the art Vehicle-to-Vehicle (V2V) communication technology is adopted. Vehicles distributively negotiate crossing priorities by running a Consensus-Based Auction Algorithm (CBAA-M). Then, each agent solves a nonlinear Model Predictive Control (MPC) problem that computes the optimal trajectory avoiding collisions with higher priority vehicles and deciding the crossing order. The scheme is shown to be real-time capable and able to respond to sudden priority changes, e.g. if a vehicle gets an emergency call. Simulations reinforce theoretical results.
Paper VI115-05.5
PDF · Video · 1 kHz Remote Control of a Balancing Robot with Wi-Fi-In-The-Loop (I)
Branz, Francesco	University of Padova
Antonello, Riccardo	University of Padova
Pezzutto, Matthias	University of Padova
Tramarin, Federico	University of Padova
Schenato, Luca	Univ of Padova
Keywords: Control over networks, Control under communication constraints, Networked embedded control systems Abstract: Countless industrial applications can potentially benefit from the implementation of wireless control systems, leading to a widespread research effort to investigate new solutions in the field. Nevertheless, currently available wireless communication standards for industrial automation are not able to achieve high control frequencies. In particular, time-critical applications (e.g. industrial robotics and manipulation) require high sampling frequencies to be properly implemented. The higher throughput provided by IEEE 802.11 (Wi-Fi) can theoretically tame critical applications, although reliability is a key issue. This work presents an innovative approach to the control over wireless problem: Wi-Fi is adopted to increase the achievable control rates up to 1 kHz, while reliability is guaranteed by mitigating communication flaws through model-based estimation techniques. The core of the proposed approach relies on a modified Kalman filter that exploits a buffer of incoming measures to account for delayed data packets. The proposed solution is validated through a hardware-in-the-loop experiment that features actual Wi-Fi hardware and a commercial embedded PC board. The obtained results give a preliminary, yet valuable, validation of the proposed approach testing the solution on relevant hardware.
Paper VI115-05.6
PDF · Video · Saving Tokens in Rollout Control with Token Bucket Specification (I)
Jaumann, Florian	University of Stuttgart
Wildhagen, Stefan	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Control over networks, Control under communication constraints, Event-based control Abstract: We consider a communication network over which transmissions must fulfill the so-called token bucket traffic specification, with a rollout (i.e., predictive) controller that both schedules transmissions and computes the corresponding control values. In the token bucket specification, a transmission is allowed if the current level of tokens is above a certain threshold. Recently, it has been shown that having a full bucket at the time of a set point change significantly improves the control performance as compared to when the bucket level is low. In this work, we develop mechanisms that guarantee that the bucket fills up after the controlled plant has converged to a set point. To do this, we consider two different setups. First, we consider that all transmissions over the network must fulfill the token bucket specification and show convergence to the upper sector of the bucket by adding a slight terminal cost on the bucket level. Afterwards, we consider a modified network which additionally features a direct link over which transmissions need not fulfill the token bucket specification. In this setup, we prove convergence of the bucket level exactly to the upper rim. These mechanisms enable a similar level of flexibility as event-triggered control: In converged state, little communication is used while in precarious operating conditions, a burst of transmissions is possible. Other than event-triggered approaches, the proposed methods allow to specify the network traffic beforehand by means of the token bucket. Lastly, we validate the proposed approaches in a numerical example.
Paper VI115-05.7
PDF · Video · Transmission Scheduling for Remote Estimation with Multi-Packet Reception under Multi-Sensor Interference (I)
Pezzutto, Matthias	University of Padova
Schenato, Luca	Univ of Padova
Dey, Subhrakanti	Uppsala University
Keywords: Sensor networks, Control and estimation with data loss, Control under communication constraints Abstract: In networked control systems, due to competing demands on bandwidth and energy constraints, sensor scheduling is an important problem for remote estimation and control tasks. Traditionally, a single sensor is scheduled in each resource block to avoid interference or collisions so that the probability of packet loss is reduced. However, receiving multiple packets from different sources under interference is routinely achieved in wireless networks using multi-packet reception techniques. In this work, we explore the problem of sensor scheduling for remote estimation when the estimator is able to simultaneously receive multiple packets. We use the typical signal-to-interference-and-noise-ratio (SINR) based capture model to compute the packet arrival probabilities. Then an optimal scheduling policy is determined by minimizing expected estimation error covariance subject to a constraint on the average number of total transmissions. In the case of two sensors, for a scalar system and for a decoupled two-dimensional system, we show that allowing multiple simultaneous transmissions can improve the quality of the estimation achieving lower energy consumptions and we provide structural results on the optimal policies. Numerical results illustrate the benefits of multi-packet reception in remote estimation.
Paper VI115-05.8
PDF · Video · Resource Allocation in Large-Scale Wireless Control Systems with Graph Neural Networks (I)
Lima, Vinícius	University of Pennsylvania
Eisen, Mark	Intel Corporation
Gatsis, Konstantinos	University of Oxford
Ribeiro, Alejandro	University of Pennsylvania
Keywords: Control over networks, Learning for control, Consensus and Reinforcement learning control Abstract: Modern control systems routinely employ wireless networks to exchange information between a large number of plants, actuators and sensors. While wireless networks are defined by random, rapidly changing conditions that challenge common control design assumptions, properly allocating communication resources helps to maintain operation reliable. Designing resource allocation policies is usually challenging and requires explicit knowledge of the system and communication dynamics, but recent works have successfully explored deep reinforcement learning techniques to find optimal model-free resource allocation policies. Deep reinforcement learning algorithms do not necessarily scale well, however, which limits the immediate generalization of those approaches to large-scale wireless control systems. In this paper we discuss the use of reinforcement learning and graph neural networks (GNNs) to design model-free, scalable resource allocation policies. On the one hand, GNNs generalize the spatial-temporal convolutions present in convolutional neural networks (CNNs) to data defined over arbitrary graphs. In doing so, GNNs manage to exploit local regular structure encoded in graphs to reduce the dimensionality of the learning space. The architecture of the wireless network, on the other, defines an underlying communication graph that can be used as basis for a GNN model. Numerical experiments show the learned policies outperform baseline resource allocation solutions.
Paper VI115-05.9
PDF · Video · A Clustering Approach to Edge Controller Placement in Software-Defined Networks with Cost Balancing
Soleymanifar, Reza	University of Illinois at Urbana-Champaign
Srivastava, Amber	University of Illinois at Urbana Champaign
Beck, Carolyn L.	Univ. of Illinois at Urbana-Champaign
Salapaka, Srinivasa	Univ of Illinois
Keywords: Machine learning, Control over networks, Sensor networks Abstract: In this work we introduce two novel maximum entropy based clustering algorithms to address the problem of Edge Controller Placement (ECP) in wireless edge networks. These networks lie at the core of the fifth generation (5G) wireless systems and beyond. Our algorithms, ECP-LL and ECP-LB, address the dominant leader-less and leader-based controller placement topologies and have linear computational complexity in terms of network size, number of clusters and dimensionality of data. Each algorithm places controllers close to edge node clusters and not far away from other controllers to maintain a reasonable balance between synchronization and delay costs. While the ECP problem can be expressed as a multi-objective mixed integer non-linear program (MINLP), our algorithms outperform state of art MINLP solver, BARON both in terms of accuracy and speed. Our proposed algorithms have the competitive edge of avoiding poor local minima through a Shannon entropy term in the clustering objective function. Most ECP algorithms are highly susceptible to poor local minima and greatly depend on initialization.

VI115-06
Distributed Optimization for Learning and Control in Smart Networks	Open Invited Session
Chair: Notarstefano, Giuseppe	University of Bologna
Co-Chair: Notarnicola, Ivano	University of Bologna
Organizer: Notarstefano, Giuseppe	University of Bologna
Organizer: Notarnicola, Ivano	University of Bologna
Organizer: Farina, Francesco	University of Bologna
Paper VI115-06.1
PDF · Video · Communication-Efficient Variance-Reduced Stochastic Gradient Descent (I)
Shokri Ghadikolaei, Hossein	EPFL
Magnusson, Sindri	KTH Royal Institute of Technology
Keywords: Machine learning, Distributed optimisation for large-scale systems, Control under communication constraints Abstract: We consider the problem of communication efficient distributed optimization where multiple nodes exchange important algorithm information in every iteration to solve large problems. In particular, we focus on the stochastic variance-reduced gradient and propose a novel approach to make it communication-efficient. That is, we compress the communicated information to a few bits while preserving the linear convergence rate of the original uncompressed algorithm. Comprehensive theoretical and numerical analyses on real datasets reveal that our algorithm can significantly reduce the communication complexity, by as much as 95%, with almost no noticeable penalty. Moreover, it is much more robust to quantization (in terms of maintaining the true minimizer and the convergence rate) than the state-of-the-art algorithms for solving distributed optimization problems. Our results have important implications for using machine learning over internet-of-things and mobile networks.
Paper VI115-06.2
PDF · Video · Combining ADMM and Tracking Over Networks for Distributed Constraint-Coupled Optimization (I)
Falsone, Alessandro	Politecnico Di Milano
Notarnicola, Ivano	University of Bologna
Notarstefano, Giuseppe	University of Bologna
Prandini, Maria	Politecnico Di Milano
Keywords: Distributed optimisation for large-scale systems, Control over networks, Consensus Abstract: In this paper, we propose a novel distributed algorithm to address constraint-coupled optimization problems in which agents in a network aim at cooperatively minimizing the sum of local objective functions subject to individual constraints and a common, linear coupling constraint. Our optimization scheme embeds a dynamic average consensus protocol in the (parallel) Alternating Direction Method of Multipliers (ADMM) to design a fully distributed algorithm. More precisely, the dual variable update step of the master node in ADMM is now performed locally by the agent, which update their own copy of the dual variable in a consensus-based scheme using a dynamic average mechanism to track the coupling constraint violation. Under convexity, we show convergence of the primal solution estimates to an optimal solution of the constraint-coupled target problem. A numerical example supports the theoretical results.
Paper VI115-06.3
PDF · Video · Cloud-Based Collaborative Learning of Optimal Feedback Controllers (I)
Breschi, Valentina	Politecnico Di Milano
Ferrarotti, Laura	IMT School for Advanced Studies, Lucca
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Consensus and Reinforcement learning control, Control over networks Abstract: Industrial systems deployed in mass production, such as automobiles, can greatly benefit from sharing selected data among them through the cloud to self-adapt their control laws. The reason is that in mass production systems are clones of each other, designed, constructed, and calibrated by the manufacturer in the same way, and thus they share the same nominal dynamics. Hence, sharing information during closed-loop operations can dramatically help each system to adapt its local control laws so to attain its own goals, in particular when optimal performance is sought. This paper proposes an approach to learn optimal feedback control laws for reference tracking via a policy search technique that exploits the similarities between systems. By using resources available locally and on the cloud, global and local control laws are concurrently synthesized through the combined use of the alternating direction method of multipliers (ADMM) and stochastic gradient descent (SGD). The enhancement of learning performance due to sharing knowledge on the cloud is shown in a simple numerical example.
Paper VI115-06.4
PDF · Video · DISROPT: A Python Framework for Distributed Optimization (I)
Farina, Francesco	University of Bologna
Camisa, Andrea	University of Bologna
Testa, Andrea	Università Di Bologna
Notarnicola, Ivano	University of Bologna
Notarstefano, Giuseppe	University of Bologna
Keywords: Distributed optimisation for large-scale systems, Distributed control and estimation, Machine learning Abstract: In this paper we introduce DISROPT, a Python package for distributed optimization over networks. We focus on cooperative set-ups in which an optimization problem must be solved by peer-to-peer processors (without central coordinators) that have access only to partial knowledge of the entire problem. To reflect this, agents in DISROPT are modeled as entities that are initialized with their local knowledge of the problem. Agents then run local routines and communicate with each other to solve the global optimization problem. A simple syntax has been designed to allow for an easy modeling of the problems. The package comes with many distributed optimization algorithms that are already embedded. Moreover, the package provides full-fledged functionalities for communication and local computation, which can be used to design and implement new algorithms. DISROPT is available at github.com/disropt/disropt under the GPL license, with a complete documentation and many examples.
Paper VI115-06.5
PDF · Video · Exponential Convergence for Distributed Optimization under the Restricted Secant Inequality Condition (I)
Yi, Xinlei	KTH Royal Institute of Technology
Zhang, Shengjun	University of North Texas
Yang, Tao	Northeastern University
Chai, Tianyou	Northeastern Univ
Johansson, Karl H.	Royal Institute of Technology
Keywords: Distributed optimisation for large-scale systems, Multi-agent systems, Consensus Abstract: This paper considers the distributed optimization problem of minimizing a global cost function formed by a sum of local smooth cost functions by using local information exchange. A standard assumption for proving exponential/linear convergence of existing distributed first-order methods is strong convexity of the cost functions. This does not hold for many practical applications. In this paper, we propose a continuous-time distributed primal-dual gradient descent algorithm and show that it converges exponentially to a global minimizer under the assumption that the global cost function satisfies the restricted secant inequality condition. This condition is weaker than strong convexity and the global minimizer is not necessarily unique. Moreover, a discrete-time distributed primal-dual algorithm is developed from the continuous-time algorithm by Euler's approximation method, which also linearly converges to a global minimizer under the same condition. The theoretical results are illustrated by numerical simulations.
Paper VI115-06.6
PDF · Video · Distributed Submodular Minimization Via Block-Wise Updates and Communications (I)
Testa, Andrea	Università Di Bologna
Farina, Francesco	University of Bologna
Notarstefano, Giuseppe	University of Bologna
Keywords: Distributed optimisation for large-scale systems, Multi-agent systems, Machine learning Abstract: In this paper we deal with a network of computing agents with local processing and neighboring communication capabilities that aim at solving (without any central unit) a submodular optimization problem. The cost function is the sum of many local submodular functions and each agent in the network has access to one function in the sum only. In this distributed set-up, in order to preserve their own privacy, agents communicate with neighbors but do not share their local cost functions. We propose a distributed algorithm in which agents resort to the Lovàsz extension of their local submodular functions and perform local updates and communications in terms of single blocks of the entire optimization variable. Updates are performed by means of a greedy algorithm which is run only until the selected block is computed, thus resulting in a reduced computational burden. The proposed algorithm is shown to converge in expected value to the optimal cost of the problem, and an approximate solution to the submodular problem is retrieved by a thresholding operation. As an application, we consider a distributed image segmentation problem in which each agent has access only to a portion of the entire image. While agents cannot segment the entire image on their own, they correctly complete the task by cooperating through the proposed distributed algorithm.
Paper VI115-06.7
PDF · Video · A Distributed Optimization Algorithm for Nash Bargaining in Multi-Agent Systems (I)
Camisa, Andrea	University of Bologna
Köhler, Philipp N.	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Notarstefano, Giuseppe	University of Bologna
Allgower, Frank	University of Stuttgart
Keywords: Distributed optimisation for large-scale systems, Distributed control and estimation, Multi-agent systems Abstract: In this paper, we consider a multi-objective optimization problem over networks in which agents aim to maximize their own objective function, while satisfying both local and coupling constraints. This set up includes, e.g., the computation of optimal steady states in multi-agent control systems. Since fairness is a key feature required for the solution, we resort to Cooperative Game Theory and search for the Nash bargaining solution among all the efficient (or Pareto optimal) points of a bargaining game. We propose a negotiation mechanism among the agents to compute such a solution in a distributed way. The problem is reformulated as the maximization of a properly weighted sum of the objective functions. The proposed algorithm is then a two step procedure in which local estimates of the Nash bargaining weights are updated online and existing distributed optimization algorithms are applied. The proposed method is formally analyzed for a particular case, while numerical simulations are provided to corroborate the theoretical findings and to demonstrate its efficacy.
Paper VI115-06.8
PDF · Video · On the Approachability Principle for Distributed Payoff Allocation in Coalitional Games (I)
Raja, Aitazaz Ali	Delft University of Technology
Grammatico, Sergio	Delft Univ. of Tech
Keywords: Multi-agent systems, Consensus, Control over networks Abstract: In the context of coalitional games, we present a partial operator-theoretic characterization of the approachability principle and, based on this characterization, we interpret a particular distributed payoff allocation algorithm to be a sequence of time-varying paracontractions. Then, we also propose a distributed payoff allocation algorithm on time-varying communication networks. The state in the proposed algorithm converges to a consensus in the "CORE" set as desired. For the convergence analysis, we rely on an operator-theoretic property of paracontraction.
Paper VI115-06.9
PDF · Video · Enhanced Gradient Tracking Algorithms for Distributed Quadratic Optimization Via Sparse Gain Design (I)
Carnevale, Guido	Alma Mater Studiorum Università Di Bologna
Bin, Michelangelo	Imperial College London
Notarnicola, Ivano	University of Bologna
Marconi, Lorenzo	Univ. Di Bologna
Notarstefano, Giuseppe	University of Bologna
Keywords: Distributed optimisation for large-scale systems, Multi-agent systems, Control of networks Abstract: In this paper we propose a new control-oriented design technique to enhance the algorithmic performance of the distributed gradient tracking algorithm. We focus on a scenario in which agents in a network aim to cooperatively minimize the sum of convex, quadratic cost functions depending on a common decision variable. By leveraging a recent system-theoretical reinterpretation of the considered algorithmic framework as a closed-loop linear dynamical system, the proposed approach generalizes the diagonal gain structure associated to the existing gradient tracking algorithms. Specifically, we look for closed-loop gain matrices that satisfy the sparsity constraints imposed by the network topology, without however being necessarily diagonal, as in existing gradient tracking schemes. We propose a novel procedure to compute stabilizing sparse gain matrices based on the iterative solution of a nonlinear problem, in which each iteration deals with a linear problem. Numerical simulations are presented showing the enhanced performance of the proposed design compared to existing gradient tracking algorithms.
Paper VI115-06.10
PDF · Video · A Proximal Point Approach for Distributed System State Estimation (I)
Fabris, Marco	University of Padova
Michieletto, Giulia	University of Padova
Cenedese, Angelo	University of Padova
Keywords: Distributed control and estimation, Multi-agent systems, Distributed optimisation for large-scale systems Abstract: System state estimation constitutes a key problem in several applications involving multi-agent system architectures. This rests upon the estimation of the state of each agent in the group, which is supposed to access only relative measurements w.r.t. some neighbors state. Exploiting the standard least-squares paradigm, the system state estimation task is faced in this work by deriving a distributed Proximal Point-based iterative scheme. This solution entails the emergence of interesting connections between the structural properties of the stochastic matrices describing the system dynamics and the convergence behavior toward the optimal estimate. A deep analysis of such relations is provided, jointly with a further discussion on the penalty parameter that characterizes the Proximal Point approach.

VI115-07
Event-Triggered and Self-Triggered Control	Open Invited Session
Chair: Heemels, Maurice	Eindhoven University of Technology
Co-Chair: Nowzari, Cameron	George Mason University
Organizer: Heemels, Maurice	Eindhoven University of Technology
Organizer: Johansson, Karl H.	Royal Institute of Technology
Organizer: Nowzari, Cameron	George Mason University
Paper VI115-07.1
PDF · Video · Decoupled Feedforward-Feedback Periodic Event-Triggered Control for Disturbance Rejection (I)
Aranda Escolástico, Ernesto	UNED
Guinaldo, Maria	UNED
Guzman, Jose Luis	University of Almeria
Dormido, Sebastián	UNED
Keywords: Event-based control, Control under communication constraints Abstract: In this paper, feedforward and feedback controllers are studied considering decoupled periodic event-triggering mechanisms for output and disturbance sensors. Stability and robustness conditions for linear systems are obtained considering transportation delays and actuator saturation following the Lyapunov-Krasovskii procedure. A numerical example shows that the proposed control strategy reduces the communication between sensors and controller significantly, while the system performance is not deteriorated.
Paper VI115-07.2
PDF · Video · Event-Triggered Control for Extended Plants of Discrete-Time Linear Systems (I)
Ichihara, Hiroyuki	Meiji University
Sawada, Kenji	The University of Electro-Communications
Kobayashi, Koichi	Hokkaido University
Tarbouriech, Sophie	LAAS-CNRS
Keywords: Event-based control, Control over networks Abstract: This paper deals with design methods of event-triggered control systems for discrete-time linear systems. An extended plant consisting of a given plant and a dynamical filter is considered and controlled by an event-triggered static output feedback. The triggering rule uses only the available signals and therefore is based on the difference between the triggered and non-triggered output signals. The paper deals with the co-design problem, that is the design of the triggering condition, the filter, and the controller simultaneously. Sufficient theoretical conditions are proposed in terms of linear matrix inequalities to ensure the asymptotic stability of the closed-loop system. Convex optimizations problems incorporate these conditions in order to optimize the closed-loop performance or to reduce the number of transmissions. Three numerical examples illustrate the design method of the triggering conditions as well as the simultaneous design method of the filter and controller.
Paper VI115-07.3
PDF · Video · Event-Triggered Control Co-Design for Rational Systems (I)
Moreira, Luciano Gonçalves	IFSUL
Gomes Da Silva Jr, Joao Manoel	Universidade Federal Do Rio Grande Do Sul (UFRGS)
Coutinho, Daniel	Universidade Federal De Santa Catarina
Tarbouriech, Sophie	LAAS-CNRS
Keywords: Stability and stabilization of hybrid systems, Event-based control, Control under communication constraints Abstract: This work deals with the problem of designing stabilizing event-triggered state-feedback controllers for rational systems. Using diferential algebraic representations and Lyapunov theory techniques, LMI-based conditions are derived to ensure regional asymptotic stability of the origin. These conditions are then cast into a convex optimization problem to the co-design of the event generator parameters and the state-feedback gain in order to reduce the controller updates while ensuring the asymptotic stability of the origin with respect to a given set of admissible initial conditions. The proposed methodology is illustrated by means of a numerical example.
Paper VI115-07.4
PDF · Video · Scalable Traffic Models for Scheduling of Linear Periodic Event-Triggered Controllers (I)
de Albuquerque Gleizer, Gabriel	TU Delft
Mazo Jr, Manuel	TU Delft
Keywords: Event-based control, Reachability analysis, verification and abstraction of hybrid systems, Control over networks Abstract: This paper addresses the problem of modeling and scheduling the transmissions generated by multiple event-triggered control (ETC) loops sharing a network. We present a method to build a finite-state similar model of the traffic generated by periodic ETC (PETC), which by construction mitigates the combinatorial explosion that is typical of symbolic models. The model is augmented with early triggering actions that can be used by a scheduler. The complete networked control system is then modeled as a network of timed game automata, for which existing tools can generate strategies that avoids communication conflicts, while keeping early triggers to a minimum. Our proposed model is relatively fast to build and is the first to constitute an exact simulation. Finally, we demonstrate modeling and scheduling for a numerical example.
Paper VI115-07.5
PDF · Video · A Resource-Aware Approach to Self-Triggered Model Predictive Control (I)
Wildhagen, Stefan	University of Stuttgart
Jones, Colin N.	EPFL
Allgower, Frank	University of Stuttgart
Keywords: Event-based control, Control under communication constraints, Control under computation constraints Abstract: In this paper, we consider a self-triggered formulation of model predictive control. In this variant, the controller decides at the current sampling instant itself when the next sample should be taken and the optimization problem be solved anew. We incorporate a pointwise-in-time resource constraint into the optimization problem, whose exact form can be chosen by the user. Thereby, the proposed scheme is made resource-aware with respect to a universal resource, which may pertain in practice for instance to communication, computation, energy or financial resources. We show that by virtue of the pointwise-in-time constraints, also a transient and an asymptotic average constraint on the resource usage are guaranteed. Furthermore, we derive conditions on the resource under which the proposed scheme achieves recursive feasibility and convergence. Finally, we demonstrate our theoretical results in a numerical example.
Paper VI115-07.6
PDF · Video · Event-Triggered PI Control of Time-Delay Systems with Parametric Uncertainties (I)
Iwaki, Takuya	KTH Royal Institute of Technology
Fridman, Emilia	Tel-Aviv Univ
Johansson, Karl H.	Royal Institute of Technology
Keywords: Event-based control, Control over networks Abstract: This paper studies sampled-data implementation of event-triggered PI control for time-delay systems with parametric uncertainties. The systems are given by continuous-time linear systems with parameter uncertainty polytopes. We propose an event-triggered PI controller, in which the controller transmits its signal to the actuator when its relative value goes beyond a threshold. A state-space formulation of the Smith predictor is used to compensate the time-delay. An asymptotic stability condition is derived in the form of LMIs using a Lyapunov-Krasovskii functional. Numerical examples illustrate that our proposed controller reduces the communication load without performance degradation and despite plant uncertainties.
Paper VI115-07.7
PDF · Video · Strongly Non-Zeno Event-Triggered Wireless Clock Synchronization (I)
Berneburg, James	George Mason University
Garcia, Eloy	Air Force Research Laboratory
Gerlach, Adam	United States Air Force
Casbeer, David Wellman	Air Force Research Laboratory
Nowzari, Cameron	George Mason University
Keywords: Event-based control, Multi-agent systems, Control under communication constraints Abstract: Agreeing on a common time is essential to many coordinated tasks in wireless networks, but this is difficult to accomplish when each agent only has access to a local hardware clock. Therefore, clock synchronization is essential in order to carry out many of these coordinated tasks. While there are numerous existing algorithms for clock synchronization, many result in disruptive discontinuous virtual clocks, and most rely on regular communication, which does not scale with large systems. Instead, this paper presents a novel clock synchronization algorithm, which allows for a continuous virtual clock, with a dynamic event-triggered communication strategy which is strongly non-Zeno because it guarantees a designable positive time between communication instances.
Paper VI115-07.8
PDF · Video · Event-Based Collision Avoidance Utilising a Channel Estimation Method
Schwung, Michael	Ruhr-Universität Bochum
Roth, Stefan	Ruhr University Bochum
Karacora, Yasemin	Ruhr University Bochum
Lunze, Jan	Ruhr-Universität Bochum
Sezgin, Aydin	Ruhr-University Bochum
Keywords: Control under communication constraints, Event-based control, Multi-agent systems Abstract: This paper proposes a networked event-based method for collision avoidance of moving objects in a leader-follower structure. It extends the results of a previous paper to cope with communication constraints from an information theoretical perspective. The objects are locally controlled and connected by a communication network, in which transmission delays and packet losses occur. In the considered setting, the leader can freely change its trajectory while the follower has to avoid collisions by predicting the leader movement, invoking communication at event times that indicate a large uncertainty of the prediction result and adapting its trajectory appropriately. The current properties of the network are determined at each event time by a channel estimation method and are taken into account when generating events and planning the trajectory. In contrast to the existing literature, trajectories are adapted online where the collision-free movement is guaranteed despite of the limited communication by considering the network effects. A simulation study with two quadrotors shows that collisions can only be avoided if the results of the channel estimation are considered.
Paper VI115-07.9
PDF · Video · Self-Triggered Finite Time Pursuit Strategy for a Two-Player Game
Mulla, Ameer	Indian Institute of Technology Dharwad
Keywords: Control under communication constraints, Event-based control, Reachability analysis, verification and abstraction of hybrid systems Abstract: A continuous-time two player pursuit-evasion game is considered. The players have double-integrator dynamics with bounded acceleration inputs. Unlike, conventional pursuit strategies, it is assumed that, the pursuer does not have continuous access to the states of the players. In this paper, we propose a self-triggered pursuit strategy, in which, the pursuer can choose when the state-information needs to be updated next. The proposed strategy is based on the time-optimal pursuit strategy for a game in which state information is available continuously to both the players. When the bound on acceleration of the evader is smaller than that of the pursuer, the proposed strategy guarantees capture in finite time, with finite number of information updates.
Paper VI115-07.10
PDF · Video · Event-Triggered Control for Switched Systems in Network Environments
Ma, Lang	Shanghai University
Wang, Yu-Long	Shanghai University
Han, Qing-Long	Swinburne University of Technology
Peng, Chen	Shanghai University
Keywords: Control under communication constraints, Event-based control, Stability and stabilization of hybrid systems Abstract: This paper is concerned with event-triggered control for a switched system in network environments. Firstly, a novel event-triggering communication scheme with switching features is proposed. The switching features are taken into full consideration to guarantee the current sampled data to be transmitted if a switch occurs between the last sampling instant and the current sampling instant. The newly proposed event-triggering scheme is advantageous in dealing with switched networked control systems. Secondly, under the event-triggering scheme, an asynchronously switched time-delay system model is established by taking into account effects of network-induced delays. Finally, a mode-dependent state feedback controller gain and event generator parameters co-design method is proposed for the asynchronously switched time-delay system. System performance analysis demonstrates the effectiveness of the proposed methods.
Paper VI115-07.11
PDF · Video · Distributed Consensus Control for General Linear Multi-Agent Systems Via a Dynamic Event-Triggered Strategy
Li, Yifei	Beijing Institute of Technology
Liu, Xiangdong	School of Automation, 231 Staff, Beijing Institute OfTechnology
Du, Changkun	Beijing Institute of Technology
Liu, Haikuo	Beijing Institute of Technology
Lu, Pingli	Beijing Institute of Technology
Keywords: Multi-agent systems, Event-based control, Consensus Abstract: This paper puts forward a distributed dynamic event-triggered strategy to solve the distributed event-triggered consensus problem of linear multi-agent systems under directed graphs. Based on dynamic triggering function, each agent can reach consensus asymptotically. Different from existing static triggering schemes, the proposed dynamic triggering scheme, where an internal dynamic variable is involved, results in larger inter-event times and also leads to less communication overheads among agents, which is conducive to guaranteeing that Zeno behavior is excluded for each agent. In addition, under the proposed strategy, neither controller updates nor triggering threshold detections require continuous communication. Finally, the effectiveness of the theoretical analysis is demonstrated by numerical simulations.
Paper VI115-07.12
PDF · Video · Event-Triggered Consensus for Euler-Lagrange Systems with Communication Delay
Budde genannt Dohmann, Pablo	Technical Unviversity of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Networked robotic systems, Event-based control Abstract: Distributed cooperative control of multi-agent systems, typically requires some form of information exchange in order to achieve coordination between individual agents. Especially in wireless communication systems, communication delays can lead to instability and can not be neglected during the design of the control law. We propose a novel coordination scheme for Euler-Lagrange systems taking into account constant communication delays. Additionally, in order to save limited resources we propose an event-triggered strategy for the communication between agents, as well as for the local actuator updates of the individual agents. We show that with the proposed algorithms a stable interaction in a consensus tasks can be guaranteed. Simulations illustrate the theoretical results.
Paper VI115-07.13
PDF · Video · A Self-Triggered Control Scheme for Markov Jump Systems under Multiple Range Performance Restrictions (I)
Wan, Haiying	Jiangnan University
Karimi, Hamid Reza	Politecnico Di Milano
Luan, Xiaoli	Jiangnan University
Liu, Fei	Jiangnan University
Keywords: Event-based control, Stochastic hybrid systems Abstract: This paper proposes a multi-frequency controller design scheme for Markov jump systems (MJSs) based on the self-triggered strategy in a resource-aware way. Firstly, a derandomization technique is introduced to make sure the transition probability information is included in the finite frequency specification analysis. Then, a self-triggered policy is developed to update the control input of the system via the history measurement. Finally, sufficient conditions are deduced that guarantee the multiple range frequency performances and the reduction of computation and communication occupation for the controlled MJSs, simultanously. The cart- spring system is employed to illustrate the effectiveness of the proposed approach.
Paper VI115-07.14
PDF · Video · Validating Continuous Tuning Rules for Event-Based PI Control of Lag-Dominant Processes
Sánchez Moreno, José	UNED
Guinaldo, Maria	UNED
Dormido, Sebastián	UNED
Visioli, Antonio	University of Brescia
Keywords: Event-based control Abstract: One of the difficulties of the tuning of event-based proportional-integral (PI) controllers using symmetric send-on-delta sampling (SSOD) is the appearance of a stable limit cycle, especially when rules designed for continuous control loops are applied. This oscillation is explained by the intersection in the Nyquist map of the system, that is, of the loop transfer function, with the negative reciprocal of the describing function (DF) of the SSOD sampler. However, as the DF theory is based on neglecting the high-order harmonics in the closed loop system, it introduces errors in the prediction of the oscillations. The paper presents an experimental study that establishes the boundaries of the PI controller parameters (proportional and integral gains) that avoid any limit cycle considering that a lag-dominant first order process model is used for the tuning. By taking into account the boundaries, a safety application in an event-based framework of any tuning rule designed for the classical time-driven case is possible.
Paper VI115-07.15
PDF · Video · Robustness of Event-Based Discrete PI Controllers. a Sampled Describing Function Approach
Miguel-Escrig, Oscar	Universitat Jaume I
Romero, Julio Ariel	Universitat Jaume I
Keywords: Event-based control Abstract: In this paper we present a study about the robustness of event-based discrete PI controllers. Our approach is based on Sampled Describing Function technique, which has been used to characterize the non-linear effect of the Symmetric Send on Delta (SSOD) sampling strategy on the control loop. Through several examples this technique is proven to produce accurate results in predicting limit cycle oscillations and to provide guidelines to avoid them, either by detuning the controller or increasing the sampling period.
Paper VI115-07.16
PDF · Video · Event-Based Stabilization of Nonlinear Lipschitz Systems
Ghodrat, Mohsen	University of Alberta
Marquez, Horacio J.	Univ. of Alberta
Keywords: Event-based control, Control under communication constraints Abstract: In this article, we propose an event-triggering mechanism for stabilization of a class of nonlinear Lipschitz systems under disturbance rejection H_infty performance. Instead of following the prevalent dwell-time approach to address the Zeno issue, we propose a novel triggering threshold which switches between a constant and a function of states norm and allows for avoiding Zeno behavior while achieving the desired performance level. The efficiency of the proposed approach is then justified through a numerical example.
Paper VI115-07.17
PDF · Video · Dynamic Event-Triggered Adaptive Control for Robust Output Regulation of Nonlinear Systems with Unknown Exosystems
Liu, Pin	North China Electric Power University
Xiao, Feng	North China Electric Power University
Wei, Bo	North China Electric Power University
Keywords: Event-based control, Nonlinear adaptive control, Stability and stabilization of hybrid systems Abstract: In this paper, robust output regulation of nonlinear systems with unknown neutral exosystems is discussed. Based on the internal model and adaptive control theory, we design the output feedback controller with a dynamic event-triggering mechanism. Under the dynamic event-triggering mechanism, the controller can be implemented in the digital platform. The effectiveness of the proposed event-triggering mechanism is illustrated through an example.
Paper VI115-07.18
PDF · Video · Dynamic Periodic Event-Triggered Control for Nonlinear Plants with State Feedback
Dhullipalla, Mani Hemanth	University of Alberta
Yu, Hao	University of Alberta
Chen, Tongwen	University of Alberta
Keywords: Event-based control, Stability and stabilization of hybrid systems, Control over networks Abstract: In this work, we propose two methods to design a dynamic periodic event-triggered controller that stabilizes nonlinear plants using static state feedback. The design methodology begins by assuming the knowledge of a continuous-time state-feedback controller that stabilizes the nonlinear plant. Considering an event-driven controller updation, the resultant closed-loop plant is modelled as a hybrid system. Two approaches are proposed for the event triggering mechanism (ETM) depending on continuous availability of states. Each method provides an ETM and an upper bound on the sampling period that ensures closed-loop stability. We provide some remarks comparing the two approaches and substantiate them through an illustrative example.
Paper VI115-07.19
PDF · Video · Event-Triggered Data-Efficient Observers of Perturbed Systems
Voortman, Quentin	Eindhoven University of Technology
Efimov, Denis	Inria
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Richard, Jean-Pierre	Ecole Centrale De Lille
Nijmeijer, Hendrik	Eindhoven Univ of Technology
Keywords: Remote sensor data acquisition, Telecommunication-based automation systems, Remote and distributed control Abstract: In this paper, an event-triggered, data-rate constrained observer for discrete-time linear systems with perturbations is presented. The system is connected to a remote location by a communication channel which can only transmit limited numbers of bits per time interval. The system is subject to perturbations in its state as well as errors in the output measurement. The objective is to reconstruct estimates of the state at the remote location, by sending messages over the communication channel. A new type of data-rate constrained observer which can be more efficient in terms of communication rate is presented. Relation between an admissible communication rate and the system parameters is evaluated. The observer’s efficiency is illustrated by simulations.

VI115-08
Social Systems: Dynamics, Games and Control on Networks	Open Invited Session
Chair: Altafini, Claudio	Linkoping University
Co-Chair: Giua, Alessandro	University of Cagliari, Italy
Organizer: Como, Giacomo	Politecnico Di Torino
Organizer: Frasca, Paolo	CNRS, GIPSA-Lab, Grenoble
Paper VI115-08.1
PDF · Video · A Mixed Logical Dynamical Model of the Hegselmann–Krause Opinion Dynamics (I)
Bernardo, Carmela	University of Sannio
Vasca, Francesco	University of Sannio
Keywords: Dynamic Networks, Consensus, Multi-agent systems Abstract: The heterogeneous bounded confidence Hegselmann–Krause (HK) model has been widely considered in the literature for describing opinion dynamics. In this paper a mixed logical dynamical (MLD) representation of the HK model is proposed. The linear MLD model provides a compact representation where the different thresholds of the agents influence functions explicitly appear into the model inequalities. Numerical experiments of the proposed model are used to analyze how consensus and clustering are influenced by different agents confidence bounds.
Paper VI115-08.2
PDF · Video · Environmental Feedback Incorporated on a Collective Decision Making Model (I)
Baar, Wouter	University of Groningen
Bauso, Dario	University of Groningen
Keywords: Multi-agent systems, Consensus Abstract: We study a collective decision making model where each player needs to commit to one of two options. The fractions of committed individuals are the states of this evolutionary model. As element of novelty we incorporate environmental feedback to our model, which translates to system parameters that are now depending on the state of the system. In the first scenario of environmental feedback, we show how we reach a stable unique equilibrium that only depends on the factor of spontaneous commitment. In a second and third scenario, we show that under a suitable form of environmental feedback, we obtain limit cycles in the behavior. All our findings are covered by simulations.
Paper VI115-08.3
PDF · Video · A Setting for Rumor Containment Using Linear Threshold Models (I)
Yang, Lan	Xidian University
Ma, Ziyue	Xidian University
Li, Zhiwu	Xidian University
Giua, Alessandro	University of Cagliari, Italy
Keywords: Complex system management, Distributed optimisation for large-scale systems, Multi-agent systems Abstract: Rumor spreads fast in social networks and may produce significant damages to the society. Blocking users in online social networks is normally used as a technical measure to control information spread. In this work, we provide a non-linear formulation to minimize rumor spread in linear threshold networks by blocking a subset of nodes in the network.
Paper VI115-08.4
PDF · Video · Autocratic Strategies for Infinitely Iterated Multiplayer Social Dilemma Games (I)
Martirosyan, Emin	University of Groningen
Govaert, Alain	Groningen
Cao, Ming	University of Groningen
Keywords: Multi-agent systems, Stochastic control and game theory Abstract: In this work, we present results on autocratic strategies in infinitely repeated multiplayer games. Extending the previously developed theory for two-player games, we formulate necessary conditions for the existence of autocratic strategies in a standard multiplayer social dilemma game, namely the public goods game. The infinitely repeated game is designed with a discount factor that reduces the values of the future payoffs. The contribution of this work is an adaptation of existing theory on autocratic strategies to multiplayer games with arbitrary action spaces. We first show the existence of an autocratic strategy that uses a finite set of points from a continuous action space. Then, using a strategy concentrated on two points of the continuous interval representing the autocrat's available actions, we show the necessary conditions for the existence of autocratic strategies in the context of the public goods game.
Paper VI115-08.5
PDF · Video · Describing Government Formation Processes through Collective Multiagent Dynamics on Signed Networks (I)
Fontan, Angela	Linköping University
Altafini, Claudio	Linkoping University
Keywords: Multi-agent systems, Consensus Abstract: The formation of a government in parliamentary democracies can be seen as a collective decision-making process where the members of the parliament (the ``agents'') cast a vote of confidence (the ``decision'') to the candidate cabinet coalition. If no party or alliance has managed to attain the majority of the votes at the election, this coalition will be the outcome of government negotiation talks between the political parties, talks which often require a long period of time as the parties need to overcome their ideological differences. To explain this process, we propose a dynamical model of collective decision-making over the signed networks representing the parliament, where the signs describe the competitive and cooperative interactions among its members and the crossing of a bifurcation represents the completion of the negotiation process. The general philosophy is that the bifurcation parameter represents the social effort, identifiable with the duration of the cabinet negotiations, required from the political parties to reach a nontrivial decision (i.e., the confidence vote). In our model the social effort grows with the frustration of the parliamentary networks, that is, the amount of ``disorder'' encoded in the network. We show that indeed the frustration is a good indicator of the complexity of the government formation process by analyzing the legislative elections in 29 European countries with a parliamentary system in the last 40 years.
Paper VI115-08.6
PDF · Video · On a Centrality Maximization Game (I)
Castaldo, Maria	Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, GIPSA-Lab, F-38
Catalano, Costanza	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Multi-agent systems, Dynamic Networks, Control of networks Abstract: The Bonacich centrality is a well-known measure of the relative importance of nodes in a network. This notion is, for example, at the core of Google's PageRank algorithm. In this paper we study a network formation game where each player corresponds to a node in the network to be formed. The action of a player consists in the assignment of m out-links and his utility is his own Bonacich centrality. We study the Nash equilibria (NE) and the best response dynamics of this game. In particular, we provide a complete classification of the set of NE when m=1 and a fairly complete classification of the NE when m=2 . Our analysis shows that the centrality maximization performed by each node tends to create undirected and disconnected or loosely connected networks, namely 2-cliques for m=1 and rings or a special "Butterfly"-shaped graph when m=2. Our results build on locality property of the best response function in such game that we formalize and prove in the paper.
Paper VI115-08.7
PDF · Video · Limit Cycles in Replicator-Mutator Dynamics with Game-Environment Feedback (I)
Gong, Lulu	University of Groningen
Yao, Weijia	University of Groningen
Gao, Jian	University of Groningen
Cao, Ming	University of Groningen
Keywords: Complex system management, Stochastic control and game theory, Synthesis of stochastic systems Abstract: This paper considers the coevolutionary game and environment dynamics under mutations of strategies. Individuals' game play affects the dynamics of changing environments while the environment in turn affects the decision-making dynamics of individuals through modulating game payoffs. For some such closed-loop systems, we prove that limit cycles will never appear; however, in sharp contrast, after allowing mutations of strategies in these systems, the resulting replicator-mutator dynamics under environmental feedback may well exhibit Hopf bifurcation and limit cycles. We prove conditions for the Hopf bifurcation and thus the existence of stable limit cycles, and also illustrate these results using simulations. For the coevolutionary game and environment system, these stable limit cycles correspond to sustained oscillations of population's decisions and richness of the environmental resource.
Paper VI115-08.8
PDF · Video · On Imitation Dynamics for Potential Population Games Over Networks with Community Patterns (I)
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Zino, Lorenzo	University of Groningen
Keywords: Multi-agent systems, Control over networks Abstract: We study the asymptotic behavior of deterministic, continuous-time imitation dynamics for potential population games. In these dynamics, which is a general class of learning protocols that encompasses the replicator equation, players exchange information through pairwise interactions, whereby getting aware of the actions played by the others and the corresponding rewards. The pattern of interactions that regulates the learning process is determined by a community structure. We characterize the set of equilibrium points of the dynamics. Then, for the class of potential games and community networks that are undirected and connected, we prove global asymptotic convergence to the set of Nash equilibria of game.
Paper VI115-08.9
PDF · Video · Graphical Games and Decomposition (I)
Arditti, Laura	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Multi-agent systems, Stochastic control and game theory, Distributed optimisation for large-scale systems Abstract: We consider graphical games as introduced by Kearns et al. (2001). First we analyse the interaction of graphicality with a notion of strategic equivalence of games, providing a minimal complexity graphical description for games. Then we study the interplay between graphicality and the decomposition of games proposed by Candogan et al. (2011), characterizing the graphical properties of each part of the decomposition.
Paper VI115-08.10
PDF · Video · Systemic Risk and Network Intervention (I)
Damonte, Luca	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Multi-agent systems, Control over networks Abstract: We consider a novel adversarial shock/protection problem for a class of network equilibria models emerging from a variety of different fields as continuous network games, production networks, opinion dynamic models. The problem is casted into a min-max problem and analytically solved for two particular cases of aggregate performances: the mean square of the equilibrium or of its arithmetic mean. The main result is on the shape of the solutions, typically exhibiting a waterfilling type structure with the optimal protection concentrated in a proper subset of the nodes, depending significantly on the aggregate performance considered. The relation of the optimal protection with the Bonacich centrality is also considered.
Paper VI115-08.11
PDF · Video · Controlling Network Coordination Games (I)
Durand, Stephane	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Multi-agent systems Abstract: We study a novel control problem in the context of network coordination games: the individuation of the smallest set of players capable of driving the system, globally, from one Nash equilibrium to another one. Our main contribution is the design of a randomized algorithm based on a time-reversible Markov chain with provable convergence guarantees.
Paper VI115-08.12
PDF · Video · Learning Multiple Network Embeddings for Social Influence Prediction
Wang, Feng	China University of Geosciences
She, Jinhua	Tokyo Univ. of Tech
Ohyama, Yasuhiro	Tokyo University of Technology
Wu, Min	China University of Geosciences
Keywords: Social Computing, Computational Social Sciences, Social Networks Abstract: How to effectively predict social influence is an essential issue in social network analysis. Almost all reported methods for social influence prediction are mainly concerned with estimating influence probabilities for each linking edge. However, all of this past work cannot accurately predict influence probabilities for all edges due to the problem of data sparsity. Unlike conventional approaches, the main research of this paper focuses on exploring a cross problem for multiple network embeddings and social influence prediction. This study develops a new end-to-end approach, Multi-Influor, that learns multiple influence vectors for each user in social networks, instead of estimating influence probabilities for each edge. The multiple network embeddings consider multi-dimensional influence factors that incorporate pairwise node interactions, network structures, and global similarity comparisons. Moreover, this study solves the problem of influence evaluation caused by sparse observations. Extensive comparisons based on large-scale datasets indicate that the Multi-Influor approach outperforms several state-of-the-art baselines, and the experimental results demonstrate that the Multi-Influor approach is more practical on real-world social networks.
Paper VI115-08.13
PDF · Video · Inferring FOLLOW Relationship from Repost Relationship between Users on Sina Weibo
Hao, Xu	Fudan University
Li, Xiang	Fudan University
Keywords: Social Networks, Computational Social Sciences Abstract: In recent years, online social platforms such as sina weibo have been playing an increasingly important role in our lives. With the improvement of public awareness of privacy protection, however, it is increasingly difficult to obtain exhaustive direct data of FOLLOW relationship between users, which restricts the analysis and research on real online social networks. In the context of incomplete disclosure of information, we have to consider inferring from limited public data to more unknown information before further analysis and research with network topology. To overcome this obstacle, we try to recover the FOLLOW relationship by repost relationship. We collect repost data of six different bloggers on sina weibo to generate six independent networks, and propose an effective method to recover FOLLOW relationship between users. Our method is superior to other existing methods, and helps us draw a conclusion that two users establishing an indirect repost relationship with other two users, compared to other indirect relationship, are of greater possibility to maintain the FOLLOW relationship. At the same time, we also extend our method to greatly improve the recovering accuracy.

VI115-09
Consensus	Regular Session
Chair: Ferrari-Trecate, Giancarlo	Ecole Polytechnique Fédérale De Lausanne
Co-Chair: Fujisaki, Yasumasa	Osaka Univ
Paper VI115-09.1
PDF · Video · Feedback Synchronization in Persidskii Systems
Mei, Wenjie	Inria
Efimov, Denis	Inria
Ushirobira, Rosane	Inria
Keywords: Consensus Abstract: A general synchronization scheme for the common dynamics of Persidskii systems is presented in this paper. The conditions of output stability of the closed-loop systems and their synchronization are established in the form of linear matrix inequalities (LMI). An example of Chua’s circuit is considered for examining the effectiveness of our proposed results. A designing method of feedback gains is also introduced.
Paper VI115-09.2
PDF · Video · Convergence and Stability Properties of a Dynamic Maximum Consensus Estimator
Monteiro, João C.	Universidade Federal Do Rio De Janeiro
Peixoto, Alessandro Jacoud	COPPE/Federal University of Rio De Janeiro (UFRJ)
Keywords: Consensus Abstract: In this paper, we present a novel dynamic consensus algorithm capable of tracking the maximum value of a given measurement in a distributed network. Each node in the network implements a sliding-mode based algorithm and only uses the information provided by its neighbors to track this maximum value on the network. Thus, at any given time, a network node is not allowed to disclose information from one of its neighbors to any other neighbor. We demonstrate the convergence and stability properties of this technique and provide a guide to select the control parameters, initial conditions, and sampling period for discrete-time implementations. From a practical perspective, the proposed technique is very promising since it relies on selecting only three parameters, which are the same for the whole network, and solving one numerical integration on each node. Numerical simulations illustrate the results and help visualize the algorithm transient behavior.
Paper VI115-09.3
PDF · Video · Synchronization in Networks of Systems with Synchronous/asynchronous Sampled-Data Couplings
Sakai, Kanako	Tokyo Metropolitan University
Yoshida, Iori	Tokyo Metropolitan University
Oguchi, Toshiki	Tokyo Metropolitan University
Keywords: Consensus, Control over networks, Multi-agent systems Abstract: This paper considers the network synchronization problem of nonlinear systems with sampled-data couplings. In particular, we focus on sufficient conditions for full synchronization of systems interconnected via sampled-data couplings. We have already derived a sufficient condition for synchronization of two mutual coupled systems whose outputs are simultaneously measured with the same constant sampling interval. By extending the result, in this paper, we show that the network synchronization condition can be estimated from that of two coupled systems by scaling the stability region with a factor related to the eigenvalues of the graph Laplacian. Furthermore, we discuss the effect of asynchronous sampling on synchronization. Numerical simulations illustrate the validity of the obtained results.
Paper VI115-09.4
PDF · Video · Leader-Following Consensus Control of Nabla Discrete Fractional Order Multi-Agent Systems
Ma, Jiayue	University of Electronic Science and Technology of China
Hu, Jiangping	University of Electronic Science and Technology of China
Zhao, Yiyi	Southwestern University of Finance and Economics
Ghosh, Bijoy	Texas Tech University
Keywords: Consensus, Distributed control and estimation, Multi-agent systems Abstract: This paper studies a consensus problem for discrete-time linear nabla fractional order multi-agent systems with Riemann-Liouville difference operator. With the help of the discrete fractional Lyapunov direct method, a state feedback stabilization problem of a discrete-time linear nabla fractional order system is firstly analyzed. Then a distributed consensus control law is proposed for a discrete-time linear nabla fractional order multi-agent system. Some sufficient conditions are presented to guarantee that the leader-following consensus can be achieved by the proposed algorithm. The control gain is determined according to an algebraic Riccati inequality. Finally, simulation results are presented to demonstrate the effectiveness of theoretical analysis.
Paper VI115-09.5
PDF · Video · Distributed Algorithm for Higher-Order Integrators to Track Average of Unbounded Signals
Sen, Arijit	IIT KANPUR
Sahoo, Soumya Ranjan	Indian Institute of Technology Kanpur
Kothari, Mangal	Indian Institute of Technology Kanpur
Keywords: Consensus, Multi-agent systems, Coordination of multiple vehicle systems Abstract: In this work, we design an algorithm for a group of higher-order integrators aiming to track the average of multiple time-varying and possibly unbounded reference signals. The existing literature has studied distributed average tracking (DAT) for higher-order systems in the presence of bounded or Lipschitz-type reference signals. In such DAT algorithms, each agent requires the knowledge of global bounds on signals for bounded references and state-dependent control gains for unbounded references. Addressing these issues, we propose a DAT algorithm for a group of higher-order integrators in the presence of time-varying references that can possibly be unbounded. The highest derivative of references become equal, asymptotically. Agents use neighbors' data obtained from the local communication framework that makes the current algorithm distributed in nature. In contrast to existing work, our DAT algorithm uses constant gains to reduce high control effort, which may be caused due to state-dependent gains. Using numerical example, the performance of the current algorithm is compared with the existing state-of-the-art. This reveals the superiority of the proposed algorithm.
Paper VI115-09.6
PDF · Video · Leader-Following Consensus of Linear Fractional-Order Multi-Agent Systems Via Event-Triggered Control Strategy
Bo, Chen	University of Electronic Science and Technology of China
Hu, Jiangping	University of Electronic Science and Technology of China
Zhao, Yiyi	Southwestern University of Finance and Economics
Ghosh, Bijoy	Texas Tech University
Keywords: Consensus, Multi-agent systems, Distributed control and estimation Abstract: Many complex systems can be more accurately described by fractional-order models. In this paper, a leader-following consensus problem of fractional-order multi-agent systems (FOMASs) is firstly formulated and then an event-trigger consensus control is proposed for each agent. Under the assumption that the interconnection network topology has a spanning tree, consensus of the closed-loop FOMAS is analyzed with the help of the Mittag-Leffler functions and stability theory of fractional-order differential equations. It is shown that Zeno behavior can be avoided. Simulation results are presented to demonstrate the effectiveness of the theoretical results.
Paper VI115-09.7
PDF · Video · Consensusability of Linear Interconnected Multi-Agent Systems
Turan, Mustafa Sahin	Ecole Polytechnique Fédérale De Lausanne
Xu, Liang	Swiss Federal Institute of Technology Lausanne
Ferrari-Trecate, Giancarlo	Ecole Polytechnique Fédérale De Lausanne
Keywords: Consensus, Multi-agent systems, Distributed control and estimation Abstract: Consensusability is an important property for many multi-agent systems (MASs) as it implies the existence of networked controllers driving the states of MAS subsystems to the same value. Consensusability is of interest even when the MAS subsystems are physically coupled, which is the case for real-world systems such as power networks. In this paper, we study necessary and sufficient conditions for the consensusability of linear interconnected MASs. These conditions are given in terms of the parameters of the subsystem matrices, as well as the eigenvalues of the physical and communication graph Laplacians. Our results show that weak coupling between subsystems and fast information diffusion rates in the physical and communication graphs favor consensusability. Technical results are verified through computer simulations.
Paper VI115-09.8
PDF · Video · EDC: Exact Dynamic Consensus
Aldana-López, Rodrigo	Universidad De Zaragoza
Aragues, Rosario	Universidad De Zaragoza
Sagues, Carlos	Universidad De Zaragoza
Keywords: Consensus, Multi-agent systems, Distributed control and estimation Abstract: This article addresses the problem of average consensus by a multi-agent system when the desired consensus quantity is a time varying signal, in particular the average of individual time varying signals localized at the agents. Although this problem has been addresses in existing literature by linear schemes, only bounded steady-state errors has been achieved. In this work, we propose a new exact dynamic consensus algorithm which leverages high order sliding modes to achieve zero steady-state error of the average of time varying reference signals in a group of agents. Moreover, our proposal is also able to achieve consensus to high order derivatives of the average signal, if desired. Finally, the effectiveness and advantages of our proposal are shown with concrete simulation scenarios.
Paper VI115-09.9
PDF · Video · Distributed Finite-Time Bipartite Consensus of Multi-Agent Systems Via Event-Triggered Control
Xu, Peng	Dalian Maritime University
Wang, Xinyu	DMU
Xie, Guangming	Peking University
Tao, Jin	Aalto University
Xu, Minyi	Dalian Maritime University
Zhou, Quan	Aalto University
Keywords: Consensus, Multi-agent systems, Event-based control Abstract: This paper investigates a distributed finite-time event-triggered bipartite consensus control for multi-agent systems. Under scenarios of energy limitation, an event-triggered strategy coupled with a nonlinear distributed control protocol is proposed only relying on local information, where the controller only updates at triggered instants. We proved that when the antagonistic network contains a spanning tree, the event-triggered controller can drive all agents to reach consensus value with an identical magnitude but opposite signs. Moreover, both the convergence time depending on the initial state and the positive lower bound of inter-event times are achieved. Simulation results show that the proposed controller has better disturbance rejection properties and can achieve bipartite consensus faster compared to an asymptotic controller.
Paper VI115-09.10
PDF · Video · On the Asymptotic Stability of Directed Nonlinear Multiagent Network Via Nonlinear Control Protocol
Liang, Quanyi	National University of Singapore
Ong, Chong-Jin	National Univ of Singapore
She, Zhikun	School of Mathematics and Systems Science, Beihang University
Keywords: Consensus, Multi-agent systems, Nonlinear adaptive control Abstract: In this paper, we investigate the asymptotic stability of nonlinear agents in a directed network using a nonlinear protocol. Inspired by the V-uniformly decreasing condition, we introduce a new condition to characterize the nonlinearity of the agents, and use it to design the distributed nonlinear control protocol for the agents. Under certain conditions, we construct proper Lyapunov function to show that the agents can achieve asymptotic stability via our nonlinear control protocol. Especially, if there exist agents that are asymptotically stable, then the multiagent network must be asymptotically stable as long as the control strengths of unstable agents are large enough. Finally, an example is given to illustrate the effectiveness of our theoretical results.
Paper VI115-09.11
PDF · Video · Prescribed Performance Consensus of Heterogeneous Quantized High-Order Uncertain Multi-Agent Systems
Kechagias, Andreas	Aristotle University of Thessaloniki
Rovithakis, George	Aristotle University of Thessaloniki
Keywords: Consensus, Multi-agent systems, Quantized systems Abstract: We consider the problem of guaranteeing output consensus, with prescribed transient and steady-state performance bounds, for a class of uncertain, heterogeneous, high-order, nonlinear multi-agent systems, in a leader-following scheme. The proposed control protocol is decentralized and of low-complexity. An interesting feature is that information (state measurements, control inputs) is exchanged only in quantized form. For that purpose, uniform-hysteric quantizers are utilized. Simulations illustrate the effectiveness of the approach.
Paper VI115-09.12
PDF · Video · Analysis of Quantized Consensus with Subtractive Dither
Morita, Ryosuke	Gifu Univ
Horie, Fuya	Gifu Univ
Ito, Satoshi	Gifu Univ
Keywords: Consensus, Multi-agent systems, Quantized systems Abstract: This paper presents a performance analysis of the average consensus for multi-agent systems, where the information exchange between agents in the system is quantized by subtractive dither method. The performance is evaluated by the distance from average. The estimated value depends on quantization noises and the correlation between separated edges.
Paper VI115-09.13
PDF · Video · Disruption Via Grounding and Countermeasures in Discrete-Time Consensus Networks
Yan, Yamin	The University of Newcastle
Stuedli, Sonja	The Univeristy of Newcastle
Seron, Maria	The Univ of Newcastle
Middleton, Richard	The University of Newcastle
Keywords: Consensus, Multi-agent systems, Secure networked control systems Abstract: We investigate the disruption of discrete-time consensus problems via grounding. Loosely speaking, grounding a network occurs if the state of one agent no longer responds to inputs from other agents and/or changes its dynamics. Then, the agent becomes a leader or a so-called stubborn agent. The disruption of the agent can be caused by internal faults, safety protocols or externally due to a malicious attack. In this paper we investigate how the grounding affects the eigenratio of expander graph families that usually exhibit good scaling properties with increasing network size. It is shown that the algebraic connectivity and eigenratio of the network decrease due to the grounding causing the performance and scalability of the network to deteriorate, even to the point of losing consensusability. We then present countermeasures to such disruptions in both passive and active manners. Our findings are supported by numerical simulations given within the paper.
Paper VI115-09.14
PDF · Video · On the Geometry of Consensus Algorithms with Application to Distributed Termination in Higher Dimension
Melbourne, James	University of Minnesota - Twin Cities
Saraswat, Govind	University of Minnesota - Twin Cities
Khatana, Vivek	University of Minnesota - Twin Cities
Patel, Sourav	University of Minnesota - Twin Cities
Salapaka, Murti V.	University of Minnesota, Twin Cities
Keywords: Consensus, Multi-agent systems, Sensor networks Abstract: We present insights into the geometry of the ratio consensus algorithm that lead to finite time distributed stopping criteria for the algorithm in higher dimension. In particular we show that the polytopes of network states indexed by time form a nested sequence. This monotonicity allows the construction of a distributed algorithm that terminates in finite time when applied to consensus problems in any dimension and guarantees the convergence of the consensus algorithm in norm, within any given tolerance. The practical utility of the algorithm is illustrated through MATLAB simulations.
Paper VI115-09.15
PDF · Video · Distributed Average Consensus under Quantized Communication Via Event-Triggered Mass Splitting
Rikos, Apostolos I.	Univesity of Cyprus
Hadjicostis, Christoforos	University of Cyprus
Keywords: Consensus, Multi-agent systems, Sensor networks Abstract: We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the agents, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we present and analyze a distributed averaging algorithm which operates exclusively with quantized values (specifically, the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed distributed averaging protocol and show that its execution, on any time-invariant and strongly connected digraph, will allow all agents to reach, in finite time, a common consensus value that is equal to the quantized average. We conclude with comparisons against existing quantized average consensus algorithms that illustrate the performance and potential advantages of the proposed algorithm.
Paper VI115-09.16
PDF · Video · Dynamic Privacy-Preserving Collaborative Schemes for Average Computation
Wang, Xin	Zhejiang University
Ishii, Hideaki	Tokyo Institute of Technology
He, Jianping	Shanghai Jiao Tong University
Cheng, Peng	Zhejiang University
Keywords: Consensus, Secure networked control systems Abstract: In this paper, we consider the privacy-preserving problem in collaborative computing. Based on a two-step average computation framework, we propose three privacy-aware schemes, all of which achieve different levels of privacy protections depending on data servers' trust degrees. Further, by carefully designing noises injected to the distributed computing process, we obtain dynamic privacy-preserving schemes, whose privacy preserving levels are measured by Kullback-Leibler differential privacy. In addition, we prove that the proposed schemes achieve convergence in different senses. Numerical experiments are finally conducted to verify the obtained privacy properties and convergence guarantees.
Paper VI115-09.17
PDF · Video · Output Sign-Consensus of Heterogenous Multi-Agent Systems: An Observer-Based Approach
Sun, Zhenyu	Southwest Jiaotong University
Zhang, Hongwei	Southwest Jiaotong Univ
Keywords: Multi-agent systems, Consensus, Adaptive control of multi-agent systems Abstract: This paper studies output sign-consensus of heterogeneous multi-agent systems over directed signed graphs. To remove the restriction that every follower knows the dynamics of the leader system, a distributed observer is maintained by each follower nodes, such that the state and dynamics of the leader node is estimated. Then a distributed state feedback control law is designed and analyzed. A simulation example is presented to illustrate the effectiveness of the proposed control law.
Paper VI115-09.18
PDF · Video · Evolution of Self-Confidence in Opinion Dynamics Over Signed Network
Bhowmick, Sourav	Indian Institute of Information Technology Guwahati
Panja, Surajit	Indian Institute of Information Technology Guwahati
Keywords: Multi-agent systems, Consensus, Control of networks Abstract: This paper discusses the evolution of self-confidence of individuals in Degroot-Friedkin (D-F) model when they interact along sequences of issues over a signed network. The underlying strongly connected signed network contains both positive and negative influences on the opinions of the individuals. It has been shown in this work that the opinions of the individuals under this network polarize into two groups with the individuals attaining same asymptotic opinion value within the same group while asymptotic opinion values having same magnitude, opposite in sign for different group. The evolution of self-confidences of the individuals along sequences of issues have been shown and they are found to converge to an equilibrium contained in an n-simplex. The numerical simulations validate the theoretical results obtained in the work.
Paper VI115-09.19
PDF · Video · An Alternative Method for Optimal Consensus Protocol Design for Scalar Single-Integrators Using Krotov Conditions
Kumar, Avinash	IIT Mandi
Jain, Tushar	Indian Institute of Technology Mandi
Keywords: Multi-agent systems, Consensus, Control under communication constraints Abstract: This article proposes a novel alternative approach for optimal consensus protocol design for scalar single-integrator multi-agent systems based on the Krotov methodology. The problem under consideration generally turns out to be non-convex due to the desired diffusive nature (i.e. using only relative information from the neighboring agents) of the control input. This work employs the Krotov framework which transforms the optimal control problem into another equivalent optimization problem via the selection of so-called Krotov function whose selection is ad-hoc. The formulation of this equivalent optimization problem provides sufficient conditions for the existence of globally optimal control law(s) and it is generally solved using iterative methods because of non-convex characteristics. In this work, these conditions are used to solve the optimal consensus protocol design problem for the single-integrator multi-agent systems by choosing the Krotov function in such a way the equivalent optimization problem can be solved non-iteratively and at the same time, the obtained optimal control law has the desired structure (as necessitated by the communication topology). The proposed method is demonstrated by a numerical example.
Paper VI115-09.20
PDF · Video · Robust Consensus and Connectivity-Maintenance under Edge-Agreement-Based Protocols for Directed Spanning Tree Graphs
Restrepo, Esteban	ONERA - the French Aerospace Lab
Loria, Antonio	CNRS
Sarras, Ioannis	ONERA-The French Aerospace Lab
Marzat, Julien	ONERA - the French Aerospace Lab
Keywords: Multi-agent systems, Consensus, Control under communication constraints Abstract: We address the consensus problem with connectivity maintenance for networks of multi-agent systems interconnected over directed spanning tree graphs in the edge-agreement space and, for the first time in the literature, we provide a strict Lyapunov function. The importance of this contribution is that it allows to establish uniform global asymptotic stability of the consensus manifold for a multi-agent system subject to proximity constraints. Moreover, robustness in the sense of input-to-state stability with respect to external disturbances is also established. These properties have not been established before when dealing with state-dependent constraints, even for a class of directed graphs, because most often in the literature only non-uniform convergence to the consensus manifold is established.
Paper VI115-09.21
PDF · Video · Rotating Consensus of Second-Order Multi-Agent Systems with Signed Directed Graphs
Yang, Yanhua	Central South University
Hu, Wenfeng	Central South University
Keywords: Multi-agent systems, Consensus, Coordination of multiple vehicle systems Abstract: This paper investigates the rotating motion control for a class of second-order multi-agent systems with both cooperative and antagonistic interactions. Compared with some existing results, the multi-agent systems are assumed to have a signed directed graph rather than an undirected graph. By using the local relative information, we design a control protocol and give a sufficient condition for rotating consensus problem with antagonistic networks. Furthermore, we derive the lower bound of parameters in the control protocol. Finally, the correctness of our results is confirmed by the simulation results.
Paper VI115-09.22
PDF · Video · Exploiting Wireless Interference for Distributively Solving Linear Equations
Molinari, Fabio	Technische Universitaet Berlin
Raisch, Joerg	Technische Universitaet Berlin
Keywords: Multi-agent systems, Consensus, Distributed control and estimation Abstract: Interference in wireless communication is generally considered as an undesired phenomenon which needs to be combatted. Unlike traditional approaches, this paper investigates the possibility of exploiting interference for the cooperative solution of a linear algebraic equation, of which each agent knows only a portion. The presented communication system, together with the designed iterative algorithm, guarantees that agents converge exponentially to a global solution (unique or non-unique) of the algebraic linear equation, notwithstanding the presence of the unknown fading wireless channel. Guaranteeing privacy is one of the benefits of this approach: the unknown fading channel prohibits the access to neighboring agents’ local equations. Such a feature is extremely useful in case local equations contain sensitive information. Randomized simulations reinforce our theoretical results.
Paper VI115-09.23
PDF · Video · Event-Triggered for Rotating Consensus with Double-Integrator Multi-Agent Systems
Shi, Xiongtao	Central South University
Li, Yonggang	Central South University
Sun, Bei	Central South University
Keywords: Multi-agent systems, Consensus, Distributed control and estimation Abstract: This paper investigates the rotating consensus problem for a class of double-integrator multi-agent systems, where the communication networks are directed. Firstly, for convenience, we transform the original rotating consensus problem in complex field to real field by a rotation matrix. Secondly, an event-triggered mechanism with the ability to predict the system state based on known triggered state is introduced, without requiring continuous communication among agents. Thirdly, based on the rotating consensus problem and the proposed event-triggered mechanism, a distributed control protocol is developed, in which the rotating consensus will be reached with an exponential convergence rate. Then, it is shown that, with the proposed event-triggering mechanism, a strictly positive lower bound between any two consecutive triggering instants can be guaranteed, that is, Zeno-freeness can be guaranteed. Finally, the simulation example is provided to illustrate the effectiveness of the proposed control protocol.
Paper VI115-09.24
PDF · Video · Synchronization of Heterogeneous Dynamical Networks Via Phase Analysis
Wang, Dan	The Hong Kong University of Science and Technology
Chen, Wei	Peking University
Qiu, Li	Hong Kong Univ. of Sci. & Tech
Keywords: Multi-agent systems, Consensus, Dynamic Networks Abstract: This paper is concerned with the synchronization of heterogeneous agents interacting over a dynamical network, where the edge dynamics are heterogeneous, modeling the nonuniform communication environment between the agents. Novel synchronization conditions are obtained from a phasic perspective by utilizing a newly formulated small phase theorem. These conditions have lower conservatism compared to gain-based conditions and generalize positive real and negative imaginary type conditions. They scale well with the size of the network and reveal the trade-off between the phases of node dynamics and edge dynamics.
Paper VI115-09.25
PDF · Video · Output Feedback Consensus of Multi-Agent Systems with Generalized Uniformly Joint-Connected Switching Networks
Su, Youfeng	Fuzhou University
Lee, Ti-Chung	Univ. of Science and Technology
Keywords: Multi-agent systems, Consensus, Hybrid and switched systems modeling Abstract: This paper presents an output feedback synthesis for leader-follower consensus of linear multi-agent systems with switching networks. We first establish uniform global exponential stability (UGES) for a class of cascaded linear switched systems by adopting weak zero-state detectibility (WZSD). Then a distributed output feedback controller is proposed based on the certainty equivalent principle, employing the neighborhood output estimation error only. A generalized uniformly joint-connected condition for switching networks is provided to check WZSD without any dwell-time condition.
Paper VI115-09.26
PDF · Video · Observer-Based Output Feedback Consensus Protocol for Double-Integrator Multi-Agent Systems under Intermittent Sampled Position Measurements
Poulsen, Dylan	Washington College
Defoort, Michael	University of Valenciennes
Djemai, Mohamed	UVHC
Keywords: Multi-agent systems, Consensus, Stability and stabilization of hybrid systems Abstract: This paper deals with the leader-follower consensus problem for double-integrator multi-agent systems using sampled position data information. An observer-based output feedback controller is designed to study this problem while taking into account intermittent sensor failures. The non-uniformity and randomness of the sampling times due to intermittent information lead to a mu-varying linear system on a discrete stochastic time domain for the closed-loop system dynamics (here mu is the graininess function). Some necessary and sufficient conditions for the observer and controller gains are derived, using positive perturbation and Lyapunov operators on the space of symmetric matrices, to guarantee mean-square exponential stability for the observation and tracking errors. Some simulation results illustrate the effectiveness of the proposed observer-based output feedback controller.
Paper VI115-09.27
PDF · Video · Optimal Control Points Problem in Domination Game on Large Scale Multi-Agent Systems
Suzuki, Tomomitsu	The University of Tokyo
Tsumura, Koji	The University of Tokyo
Keywords: Multi-agent systems, Control of networks, Consensus Abstract: In this paper, we deal with large-scaled multi-agent consensus systems in which some agents are assumed to be weakly controlled with feedback and consider a domination game between several players. We assume that each player can choose a set of controlled agents and input signals to control the states of all the agents to its own desired reference state. The reference states of the players are assumed to be different from each other, therefore, a conflict occurs between the players. The problem for each player is to choose a set of controlled agents to dominate the whole system as possible and we call this as a domination game. To find the optimal set of the controlled agents is essentially a complex combination problem, however, in this paper, we show that the optimal set can be given by small calculations. This result provides a strategy to the players for the domination game and we discuss the relationship between the structure of networks and monopolistic/equally domination games.
Paper VI115-09.28
PDF · Video · Scaled Group Consensus Over Weakly Connected Structurally Balanced Graphs
Hanada, Kenta	Osaka University
Wada, Takayuki	Osaka University
Masubuchi, Izumi	Kobe University
Asai, Toru	Nagoya University
Fujisaki, Yasumasa	Osaka Univ
Keywords: Multiagent systems, Decentralized and distributed control, Efficient strategies for large scale complex systems Abstract: A graph Laplacian based distributed protocol that can achieve a group consensus over weighted, signed, directed, and weakly connected graphs is investigated. It is said to achieve the group consensus if the state of agents who belong to the same group converges to a common value, while the one of agents who belong to another group converges to a different value. It is assumed that no agent knows which group she belongs to before the protocol is executed. In this paper, for a given signed graph which contains a directed spanning tree, namely, at least one leader that can affect all of the other agents, a definition of n-structurally balanced is proposed. It is emphasized that this definition is a generalization of the structurally balanced which leads a bipartite consensus. Then, necessary and sufficient conditions are established to guarantee the agents' state reaching the group consensus. The results are illustrated through numerical examples.
Paper VI115-09.29
PDF · Video · Disturbance Induced Synchronization in Networked Oscillatory System
Joshi, Shyam Krishan	Indian Institute of Technology, Delhi, New Delhi, India
Keywords: Bio-signals analysis and interpretation, Biomedical system modeling, simulation and visualization Abstract: The problem of synchronization of oscillators which are not coupled directly but are connected to a common disturbance has been studied in this work. Mathematical formalisms to obtain sufficient coupling gain for synchronization of complex network of oscillators forced by a common disturbance have been developed. The Lyapunov stability approach using quadratic Lyapunov function and non-smooth Lyapunov function has been used for the purpose. The networked oscillatory systems considered are formed by Van der Pol and Fitzhugh Nagumo oscillators independently. These oscillators are diffusively coupled to common disturbance. The comparison of analytical approaches has been done and the results are validated through numerical simulations.
Paper VI115-09.30
PDF · Video · Maximal Delay Range for Robust Consensus Achieved by PID-Type Control Protocol with Time-Varying Delay
Ma, Xueyan	Northeastern University
Ma, Dan	Northeastern University
Keywords: Robustness analysis, Systems with time-delays Abstract: In this paper, we examine the maximal delay range for robust consensus by using PID-type control protocol for linear first-order multi-agent systems subject to time-varying delays. We derive explicit lower bounds for guaranteed robust consensus of first-order unstable agents collaborated with each other under PID-type control protocol with time-varying delays, which provide a priori the range of delay over which the multi-agent system is guaranteed to obtain robustly consensus by proportional (P) and proportional-derivative (PD) protocols for undirected graphs respectively. The results show how the agent dynamics and graph connectivity may fundamentally limit the range of delay tolerable. They also indicate that the derivative control protocol provides an added benefit to increase the allowable delay range by incorporating the delay variation rate. Finally, the numerical examples are used to illustrate the effectiveness of the proposed theoretical results.

VI115-10
Control under Communication Constraints	Regular Session
Chair: Ishii, Hideaki	Tokyo Institute of Technology
Co-Chair: Vargas, Francisco J.	Universidad Técnica Federico Santa María
Paper VI115-10.1
PDF · Video · DoS-Aware Quantized Control of Nonlinear Systems Via Linearization
Kato, Rui	Tokyo Institute of Technology
Cetinkaya, Ahmet	National Institute of Informatics
Ishii, Hideaki	Tokyo Institute of Technology
Keywords: Control over networks, Control under communication constraints, Control and estimation with data loss Abstract: This paper deals with a quantized feedback stabilization problem of nonlinear networked control systems via linearization. In particular, we study circumstances where the communication channel is interrupted by Denial-of-Service (DoS) attacks and its data rate is limited. We employ a deterministic DoS attack model which constraints the amount of attacks only by their frequency and duration, allowing us to capture a large class of potential attacks. To achieve asymptotic stabilization, we propose a resilient dynamic quantizer in the sense that it does not saturate in the presence of packet losses caused by DoS attacks. A sufficient condition for stability is derived by restricting the average frequency and duration of attacks. Since our result only guarantees local stability, we explicitly investigate an estimate of the region of attraction, which may be reduced by attacks. A simulation example is presented for demonstration of our results.
Paper VI115-10.2
PDF · Video · Topological Entropy and Minimal Data Rate for State Observation of LTV Systems
Berger, Guillaume	UCLouvain
Jungers, Raphaël M.	Université Catholique De Louvain
Keywords: Control under communication constraints Abstract: In this paper, we show that the topological entropy of linear time-varying systems coincide with their minimal data rate for state observation, thereby extending the well-known ``observation data rate'' theorem for LTI systems and time-invariant nonlinear systems with compact domain. This result is relevant for the problem of controlling and observing dynamical systems via limited-capacity communication networks, as it provides a tight bound on the data rate required for the state observation of these systems. This bound, which relies only on the topological properties of the system, can thus be used as a benchmark for the comparison of different implementations of coders--decoders observing the system.
Paper VI115-10.3
PDF · Video · An Alternative Setup to Study Stabilization of Networked Control Systems Over Correlated Fading Channels
Maass, Alejandro I.	The University of Melbourne
Zamora, Jimmy	Universidad Técnica Federico Santa Maria
Vargas, Francisco J.	Universidad Técnica Federico Santa María
Keywords: Control under communication constraints, Control over networks Abstract: This paper studies stability of control systems over a communication network with spatially correlated fading channels. We consider a multiple-input multiple-output linear time-invariant discrete-time closed-loop system in which communications are done through multiple correlated multiplicative channels. Particularly, we provide conditions that relate the stability of the above networked control system (NCS) to the stability of an auxiliary closed-loop system that replaces the multiplicative channels by additive noise channels. This provides a simple framework to analyse NCSs over correlated multiplicative channels since standard linear systems tools can be used to analyse stability as opposed to consider the multiplicative non-linearity explicitly in the analysis. Thereby, we extend existing results in the literature that contain similar conditions for uncorrelated channels only.
Paper VI115-10.4
PDF · Video · Distributed Linear Quadratic Regulator Robust to Communication Dropouts
Amo Alonso, Carmen	California Institute of Technology
Ho, Dimitar	Caltech
Maestre, Jose M.	University of Seville
Keywords: Control under communication constraints, Control over networks, Distributed control and estimation Abstract: We present a solution to deal with information package dropouts in distributed controllers for large-scale networks. We do this by leveraging the System Level Synthesis approach, a control framework particularly suitable for large-scale networks that addresses information exchange in a very transparent manner. To this end, we propose two different schemes for controller synthesis and implementation. The first one synthesizes a controller inherently robust to dropouts, which is later implemented in an offline fashion. For the second approach, we synthesize a collection of controllers offline and then switch between different controllers online depending on the current dropouts detected in the system. The two approaches are illustrated and compared by means of a simulation example.
Paper VI115-10.5
PDF · Video · Input-To-State Stability of Networked and Quantized Control Systems
Ren, Wei	KTH Royal Institute of Technology
Xiong, Junlin	University of Science and Technology of China
Keywords: Control under communication constraints, Hybrid and switched systems modeling, Networked embedded control systems Abstract: This paper studies input-to-state stability of networked and quantized control systems with external disturbances. Since the external disturbance is considered, the state may escape from the quantization regions, which thus leads to the introduction of the quantization mechanism with zooming-out and zooming-in stages. We first propose a novel hybrid system to incorporate both the open-loop and closed-loop systems. Based on the developed hybrid model, we establish the boundedness of the state in the zooming-out stage, and the convergence of the state in the zooming-in stage. Furthermore, sufficient conditions are established for input-to-state stability in the case of switching between the zooming-in and zooming-out stages. Finally, a numerical example is presented to illustrate the obtained results.
Paper VI115-10.6
PDF · Video · Stability Analysis of Multivariable Digital Control Systems with Uncertain Timing
Gaukler, Maximilian	Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Roppenecker, Günter	Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Ulbrich, Peter	Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Keywords: Control over networks, Networked embedded control systems Abstract: The ever increasing complexity of real-time control systems results in significant deviations in the timing of sensing and actuation, which may lead to degraded performance or even instability. In this paper we present a method to analyze stability under mostly-periodic timing with bounded uncertainty, a timing model typical for the implementation of controllers that were actually designed for strictly periodic execution. In contrast to existing work, we include the case of multiple sensors and actuators with individual timing uncertainty. Our approach is based on the discretization of a linear impulsive system. To avoid the curse of dimensionality, we apply a decomposition that breaks down the complex timing dependency into the effects of individual sensor-actuator pairs. Finally, we verify stability by norm bounding and a Common Quadratic Lyapunov Function. Experimental results substantiate the effectiveness of our approach for moderately complex systems.
Paper VI115-10.7
PDF · Video · Prescribed Performance Tracking Using State Quantization for Uncertain Feedback Linearizable Systems
Bikas, Lampros	Aristotle University of Thessaloniki
Rovithakis, George	Aristotle University of Thessaloniki
Keywords: Quantized systems Abstract: This paper addresses the problem of imposing pre-defined performance characteristics (by means of maximum steady-state error and minimum convergence rate) on the output tracking errors for a class of uncertain multi-input multi-output (MIMO) nonlinear system in the presence of state quantization implemented by uniform-hysteretic quantizers. A low-complexity control design that requires reduced system knowledge and utilizes only quantized measurements of the state is proposed. The desired performance is achieved by assuming knowledge of the stepsize of the quantizers involved. Simulation results verify the theoretical findings.
Paper VI115-10.8
PDF · Video · How to Simulate Networked Control Systems with Variable Time Delays?
Steinberger, Martin	Graz University of Technology
Tranninger, Markus	Graz University of Technology
Horn, Martin	Graz University of Technology
Johansson, Karl H.	Royal Institute of Technology
Keywords: Control over networks Abstract: Techniques to accurately simulate networked control systems with bounded time-varying delays are proposed. They link delays in transmission channels to individual packets and can take into account packet disordering that may occur in wireless multi-hop networks. Examples underpin the properties of the proposed approach and show why other simulation and modeling approaches may fail.
Paper VI115-10.9
PDF · Video · Stability Analysis of Polytopic Markov Jump Linear Systems with Applications to Sequence-Based Control Over Networks
Rosenthal, Florian	Karlsruhe Institute of Technology
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Control over networks, Hybrid and switched systems modeling, Control under communication constraints Abstract: This paper deals with sequence-based control over networks with time-varying and generally unknown delay and loss probabilities. We show that the problems of stability analysis and controller synthesis can be addressed using a polytopic Markov jump linear system describing an augmented system. For this kind of systems, we derive a necessary and sufficient condition for mean square stability that extends existing results in literature. Likewise, we provide a sufficient condition for mean square stabilizability in terms of an LMI feasibility test. The results are illustrated in a numerical example.

VI115-11
Coordination of Multiple Vehicle Systems	Regular Session
Chair: Batista, Pedro	Instituto Superior Técnico, Universidade Técnica De Lisboa
Co-Chair: Nguyen, Dinh Hoa	Kyushu University
Paper VI115-11.1
PDF · Video · Synchronization of a Swarm of Unicycle Robots Using Dynamic Control
Ruiz, Isaac	Robotics and Advanced Manufacturing Program CINVESTAV
Morales, America	CINVESTAV SALTILLO
Pena Ramirez, Jonatan	Center for Scientific Research and Higher Education at Ensenada
Keywords: Coordination of multiple vehicle systems, Consensus, Control of networks Abstract: This paper proposes a dynamic controller for a swarm of unicycle robots following a desired trajectory and maintaining a prescribed formation. Furthermore, a comparison of the proposed dynamic controller versus a traditional static feedback controller is presented.The stability analysis of the closed loop system is determined by using the Lyapunov stability theory and the theoretical results are numerically illustrated. Also a comparison in terms of energy, between the proposed dynamic controller and the classical static feedback controller is provided.
Paper VI115-11.2
PDF · Video · Distributed Formation Control of Double-Integrator Vehicles with Disturbance Rejection
Trindade, Pedro	Instituto Superior Técnico, Universidade De Lisboa
Cunha, Rita	Instituto Superior Técnico, Universidade De Lisboa
Batista, Pedro	Instituto Superior Técnico, Universidade Técnica De Lisboa
Keywords: Coordination of multiple vehicle systems, Consensus, Multi-agent systems Abstract: This paper presents the development of a robust distributed and cooperative control algorithm for formation tracking by teams of vehicles modeled as double integrators, seeking its application to multirotor vehicles. Consensus-based protocols are considered to achieve coordination between the vehicles in a distributed manner, in the sense that only local information is either exchanged or perceived. A consensus protocol for agents modeled as triple integrators is proposed, and explicit necessary and sufficient conditions for convergence are provided. As a corollary, these conditions are particularized for the case of double integrators, yielding necessary and sufficient conditions that reduce the conservatism of existing sufficient conditions presented in the literature. The effect of constant disturbances on the system is then described, and finally, the third-order consensus protocol is used to incorporate integral action in a formation tracking controller used for double integrator vehicles.
Paper VI115-11.3
PDF · Video · Information-Constrained Model Predictive Control with Application to Vehicle Platooning
Causevic, Vedad	Technical University of Munich
Fanger, Yunis	Technical University of Munich
Brüdigam, Tim	Technical University of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Coordination of multiple vehicle systems, Distributed control and estimation, Control under communication constraints Abstract: Information constraints, induced by a delayed communication between individual decision makers (DMs) pose a significant challenge for the optimal control of physically interconnected systems, as for example vehicle platoons. In this work, we address the problem of distributed state/input power-constrained optimal control of a vehicle platoon under the assumption that neighboring vehicles communicate to each other with one step delay. In order to account for sudden changes in the environment such as different speed limits, or change of the desired relative distances between vehicles, a model-predictive control (MPC) approach is adopted. Despite the information constraints and state/input constraints we prove the optimality of linear control policy. To this end, we provide an optimal structure of control law that is imposed into the MPC optimization problem, to account for information constraints induced by one-step communication delay between neighboring vehicles. The efficacy of the approach is illustrated in simulation.
Paper VI115-11.4
PDF · Video · Distributed Formation Control of Mobile Robots Using Discrete-Time Distributed Population Dynamics
Martinez-Piazuelo, Juan	Universidad De Los Andes
Diaz-Garcia, Gilberto	Universidad De Los Andes
Quijano, Nicanor	Universidad De Los Andes
Giraldo, Luis Felipe	University of Los Andes
Keywords: Coordination of multiple vehicle systems, Networked robotic systems, Control under communication constraints Abstract: This paper studies the distributed formation control of multiple differential-drive robots. To solve such problem, we propose a novel class of distributed population dynamics, formulated in discrete-time, and we obtain sufficient conditions to guarantee asymptotic stability in practical implementations where computations are necessarily discrete. Moreover, we apply the proposed dynamics to a real multi-robot platform where robots achieve geometric formations under partial information and limited communication capabilities. Our proposed method achieves comparable and even better performance than other distributed methods, and displays some invariance properties that make it attractive for several other engineering applications.
Paper VI115-11.5
PDF · Video · Robustness of Multi-Robot Systems Controlling the Size of the Connected Component after Robot Failure
Murayama, Toru	National Institute of Technology, Wakayama College, Japan
Sabattini, Lorenzo	University of Modena and Reggio Emilia
Keywords: Coordination of multiple vehicle systems, Networked robotic systems, Distributed control and estimation Abstract: This study approaches a robustification method for a multi-robot network connectivity. Instead of the vertex connectivity, which is commonly used as a robustness index, here we consider the size of the connected component remaining after one robot has been removed from the network, and we propose a distributed control law for improvement and preservation of the remaining connected component size. Some conditions of a modified graph Laplacian eigenvalue are analyzed for the improvement and the preservation, and then the control strategy is composed using the Laplacian eigenvalue as an indicator of the remaining connected component size. From simulations, we observed that a multi-robot system with our control method achieves a convincing state regarding the trade-off between a network robustness and a coverage task performance.
Paper VI115-11.6
PDF · Video · Distributed Parameterized Predictive Control for Multi-Robot Curve Tracking
Viana Pacheco, Gabriel	Universidade Federal De Minas Gerais
Pimenta, Luciano	Universidade Federal De Minas Gerais
Raffo, Guilherme Vianna	Federal University of Minas Gerais
Keywords: Coordination of multiple vehicle systems, Networked robotic systems, Distributed control and estimation Abstract: This work proposes a guidance strategy of multiple robots to converge and circulate a curve while avoiding collisions by using a distributed model predictive control. To build the model predictive control framework, systems guided by control laws with parameters are considered, which laws are embedded in the optimization problem. After that, the same problem is distributed using the Alternating Direction Method of Multipliers and nonlinear optimization. To solve the task of convergence and circulation of a closed path, a vector field based control law is embedded in the predictive control scheme. The control law results from the sum of two components, a convergence term and a circulation term, whereas each term has one proportional parameter associated. Numerical results present an application example, and the strategy effectiveness is discussed.
Paper VI115-11.7
PDF · Video · Platoon Stability Conditions under Inter-Vehicle Additive Noisy Communication Channels
Gordon, Marco A.	Universidad Técnica Federico Santa María
Vargas, Francisco J.	Universidad Técnica Federico Santa María
Peters, Andrés Alejandro	Universidad Tecnológica Metropolitana
Maass, Alejandro I.	The University of Melbourne
Keywords: Multi-agent systems, Control over networks, Coordination of multiple vehicle systems Abstract: This paper studies the behavior of a platoon control system under the presence of inter-vehicle noisy communication channels. A set of homogeneous vehicles modelled as LTI systems with a predecessor-following topology is analyzed. Our main contribution is to study the stochastic scenario when additive white noise is affecting the communication between agents. We aim to provide conditions for mean square string stability and look over its relationship with the mean and variance of the tracking error. Finally, through computational analysis, we discuss the scalability, convergence and boundedness properties related to string stability in stochastic multi-agent systems.
Paper VI115-11.8
PDF · Video · Decentralized Formation Control for Multiple Quadrotors under Unidirectional Communication Constraints
Roque, Pedro	KTH Royal Institute of Technology, Stockholm, Sweden
Heshmati-Alamdari, Shahab	Royal Institute of Technology (KTH)
Nikou, Alexandros	KTH Royal Institute of Technology
Dimarogonas, Dimos V.	KTH Royal Institute of Technology
Keywords: Multi-agent systems, Control under communication constraints, Distributed control and estimation Abstract: This paper addresses the problem of formation control for multiple Unmanned Aerial Vehicles (UAVs) with relative sensing capabilities and operating under input--state limitations as well as unidirectional communication constraints. More specifically, we propose a novel distributed leader-follower architecture for a team of aerial robots to follow cooperatively a desired path while maintaining a predefined formation geometry. In the proposed control strategy, knowledge of the desired formation path is restricted to the leader UAV, which can also broadcast its state information to all following agents. In this way, the leader UAV, by employing a Nonlinear Model Predictive Control (NMPC) law, tries to navigate the whole group of agents towards the desired path while ensuring the connectivity of the team. More specifically, in order to maintain the connectivity, the leading UAV estimates the following agents' motion, by employing a fast geometric propagation that exploits the knowledge of the desired formation and sensing capabilities. On the other hand, the followers estimate the motion of the leading UAV by receiving its local state information and implementing a NMPC law that achieves tracking of the desired formation and maintains the connectivity with respect to the leader UAV. As a result, no explicit data is sent from the followers to other agents, making in this way the whole system scalable with respect to the number of agents involved to the cooperative task. Finally, simulation results verify the performance and efficiency of the proposed framework.
Paper VI115-11.9
PDF · Video · Distributed PI Formation Control Design for Autonomous Vehicles Using Edge Dynamics
Nguyen, Dinh Hoa	Kyushu University
Keywords: Multi-agent systems, Coordination of multiple vehicle systems, Control of networks Abstract: A novel fully distributed proportional-integral (PI) formation controller design approach is proposed in this paper for general linear multi-agent systems (MASs) with model uncertainties and disturbances. First, an edge dynamics is developed for uncertain and perturbed linear MASs, based on which the formation control problem for the initial MAS is shown to be equivalent to a decentralized stabilizing problem for the obtained edge dynamics. Afterward, a necessary and sufficient condition for the PI controller gains is derived. A corollary of this condition shows that for integrator agents, PI controller gains can be any positive scalars. This result is then applied to the formation control of autonomous four-wheel vehicles described by nonlinear models, of which the efficiency of the proposed method is demonstrated in presence of both uncertainties and disturbances.

VI115-12
Distributed Control and Estimation	Regular Session
Chair: Cacace, Filippo	Universita Campus Biomedico Di Roma
Co-Chair: Dashkovskiy, Sergey	University of Würzburg
Paper VI115-12.1
PDF · Video · Robust Stability of a Perturbed Nonlinear Wave Equation
Dashkovskiy, Sergey	University of Würzburg
Slyn'ko, Vitaliy	S.P. Timoshenko Institute of Mechanics of NAS of Ukraine
Keywords: Distributed control and estimation Abstract: In this work we consider a nonlinear wave equation subject to both distributed as well as boundary perturbations and derive several ISS-like estimates for solutions for such equations by means of Lyaponov and Faedo-Galerkin methods. Depending on the regulation of the boundary input signals different types of estimates are derived.
Paper VI115-12.2
PDF · Video · The ISS Property for a Feedback Connection of an ODE with a Parabolic PDE
Dashkovskiy, Sergey	University of Würzburg
Slyn'ko, Vitaliy	S.P. Timoshenko Institute of Mechanics of NAS of Ukraine
Keywords: Distributed control and estimation Abstract: We consider a linear non-autonomous ODE with an input signal, which is a solution of a linear non-autonomous parabolic PDE for which the solution of the ODE enters as an input. Moreover there are external disturbances entering through the boundary conditions of the parabolic equation. In this work we derive ISS estimates for this feedback connection under certain linear matrix inequality conditions. The derivation of results is based on the Lyapunov method.
Paper VI115-12.3
PDF · Video · Stability of Uniformly Attracting Sets for Impulsive-Perturbed Multi-Valued Semiflows
Dashkovskiy, Sergey	University of Würzburg
Kapustyan, Oleksiy	Taras Shevchenko National University of Kyiv
Perestyuk Yuriy, Yuriy	Taras Shevchenko National University of Kyiv
Keywords: Distributed control and estimation Abstract: In this paper we investigate stability of uniformly attracting sets for semiflows generated by impulsive infinite-dimensional dynamical systems without uniqueness. Obtained abstract results are applied to weakly nonlinear parabolic system, whose trajectories have jumps at moments of intersection with certain surface in the phase space.
Paper VI115-12.4
PDF · Video · Input-To-State Stability Results W.r.t. Global Attractors of Semi-Linear Reaction-Diffusion Equations
Dashkovskiy, Sergey	University of Würzburg
Kapustyan, Oleksiy	Taras Shevchenko National University of Kyiv
Schmid, Jochen	Fraunhofer Institute for Industrial Mathematics
Keywords: Distributed control and estimation Abstract: We establish local input-to-state stability and asymptotic gain results for a class of nonlinear infinite-dimensional systems with respect to the global attractor of the respective undisturbed system. We apply our results to a large class of reaction-diffusion equations with nontrivial global attractors.
Paper VI115-12.5
PDF · Video · Price Based Linear Quadratic Control under Transportation Delay
Heyden, Martin	Lund University
Pates, Richard	Lund University
Rantzer, Anders	Lund Univ
Keywords: Distributed control and estimation Abstract: We study a simple transportation problem on a string graph. The objective is to regulate the node levels of some decaying quantity to optimize dynamical performance. This can be achieved by controlling the flows, which are subject to delay, between neighbouring nodes. The problem is considered from two perspectives. In the first (the social perspective), all nodes cooperate to find the flows that maximize the aggregated utility of the entire transportation network. In the second (the user perspective), the nodes instead try to maximimize their own utility. Our main contribution is to give an implementation of the feedback law that gives the social optimum, that only depends on the local states and a set of prices defined by a distributed update rule. These prices align the social and user optimum in a budget neutral way, and give all nodes no worse cost than if they were on their own.
Paper VI115-12.6
PDF · Video · Event-Triggered Task-Switching Control Based on Distributed Estimation
He, Xingkang	KTH Royal Institute of Technology
Hashemi, Ehsan	University of Waterloo
Johansson, Karl H.	Royal Institute of Technology
Keywords: Distributed control and estimation, Consensus, Sensor networks Abstract: This paper studies how to control an agent in an uncertain environment over a connected sensor network, such that the agent is able to finish a sequence of tasks, namely, reaching certain sets in order. Based on multiple offline reference trajectories and constrained communication between the agent and the sensor network, an event-triggered task-switching control framework is proposed, so that the agent state remains in each task set for the desired time and then switches to the next task. Employing a local predicted control law and the messages from neighboring sensors, a two time-scale distributed filter is proposed for each sensor to estimate the agent state. Under mild system conditions (i.e., stabilization and collective detectability), the estimation error and trajectory tracking error are shown to be asymptotically upper bounded.
Paper VI115-12.7
PDF · Video · Sparsity Preserving Discretization with Error Bounds
Anderson, James	Columbia University
Matni, Nikolai	University of Pennsylvania
Chen, Yuxiao	University of Michigan
Keywords: Distributed control and estimation, Control of networks, Control under computation constraints Abstract: Typically when designing distributed controllers it is assumed that the state-space model of the plant consists of sparse matrices. However, in the discrete-time setting, if one begins with a continuous-time model, the discretization process annihilates any sparsity in the model. In this work we propose a discretization procedure that maintains the sparsity of the continuous-time model. We show that this discretization out-performs a simple truncation method in terms of its ability to approximate the "ground truth" model. Leveraging results from numerical analysis we are also be able to upper-bound the error between the dense discretization and our method. Furthermore, we show that in a robust control setting we can design a distributed controller on the approximate (sparse) model that stabilizes the dense model.
Paper VI115-12.8
PDF · Video · An Application of RLS to the Online Parameter Identification of Three-Phase AC Mesh Grids
Parada Contzen, Miguel	Universidad Del Bio Bio
Keywords: Distributed control and estimation, Identification for control, Continuous time system estimation Abstract: This paper focuses on parameter identification of mesh distribution grids. In order to tune secondary level controllers, accurate microgrids models, in terms of topology and impedances values, are needed. Furthermore, an efficient energy management strategy relays on the correct estimation of the load behavior considering only measurable signals. We apply the well known Recursive Least Squares (RLS) methodology to identify the complex admittances of the lines between, and loads at, nodes where voltage and current measurements are available. The proposed algorithm has little communication requirements as the signals can be sampled at low frequencies compared with the grid standard. The relatively low computation load of the algorithm makes it suitable for on-line implementation on real time. The main characteristics of the methodology are illustrated with help of simulation examples.
Paper VI115-12.9
PDF · Video · Spatial Estimation of Solar Radiation Using Geostatistics and Machine Learning Techniques
Núñez-Reyes, Amparo	University of Seville
Ruiz-Moreno, Sara	University of Seville
Keywords: Distributed control and estimation, Machine learning, Sensor networks Abstract: In large solar fields, where the control system is distributed, it is important to know the values of solar radiation in the complete area of the field. Local solar radiation can be obtained by means of static sensors, using e.g. a wireless sensor network or movable sensors using drones for the general obtainment of variables. In this paper, solar radiation estimation is accomplished using Ordinary Kriging and distance weighting, and an alternative method is presented, which is based on a non-supervised competitive artificial neural network called Self-Organizing Map. This neural network generates a map with the most representative nodes and their weights, which are used to obtain the spatial variability of solar radiation in the area.
Paper VI115-12.10
PDF · Video · Distributed Stabilization of Interconnected Multiagent Systems Using Structurally Nonsymmetric Control Layers
Rezaei, Vahid	University of Denver
Stefanovic, Margareta	University of Denver
Keywords: Distributed control and estimation, Multi-agent systems Abstract: Recently, graph theoretic distributed protocols have been introduced for the stabilization of interconnected multiagent systems with separate agent and control layers. For the case of unstable local agent dynamics, the existing results focus on only the matched interconnections. Further, except for a multiagent system of first- and second-order agents, the existing results are limited to the structurally symmetric control layers based on the undirected communication among controllers. We aim to relax these restrictions for multiagent systems with partially known unmatched or matched interconnections.We propose two step-by-step procedures to design robust distributed stabilization gains for the candidate nonsymmetric control layers in the presence of agent- and multiagent system-level modeling uncertainties. Combined with an optimal control formulation, we develop a matrix algebraic approach for the unmatched scenario and a Lyapunov-based approach for the matched case. In each case, we prove that all state trajectories of the two-layer interconnected multiagent system exponentially converge to the origin. We examine the feasibility of the proposed ideas in simulation.
Paper VI115-12.11
PDF · Video · Event-Triggered Consensus Control of Multi-Agent Systems with Nonuniform Communication Delays Via Reduced-Order Observers
Wang, Qiuzhen	University of Electronic Science and Technology of China
Hu, Jiangping	University of Electronic Science and Technology of China
Zhao, Yiyi	Southwestern University of Finance and Economics
Ghosh, Bijoy	Texas Tech University
Keywords: Distributed control and estimation, Multi-agent systems, Consensus Abstract: This paper studies a consensus problem for linear multi-agent systems (MASs) over directed communication networks with nonuniform time-varying delays. To overcome the limited computing and storage resources, a distributed control scheme is designed for each agent by using the event-triggered strategy. At the same time, a reduced-order observer is put forward in the controller design when only the relative output measurement is available. The communication network model with nonuniform time-varying delays is more challenging than the fixed delays or non-delays in the literature. Theoretical analysis is provided to show that the proposed control scheme can guarantee the consensus of MASs, with Zeno-behavior excluded and the upper bound of time delay obtained. A numerical example is provided to illustrate the feasibility and effectiveness of the theoretical results.
Paper VI115-12.12
PDF · Video · Reconstruction of Cross-Correlations between Heterogeneous Trackers Using Deterministic Samples
Radtke, Susanne	KIT – the Research University in the Helmholtz Association
Noack, Benjamin	Karlsruhe Institute of Technology (KIT)
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Distributed control and estimation, Sensor networks Abstract: The exploitation of dependencies between state estimates from distributed trackers plays a vital role in so-called track-to-track fusion and has been extensively studied for state estimates with the same state space. In contrast, dependencies are often neglected when considering heterogeneous state estimates referring to different state spaces, since the necessary transformations make the analytic calculation complex or infeasible. This paper aims to develop an overarching framework for the reconstruction of cross-covariances between state estimates obtained in heterogeneous state spaces. The proposed method uses a set of deterministic samples to calculate dependent information. Thus, it allows for a distributed track-keeping of correlations that also encodes the transformation into the local subsystems. To highlight the algorithm, we use a linear problem with heterogeneous trackers only and discuss the correlation problem in detail. The results show superior performance compared to neglecting the correlations.
Paper VI115-12.13
PDF · Video · Asymptotically Optimal Distributed Filtering of Continuous-Time Linear Systems
Battilotti, Stefano	Univ. La Sapienza
Cacace, Filippo	Universita Campus Biomedico Di Roma
d'Angelo, Massimiliano	Università Di Roma La Sapienza
Germani, Alfredo	University of L'Aquila
Keywords: Distributed control and estimation, Sensor networks, Estimation and filtering Abstract: In this paper we prove the following new and unexpected result: it is possible to design a continuous-time distributed filter for linear systems that asymptotically tends at each node to the optimal centralized filter. The result concerns distributed estimation over a connected undirected graph and it only requires to exchange the estimates among adjacent nodes. We exhibit an algorithm containing a consensus term with a parametrized gain and show that when the parameter becomes arbitrarily large the error covariance at each node becomes arbitrarily close to the error covariance of the optimal centralized Kalman filter.
Paper VI115-12.14
PDF · Video · Results on Distributed State Estimation for LTI Systems Facing Communication Failures
Rodríguez, álvaro	Universidad Loyola Andalucía
Orihuela Espina, Luis	Universidad Loyola Andalucía
Millan Gata, Pablo	Universidad Loyola Andalucía
Seuret, Alexandre	Cnrs / Laas
Zaccarian, Luca	LAAS-CNRS and University of Trento
Keywords: Control and estimation with data loss, Distributed control and estimation, Multi-agent systems Abstract: We address distributed estimation of the state of a linear plant by a set of agents. The problem is cast in a setting where the communication capabilities of an agent might be deactivated from time to time, due to failures in the communication devices or malicious attacks. An observer architecture is proposed to achieve our estimation goal, based on a multi-hop subspace decomposition. Uniform exponential convergence to zero of the estimation errors is proven in the presence of communication failures, under a persistence of excitation assumption. Finally, the observer performance is evaluated in simulation, showing the merits of the proposed method and suggesting directions for future developments.

VI115-13
Distributed Optimization for Large-Scale Systems	Regular Session
Chair: Ebenbauer, Christian	University of Stuttgart
Co-Chair: Li, Huiping	Northwestern Polytechnical University
Paper VI115-13.1
PDF · Video · Towards an O(1/t) Convergence Rate for Distributed Dual Averaging
Liu, Changxin	Northwestern Polytechnical University
Li, Huiping	Northwestern Polytechnical University
Shi, Yang	University of Victoria
Keywords: Distributed optimisation for large-scale systems, Consensus, Multi-agent systems Abstract: Recently, distributed dual averaging has received increasing attention due to its superiority in handling constraints and dynamic networks in multiagent optimization. However, all distributed dual averaging methods reported so far considered nonsmooth problems and have a convergence rate of O(1/sqrt(t)). To achieve an improved convergence guarantee for smooth problems, this work proposes a second-order consensus scheme that assists each agent to locally track the global dual variable more accurately. This new scheme in conjunction with smoothness of the objective ensures that the accumulation of consensus error over time caused by incomplete global information is bounded from above. Then, a rigorous investigation of dual averaging with inexact gradient oracles is carried out to compensate the consensus error and achieve an O(1/t) convergence rate. The proposed method is examined in a large-scale LASSO problem.
Paper VI115-13.2
PDF · Video · Distributed Solving Sylvester Equations with an Explicit Exponential Convergence
Cheng, Songsong	Academy of Mathematics and Systems Science, Chinese Academy of S
Zeng, Xianlin	Beijing Institute of Technology
Hong, Yiguang	Chinese Academy of Sciences
Keywords: Distributed optimisation for large-scale systems, Multi-agent systems, Consensus Abstract: This paper addresses distributed achieving the least squares solution of Sylvester equations in the form of AX+XB=C. By decomposing the parameter matrices A, B and C, we formulate the problem of distributed solving Sylvester equations as a distributed optimization model and propose a continuous-time algorithm from the primal-dual viewpoint. Then, by constructing a Lyapunov function, we prove that the proposed algorithm can achieve a least squares solution of Sylvester equations with an explicit exponential convergence rate. Additionally, we illustrate the convergence performance by using a numerical example.
Paper VI115-13.3
PDF · Video · Approximating Regions of Attraction of a Sparse Polynomial Differential System
Tacchi, Matteo	LAAS-CNRS
Cardozo, Carmen	RTE
Henrion, Didier	LAAS-CNRS, Univ. Toulouse
Lasserre, Jean B.	CNRS
Keywords: Distributed optimisation for large-scale systems, Secure networked control systems Abstract: Motivated by stability analysis of large scale power systems, we describe how the Lasserre (moment - sums of squares, SOS) hierarchy can be used to generate outer approximations of the region of attraction (ROA) of sparse polynomial differential systems, at the price of solving linear matrix inequalities (LMI) of increasing size. We identify specific parsity structures for which we can provide numerically certified outer approximations of the region of attraction in high dimension. For this purpose, we combine previous results on non-sparse ROA approximations with sparse semi-algebraic set volume computation.
Paper VI115-13.4
PDF · Video · On Privatizing Equilibrium Computation in Aggregate Games Over Networks
Gade, Shripad	University of Illinois at Urbana-Champaign
Winnicki, Anna	University of Illinois at Urbana-Champaign
Bose, Subhonmesh	University of Illinois at Urbana Champaign
Keywords: Distributed optimisation for large-scale systems, Stochastic control and game theory, Randomized methods Abstract: We propose a distributed algorithm to compute an equilibrium in aggregate games where players communicate over a fixed undirected network. We prove that our algorithm does not reveal private information of players to an honest-but-curious adversary who monitors several nodes in the network. In contrast with differential privacy based algorithms, our method does not sacrifice accuracy of equilibrium computation to provide privacy guarantees.
Paper VI115-13.5
PDF · Video · A Discrete-Time Distributed Algorithm for Minimum L_1-Norm Solution of an Under-Determined Linear Equation Set
Wang, Xuan	Purdue
Mou, Shaoshuai	Purdue University
Anderson, Brian D. O.	Australian National Univ/NICTA
Keywords: Multi-agent systems, Distributed control and estimation, Distributed optimisation for large-scale systems Abstract: This paper proposes a discrete-time, distributed algorithm for multi-agent networks to achieve the minimum l_1-norm solution to a group of linear equations known to possess a family of solutions. We assume each agent in the network knows only one equation and can communicate with only its neighbors. The algorithm is developed based on a combination of the projection-consensus idea and the sub-gradient descent method. Given the underlying network graph to be directed and strongly connected, we prove that the algorithm enables all agents to achieve a common minimum l_1-norm solution. The major difficulty to be dealt with is the non-smooth nature of the norm and the lack of strict convexity of the associated relevant performance index.
Paper VI115-13.6
PDF · Video · Distributed Signal Signature Minimization Via Network Topology Modification
Zamani, Mohammad	DST Group
Shames, Iman	University of Melbourne
Hunjet, Robert	DST Group
Keywords: Multi-agent systems, Distributed optimisation for large-scale systems, Sensor networks Abstract: In this paper a distributed Received Signal Strength (RSS) minimization algorithm is proposed that guarantees strong connectivity of the network topology while minimizing the RSS of the network received at a given eavesdropper's location. The proposed algorithm is composed of multiple rounds of maximum consensus network communications implementing a distributed greedy solution of the problem. The proposed RSS minimization algorithm is distributed in the sense that nodes do not assume, estimate or communicate any network connectivity knowledge such as a routing table, the Laplacian matrix, neighbour lists or the total number of nodes. The proposed algorithm assumes that the initial network topology is strongly connected and that each agent knows its own location and that of the eavesdropper. We provide an extension of the proposed algorithm for dealing with multiple and moving eavesdropper. In this case, we also propose a heuristic for increasing nodal transmit power to effectively reshape the network topology according to the closer eavesdropper. Performance of the proposed algorithm is demonstrated in simulations.
Paper VI115-13.7
PDF · Video · Heat Balancing in Cooling Systems Using Distributed Pumping
Kallesøe, Carsten Skovmose	Grundfos
Nielsen, Brian Kongsgaard	Grundfos
Tsouvalas, Agisilaos	Grundfos
Keywords: Distributed optimisation for large-scale systems, Control over networks, Distributed control and estimation Abstract: Hydronic cooling systems are often used in large buildings. In these systems, chilled water is transported from the chillers to Air Handling Units (AHUs) via a water distribution system. The temperature of the exhaust air from the AHU is controlled by the flow of the chilled water in AHUs. Installation costs are very important for the building sector, which has lead to a new structure of the hydronic system using distributed pumps. This paper derives a control scheme for this new structure that ensures flow requirements at the chillers and controls the air temperature at the local AHUs. Saturation problems are well known in hydronic systems and can lead to poor control performance in parts of the building. To mitigate this problem the hydronic system needs to be hydraulically balanced. With the proposed control this balancing procedure is handled automatically. The balancing algorithm is verified by a Modelica model of an office building.
Paper VI115-13.8
PDF · Video · Control of Networked Systems by Clustering: The Degree of Freedom Concept
Martinelli, Andrea	ETH Zurich
Lygeros, John	ETH Zurich
Keywords: Control of networks, Distributed optimisation for large-scale systems Abstract: We address the problem of local flux redistribution in networked systems. The aim is to detect a suitable cluster which is able to locally adsorb a disturbance by means of an appropriate redistribution of control load among its nodes, such that no external node is affected. Traditional clustering measures are not suitable for our purpose, since they do not explicitly take into account the structural conditions for disturbance containment. We propose a new measure based on the concept of degree of freedom for a cluster, and we introduce a heuristic procedure to quickly select a set of nodes according to this measure. Finally, we show an application of the method in the context of DC microgrids voltage control.
Paper VI115-13.9
PDF · Video · Resource and Network Management for Satellite Communications Systems: A Chance-Constrained Approach
Abe, Yuma	National Institute of Information and Communications Technology
Ogura, Masaki	Osaka University
Tsuji, Hiroyuki	National Institute of Information and Communications Technology
Miura, Amane	National Institute of Information and Communications Technology
Adachi, Shuichi	Keio University
Keywords: Control of networks Abstract: In this paper, we propose an optimization framework for the resource and network management in large-scale satellite communications (SATCOM) systems with stochastic and time-varying communication requests. Because further expansions of SATCOM systems are expected in the near future, it is of practical importance to develop management methodologies for efficiently and robustly operating large-scale SATCOM systems. To address this problem, in this paper, we formulate a SATCOM network optimization problem within the framework of the chance-constrained model predictive control. In this problem, we require that a joint chance constraint on the bandwidth loss rate is satisfied with a user-specified performance and probability. Because the joint chance constraint is nonlinear in design variables, we relax the constraint to a linear deterministic one for reformulating the original problem into a relaxed deterministic problem. We numerically verify that the proposed method outperforms a baseline methodology and therefore allows us to efficiently manage large-scale SATCOM systems.

VI115-14
Multi-Agent Systems	Regular Session
Chair: Muenz, Ulrich	Siemens
Co-Chair: Tallapragada, Pavankumar	Indian Institute of Science
Paper VI115-14.1
PDF · Video · Exploiting Structure in the Bottleneck Assignment Problem
Khoo, Mitchell	The University of Melbourne
Wood, Tony A.	University of Melbourne
Manzie, Chris	The University of Melbourne
Shames, Iman	University of Melbourne
Keywords: Multi-agent systems Abstract: An assignment problem arises when there exists a set of tasks that must be allocated to a set of agents. The bottleneck assignment problem (BAP) has the objective of minimising the most costly allocation of a task to an agent. Under certain conditions the structure of the BAP can be exploited such that subgroups of tasks are assigned separately with lower complexity and then merged to form a combined assignment. In particular, we discuss merging the assignments from two separate BAPs and use the solution of the subproblems to bound the solution of the combined problem. We also provide conditions for cases where the solution of the subproblems produces an exact solution to the BAP over the combined problem. We then introduce a particular algorithm for solving the BAP that takes advantage of this insight. The methods are demonstrated in a numerical case study.
Paper VI115-14.2
PDF · Video · Bipartite Synchronization of Coupled System with Markov Switching Topology
Du, Ku	University of Science and Technology of China
Kang, Yu	University of Science and Technology of China
Keywords: Multi-agent systems, Consensus Abstract: In this paper, we investigate the leaderless bipartie synchronization problem about nonlinear systems with time delay under Markov switching topologies. We first deal with the strongly connected part of the coupled system. Then, by utilizing the consensus trajectory of the strongly connected agents, we transform the consensus problem into a stable problem. A mild condition about switching topology is proposed which just require the union graph has a spanning tree. We also propose a novel method to deal with the error system. Then, sufficient conditions are presented to make all the systems achieve bipartite synchronization under ergodic Makrov switching topology. At last, an example is given to verify our theory.
Paper VI115-14.3
PDF · Video · Finite-Time Consensus Tracking Control for Multi-Agent Systems with Nonlinear Dynamics under Euler Digraph and Switching Topology
He, Shengchao	Beijing Institute of Technology
Liu, Xiangdong	School of Automation, 231 Staff, Beijing Institute OfTechnology
Lu, Pingli	Beijing Institute of Technology
Du, Changkun	Beijing Institute of Technology
Liu, Haikuo	Beijing Institute of Technology
Chen, Zhen	School of Automation, 231 Staff, Beijing InstituteofTechnology
Keywords: Multi-agent systems, Consensus Abstract: In this paper, the finite-time consensus tracking control for multi-agent systems under Euler digraph and switching topology are discussed. The new nonlinear distributed control protocol is proposed under which the systems can reach finite-time consensus tracking. Furthermore, the leader need to connect with only one follower and which agent is connected will have no effect on finite-time consensus under Euler digraph. It is found that adding edges or increasing feedback gains will be an effective way to reduce the settling time. Two sufficient conditions are proposed to achieve finite-time consensus tracking for multi-agent systems under Euler digraph and switching topology. Finally, numerical simulations are presented to verify the effectiveness of obtained theoretical results.
Paper VI115-14.4
PDF · Video · Design of Controller and Observer for Dynamical Network Systems Based on Weighted Degrees
Adachi, Ryosuke	Yamaguchi University
Yamashita, Yuh	Hokkaido University
Kobayashi, Koichi	Hokkaido University
Keywords: Multi-agent systems, Distributed control and estimation Abstract: In this paper, stability conditions based on graph theory for dynamical network systems are shown. Although many frameworks based on graph theory for analysis of dynamical systems have been proposed, there is no stability condition that can be utilized to design of controllers and observers for linear dynamical systems. In this work, to show the stability condition based on graph theory for control and estimation, the dynamical system is represented by a directed graph with weights. The proposed stability conditions are obtained as the inequality of the weighted degrees defined in this paper. As applications, equilibrium point analysis of Lotka-Volterra system and design of pinning controllers and observers for consensus systems are proposed.
Paper VI115-14.5
PDF · Video · A Resilient Leader Election Algorithm Using Aggregate Computing Blocks
Mo, Yuanqiu	Westlake University
Audrito, Giorgio	University of Turin
Dasgupta, Soura	University of Iowa
Beal, Jacob	Raytheon BBN Technologies Cambridge
Keywords: Multi-agent systems, Distributed control and estimation, Complex system management Abstract: Leader election, a fundamental coordination problem in distributed systems, has been addressed in many different ways. Among these works, resilient leader election algorithms are of particular interest due to the ongoing emergence of open, complex distributed systems such as smart cities and the Internet of Things. However, previous algorithms with O(diameter) stabilization time complexity either assume some prior knowledge of the network or that very large messages can be sent. In this paper, we present a resilient leader election algorithm with O(diameter) stabilization time, small messages, and no prior knowledge of the network. This algorithm is based on aggregate computing, which provides a layered approach to algorithm development based on composition of resilient algorithmic "building blocks". With our algorithm, a key design parameter K defines important performance attributes: a larger K will delay the recovery from loss of current leader, while a small K may lead to multiple leaders, and the algorithm will stabilize with O(diameter) time complexity when K geq 2.
Paper VI115-14.6
PDF · Video · Coalitional MPC with Predicted Topology Transitions
Masero, Eva	University of Seville
Maestre, Jose M.	University of Seville
Francisco, Mario	Univ of Salamanca
Camacho, Eduardo F.	University of Seville
Keywords: Multi-agent systems, Distributed control and estimation, Control under communication constraints Abstract: This paper proposes a novel hierarchical coalitional MPC technique, where transitions to the best communication topology are considered over the prediction horizon. For this reason, a new variable, called transition horizon, is added to the optimization problem to compute the optimal instant to introduce a new topology. Consequently, local controllers can anticipate topology transitions and adapt their trajectories whilst optimizing their local interests. Furthermore, stability guarantees in the closed-loop control of each coalition are provided. The benefits of this control method are shown via a simulated non-linear eight-coupled tanks plant.
Paper VI115-14.7
PDF · Video · Forced Variational Integrator for Distance-Based Shape Control with Flocking Behavior of Multi-Agent Systems
Colombo, Leonardo Jesus	Instituto De Ciencias Matemticas (ICMAT-CSIC)
Moreno, Patricio	Facultad De Ingeniería, Universidad De Buenos Aires
Ye, Mengbin	Curtin University
Garcia de Marina, Hector	University of Southern Denmark
Cao, Ming	University of Groningen
Keywords: Multi-agent systems, Distributed control and estimation, Discrete event modeling and simulation Abstract: A multi-agent system designed to achieve distance-based shape control with flocking behavior can be seen as a mechanical system described by a Lagrangian function and subject to additional external forces. Forced variational integrators are given by the discretization of Lagrange-d'Alembert principle for systems subject to external forces, and have proved useful for numerical simulation studies of complex dynamical systems. We derive forced variational integrators that can be employed in the context of control algorithms for distance-based shape with velocity consensus. In particular, we provide an accurate numerical integrator with a lower computational cost than traditional solutions, while preserving the configuration space and symmetries. We also provide an explicit expression for the integration scheme in the case of an arbitrary number of agents with double integrator dynamics. For a numerical comparison of the performances, we use a planar formation consisting of three autonomous agents.
Paper VI115-14.8
PDF · Video · Online Control of Affine Systems in Stochastically Modeled Contexts
Flüs, Patrick	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Multi-agent systems, Distributed control and estimation, Stochastic control and game theory Abstract: This paper proposes an algorithm for online controller synthesis for autonomous systems with LTI dynamics considering obstacle avoidance. The obstacles are assumed to be other systems with affine probabilistic dynamics. The initial state as well as the disturbances of these systems are Gaussian distributed. To guarantee that the probability of a collision is smaller than a predefined threshold, probabilistic reachable sets are used. Due to the Gaussian distribution, the probabilistic reachability procedure can use the principles of the ellipsoidal calculus. For the autonomous system, these time-varying reachable sets of the other systems are avoided by an approach, which is based on model predictive control and successive convexification of the constraints. Due to high computational times required for the computation of probabilistic reachable sets and the convexification, different techniques to reduce the computational time significantly are also proposed.
Paper VI115-14.9
PDF · Video · A Nonlinear Distributed Model Predictive Scheme for Systems Based on Hammerstein Model
Gedachi, Hadger	National Engineering School of Tunis
Chanfreut, Paula	University of Seville
Maestre, Jose M.	University of Seville
Keywords: Multi-agent systems, Distributed optimisation for large-scale systems Abstract: A distributed model predictive control (DMPC) scheme for systems based on the Hammerstein structure is proposed in this work. To deal with the nonlinearity of the Hammerstein model, the DMPC problem is reduced to an optimization problem on the intermediate variable and, subsequently, the inverse of the nonlinear block is considered to find the corresponding control inputs. Also, a sub-optimality bound of the method is presented. To illustrate our approach, we consider a nonlinear system controlled in a distributed manner by two agents that exchange information and make cooperative decisions. The efficiency of the proposed DMPC is demonstrated through a simulation example where it is compared to the corresponding centralized approach.
Paper VI115-14.10
PDF · Video · Geometric Convergence of Distributed Gradient Play in Games with Unconstrained Action Sets
Tatarenko, Tatiana	Technische Universität Darmstadt
Nedich, Angelia	Arizona State University
Keywords: Multi-agent systems, Distributed optimisation for large-scale systems, Stochastic control and game theory Abstract: We provide a distributed algorithm to learn a Nash equilibrium in a class of non-cooperative games with strongly monotone mappings and unconstrained action sets. Each player has access to her own smooth local cost function and can communicate to her neighbors in some undirected graph. We consider a distributed communication-based gradient algorithm. For this procedure, we prove geometric convergence to a Nash equilibrium. In contrast to our previous works, where the proposed algorithms required two parameters to be set up and the analysis was based on a so called augmented game mapping, the procedure in this work corresponds to a standard distributed gradient play and, thus, only one constant step size parameter needs to be chosen appropriately to guarantee fast convergence to a game solution. Moreover, we provide a rigorous comparison between the convergence rate of the proposed distributed gradient play and the rate of the GRANE algorithm. It allows us to demonstrate that the distributed gradient play outperforms the GRANE in terms of convergence speed.
Paper VI115-14.11
PDF · Video · Scalable Robustness of Interconnected Systems Subject to Structural Changes
Knorn, Steffi	Uppsala University
Besselink, Bart	University of Groningen
Keywords: Multi-agent systems, Dynamic Networks Abstract: This paper studies the robustness of large-scale interconnected systems with respect to external disturbances, focussing on their scalability properties. Specifically, a notion of scalability is introduced that asks for these robustness properties to remain unchanged under a structural change of the system, such as the addition/removal of a subsystem or a change in the interconnection structure. Both necessary and sufficient conditions, in terms of the interconnection structure and edge weights, are given under which elementary structural changes are scalable. The results are illustrated through a simple example.
Paper VI115-14.12
PDF · Video · Topology-Independent Robust Stability for Networks of Homogeneous MIMO Systems
Devia Pinzón, Carlos Andrés	Pontificia Universidad Javeriana
Giordano, Giulia	University of Trento
Keywords: Multi-agent systems, Dynamic Networks Abstract: We study dynamic networks described by a directed graph where the nodes are associated with MIMO systems with transfer-function matrix F(s), representing individual dynamic units, and the arcs are associated with MIMO systems with transfer-function matrix G(s), accounting for the dynamic interactions among the units. In the nominal case, we provide a topology-independent condition for the stability of all possible dynamic networks with a maximum connectivity degree, regardless of their size and interconnection structure. When node and arc transfer-function matrices are affected by norm-bounded homogeneous uncertainties, the robust condition for size- and topology-independent stability depends on the uncertainty magnitude. Both conditions, expressed as constraints for the Nyquist diagram of the poles of the transfer-function matrix H(s)=F(s)G(s), are scalable and can be checked locally to guarantee stability-preserving "plug-and-play" addition of new nodes and arcs.
Paper VI115-14.13
PDF · Video · Evolution of a Population of Selfish Agents on a Network
Mandal, Nirabhra	Indian Institute of Science, Bengaluru
Tallapragada, Pavankumar	Indian Institute of Science
Keywords: Multi-agent systems, Dynamic Networks, Distributed control and estimation Abstract: In this work, we consider a population composed of a continuum of agents that seek to selfishly minimize a cost function by moving on a network. The nodes in the network may represent physical locations or abstract choices. Taking inspiration from how water distributes itself in a system of connected tanks of varying heights, we formulate a best response dynamics for the population. In this dynamics, the population in each node simultaneously seeks to redistribute itself according to the `best response' to the state of the population in the node's neighborhood. We provide an algorithm to determine the best response as a function of the state of the population. We then show that given the state of the population, the best response is unique. For the continuous time version of the best response dynamics, we show asymptotic convergence to an equilibrium point for an arbitrary initial condition. We then explore a second dynamics, in which the population evolves according to centralized gradient descent of the social cost. Again, we show asymptotic convergence for an arbitrary initial condition. We illustrate our results through simulations.
Paper VI115-14.14
PDF · Video · Affine Formation Maneuver Control of Event-Triggered Multi-Agent Systems
Yang, Junyi	University of Alberta
Yu, Hao	University of Alberta
Chen, Tongwen	University of Alberta
Keywords: Multi-agent systems, Event-based control, Control over networks Abstract: An event-triggered affine formation maneuver control problem is studied in this work. The formations are invariant for any affine transformation. An event-triggered mechanism is proposed for the closed-loop system under which the controller updates and information broadcasting are generated only when it is necessary to maintain the system behavior. The practical convergence is guaranteed for the closed-loop system and the Zeno behavior is excluded. Simulations are provided to verify the effectiveness of the method.
Paper VI115-14.15
PDF · Video · Formation Control with Orientation Alignment by Constrained Input
Chen, Yu-Wen	National Taiwan University
Chiang, Ming-Li	National Taiwan Univ
Fu, Li-Chen	National Taiwan Univ
Keywords: Multi-agent systems, Nonlinear adaptive control, Coordination of multiple vehicle systems Abstract: We design a formation controller for Multi-Agent System such that the agents can form into the desired shape and track a given reference trajectory. The main feature of the proposed design is that not only the orientation of individual agents, but also the orientation of the whole formation is considered and is designed to be aligned with the moving direction of the reference trajectory, which helps the tracking movement to be smoother compared with the common tracking results. Moreover, the control inputs are designed in predefined input ranges to reflect the practical system. System stability is proved based on nonlinear system theory and some simulations are given to validate the proposed results.
Paper VI115-14.16
PDF · Video · A Posteriori Probabilistic Feasibility Guarantees for Nash Equilibria in Uncertain Multi-Agent Games
Pantazis, Georgios	Univerdity of Oxford
Fele, Filiberto	University of Oxford
Margellos, Kostas	University of Oxford
Keywords: Multi-agent systems, Randomized methods, Stochastic control and game theory Abstract: In this paper a distribution-free methodology is presented for providing robustness guarantees for Nash equilibria (NE) of multi-agent games. Leveraging recent a posteriori developments of the so called scenario approach, we provide probabilistic guarantees for feasibility problems with polytopic constraints. This result is then used in the context of multi-agent games, allowing to provide robustness certificates for constraint violation of any NE of a given game. Our guarantees can be used alongside any NE seeking algorithm that returns some equilibrium solution. Finally, by exploiting the structure of our problem, we circumvent the need of employing computationally prohibitive algorithms to find an irreducible support subsample, a concept at the core of the scenario approach. Our theoretical results are accompanied by simulation studies that investigate the robustness of the solutions of two different problems, namely, a 2-dimensional feasibility problem and an electric vehicle (EV) charging control problem.
Paper VI115-14.17
PDF · Video · Resilient Consensus against Mobile Malicious Agents
Wang, Yuan	Tokyo Institute of Technology
Ishii, Hideaki	Tokyo Institute of Technology
Bonnet, Francois	Tokyo Institute of Technology
Defago, Xavier	Tokyo Institute of Technology
Keywords: Multi-agent systems, Secure networked control systems, Consensus Abstract: This paper addresses novel consensus problems in the presence of adversaries that can move within the network and induce faulty behaviors in the attacked agents. By employing mobile adversary models from the computer science literature, we develop three protocols which can mitigate the influence of such malicious agents. The algorithms follow the class of mean subsequence reduced (MSR) algorithms, under which agents ignore the suspicious values received from neighbors during their state updates. Different from the static adversary models, even after the adversaries move away, the infected agents may remain faulty in their values for a short while, whose effects must be taken into account. We develop conditions on the network structures for both the complete and non-complete graph cases, under which the proposed algorithms are guaranteed to attain resilient consensus. An illustrative example is provided to verify the effectiveness of our approach.
Paper VI115-14.18
PDF · Video · Boundary Control for Exponential Synchronization of Reaction-Diffusion Neural Networks Based on Coupled PDE-ODEs
Yang, Chengdong	Linyi University
Li, Zhenxing	Linyi University
Chen, Xiangyong	Northeastern University, China
Zhang, Ancai	Central South University
Jianlong, Qiu	University of Rhode Island
Keywords: Control of networks Abstract: This paper studies synchronization and exponential synchronization of reaction-diffusion neural networks based on semi-linear coupled partial differential equations-ordinary differential equations. Two kinds of boundary control methods are studied, one collocated boundary measurement based form and the other distributed measurement based form. Sufficient conditions for existence of the two proposed boundary controllers for synchronization and exponential synchronization are respectively obtained in terms of LMIs. Two examples are given to show the effectiveness of the proposed boundary control.
Paper VI115-14.19
PDF · Video · Dynamic Resilient Graph Games for State-Dependent Jamming Attacks Analysis on Multi-Agent Systems
Nugraha, Yurid	Tokyo Institute of Technology
Cetinkaya, Ahmet	National Institute of Informatics
Hayakawa, Tomohisa	Tokyo Institute of Technology
Ishii, Hideaki	Tokyo Institute of Technology
Zhu, Quanyan	New York University
Keywords: Multi-agent systems, Stochastic control and game theory Abstract: A cybersecurity problem for a multi-agent consensus problem is investigated through a dynamic game formulation. Specifically, we consider a game repeatedly played between a jamming attacker and a defender. The attacker attempts to jam the links between a number of agents to delay their consensus. On the other hand, the defender tries to maintain the connection between agents by attempting to recover some of the jammed links with the goal of achieving faster consensus. In each game, the players decide which links to attack/recover and for how long to continue doing so based on a Lyapunov-like function representing the largest difference between the states of the agents. We analyze the subgame perfect equilibrium of the game and obtain an upper bound of the consensus time that is influenced by the strategies of the players. The results are illustrated with a numerical example.
Paper VI115-14.20
PDF · Video · Laplacian Controllability of a Class of Non-Simple Ring Graphs
Yang, Ping-Yen	National Chung-Hsing University
Hsu, Shun-Pin	National Chung Hsing Univ
Keywords: Control of networks, Multi-agent systems, Consensus Abstract: The Laplacian controllability of a family of graphs that are non-simple is studied in the paper. Without the regular assumption that the adjacency matrix is binary, the authors consider more flexible weighting parameters to represent the practical connection strength between nodes. Suppose the node states of the graphs evolve according to the Laplacian dynamics. The Laplacian eigenspaces of a class of ring graphs are explored, by which a sufficient condition to render the graphs controllable with the minimum number of input is proposed. Numerical examples are provided to illustrate the theoretical results.
Paper VI115-14.21
PDF · Video · Asymptotic Analysis for Greedy Initialization of Threshold-Based Distributed Optimization of Persistent Monitoring on Graphs
Welikala, Shirantha	Boston University
Cassandras, Christos G.	Boston Univ
Keywords: Control over networks, Multi-agent systems, Optimal control of hybrid systems Abstract: We consider the optimal multi-agent persistent monitoring problem defined for a team of agents on a set of nodes (targets) interconnected according to a fixed graph topology. The objective is to minimize a measure of mean overall node state uncertainty evaluated over a finite time interval. In prior work, a class of distributed threshold-based parametric controllers has been proposed where agent dwell times at nodes and transitions from one node to the next are controlled by enforcing thresholds on the respective node uncertainties. Under such a threshold policy, on-line gradient-based techniques are then used to determine optimal threshold values. However, due to the non-convexity of the problem, this approach leads to often poor local optima highly dependent on the initial thresholds used. To overcome this initialization challenge, in this paper, the asymptotic steady-state behavior of the agent-target system is extensively analyzed for a single-agent system and dense graphs. Based on the obtained theoretical results, a computationally efficient off-line greedy technique is developed to systematically generate initial thresholds. Extensive numerical results show that the initial thresholds obtained lead to significantly better results than the locally optimal solutions known to date.
Paper VI115-14.22
PDF · Video · No-Regret Learning for Coalitional Model Predictive Control
Chanfreut, Paula	University of Seville
Maestre, Jose M.	University of Seville
Zhu, Quanyan	New York University
Camacho, Eduardo F.	University of Seville
Keywords: Control under communication constraints, Multi-agent systems, Learning for control Abstract: In this paper, we introduce a learning approach for the controller structure in coalitional model predictive control (MPC) schemes. In this context, the local control entities can dynamically perform in a decentralized manner or assemble into groups of controllers that coordinate their control actions. Such control strategy aims at maximizing system performance while reducing coordination and computation burden. In this paper, we pose a muli-armed bandit problem where the arms are a set of possible controller structures and the player performs as a supervisory layer that can periodically change the composition of the coalitions. The goal is to use real-time observations to progressively learn to choose the controller structure that best suits the needs of the system. A heuristic learning algorithm and illustrative results are provided.
Paper VI115-14.23
PDF · Video · Privacy Preserving Distributed Summation in a Connected Graph
Tjell, Katrine	Aalborg University
Wisniewski, Rafal	Aalborg University
Keywords: Privacy Abstract: Most decentralized algorithms for multi-agent systems used in control, signal processing and machine learning for example, are designed to fit the problem where agents can only communicate with immediate neighbors in the network. For instance, decentralized and distributed optimization algorithms are based on the fact that every agent in a network will be able to influence every other agent in the network even if each agent only communicates with its immediate neighbors (given that the network is connected). That is, a distributed optimization problem can be solved in a decentralized manner by letting the agents exchange messages with their neighbors iteratively. In many algorithms that solve this kind of problem, agents in the network does not need individual values from their neighbors, rather they need a function of the values from its neighbors. This observation makes it interesting to consider privacy preservation in such algorithms. By privacy preservation, we mean that raw data from individual agents will not be exposed at any time during calculations. This paper is concerned with decentralized algorithms, where each agent must learn the sum of its neighbors values, and we propose a privacy preserving method to compute this sum. Employing this method in corresponding decentralized algorithms makes the whole algorithm privacy preserving. The only restriction we make on the graph topology of the network is that each agent must have at least two neighbors. We provide simulations of the proposed method, which illustrates the scalability of it.
Paper VI115-14.24
PDF · Video · A Receding Horizon Scheduling Approach for Search & Rescue Scenarios
Emam, Yousef	Georgia Institute of Technology
Wilson, Sean	Georgia Institute of Technology
Hakenberg, Mathias	Siemens
Muenz, Ulrich	Siemens
Egerstedt, Magnus	Georgia Institute of Technology
Keywords: Multiagent systems, Job and activity scheduling Abstract: Many applications involving complex multi-task problems such as disaster relief, logistics and manufacturing necessitate the deployment and coordination of heterogeneous multi-agent systems due to the sheer number of tasks that must be executed simultaneously. A fundamental requirement for the successful coordination of such systems is leveraging the specialization of each agent within the team. This work presents a Receding Horizon Planning (RHP) framework aimed at scheduling tasks for heterogeneous multi-agent teams in a robust manner. In order to allow for the modular addition and removal of different types of agents to the team, the proposed framework accounts for the capabilities that each agent exhibits (e.g. quadrotors are agile and agnostic to rough terrain but are not suited to transport heavy payloads). An instantiation of the proposed RHP is developed and tested for a search and rescue scenario. Moreover, we present an abstracted search and rescue simulation environment, where a heterogeneous team of agents is deployed to simultaneously explore the environment, find and rescue trapped victims, and extinguish spreading fires as quickly as possible. We validate the effectiveness of our approach through extensive simulations comparing the presented framework with various planning horizons to a greedy task allocation scheme.
Paper VI115-14.25
PDF · Video · Information Value on Private State Inference in Network Systems
Jiang, Hao	Shanghai Jiao Tong University
Ding, Xuda	Shanghai Jiao Tong University
He, Jianping	Shanghai Jiao Tong University
Peng, Yunfeng	Shanghai Jiao Tong University
Keywords: Privacy, Security Abstract: In network systems, neighboring nodes usually need to exchange and update their state information iteratively to achieve a global computation and control goal. Considering the nodes' states may include some sensitive/private information, e.g., location and income, different random mechanises have been proposed to preserve the privacy of the states. However, no matter what type of random mechanisms is used, the eavesdropping attacker can infer/estimate a node's state based on the information it holds, and the estimation depends on the available information. The relationship between the estimation and the information is a critical and open issue. Therefore, in this paper, we investigate how to obtain the optimal estimation of a node's state with available information and how to quantify the value of the information in the state inference. First, we exploit a utility function to quantify the utility of the estimation accuracy, and then the optimal estimation and information value are defined to depict the estimation and quantify the information, respectively. Next, the optimal estimation under different settings of the noise and utility function are provided. Lastly, we obtain some important properties of information value and analyze the value of state outputs in distributed algorithms.
Paper VI115-14.26
PDF · Video · Two-On-One Pursuit When the Pursuers Have the Same Speed As the Evader
Vlassakis, Mark	Air Force Institute of Technology
Pachter, Meir	Air Force Institute of Technology
Keywords: Guidance, navigation and control of vehicles, Navigation, Guidance and Control, Robot Navigation, Programming and Vision Abstract: A two-on-one pursuit-evasion differential game is considered. The setup is akin to Isaacs' Two Cutters and Fugitive Ship differential game. In this paper it is however assumed that the three players have equal speeds and the two cutters/pursuers have a non-zero capture radius. The case where just one of the Pursuers is endowed with a circular capture set is also considered. The state space region where capture is guaranteed is delineated, thus providing the solution of the Game of Kind, and the players' optimal state feedback strategies and the attendant value function are synthesized, thus providing the solution of the Game of Degree.
Paper VI115-14.27
PDF · Video · Distributed Linear Quadratic Tracking Control for Leader-Follower Multi-Agent Systems: A Suboptimality Approach
Jiao, Junjie	University of Groningen
Trentelman, Harry L.	Univ. of Groningen
Camlibel, Kanat	University of Groningen
Keywords: Complex systems, Optimal control theory, Linear systems Abstract: In this paper, we extend the results from Jiao et al. (2019) on distributed linear quadratic control for leaderless multi-agent systems to the case of distributed linear quadratic tracking control for leader-follower multi-agent systems. Given one autonomous leader and a number of homogeneous followers, we introduce an associated global quadratic cost functional. We assume that the leader shares its state information with at least one of the followers and the communication between the followers is represented by a connected simple undirected graph. Our objective is to design distributed control laws such that the controlled network reaches tracking consensus and, moreover, the associated cost is smaller than a given tolerance for all initial states bounded in norm by a given radius. We establish a centralized design method for computing such suboptimal control laws, involving the solution of a single Riccati inequality of dimension equal to the dimension of the local agent dynamics, and the smallest and the largest eigenvalue of a given positive definite matrix involving the underlying graph. The proposed design method is illustrated by a simulation example.
Paper VI115-14.28
PDF · Video · Cooperative R-Passivity Based Control for Mechanical Systems
de Groot, Oscar	Delft University of Technology
Keviczky, Tamas	Delft University of Technology
Keywords: Remote and distributed control, Tele-robotics, Telecommunication-based automation systems Abstract: In this work we consider the problem of cooperative end-effector control between heterogeneous fully actuated agents when varying-time delays and/or packet loss are present. We couple agents via outputs encoded with task-space coordinates and velocities that are transformed into wave-variables to overcome the destabilising effects of the communication network. The scheme poses dynamic requirements on the agents which are locally satisfied with feedback control that integrates subtasks, such as joint-limit avoidance or local tracking, when there are redundant degrees-of-freedom. The proposed approach extends existing methods to task-space control. The approach is robust to network effects, applies to nonlinear systems and is scalable by design. The tuning task is simplified considerably by separation of the cooperative and non-cooperative control terms. We demonstrate the efficacy of the proposed approach experimentally.

VI115-15
Security of Networked Control Systems	Regular Session
Chair: Ishii, Hideaki	Tokyo Institute of Technology
Co-Chair: Xie, Lihua	Nanyang Technological University
Paper VI115-15.1
PDF · Video · Security Enhancement of Sampled-Data Systems: Zero Assignment Via Generalized Sampler
Kim, Daehan	Kwangwoon University
Ryu, Kunhee	Kwangwoon University
Back, Juhoon	Kwangwoon University
Keywords: Secure networked control systems Abstract: Remote control systems have advantages in terms of flexibility and efficiency, but at the same time, they are exposed to cyber-attacks. Zero-dynamics attack is one of the most lethal model-based cyber attacks due to its stealthiness. In this paper, a new zero-dynamics attack neutralizing strategy is proposed, which is based on the generalized sampler. By using generalized sampler, the zeros of the discrete-time system can be placed at arbitrary locations, and if all zeros are placed inside the unit circle, the attack signal itself is neutralized. This strategy still works even if all the information is exposed to hackers. Furthermore, the proposed method is insensitive to shifting the intrinsic zeros comparing to the existing zero-assignment based methods. A design procedure of generalized sampler is provided, and theoretical findings are validated through the numerical simulations.
Paper VI115-15.2
PDF · Video · Denial of Service Attacks on Control Systems with Packet Loss
Casbolt, William	University of Sheffield
Esnaola, Iñaki	University of Sheffield
Jones, Bryn L.	University of Sheffield
Keywords: Secure networked control systems, Control and estimation with data loss, Control under communication constraints Abstract: The performance of control systems with packet loss as a result of an attack over the actuation communication channel is analysed. The operator is assumed to monitor the state of the channel by measuring the average number of packet losses and an attack detection criteria is established based on the statistic. The performance of the attacker is measured in terms of the increase of the linear quadratic cost function of the operator subject to a given detection constraint. Within that setting, the optimal denial of service (DoS) attack strategy is formulated for UDP-like and TCP-like communication protocols. For both communication protocols, DoS attack constructions that are independent and identically distributed (IID) are compared to those that are non-stationary. The main contributions of this paper are (i) explicit characterisation of the expected cost increase of the optimal attack constructions and the associated packet loss parameter for the IID case, (ii) proof, by example, that non-stationary random attacks outperform IID attacks in the presence of detection constraints.
Paper VI115-15.3
PDF · Video · Towards the Coarsest Quantized Controller under Denial-Of-Service Attacks
van Dinther, Dorus	Eindhoven University of Technology
Feng, Shuai	Tokyo Institute of Technology
Ishii, Hideaki	Tokyo Institute of Technology
Heemels, Maurice	Eindhoven University of Technology
Keywords: Secure networked control systems, Control and estimation with data loss, Control under communication constraints Abstract: In this paper, we consider networked control systems under Denial-of-Service (DoS) attacks. The control objective is to synthesize a quantized controller in which the quantizer is as coarse as possible for a networked control system subject to DoS attacks, while still guaranteeing (quadratic) stability. Our main result will explicitly show the trade-offs between system robustness against DoS and quantizer coarseness. A simulation example will demonstrate the strengths of the new method.
Paper VI115-15.4
PDF · Video · Event-Triggered Approach to Increasing Sampling Period of Encrypted Control Systems
Teranishi, Kaoru	The University of Electro-Communications
Ueda, Jun	Georgia Institute of Technology
Kogiso, Kiminao	University of Electro-Communications
Keywords: Secure networked control systems, Control over networks, Quantized systems Abstract: Controller encryption is a cryptographic approach to enhancing the security of networked control systems. The method would be effective in reducing risks of eavesdropping attacks. However, encryption may cause high communication traffic and processing delays. This study proposes a redetermination method for a sampling period of a given encrypted control system to increase the sampling period. The proposed method can reduce the bit rate of communication between a plant and controller and improving the strength of ciphertexts. The validity of the proposed method is examined through numerical simulations. The simulation results demonstrate that the sampling period-redetermined encrypted control system achieves asymptotic stability and retains control performance of the original encrypted control system.
Paper VI115-15.5
PDF · Video · Encrypted MPC Based on ADMM Real-Time Iterations
Schulze Darup, Moritz	Universität Paderborn
Keywords: Secure networked control systems, Control over networks, Quantized systems Abstract: Encrypted control enables confidential controller evaluations in cloud-based or networked control systems. Technically, an encrypted controller is a modified control algorithm that is capable of computing encrypted control actions based on encrypted system states without intermediate decryption. The realization of such controllers, e.g., using homomorphic encryption, is non-trivial. Nevertheless, even optimization-based model predictive control (MPC) has already been implemented in an encrypted fashion. However, the existing schemes either require an explicit solution of the parametric optimal control problem (OCP) or they can only consider input constraints. In this paper, we present a novel encrypted MPC that allows to include state and input constraints without the requirement of an explicit solution of the OCP. The approach builds on the encrypted implementation of a single iteration of the alternating direction method of multipliers (ADMM) per time step, i.e., ADMM real-time iterations.
Paper VI115-15.6
PDF · Video · Disconnection-Aware Attack Detection in Networked Control Systems
Sasahara, Hampei	KTH Royal Institute of Technology
Ishizaki, Takayuki	Tokyo Institute of Technology
Imura, Jun-ichi	Tokyo Institute of Technology
Sandberg, Henrik	KTH Royal Institute of Technology
Keywords: Secure networked control systems, Distributed control and estimation Abstract: This study deals with security issues in dynamical networked control systems. The goal is to establish a uni ed framework of the attack detection stage, which includes the four processes of monitoring the system state, making a decision based on the monitored signal, disconnecting the corrupted subsystem, and operating the remaining system during restoration. This paper, in particular, considers a disconnection-aware attack detector design problem. Traditionally, observer-based attack detectors are designed based on the system model with afixed network topology and cannot cope with a change of the topology caused by disconnection. The disconnection-aware design problem is mathematically formulated and a solution is proposed in this paper. A numerical example demonstrates the effectiveness of the proposed detector through an inverter-based voltage control system in a benchmark model.
Paper VI115-15.7
PDF · Video · On Detectability of Cyber-Attacks for Large-Scale Interconnected Systems
Gallo, Alexander J.	Imperial College London
Barboni, Angelo	Imperial College London
Parisini, Thomas	Imperial College & Univ. of Trieste
Keywords: Secure networked control systems, Distributed control and estimation, Fault detection and diagnosis Abstract: The paper deals with the key problem of detecting cyber-attacks in the context of large-scale systems (LSS). As these systems grow in size and complexity, cyber-attacks may target limited parts of the LSS, leading to tackling the problem in a decentralized way. We analyze the properties of distributed detection schemes under both local and interconnection attacks, and show that they are vulnerable to attacks that exploit the structure of the interconnections between subsystems. We also provide conditions and strategies that may be adopted to make the distributed control architecture regulating the LSS robust to this class of cyber-attacks.
Paper VI115-15.8
PDF · Video · An Optimal Linear Attack Strategy on Remote State Estimation
Liu, Hanxiao	Nanyang Technological University
Ni, Yuqing	Hong Kong University of Science and Technology
Xie, Lihua	Nanyang Technological University
Johansson, Karl H.	Royal Institute of Technology
Keywords: Secure networked control systems, Estimation and filtering, Sensor networks Abstract: This work considers the problem of designing an attack strategy on remote state estimation under the condition of strict stealthiness and epsilon-stealthiness of the attack. An attacker is assumed to be able to launch a linear attack to modify sensor data. A metric based on Kullback-Leibler divergence is adopted to quantify the stealthiness of the attack. We propose a generalized linear attack based on past attack signals and the latest innovation. We prove that the proposed approach can obtain a worse attack than linear attack strategies recently studied in the literature. The result thus provides a bound on the tradeoff between available information and attack performance, which is useful in the development of mitigation strategies. Finally, some numerical examples are given to evaluate the performance of the proposed strategy.
Paper VI115-15.9
PDF · Video · Dynamic Quantized Consensus of General Linear Multi-Agent Systems under Denial-Of-Service Attacks
Feng, Shuai	Tokyo Institute of Technology
Ishii, Hideaki	Tokyo Institute of Technology
Keywords: Secure networked control systems, Multi-agent systems, Control under communication constraints Abstract: In this paper, we study a multi-agent consensus problem under Denial-of-Service (DoS) attacks with data rate constraints. We consider leaderless consensus under an undirected communication graph and assume that the graph is connected in the absence of DoS. The dynamics of the agents take general forms modeled as homogeneous linear time-invariant systems. In our analysis, we derive specific bounds on the data rate for the multi-agent system to achieve consensus even in the presence of DoS attacks. The main contribution of the paper is the characterization of the trade-off between the tolerable DoS attack level and the required data rates for the communication among the agents. To avoid quantizer saturation under DoS attacks, we employ dynamic quantization with zoom-in and zoom-out capabilities.
Paper VI115-15.10
PDF · Video · On Event-Triggered Implementation of Moving Target Defense Control
Tamba, Tua Agustinus	Parahyangan Catholic University
Hu, Bin	Old Dominion University
Nazaruddin, Yul Yunazwin	Institut Teknologi Bandung (ITB)
Keywords: Secure networked control systems, Optimal control of hybrid systems, Event-based control Abstract: This paper proposes an event-triggered switched control system (ET-SCS) scheme for the implementation of moving target defense (MTD) control strategy in cyber-physical system (CPS). The proposed scheme uses the ET-SCS to obfustace the system structure/appearance while at the same time renders the closed loop CPS trajectories stable in the presence of cyber intrusion on the CPS actuator. The paper develops a mechanism for detecting the presence of such intrusions and then shows the asymptotic stability of the closed loop CPS.
Paper VI115-15.11
PDF · Video · Optimal Tracking Control of Linear Discrete-Time Systems under Cyber Attacks
Liu, Hao	Shenyang Aerospace University
Qiu, Hui	Shenyang Aerospace University
Keywords: Control under communication constraints, Secure networked control systems Abstract: In this paper, the optimal tracking control problem is solved based on the reinforcement learning for linear systems subject to multiple false-data-injection (FDI) attacks. An augmented system is established, which includes the original system and reference-trajectory generator system. The corresponding optimal control issue is formulated as a game problem between the system and malicious adversaries. A Q-learning algorithm is proposed to solve the game algebraic Riccati equation without requiring any knowledge about the dynamics of the augmented system. Finally, an example is provided to show that the system output can track the reference trajectory under cyber attacks.
Paper VI115-15.12
PDF · Video · Graph Anomaly Detection Using Dictionary Learning
Băltoiu, Andra-Elena	University of Bucharest
Patrascu, Andrei	University of Bucharest
Irofti, Paul	University of Bucharest
Keywords: Machine learning Abstract: Anomaly detection in networks often boils down to identifying an underlying graph structure on which the abnormal occurrence rests on. We investigate the problem of learning graph structure representations using adaptations of dictionary learning aimed at encoding connectivity patterns. In particular, we adapt dictionary learning strategies to the specificity of network topologies and propose new methods that impose Laplacian structure on the dictionaries themselves. In one adaption we focus on classifying topologies by working directly on the graph Laplacian and cast the learning problem to accommodate its 2D structure. We tackle the same problem by learning dictionaries which consist of vectorized atomic Laplacians, and provide a block coordinate descent scheme to solve the new dictionary learning formulation. Imposing Laplacian structure on the dictionaries is also proposed in an adaptation of the Single Block Orthogonal learning method. Results on synthetic graph datasets comprising different graph topologies confirm the potential of dictionaries to directly represent graph structure information.

VI115-16
Sensor Networks	Regular Session
Chair: Bhushan, Mani	Indian Institute of Technology Bombay
Co-Chair: Terra, Marco Henrique	University of Sao Paulo
Paper VI115-16.1
PDF · Video · Estimation Oriented Co-Design of Sensor Scheduling Over Stochastic Delayed Channel under Power Constraints
Li, Yao	Shanghai Jiao Tong University
Zhu, Shanying	Shanghai Jiao Tong University
Chen, Cailian	Shanghai Jiao Tong University
Keywords: Sensor networks Abstract: This paper investigates the scheduling problem over a delayed channel. Different from most existing documents, a novel hybrid model is proposed which combines both delay and packet-loss to minimize the error covariance update at the estimator side. With the help of this setup, a co-design problem between power consumption and estimation performance is considered. We first derive out a globally optimal off-line schedule. Moreover, an on-line schedule based on a designed threshold is proposed to further enhance the performance, which is aided by feedback information. Comparisons between on-line and off-line strategies are illustrated by numerical simulations, which has shown the superiority of on-line one to the off-line one.
Paper VI115-16.2
PDF · Video · Distributed Observer Design for Achieving Omniscience Asymptotically Over Time-Variant Disconnected Communication Networks
Xu, Haotian	Shanghai Jiao Tong University
Wang, Jingcheng	Shanghai JiaoTong Univ
Wang, Hongyuan	Shanghai Jiaotong University
Zhao, Shangwei	Shanghai Jiao Tong University
Lin, Hai	Shanghai Jiao Tong University
Keywords: Sensor networks, Consensus, Continuous time system estimation Abstract: This paper investigates the distributed observer design for linear system under time-variant disconnected communication network. By constructing basic eigenvectors of 0-eigensubspace of disconnected Laplacian Matrix and using LMIs method, we prove the distributed observer cannot achieve omniscience asymptotically under switching topology without constraining the system matrix or alternative topologies set. To deal with this problem, this paper investigates three kinds of constraints and the system matrix only needs to satisfy any one of them. Then a group of sufficient conditions corresponding to the asymptotic omniscience of distributed observer under switching topology are proved by Lyapunov analysis. Furthermore, our results are also valid for some unstable system matrices. Finally, two numerical simulations show the validity of our method.
Paper VI115-16.3
PDF · Video · Robust Distributed Consensus-Based Filtering for Uncertain Systems Over Sensor Networks
Teófilo Rocha, Kaio Douglas	University of São Paulo
Terra, Marco Henrique	University of Sao Paulo
Keywords: Sensor networks, Distributed control and estimation, Consensus Abstract: Distributed consensus-based estimation is one of the main applications of sensor networks. Most approaches are highly dependent on exact model knowledge. This limitation motivated the development of robust distributed filters that deal with model uncertainties. Many of these works, however, are not fully distributed filters or demand high communication and computational efforts. In this paper, we propose a robust distributed consensus-based filter for uncertain discrete-time linear systems. We assume norm-bounded parametric uncertainties in all matrices of both the target system and sensing models. The approach consists of adopting a purely deterministic interpretation of the robust distributed estimation problem, formulated by combining the penalty function method and the robust regularized least-squares estimation problem. The filter is presented in a fully distributed Kalman-like structure that is suitable for online applications, requiring acceptable computational and communication efforts. We evaluate the effectiveness of the proposed filter by comparing its performance with an existing robust distributed filter, as well as with a centralized strategy.
Paper VI115-16.4
PDF · Video · Distributed Diffusion Unscented Kalman Filtering Algorithm with Application to Object Tracking
Chen, Hao	Beijing Institute of Technology
Wang, Jianan	Beijing Institute of Technology
Wang, Chunyan	Beijing Institute of Technology
Wang, Dandan	Beijing Institute of Technology
Shan, Jiayuan	Beijing Institute of Technology
Xin, Ming	University of Missouri
Keywords: Sensor networks, Distributed control and estimation, Estimation and filtering Abstract: In this paper, a distributed diffusion unscented Kalman filtering algorithm based on covariance intersection strategy (DDUKF-CI) is proposed for object tracking. By virtue of the pseudo measurement matrix, the standard unscented Kalman filtering (UKF) is transformed to the information form that can be fused by the diffusion strategy. Then, intermediate information from neighbors are fused based on the diffusion framework to attain better estimation performance. Considering the unknown correlations in sensor networks, covariance intersection (CI) strategy is combined with the diffusion algorithm. Moreover, it is proved that the estimation error of the proposed DDUKF-CI is exponentially bounded in mean square using the stochastic stability theory. Finally, the performances of the proposed algorithm and the weighted average consensus unscented Kalman filtering (CUKF) are compared in a target tracking problem with a sensor network.
Paper VI115-16.5
PDF · Video · A Novel Information Theoretic Measure Based Sensor Network Design Approach for Steady State Linear Data Reconciliation
Prakash, Om	Indian Institute of Technology Bombay
Bhushan, Mani	Indian Institute of Technology Bombay
Keywords: Sensor networks, Estimation and filtering Abstract: The current work proposes a novel information theoretic based sensor network design (SND) approach for data reconciliation in a steady state linear process. The proposed approach is based on Kullback-Leibler divergence (KLD), which measures the difference of a density function from a reference density function. In particular, the optimal design is the one that leads to the smallest KLD value of the designed density function of the estimates from a reference density function. This reference density function can be provided by the end-user, and the approach thus enables explicit incorporation of the end-user’s preference in the SND procedure. Additionally, the approach does not assume specific forms for the density functions of the estimates and is thus also applicable for cases when the estimates have non-Gaussian density. The significance of the approach is illustrated on a small example. To demonstrate its utility in obtaining optimal sensor networks, it is also applied to a popular case study from SND literature and results are compared with existing approaches.
Paper VI115-16.6
PDF · Video · Consensus-Based Distributed Algorithm for Multisensor-Multitarget Tracking under Unknown-But-Bounded Disturbances
Amelina, Natalia	Saint-Petersburg State University
Erofeeva, Victoria	Saint Petersburg State University
Granichin, Oleg	Saint Petersburg State University
Ivanskiy, Yury	Saint Petersburg State University
Jiang, Yuming	Norwegian University of Science and Technology
Proskurnikov, Anton V.	Politecnico Di Torino
Sergeenko, Anna	St. Petersburg State University
Keywords: Sensor networks, Randomized methods, Consensus Abstract: We consider a dynamic network of sensors that cooperate to estimate parameters of multiple targets. Each sensor can observe parameters of a few targets, reconstructing the trajectories of the remaining targets via interactions with 'neighbouring' sensors. The multi-target tracking has to be provided in the face of uncertainties, which include unknown-but-bounded drift of parameters, noise in observations and distortions introduced by communication channels. To provide tracking in presence of these uncertainties, we employ a distributed algorithm, being an 'offspring' of a consensus protocol and the stochastic gradient descent. The mathematical results on the algorithm's convergence are illustrated by numerical simulations.
Paper VI115-16.7
PDF · Video · Social Organisation of Mobile Sensors for Wildfire Spread Estimation
Plenet, Théo	University of Perpignan Via Domitia
Lefevre, Laurent	Univ. Grenoble Alpes
Raievsky, Clement	Université Grenoble Alpes
El Yacoubi, Samira	University of Perpignan Via Domitia
Keywords: Multi-agent systems, Sensor networks, Distributed control and estimation Abstract: In this paper, we focus on social organisation of mobile sensor network for the observation of distributed parameter systems. We built a framework that allows us to compare different social organisation in terms of observation performance. First, we studied the topology of generic social organisation with graph theory criteria. Then, we benchmarked some of these organisations when we applied them to mobile sensor network for the observation of a cellular-automaton simulated wildfire.

VI121
Design Methods - Control Design
VI121-01 New Trends on Digital Control Systems   Invited Session, 6 papers
VI121-02 Fractional Order Differentiation in Modeling and Control   Open Invited Session, 20 papers
VI121-03 Adaptive Control Design   Regular Session, 21 papers
VI121-04 Controller Constraints and Structure   Regular Session, 7 papers
VI121-05 Data Based and Data Driven Control   Regular Session, 13 papers
VI121-06 Decentralised and Distributed Control   Regular Session, 11 papers
VI121-07 Fault Tolerant Control Design   Regular Session, 9 papers
VI121-08 Observer and Estimator Design   Regular Session, 14 papers
VI121-09 Optimal and Predictive Controller Design and Optimization   Regular Session, 8 papers
VI121-10 Singular and Descriptor Systems   Regular Session, 6 papers

VI121-01
New Trends on Digital Control Systems	Invited Session
Chair: Mattioni, Mattia	Università Degli Studi Di Roma La Sapienza
Co-Chair: Normand-Cyrot, Marie-Dorothée	CNRS-Univ. Paris-Sud-Supélec
Organizer: Normand-Cyrot, Marie-Dorothée	CNRS-Univ. Paris-Sud-Supélec
Organizer: Monaco, Salvatore	Sapienza Università Di Roma
Organizer: Mattioni, Mattia	Università Degli Studi Di Roma La Sapienza
Paper VI121-01.1
PDF · Video · Using Delays for Digital Implementation of Derivative-Dependent Control of Stochastic Multi-Agents (I)
Zhang, Jin	Tel Aviv University
Fridman, Emilia	Tel-Aviv Univ
Keywords: Digital implementation, infinite-dimensional multi-agent systems and networks, Output feedback control Abstract: In this paper, we study the digital implementation of derivative-dependent control for consensus of the nth-order stochastic multi-agent systems. The consensus controllers that depend on the output and its derivatives up to the order n-1 are approximated as delayed sampled-data controllers. For the consensus analysis, we propose novel Lyapunov-Krasovskii functionals to derive linear matrix inequalities (LMIs) that allow to find admissible sampling period. The efficiency of the presented approach is illustrated by numerical examples.
Paper VI121-01.2
PDF · Video · Hypertracking: A New Approach to Signals Beyond the Nyquist Frequency —a Brief Overview (I)
Yamamoto, Kaoru	Kyushu University
Yamamoto, Yutaka	Kyoto Univ
Nagahara, Masaaki	The University of Kitakyushu
Keywords: Linear systems, Disturbance rejection (linear case), Robust control (linear case) Abstract: Shannon’s sampling theory has had a great impact not only on signal processing, but also on digital control theory. According to this theory it is universally believed that the so-called Nyquist frequency is the absolute upper bound for any control objectives. For example, tracking or rejection of signals that resides beyond the Nyquist frequency has been regarded impossible. On the other hand, such a demand can often be encountered in practice. Disturbance rejection of winds in hard disc drives where such a disturbance usually occurs at a frequency higher than the Nyquist frequency are such examples. The present paper summarizes the recent results obtained by the authors that show that such high frequency tracking/rejection problems are indeed solvable, even for the case that involve multiple tacking and rejection signals simultaneously. It is also possible to give a robustness result that also exhibits an interesting relationship between robustness and delay length introduced for tracking and rejection. The paper gives a brief overview of the results obtained thus far, and also provides a new result on robustness. Some simulation results are presented to show that the method can work in various practical situations.
Paper VI121-01.3
PDF · Video · Stability Analysis for a Class of Linear Hyperbolic System of Balance Laws with Sampled-Data Control (I)
Wang, Xinyong	Centralelille, CRIStAL UMR CNRS 9189
Tang, Ying	Université De Lille, CNRS-CRIStAL UMR 9189
Fiter, Christophe	Université Lille1 - Sciences Et Technologies
Hetel, Laurentiu	CNRS
Keywords: Digital implementation, stability of distributed parameter systems, Lyapunov methods Abstract: The stability for a class of linear hyperbolic systems with distributed sampled-data controllers is discussed in this paper. The original sampled-data system is firstly transformed into a new equivalent system by modelling the sampling induced error as a reset integrator operator. Then we construct an appropriate Lyapunov function and obtain sufficient conditions for the R epsilon - stability of the system based on linear matrix inequalities (LMIs). A numerical example illustrates our results: when the sampling interval is within the allowable range, the solution of the system converges from the domain of attraction to a positive invariant set.
Paper VI121-01.4
PDF · Video · Sampled-Data Output Feedback Controllers for Nonlinear Systems with Time-Varying Measurement and Control Delays (I)
Battilotti, Stefano	Univ. La Sapienza
Keywords: Asymptotic stabilization, Systems with time-delays, Digital implementation Abstract: In this paper, we propose sampled-data output feedback controllers for nonlinear systems with time-varying measurement and input delays. A state prediction is generated by chains of saturated high-gain observers with switching error-correction terms and the state prediction is used to stabilize the system with saturated controls. The observers reconstruct the unmeasurable states at dierent delayed time-instants, which partition the maximal variation interval of the time-varying delays. The density of these delayed time instant depend both on the magnitude of the delays and the growth rate of the nonlinearities. Our sampled-data feedback controllers are obtained as zero-order discretizations of continuous time controllers.
Paper VI121-01.5
PDF · Video · Sampled-Data Tracking under Model Predictive Control and Multi-Rate Planning (I)
Elobaid, Mohamed	Università Degli Studi Di Roma La Sapienza
Mattioni, Mattia	Università Degli Studi Di Roma La Sapienza
Monaco, Salvatore	Sapienza Università Di Roma
Normand-Cyrot, Marie-Dorothée	CNRS-Univ. Paris-Sud-Supélec
Keywords: Digital implementation, Nonlinear predictive control, Tracking Abstract: In this paper, a new control scheme for sampled-data nonlinear model predictive control is proposed making use of a multi-rate based trajectory planning for designing admissible references over the prediction horizon. The proposed controller is compared with existing reference generators for model predictive control through simulations over a benchmark example.
Paper VI121-01.6
PDF · Video · Sampled-Data Static Output Feedback Control of the Glucose-Insulin System (I)
Di Ferdinando, Mario	Università Degli Studi Dell'Aquila
Pepe, Pierdomenico	University of L'Aquila
Di Gennaro, Stefano	Univ. Di L'Aquila
Palumbo, Pasquale	University of Milano-Bicocca
Keywords: Delay systems, Digital implementation, Control in system biology Abstract: In this paper, the plasma glucose regulation problem for Type 2 diabetic patients is studied. A nonlinear time-delay model of the glucose-insulin regulatory system is exploited in order to design a sampled-data static output feedback control, which makes use of only sampled glucose measurements. It is shown that the proposed control law is a stabilizer in the sampled-and-hold sense. The presence of a state-delay in the model prevents the availability in the buffer of suitable needed past values of the glucose. Such a drawback is overcome by means of spline interpolation. A pre-clinical validation, concerning the performances of the proposed glucose control law, is carried-out by means of a well known simulator of diabetic patients broadly accepted for testing insulin infusion therapies. Simulations results are encouraging for further evaluation.

VI121-02
Fractional Order Differentiation in Modeling and Control	Open Invited Session
Chair: Victor, Stephane	Université De Bordeaux, IMS
Co-Chair: Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Organizer: Victor, Stephane	Université De Bordeaux, IMS
Organizer: Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Paper VI121-02.1
PDF · Video · On-Line Estimation of the Caputo Fractional Derivatives with Application to P I^mu D^nu Control (I)
Ibrir, Salim	King Fahd University of Petroleum and Minerals
Keywords: Fractional systems, Time-varying systems, Robust estimation Abstract: This paper proposes new procedures for calculation of the Caputo derivative of model-free measured signals. The evaluation of the non-integer derivative is realized by integrating a set of ordinary differential equations and convolution. The derivative of order nu (0 < nu < 2) is seen as an output of a linear-time-varying system driven by a time-dependent known signal. Two procedures are proposed depending on the variation range of the non-integer differentiation order. The proposed formulations facilitate the estimation of the fractional derivatives when they are associated to dynamical systems represented by integer-order differential equations. The efficiency of the developed numerical procedures are validated and compared to exact fractional derivatives for different values of nu. It is shown that P I^mu D^nu controllers can be easily realized by system augmentation and convolution. The advantages, the straightforwardness and the main features of the proposed design are given.
Paper VI121-02.2
PDF · Video · Hinf-Synthesis and Control of Uncertain Fractional-Order Systems of Commensurate Type (I)
Ibrir, Salim	King Fahd University of Petroleum and Minerals
Keywords: Robust control (linear case), Fractional systems, Control problems under conflict and/or uncertainties Abstract: New Linear-Matrix-Inequality (LMI) conditions are proposed for Hinf analysis and synthesis of uncertain fractional-order systems where the non-integer order of differentiation belongs to the set ]0 2[. The developed conditions are extended LMI conditions involving additional LMI variables needed for numerical calculation of the feedback gains. The stability conditions are embedded with the necessary Hinf LMI conditions leading to new formulation of the bounded-real-lemma result. The stabilizability conditions with Hinf performance are subsequently derived and tested with static-pseudo-state feedbacks and static-output feedbacks as well.
Paper VI121-02.3
PDF · Video · On Fractional Order Predictive PI Controller Design for a MIMO Reactive Distillation Process (I)
Edet, Emmanuel	University of Chichester
Keywords: Predictive control, Linear multivariable systems, Fractional systems Abstract: In this paper, fractional-order predictive PID control scheme is applied in composition control of boiling fractions of a reactive distillation plant set up for the esterification reaction between acetic acid and ethanol. The controller shares similar structural features with Model-based Predictive Controller (MPC) as many attractive benefits of Dynamic Matrix Control (DMC) are retained such as constraint handling capability. However, it optimizes a different objective function formulated to achieve a more robust control action. These robust properties make it attractive to multivariable process control applications. Process’s state space model is assumed to be available and the model is augmented for prediction of future outputs. Thereafter, a structured cost function is defined which retains the design objective of fractional-order predictive PI controller. Optimisation of this cost function results in realising a near-optimal MIMO controller with reduced input control efforts. Simulation studies using Giwa’s reactive distillation column demonstrates better control performance over dynamic matrix control of the same system. It also rejects disturbances, both measured and unknown disturbances, better than Dynamic Matrix Control system under similar conditions. A major contribution of this paper is the development of a MIMO fractional order predictive PI controller for multivariable process control applications such as composition control of a reactive distillation column.
Paper VI121-02.4
PDF · Video · Fractional Order [Proportional Integral Derivative] Controller Design with Specification Constraints: More Flat Phase Idea (I)
Wu, Zhenlong	Tsinghua University
Chen, Yuquan	University of Science and Technology of China
Viola, Jairo	University of California Merced
Luo, Ying	South China Univ. of Tech. & Utah State Univ
Chen, YangQuan	University of California, Merced
Li, Donghai	Tsinghua University
Keywords: Robust controller synthesis, Parametric optimization, Time-invariant systems Abstract: The fractional order proportional integral derivative controller is attracting more and more attention. To design a controller with some specification constraints for the first order plus time delay (FOPTD) system, the idea of the "more flat phase" and the structure of the fractional order [proportional integral derivative] (FO[PID]) controller are proposed in this paper. Firstly, the stability region of the FO[PID] controller and the controller design with the "more flat phase" are introduced. Then the design procedure is presented by a simulation, and the pseudo code of the design procedure to obtain the parameter pairs and the achievable region is offered. The effectiveness of the proposed design method for the FO[PID] controller is verified by the experiment on the Peltier temperature control platform and the experiment results show a great potential in industrial applications.
Paper VI121-02.5
PDF · Video · Design of a Robust Fractional Order Controller for Burning Zone Temperature Control in an Industrial Cement Rotary Kiln (I)
Feliu, Vicente	Univ of Castilla-La Mancha
Rivas-Perez, Raul	Havana Technological University
Keywords: Fractional systems, Systems with time-delays, Robust control (linear case) Abstract: The control of the temperature of the burning zone of an industrial cement rotary kiln is addressed in this paper. An experimental identification of the process was carried out, which yielded a second order transfer function with no zeros but with a very large time delay. Moreover, it was detected that this time delay could change between ±8% of its nominal value. Then a robust controller had to be designed for this process. A standard PI controller, a PI controller embedded in a Smith Predictor scheme, and a fractional-order controller embedded in a Smith Predictor have been studied. A method to design the fractional-order controller is developed in this paper that yields better results than the other studied controllers. Simulated results are presented.
Paper VI121-02.6
PDF · Video · A Fractional Order Controller Design Based on Bode's Ideal Transfer Function and Bode's Ideal Cut-Off Ideas (I)
Zheng, Weijia	Foshan University
Luo, Ying	South China Univ. of Tech. & Utah State Univ
Chen, YangQuan	University of California, Merced
Keywords: Fractional systems, Disturbance rejection (linear case), Analytic design Abstract: In order to improve the anti-load disturbance performance of a class of motion control systems, an improved fractional order controller design based on the Bode's ideal transfer function (BITF) is proposed in this paper. By adding a proportional-integral (PI) controller and a Bode's ideal cut-off (BICO) filter into the existing BITF based controller, the frequency characteristics of the control system in the low and high frequency ranges are improved without affecting the characteristics in the middle frequency range. Therefore, the steady-state accuracy and anti-disturbance performance of the system can be improved. A tuning method for the improved BITF based controller is proposed, using which the controller parameters can be obtained through simple calculation. The step response and disturbance rejection performance of the improved BITF based control system is illustrated by motion control simulation. Besides, the advantage of the proposed method is verified by the comparisons with some existing methods.
Paper VI121-02.7
PDF · Video · Design of Fractional-Order Lag Network and Fractional-Order PI Controller for a Robotic Manipulator (I)
Mandić, Petar D.	University of Belgrade
Lino, Paolo	Politecnico Di Bari
Maione, Guido	Politecnico Di Bari
Lazarevic, Mihailo	Full Professor, University of Belgrade, Faculty of Mechanical
Šekara, Tomislav	Faculty of Electrical Engineering, University of Belgrade
Keywords: Fractional systems, Infinite-dimensional systems, Output feedback control (linear case) Abstract: Motion control of robotic manipulators is frequently realized by independent control of the DC motors actuating robot joints. Namely, nonlinearities, coupling between actuators and other complex dynamics are neglected if high gear ratios between the actuators and robot joints are considered. This paper proposes a fractional-order lag network or a fractional-order PI controller to control the position of the actuators shafts. The introduced fractional compensators are designed by using the symmetrical optimum principle and by parameters optimization or by frequency-domain loop shaping, respectively. Simulation results and frequency response show effectiveness and robustness of the approach.
Paper VI121-02.8
PDF · Video · Topology Identification of Fractional Complex Networks with an Auxiliary Network (I)
Hai, Xudong	Beijing Jiaotong University
Yu, Yongguang	Beijing Jiaotong University
Keywords: Fractional systems, Networked systems, system identification and adaptive control of distributed parameter systems Abstract: In this paper, topology identification of fractional complex networks is investigated. First of all, an important result is obtained, which reveals some special relations between the primitive function and its fractional derivative. Then an auxiliary network consisting of isolated nodes and a regulation mechanism are designed in order that there is no need to check the linear independence condition (LIC) and the identification failure caused by network synchronization can be avoided. By applying inequality techniques, the realizability of topology identification for fractional systems is proved. And then two algorithms are given to identify the unknown parameters in the original network. In order to have more realistic significance, the accuracy function, which is an upper bound of the estimation error between the estimated results and the corresponding unknown parameters, is considered to evaluate the validity of our estimation algorithms. Furthermore, an example is provided to demonstrate the effectiveness of the main results.
Paper VI121-02.9
PDF · Video · Robust Interval Observer Design for Fractional-Order Models with Applications to State Estimation of Batteries (I)
Hildebrandt, Erik	University of Rostock, Chair of Technical Dynamics
Kersten, Julia	University of Rostock
Rauh, Andreas	University of Rostock
Aschemann, Harald	University of Rostock
Keywords: Fractional systems, Robust estimation, Energy systems Abstract: Interval observers have been investigated by many researchers during the last decade, especially for those classes of systems that can be described by finite-dimensional continuous-time ordinary differential equations, discrete-time difference equations, and sets of partial differential equations in which both, system parameters and external disturbances, may be subject to bounded uncertainty. In contrast to this, only preliminary investigations were performed for fractional-order models. Due to the fact that many electro-chemical processes such as the charging and discharging dynamics of batteries can be described in good accuracy by using fractional-order models, this paper focuses on the design and numerical validation of interval observers for such systems. Here, we present a cooperativity-enforcing observer structure leading directly to decoupled lower and upper bounding systems for the sets of reachable states. This is visualized by a battery model with interval uncertainty in the output equation.
Paper VI121-02.10
PDF · Video · NILT and Prony Technique for New Definitions of Fractional Calculus for Modeling Very Slow Decay Phenomena (I)
Cai, Ruiyang	Donghua University
Chen, YangQuan	University of California, Merced
Chen, Yuquan	University of Science and Technology of China
Kou, Chunhai	Donghua University
Keywords: Fractional systems Abstract: Based on the data from the Tesla users about the degradation of Tesla Model S battery capacity, this paper introduces two new definitions of fractional integrals and derivatives to describe these very slow decay phenomena, which fill the blanks in this field. Several existing definitions of fractional calculus are reviewed at first, together with their drawbacks in describing very slow decay. Then, two new definitions governed by new kernel functions are introduced. With the aids of Numerical Inverse Laplace Transform (NILT), Prony technique and MATLAB command stmcb(), mathematical properties of these two fractional operators are investigated.
Paper VI121-02.11
PDF · Video · Boundary Stabilization and Disturbance Rejection for a Time Fractional Order Diffusion-Wave Equation (I)
Zhou, Hua-Cheng	Academy of Mathematics and Systems Science, Academia Sinica
Wu, Ze-Hao	Foshan University
Guo, Bao-Zhu	The Chinese Academy of Sciences
Chen, YangQuan	University of California, Merced
Keywords: fractional-order systems, stability of distributed parameter systems, Disturbance rejection (linear case) Abstract: In this paper, we study the boundary stabilization and disturbance rejection for an unstable time fractional diffusion-wave equation involving Caputo time fractional derivative. When there is no boundary external disturbance, both state feedback control and output feedback control via boundary actuation are proposed by the classical backstepping method. It is proved that the state feedback makes the closed-loop system Mittag-Leffler stable while the output feedback makes the closed-loop system asymptotically stable. When there is boundary external disturbance, we propose a disturbance estimator which is constructed by two infinite dimensional auxiliary systems to recover the external disturbance. The resulting closed-loop system is Mittag-Leffler stable and the states of all subsystem involved are uniformly bounded. As a byproduct, we solves rigorously completely the two longtime unsolved problems raised in [Nonlinear Dynam., 38(2004), 339-354] where all the results are only verified by simulations.
Paper VI121-02.12
PDF · Video · An Optimal Instrumental Variable Approach for Continuous-Time Multiple Input-Single Output Fractional Model Identification (I)
Mayoufi, Abir	ENIG
Victor, Stephane	Université De Bordeaux, IMS
Malti, Rachid	Univ. Bordeaux
Chetoui, Manel	ENIG
Aoun, Mohamed	Bordeaux 1
Keywords: Fractional systems, Time-invariant systems, Linear systems Abstract: This article proposes an instrumental variable approach for continuous-time system identification using fractional models with multiple input single output context. This work is an extension of the simplified refined instrumental variable approach (srivcf ) developed for single input-single output fractional model identification (Malti et al. (2008a); Victor et al. (2013)) to the multiple input-single output case. Monte Carlo simulation analysis is used to demonstrate the performance of the proposed approach. A study is then provided to motivate differentiation order estimation, and more specifically, commensurate order estimation.
Paper VI121-02.13
PDF · Video · Fractional Order BPNN for Estimating State of Charge of Lithium-Ion Battery under Temperature Influence (I)
Wang, Yanan	Department of Automation, Beijing Institute of Technology
Liao, Xiaozhong	Beijing Institute of Technology
Lin, Da	Beijing Institute of Technology
Yang, Xin	Beijing Institute of Technology
Chen, YangQuan	University of California, Merced
Keywords: Observer design, Fractional systems, Energy systems Abstract: State of charge (SOC) estimation for lithium-ion battery (LIB) is always a vital issue for battery management system (BMS) of LIBs. Due to the complex nonlinear characteristics of LIBs, data-driven model and estimation methods have been proposed. Among them, back propagation neural network (BPNN) is one of the widely used machine learning (ML) method. To enhance the performance of BPNN of LIBs, a fractional-order BPNN (FO BPNN) based on fractional-order gradient method is designed for SOC estimation of LIB in this paper. Moreover, temperature acting as key factor is also taken into consideration. Hence, the charging or discharging current, voltage, and temperature are applied as the inputs of the proposed FO BPNN, and SOC is obtained from the network. By Dynamic Stress Test (DST) experiments under five different temperatures of four 18650 LIBs, it proves that the proposed FO BPNN is able to estimate SOC of LIBs accurately in a data-driven way.
Paper VI121-02.14
PDF · Video · Modelling, Implementation and Control of a Wind Musical Instrument (I)
Abou Haidar, Gaby	American University of Science and Technology
Moreau, Xavier	University of Bordeaux
Abi Zeid Daou, Roy	Lebanese German University, Faculty of Public Health
Keywords: Model validation, Fractional systems, Digital implementation Abstract: This paper presents the second part of a larger project whose final objective is the study of viscous thermal losses in a wind musical instrument from a hardware-in-the-loop simulation platform. After the realization of the platform in the first part of this project, the objective of the second part, presented in this paper, is to adjust the dynamic behaviour of the numerical simulator with respect to the real dynamic behaviour of the test bench. So, in this paper, the different parts that constitute the platform are recalled, and the modelling/validation of each part are described. A control-oriented model is derived. The control architecture is designed for a robust control of the artificial mouth. The robust controller method uses CRONE system design methodology. The investigations show that the design of the artificial mouth and of its controller provides very good dynamic performances.
Paper VI121-02.15
PDF · Video · A New Dynamical Repulsive Fractional Potential for UAVs in 3D Dynamical Environment (I)
Ruiz, Kendric	Université De Bordeaux, IMS, CNRS UMR 5218
Victor, Stephane	Université De Bordeaux, IMS
Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Chaumette, Serge	Université De Bordeaux, Labri, CNRS UMR 5800
Keywords: Fractional systems, Time-invariant systems, Tracking Abstract: In recent years, applications for drones have increased, from surveillance, exploration, rescue to transport applications. UAVs are more and more autonomous, therefore real-time trajectory planning is necessary and can be achieved with potential fields. A study is proposed to better scale attractive and repulsive forces which has always been problematic when dealing with artificial potential fields. The purpose of this article is to develop a new dynamical fractional potential repulsive field usable in a 3D environment by taking into account the obstacle dynamics (position and speed) and their dangerousness. Obstacle avoidance robustness is guaranteed, both from a safety point of view and from a trajectory optimization point of view. The potential fields are based on the relative position and speed of the drone in relation to the target for the attractive potential field or to the obstacle for the repulsive one.
Paper VI121-02.16
PDF · Video · Study on Obstacle Avoidance for Fractional Artificial Potential Fields (I)
Duhé, Jean-François	Université De Bordeaux, IMS, CNRS UMR 5218
Victor, Stephane	Université De Bordeaux, IMS
Ruiz, Kendric	Université De Bordeaux, IMS, CNRS UMR 5218
Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Keywords: Fractional systems, Linear systems, Tracking Abstract: One of the main problems related to path planning is to find a method which will effectively allow the robot or vehicle to avoid obstacles, provided that these obstacles can be static or dynamic. One of the most interesting methods for path planning is the use of the artifficial potential fields in order to create a representation of the environment as proposed by Khatib and Ge & Cui. These approaches enable handling online situations, which is desirable when facing uncertain obstacles appearing in the path. Three propositions are provided in the repulsive potential fields to avoid acceleration oscillations occurring while the ego-vehicle enters the limit boundaries of an obstacle. The advantages and limitations of the proposed methods will be explored. The performance of the different propositions will be compared by using criteria such as length and energy in a simple scenario.
Paper VI121-02.17
PDF · Video · Switched Fractional Order Model Reference Adaptive Control for Unknown Linear Time Invariant Systems (I)
Aguila-Camacho, Norelys	University of Chile
Gallegos, Javier	University of Chile
Keywords: Fractional systems, Model following control, Control of switched systems Abstract: This paper presents a model reference adaptive controller for linear time invariant systems with unknown parameters. The adaptive laws used to estimate the controller parameters are based on fractional differential equations, whose orders are switched among a fractional value in the interval (0,1) and 1 at certain time instants. Boundedness of the signals in the resulting controlled system is proved using recent results. A simulation study is provided for a second order system to show how the proposed control strategy can improve the behavior and decrease the control energy used, compared to the classic model reference adaptive controllers and fractional order model reference adaptive controllers with non-switched adaptive laws.
Paper VI121-02.18
PDF · Video · A More Optimal Stochastic Extremum Seeking Control Using Fractional Dithering for a Class of Smooth Convex Functions (I)
Hollenbeck, Derek	University of California Merced
Chen, YangQuan	University of California, Merced
Keywords: Fractional systems, fractional-order systems, Randomized algorithms Abstract: Adaptive control such as extremum seeking control (ESC) can be a very useful tool to optimize problems with smooth convex functions. However, some systems can be noisy or contain nonconvex regions where the solution may result in a local minimum or maximum. Using perturbation based ESC with appropriate amplitude, one can overcome local regions to find the global extremum. This work introduces fractional dithering noise into stochastic ESC to improve performance for a class of smooth convex functions. Noise with long range dependent behavior can yield a more optimal solution.
Paper VI121-02.19
PDF · Video · Bilateral Output Feedback Control of Fractional PDEs with Space-Dependent Coefficients
Chen, Juan	Tallinn University of Technology
Tepljakov, Aleksei	Tallinn University of Technology
Petlenkov, Eduard	Tallinn University of Technology
Zhuang, Bo	Jiangnan University
Keywords: Fractional systems, Output feedback control (linear case), fractional-order systems Abstract: This paper develops an extension of the bilateral control method for fractional partial differential equations (PDEs) with space-dependent coefficients by output feedback. Using a backstepping transformation, a full state feedback control law is designed. Then the fractional PDE system is folded into two subsystems and Mittag-Leffler convergent state observers of these subsystems are derived. Although the observers are coupled with boundary conditions (BCs), error subsystems are decoupled by assuming some available measurements. Hence, the observer gains are easily obtained. After this, we compose the designed state feedback controller and observers to enable Mittag-Leffler stabilization by output feedback. Finally, a fractional numerical example is provided to support the effectiveness of the proposed synthesis for the case when neither the control kernel nor the estimation kernel has an explicit solution.
Paper VI121-02.20
PDF · Video · Smith Predictor Embedded Analytical Fractional-Order Controller Design: A Delayed Bode’s Ideal Transfer Function Approach
Nagarsheth, Shaival	Sardar Vallabhbhai National Institute of Technology, Surat
Sharma, Shambhu N.	National Institute of Technology, Surat, Gujarat
Keywords: Analytic design, Fractional systems, Process control Abstract: The main contribution of this paper is to design an enhanced fractional-order controller for the higher-order system. The analytical design methodology utilizes a delayed Bode’s ideal transfer function in place of the conventional one as the reference model. A reduced fractional-order plus dead-time transfer function is used to represent a higher-order process. The design also embeds a Smith predictor for the enhanced closed-loop performance. Analytical tuning for the designed fractional-order controller is provided based on frequency domain specifications. The proposed methodology is applied to two higher-order systems, which can be represented by a reduced fractional-order plus dead-time transfer function. The closed-loop performance of the designed controller is compared with that of the three other related controllers. Frequency domain characteristics, load disturbance, sensitivity analysis, and model mismatch performance are demonstrated and compared with those of other controllers as well. The results of the paper reveal that the proposed controller leads to an overall enhanced closed-loop performance.

VI121-03
Adaptive Control Design	Regular Session
Chair: Monnigmann, Martin	Ruhr-Universität Bochum
Co-Chair: Nielsen, Christopher	University of Waterloo
Paper VI121-03.1
PDF · Video · Adaptive Neural Network Control for Nonlinear Output-Feedback Systems under Disturbances with Unknown Bounds
Wang, Qiufeng	Qufu Normal University, College of Engineering
Zhang, Zhengqiang	Qufu Normal University
Keywords: Adaptive control Abstract: This paper is concerned with the problem of adaptive backstepping neural network tracking control for a class of output feedback systems with unknown functions under bounded disturbances whose boundaries is unknown. Unknown functions are approximated via online radial basis function (RBF) neural network, high order continuous differentiable functions are introduced into Lyapunov function to realize the estimation of unknown parameters and unknown boundary, and a new dead zone function is designed to replace symbolic function to realize the continuity of virtual control. During the design process, the backstepping design method is applied to deal with the cross terms generated by the tuning function. Barbalat lemma proves that all the signals of closed-loop system are bounded and the output tracking error converges to an arbitrarily small neighborhood of the origin. A simulation example are given to illustrate the effectiveness of the control scheme.
Paper VI121-03.2
PDF · Video · Adaptive Stabilization of Minimum-Phase Systems under Quantized Measurements
Selivanov, Anton	The University of Sheffield
Fradkov, Alexander L.	Russian Academy of Sciences
Keywords: Adaptive control Abstract: We construct an adaptive controller for a linear minimum-phase system of an arbitrary relative degree with an unknown bounded disturbance and dynamically quantized measurements. The key novelty is the extension of the shunting method (parallel feedforward compensator) to plants with bounded disturbances. This method leads to an augmented system of relative degree one that is stabilized by a passification-based adaptive controller. Moreover, we design a switching procedure for the controller parameters and the quantizer's zoom that ensures the state convergence from an arbitrary set to an ellipsoid whose size depends on the disturbance bound. The results are demonstrated by an example of an aircraft flight control.
Paper VI121-03.3
PDF · Video · Composite Adaptive Backstepping Control Considering Computational Complexity and Relaxation of Persistent Excitation
Jeon, Byoung-Ju	Cranfield University
Shin, Hyo-Sang	Cranfield University
Tsourdos, Antonios	Cranfield University
Keywords: Adaptive control, Aerospace Abstract: A new composite adaptive backstepping control is proposed in this paper, which achieves parameter estimation convergence without persistent excitation and reduces estimation problem dimension for less computational complexity. A composite adaptation law is utilized to improve estimation and tracking performance. Relaxation of the persistent excitation requirement for parameter convergence is accomplished by making information matrix full rank only with finite excitation. The adaptation law for the proposed composite adaptive backstepping control algorithm estimates parameters in each loop separately by taking an advantage from a cascade control structure of backstepping control. Comparing to the adaptation laws which estimate whole parameters of the dynamic system at once, the designed adaptation law deals with smaller estimation problems, resulting in reduced computational complexity.
Paper VI121-03.4
PDF · Video · On Key Properties of the Lion’s and Kreisselmeier’s Adaptation Algorithms
Gerasimov, Dmitry	ITMO University
Nikiforov, Vladimir O.	ITMO University
Keywords: Adaptive control, Asymptotic stabilization Abstract: The paper revises properties of two identification/adaptation algorithms proposed by Lion (1967) and Kreisselmeier (1977) more than 40 years ago to accelerate parametric convergence under regressor persistency of excitation (PE) condition. First, being motivated by paper Aranovskiy et al. (2017) it is demonstrated that these algorithms can provide asymptotic (not exponential) parametric convergence under simple condition which is weaker than requirement of PE. Second, it is shown that via some condition these schemes can be used for generating the high order time derivatives (HOTD) of the adjustable parameters that are necessary for solution of a wide range of problems of identification and adaptive control including backstepping design procedure.
Paper VI121-03.5
PDF · Video · Adaptive Control for Systems with Two Binary Measurements
Leonow, Sebastian	Ruhr University Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Adaptive control, Data-based control, Control of switched systems Abstract: We propose a new type of binary controller for control loops with two binary measurements and an analog, continuous actuator. Unlike common binary controllers, the proposed adaptive controller requires no continued oscillation of the plant output. Instead, the proposed controller adapts an internal plant model to compute an optimal plant input so that the plant output settles on a constant value in between the two binary sensors. The parameter identification is fully automated and requires no user interaction, so that the proposed controller is as simple to implement as a conventional on-off controller. We evaluate the controller in a laboratory test setup and compare the energy comsumption to established control approaches.
Paper VI121-03.6
PDF · Video · Swarm Optimized Simple Adaptive Controller for Spacecraft Proximity Operations Trajectory Tracking
Predmyrskyy, Andriy	Carleton University
Ulrich, Steve	Carleton University
Keywords: Adaptive control, Evolutionary algorithms for optimal control, Parametric optimization Abstract: Adaptive control design allows for the management of systems with time varying or unknown dynamics. Despite their versatility, few well defined design techniques exist for some classes of adaptive controller. Without analytical techniques it is difficult to prove the efficacy of an adaptive controller design. One solution to this issue is the application of parametric search techniques to adaptive controller design. This paper explores the application of differential evolution on the simple adaptive control law formulation and compares its solution to one found using particle swarm optimization. Afterwards, variations on these techniques, namely the selection particle swarm optimization and self-adaptive differential evolution, are implemented and their results compared. The final swarm-optimized controller is compared to a classical Linear Quadratic Regulator (LQR) controller, and a manually designed simple adaptive controller for precision trajectory tracking control of spacecraft proximity operations. Parametric search techniques are able to determine controller parameters that produce a superior control response. Swarm-optimization techniques determine controllers with parameters drastically different from manually designed efforts.
Paper VI121-03.7
PDF · Video · Inversion Based Adaptive Feedforward Control for Multivariable Systems
Rouhani, Shahin	University of California Los Angeles
Rai, Sandeep	UCLA
Tsao, Tsu-Chin	University of California Los Angeles
Keywords: Adaptive control, Linear multivariable systems, Disturbance rejection Abstract: This paper presents a novel adaptive feedforward control (AFC) method for rejecting sinusoidal disturbances with known frequencies acting on multi-input-multi-output (MIMO) discrete time linear systems based on the H-infinity synthesis. First, the gradient AFC (GAFC) for MIMO systems is reviewed, and the linear time invariant (LTI) equivalent form of the GAFC is approximated for stability analysis. For single-input-single-output (SISO) systems, this paper shows small adaptation gains guarantee the stability of GAFC for any disturbance frequency. Then inspired by the stability of SISO GAFC, the inversion based AFC (IAFC) is proposed for MIMO systems. In this method, the GAFC is compensated by an H-infinity model matching filter, which renders nearly decoupled systems with fixed time delays. The LTI analysis, simulation study and experimental results from an open-loop unstable MIMO Active Magnetic Bearing Spindle (AMBS) are presented to demonstrate the stability and effectiveness of the proposed IAFC in rejecting narrow-band disturbances.
Paper VI121-03.8
PDF · Video · Lyapunov Design of Least-Squares Model-Reference Adaptive Control
Costa, Ramon R.	COPPE - Federal Univ of Rio De Janeiro
Keywords: Adaptive control, Lyapunov methods, Asymptotic stabilization Abstract: A Lyapunov design of a least-squares model-reference adaptive control (LS-MRAC) algorithm is presented. The plants considered are continuous with relative degree one. A Monopoli multiplier, originally proposed to extend the MRAC algorithm to the case of relative degree two, is introduced. As a result, fast convergence of the tracking error is achieved and, moreover, the Lyapunov analysis shows that a quadratic term depending on the parametric error belongs to L2, which improves the stability properties of the system. This is the key feature that allows a more powerful LS algorithm to be employed in the update law. The resulting LS-MRAC seems to be a missing algorithm in the literature. Simulation results illustrate the improvement in the transient behavior as well as in the parameter convergence attained with the proposed adaptive schemes.
Paper VI121-03.9
PDF · Video · Mixed Driven Iterative Adaptive Critic Control Design towards Nonaffine Discrete-Time Plants
Wang, Ding	Beijing University of Technology
Ha, Mingming	University of Science and Technology Beijing
Keywords: Adaptive control, Optimal control theory, Data-based control Abstract: In this paper, an effective mixed driven framework is constructed involving both data and event considerations. The primary purpose lies in that the mixed driven iterative adaptive critic method is established to address approximate optimal control towards discrete-time nonlinear dynamics. The neural dynamic programming technique is inventively integrated with the mixed driven architecture, such that the knowledge of the controlled plant is needless and the number for updating control inputs is prominently reduced. A triggering threshold is also designed with theoretical guarantee, which renders that the control signals can be updated conditionally. Through carrying out simulation studies with comparisons, the superiority of the present near-optimal regulation approach is confirmed at last.
Paper VI121-03.10
PDF · Video · Output Tracking Control Based on Output Feedback with Adaptive PFC for Discrete-Time Systems
Fujii, Seiya	Hiroshima University
Mizumoto, Ikuro	Kumamoto Univ
Yamamoto, Toru	Hiroshima Univ
Keywords: Adaptive control, Output feedback control (linear case) Abstract: This paper provides an output tracking control system design strategy based on an output feedback control with an adaptive parallel feedforward compensator (PFC) for discrete-time systems. In the proposed method, a PFC is introduced for non-almost strictly positive real (ASPR) systems in order to guarantee the stability of the designed adaptive control system. The PFC parameters are adaptively adjusted to remain the ASPR-ness of the resulting augmented system with the PFC. Moreover, in order to attain output tracking, a two-degree-of-freedom output feedback control system with an adaptive neural network (NN) feedforward control is designed. The stability of the resulting adaptive control system is analyzed theoretically and the effectiveness of the proposed method is confirmed through numerical simulations.
Paper VI121-03.11
PDF · Video · An Indirect Adaptive Control Approach to Image Based Visual Servoing for Translational Trajectory Tracking
Fried, Jonathan	Federal University of Rio De Janeiro
Lizarralde, Fernando	Federal Univ. of Rio De Janeiro
Candea Leite, Antonio	Norwegian University of Life Sciences
Keywords: Adaptive control, Passivity-based control, Tracking Abstract: In this work, it is considered an image based visual servoing control problem, for uncertain robot manipulators. Visual feedback is provided by a fixed monocular camera with uncertain parameters, for the purpose of tracking translational trajectories of a spherical target, both the trajectory on image plane and depth. Based on a cascade structure, the proposed adaptive visual servoing is combined with an adaptive motion control strategy. Stability and passivity properties are analyzed with the Lyapunov method. Simulation results illustrate and highlight performance of the proposed controller.
Paper VI121-03.12
PDF · Video · Adaptive Prescribed-Time Control for Uncertain Nonlinear Systems with Non-Affine Actuator Failures
Wang, Ziwei	Tsinghua University
Lam, H. K.	King's College London
Chen, Zhang	Tsinghua University
Liang, Bin	Tsinghua University
Zhang, Tao	Tsinghua University
Keywords: Adaptive control, Stability of nonlinear systems, Fault-tolerant Abstract: In this paper, we present a novel prescribed-time fault-tolerant control method for a class of nonlinear systems with time-varying unmodeled actuator faults. Non-affine actuator failures and uncertain control direction can be addressed in a universal control framework, where any prior information about faults is not required in control design. We show that, with the proposed control scheme, the system trajectory can converge to a user-defined residual-set within prescribed settling time. The requirements on pre-assigned rapidity and accuracy can be simultaneously satisfied, leading to the settling time and convergence set only determined by fewer user-defined parameters rather than approximation errors, which is fundamentally different from conventional finite and fixed-time control. Simulation and experiment results are provided to valid the effectiveness of the proposed controller.
Paper VI121-03.13
PDF · Video · Adaptive Control for Nonlinear Systems with Time-Varying Parameters and Control Coefficient
Chen, Kaiwen	Imperial College London
Astolfi, Alessandro	Imperial Col. London & Univ. of Rome Tor Vergata
Keywords: Adaptive control, Time-varying systems Abstract: This paper exploits the so-called congelation of variables method to design an adaptive controller for nonlinear systems with time-varying parameters. Two motivating examples describing scalar systems are discussed to illustrate the flexibility of the congelation of variables method to deal with the cases in which the time-varying parameters are coupled with the state and with the input, respectively. Interpretations from a passivity perspective are also provided. Then design procedures are derived for general nonlinear systems in parametric strict-feedback form, and it is shown that the state of the underlying system converges to the origin and all signals of the closed-loop system remain bounded. Simulations show that, in the presence of parameter variations, the performance of the proposed controller is superior to that of the classical adaptive controller designed for time-invariant systems.
Paper VI121-03.14
PDF · Video · Improved Adaptive Servotracking for a Class of Nonlinear Plants with Unmatched Uncertainties
Gerasimov, Dmitry	ITMO University
Pashenko, Artem	ITMO University
Nikiforov, Vladimir O.	ITMO University
Keywords: Adaptive control, Tracking, Output regulation Abstract: The paper addresses the problem of adaptive tracking of multi-sinusoidal reference signal for the class of nonlinear systems with unknown unmatched parameters. It is assumed that the frequencies, amplitudes and phases of the reference harmonics are a priori unknown. The problem solution uses linear parameterization of reference signal, modular backstepping design and special adaptation algorithm (identifier) with memory regressor extension. The algorithm has two important properties. First of all, it offers improved parametric convergence achieved by regressor recording over past period of time. Recording is provided by involving a linear SISO filter of sufficiently large relative degree into the structure of the algorithm. Second, the structure of the filter allows us to apply the adaptation algorithm for generating the high-order time derivatives of adjustable parameters used in virtual and actual controls.
Paper VI121-03.15
PDF · Video · Adaptive Robust Generalized Dynamic Inversion Quadrotor Control
Ansari, Uzair	King Abdulaziz University
Bajodah, Abdulrahman H.	King Abdulaziz Univ
Keywords: Adaptive control, Tracking, Sliding mode control Abstract: This paper proposes a two loops control system structure for position and attitude of the Quadrotor flying vehicle. To control the Quadrotor's center of gravity position in the instantaneous horizontal inertial planes, a small disturbance linearization-based Proportional-Derivative controller is employed in the outer (position) loop to provide reference pitch and roll tilting commands to the inner (attitude) loop. The outer loop also generates the thrust command required to track desired altitude trajectories. The inner loop utilizes a novel Adaptive Robust Generalized Dynamic Inversion (ARGDI) control design that is made by augmenting a direct adaptive control element in the baseline Robust Generalized Dynamic Inversion control system. The adaptive control law is obtained via a control Lyapunov function, and it aims to reduce the dependency of the control system on the geometric and inertia parameters of the Quadrotor in order to overcome control performance degradation due to modeling and parametric uncertainties, and due to external wind disturbances and dynamic scaling of the Moore-Penrose Generalized inverse. Computer simulations are performed in the Matlab/Simulink environment on a six DOFs Quadrotor model to demonstrate the robust globally asymptotically stable performance of the two loops control system. Additionally, performance of the inner ARGDI attitude control loop is tested on an experimental Quanser's three DOFs Hover test bench.
Paper VI121-03.16
PDF · Video · Digital Identification and Control of Multivariable Plants Using Markov Parameters
Gaiduk, Anatoliy	Taganrog Technological Institute of Southern Federal University
Pshikhopov, Vyacheslav	Taganrog Institute of Technology of Southern Federal University
Medvedev, Mikhail	Taganrog Technological Institute of Southern Federal University
Keywords: Adaptive control, Linear multivariable systems, Analytic design Abstract: The algorithm of the digital adaptive controller is offered in this article for control systems with identification of uncertain multivariable continuous-time objects. The adaptive controller includes unit of digital identification and unit of digital control. The algorithm of the identification unit allows to define the transfer matrix of the uncertain continuous-time plant. Unlike traditional methods of identification, the offered analytical algorithm uses Markov parameters not of the uncertain continuous- time plant, but virtual discrete-like plant. Markov parameters are determined by data of I/O of the uncertain continuous-time plant. The algorithm of the control unit is developed with use of control of two types: decomposition control and digital control on the output and impacts. The order and parameters of the control unit are determined by the method of the analytical design of digital control systems. Normalized standard transfer functions are used to create the transfer functions of the adaptive system according to required values of astatism order, settling time and overshot. The effectiveness of the proposed algorithm of adaptive controller is illustrated by a numerical example. The proposed approach can be applied to create control systems for agricultural, food, mining, and other industries.
Paper VI121-03.17
PDF · Video · Adaptive Passivity-Based Hybrid Pose/Force Control for Uncertain Robots
Candea Leite, Antonio	Norwegian University of Life Sciences
Lostalo Cruz, Francisco	Independent Researcher
Lizarralde, Fernando	Federal Univ. of Rio De Janeiro
Keywords: Adaptive control, Passivity-based control, Lyapunov methods Abstract: In this work, we consider a novel adaptive hybrid pose/force control strategy for uncertain robot manipulators capable of performing interaction tasks on poorly structured environments. A unique hybrid control law, based on an orientation-dependent term, is proposed to overcome the performance degradation of the feedback system due to the presence of uncertainties in the geometric parameters of the contact surfaces. A gradient-based adaptive law, which depends on the tracking error, is designed to deal with parametric uncertainties in the robot kinematics and the stiffness of the environment. In our solution, the effect of the uncertain robot dynamics is addressed by using an adaptive dynamic control based on a cascade control strategy. The Lyapunov stability theory and the passivity paradigm are employed to carry out the stability analysis of the overall closed-loop control system. Numerical simulations are included to illustrate the performance and feasibility of the proposed methodology.
Paper VI121-03.18
PDF · Video · Robust Adaptive Sliding Mode Controller for Wearable Robots
Madani, Tarek	University of Paris-Est Creteil (UPEC)
Djouani, Karim	Université Paris XII Creteil, Laboratoire LiSSI
Keywords: Adaptive control, Sliding mode control, Lyapunov methods Abstract: This paper concerns adaptive sliding-mode control for wearable robots with a human in the loop. The exoskeletons are wearable robots in interaction with different users. The proposed approach supposes that the dynamic model of the exoskeleton-human system is unknown except for some classical bounded properties. The controller guarantees the closed-loop convergence with an embedded-in estimation of unknown dynamics and uncertainties. The stability analysis of the system is demonstrated using the Lyapunov theory. Experimentation on an upper arm exoskeleton was conducted in order to exhibit the effectiveness of the proposed control method. The results show good tracking of the desired trajectories, which can be used in the assistive phase of the functional rehabilitation.
Paper VI121-03.19
PDF · Video · Immersion and Invariance Based Composite Adaptive Control for Nonlinear Systems with Both Parametric and Non-Parametric Uncertainties
Liu, Zhen	Institute of Automation, Chinese Academy of Sciences
Pu, Zhiqiang	Institute of Automation, Chinese Academy of Sciences
Qiu, Tenghai	Institute of Automation, Chinese Academy of Sciences
Wang, Huimu	University of Chinese Academy of Science
Yi, Jianqiang	Institute of Automation, Chinese Academy of Sciences
Keywords: Adaptive control, Stability of nonlinear systems Abstract: The design of an immersion and invariance (I&I) based composite adaptive control for a class of uncertain nonlinear systems is presented in this paper. The key feature of this control scheme lies in the construction of the novel adaptive laws, aiming to address both parametric and non-parametric uncertainties simultaneously. Composite adaptive laws, which are driven by both the information of tracking error and prediction error, are first proposed using I&I theory for the estimations of parametric uncertainties. Then the technique of σ-modification is used to guarantee the stability in the presence of non-parametric uncertainties. Stability analysis is presented using the Lyapunov theory. Improved performance of the proposed control scheme is observed via numerical simulations.
Paper VI121-03.20
PDF · Video · Adaptive Path Following for a Nonholonomic Mobile Manipulator
Barrera Perez, Orlando	University of Waterloo
Fidan, Baris	University of Waterloo
Nielsen, Christopher	University of Waterloo
Keywords: Adaptive control, Tracking, Lagrangian and Hamiltonian systems Abstract: We investigate an adaptive path following problem for a nonholonomic mobile manipulator system and closed planar curves. As opposed to adapting to uncertain or unknown dynamics in the plant, we apply an adaptation approach with respect to an unknown path. First, we present a solution to the non-adaptive path following problem using the concept of a path following output. Then, we use an indirect adaptive control approach to design path following controllers for a feasible class of strictly convex paths.
Paper VI121-03.21
PDF · Video · Adaptive Speed Tracking Controller for a Brush-Less DC Motor Using Singular Perturbation
Gil Bayardo, Raul	Cinvestav
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Fuentes, Rita Q.	Tecnológico De Monterrey, Escuela De Ingeniería Y Ciencias
Utkin, Vadim I.	Ohio State Univ
Keywords: Adaptive control, Tracking, Model reduction Abstract: This work proposes a speed tracking controller for a brush-less DC (BLDC) motor in presence of plant parameters uncertainty and lack of current sensors. The designed controller is based on singular perturbation and adaptive control methods. Singular perturbation method is used to reduce the plant model order neglecting the current fast dynamics. Based on this reduced order model, an adaptive control law that has no dependency of the phase currents measurements, is formulated. The effectiveness of the proposed controller is demonstrated by numerical simulations.

VI121-04
Controller Constraints and Structure	Regular Session
Chair: Skogestad, Sigurd	Norwegian Univ. of Science & Tech
Co-Chair: Wang, Jiqiang	Nanjing University of Aeronautics & Astronautics
Paper VI121-04.1
PDF · Video · An Aeroengine U-Control Method Based on LPV Model
Chen, Jiajie	Nanjing University of Aeronautics and Astronautics
Wang, Jiqiang	Nanjing University of Aeronautics & Astronautics
Hu, Zhongzhi	Nanjing University of Aeronautics and Astronautics
Dimirovski, Georgi Marko	Dogus University of Istanbul
Keywords: Controller constraints and structure, Analytic design Abstract: Due to the harsh working environment, the engine control unit (ECU) has very limited computational ability and few control methods can be applied to the real ECU maturely. Developing advanced control methods with good performance as well as low computational complexity is the research focus in the field of aeroengine control. This paper combines the aeroengine LPV model with U-control concept, which simplifies the solve difficulty and complexity of traditional LPV variable gain controller. The result of simulation shows that this U-control method based on LPV model can be used for aeroengine speed control system design. It ensures a good control performance and has great application potential.
Paper VI121-04.2
PDF · Video · An LMI-Based Approach for Semivalues Constraints in Coalitional Feedback Control
Muros, Francisco Javier	University of Seville
Maestre, Jose M.	University of Seville
Keywords: Controller constraints and structure, Differential or dynamic games, Decentralized control Abstract: In coalitional approaches, communication links are dynamically enabled/disabled by the control scheme to reduce the cooperation burden without compromising the system performance. This problem setup can be interpreted as a cooperative game where solution concepts provide a measure of the impact of links on system behavior. Here, we present how constraints on the set of semivalues can be introduced via linear matrix inequalities (LMIs) to impose design requirements. To this end, an LMI-based iterative method is presented. Finally, an academic example is simulated to illustrate the feasibility of the proposed approach.
Paper VI121-04.3
PDF · Video · Design of LPV-PI-Like Controller with Guaranteed Performance for Discrete-Time Systems under Saturating Actuators
Figueiredo, Larissa Soares	CEFET-MG
Parreiras, Tarsis A. R.	CEFET-MG
Lacerda, Márcio J.	Federal University of São João Del-Rei
Leite, Valter J. S.	CEFET/MG - Campus Divinopolis
Keywords: Controller constraints and structure, Linear parameter-varying systems, Constrained control Abstract: This paper presents new conditions to design linear parameter-varying (LPV) state-feedback controllers for systems under saturating actuators. The proposed design ensures a minimal rate of contractivity of an associated Lyapunov function. A proportional-integral (PI) like structure is employed to ensure null tracking error for piecewise constant reference signals. Therefore, this proposal fits the design requirements of LPV and quasi-LPV real systems under saturating actuators. Experimental essays conducted on a second-order nonlinear level control illustrate the potential of the proposed approach. Additionally, the tests indicate how the contractivity rate affects the size of the estimate of the region of attraction.
Paper VI121-04.4
PDF · Video · Control Allocation for Wheeled Mobile Robots Subject to Input Saturation
Alves, Jhomolos Gomes	Federal University of Rio De Janeiro
Lizarralde, Fernando	Federal Univ. of Rio De Janeiro
Monteiro, João C.	Universidade Federal Do Rio De Janeiro
Keywords: Controller constraints and structure, Optimal control theory, Systems with saturation Abstract: This paper addresses the problem of input saturation in wheeled mobile robot control. Depending on the desired trajectory or on the terrain, wheel motors may be demanded to work beyond their limits. This situation can lead to undesired performance, and therefore, input saturation has to be properly managed. Although control allocation has been mainly employed in over-actuated systems to enhance the control distribution, it can be also utilized for under-actuated systems as well to grant performance. For this purpose, three different control allocation strategies, along with Lyapunov-based time-varying feedback controller, are applied to a differential drive mobile robot subject to input saturation. Experimental results illustrate the performance of the proposed strategies.
Paper VI121-04.5
PDF · Video · Adaptive Second-Order Sliding Mode Control for a Tilting Quadcopter with Input Saturations
Ji, Ruihang	Harbin Institute of Technology
Ma, Jie	Harbin Institute of Technology
Ge, Shuzhi	National University of Singapore
Ji, Ranming	China Aerospace Science and Industry Corporation
Keywords: Controller constraints and structure, Sliding mode control, UAVs Abstract: In this paper, we address the problem of tracking control for a novel tilting quadcopter in the presence of uncertainties and disturbance. To handle these effects, an adaptive second-order sliding mode control (ASOSMC) is proposed to obtain fast convergence rate and high precision with alleviating chattering effect. Considering the input saturations, a new scheme is designed toward the time derivative of the control inputs where an auxiliary system is adopted to the controller. Moreover, the overall uncertainties are expressed in a linearly parametric form without any prior knowledge. It can be proved that the sliding mode manifolds can fast converge to a small neighborhood around zero within finite-time, and then tracking errors exponentially. Finally, simulation results are carried out to demonstrate the effectiveness and robustness of the proposed controller.
Paper VI121-04.6
PDF · Video · Model-Free Adaptive Fault-Tolerant Control for Multiple Point-Mass Subway Trains with Speed and Traction/Braking Force Constraints
Wang, Haojun	Beijing Jiaotong University
Hou, Zhongsheng	Beijing Jiaotong University
Jin, Shangtai	Beijing Jiaotong University
Keywords: Data-based control, Adaptive control, Fault-tolerant Abstract: This paper considers the model-free adaptive fault-tolerant control for a subway train based on multiple point-mass model with the actuator fault under the constraints of speed and traction/braking force. The complex subway train model is first transformed into a compact form dynamic linearization (CFDL) data model with pseudo gradient (PG). The actuator fault function is approximated with radial basis function neural network (RBFNN). Finally a fault-tolerant controller only using saturated input/output (I/O) data is designed. The effectiveness of proposed controller is illustrated by a simulation.
Paper VI121-04.7
PDF · Video · Active Constraint Switching with the Generalized Split Range Control Structure Using the Baton Strategy
Reyes-Lúa, Adriana	Norwegian University of Science and Technology
Skogestad, Sigurd	Norwegian Univ. of Science & Tech
Keywords: Decentralized control, Controller constraints and structure, Process control Abstract: Split range control is used to extend the steady-state operating range for a single output (controlled variable, CV) by using more than one input (manipulated variable, MV). In the context of optimal operation, this advanced control structure can be used for active constraint switching, also in combination with selectors. The generalized split range control structure analyzed in this paper overcomes the limitations of standard split range control in terms of tuning by using multiple independent controllers with the same setpoint. By using the baton strategy, this structure avoids undesired switching between the controllers. In this contribution, we implement in this novel control structure in a simulation case study of a mixing process in which we must switch the MV used to control a high priority CV due to MV saturation.

VI121-05
Data Based and Data Driven Control	Regular Session
Chair: Pola, Giordano	University of L'Aquila
Co-Chair: Kosaka, Manabu	Kindai Univ
Paper VI121-05.1
PDF · Video · On Data–driven Controller Synthesis with Regular Language Specifications
Pola, Giordano	University of L'Aquila
Masciulli, Tommaso	University of L'Aquila
De Santis, Elena	University of L'Aquila
Di Benedetto, M. Domenica	Univ of L'Aquila
Keywords: Data-based control Abstract: Data-driven control design for general systems with regular language specifications is addressed. We consider a discrete–time control system described as an abstract system i.e. as a collection of input–state functions. The abstract system is assumed to be suffix and concatenation closed, causal, deterministic and time–invariant. State variables are known but their dynamics are not, apart from a finite set of experiments. Given a specification expressed as a regular language defined over an alphabet consisting of a finite set of states of the plant, we design a controller based on the finite set of experiments, that guarantees that the specification is met, up to an error that can be chosen as small as desired. We also present results on maximality, convergence and adaptivity of the controller as the set of experiments increases.
Paper VI121-05.2
PDF · Video · Energy Saving Control of Bionic Robotic Fish Based on Model-Free Adaptive Control
Zhang, Biying	Beijing Jiaotong University
Jin, Shangtai	Beijing Jiaotong University
Hou, Zhongsheng	Beijing Jiaotong University
Keywords: Data-based control, Adaptive control, Control in system biology Abstract: In this paper, an energy-saving model-free adaptive control (MFAC) is proposed for the control of the bionic roboticfish. First, the original MFAC controllers for the speed based on the full form dynamic linearization data model are presented as an example of the controlled variable of the controlled object. Then by modifying the criterion function for control input optimization, an energy-saving MFAC controller is designed to reduce the energy consumption. The proposed method is a data-driven control method, which means that the control system designing process merely needs input and output (I/O) measurement data of the controlled plant, and does not need any model information. Simulation results demonstrate the effectiveness of the improved MFAC in speed and attitude control of the bionic robotic fish.
Paper VI121-05.3
PDF · Video · Modified Model-Free Adaptive Control Using Compact-Form Dynamic Linearization Technique
Pham, Hoang Anh	University of Duisburg-Essen
Söffker, Dirk	Univ of Duisburg-Essen
Keywords: Data-based control, Adaptive control, Parameter-varying systems Abstract: Model-free adaptive control has been used to design feedback in cases when accurate mathematical modeling of the system can not be realized. By using only input-output information, the control approach is attractive with respect to minimal design efforts. In this contribution an improved model-free control program is proposed and applied to flexible systems. The main control idea is based on the compact-form dynamic linearization technique. A linearized controller structure which contains a matrix of unknown time-varying parameters namely pseudo-partial derivative can be designed. First, an equivalent linearized data-based model of the original system is established and corrected locally by using the recursive least-squares estimation algorithm. Then a modified objective function with respect to the controller parameter matrix considering minimization of the current tracking errors and its variations is proposed for control performance improvement. Finally, the required control inputs are calculated to fulfill control requirements. For illustration and as example, the newly introduced method is applied to reduce vibrations of an elastic crane representing a multivariable system. The control effectiveness is verified nummerically and compared with conventional model-free and PI controllers.
Paper VI121-05.4
PDF · Video · Virtual Time-Response Based Iterative Gain Evaluation and Redesign
Kosaka, Mato	Nara Institute of Science and Technology
Kosaka, Ayato	Aoyama Gakuin University, College of Science and Engineering
Kosaka, Manabu	Kindai Univ
Keywords: Data-based control, Adaptive control, Time-invariant systems Abstract: Since Artificial Intelligence (AI) has won over human pros such as Chess, Shogi and Go, expectations for AI have been increasing dramatically. One of the reasons why AI has developed so much is the tremendous increase in processing speed of computers, which makes it possible to virtually repeat simulated competitions such as Othello, Shogi, Go and so on in the computer very fast. Finally, AI has gained strength over human pros. Also in control engineering, if gain tuning experiments of controllers can be virtually performed in a computer, it can be expected to dramatically improve control performance with an AI-like approach. This paper proposes a new method called `Virtual Time-response based Iterative Gain Evaluation and Redesign' (V-Tiger) which iterates: 1) to calculate virtual time responses of the closed loop system when a certain controller is inserted based on one-shot experimental data, 2) to measure the overshoot and settling time from the virtual time responses, and 3) to evaluate and redesign the controller gain considering the stability margin.
Paper VI121-05.5
PDF · Video · Data-Based Guarantees of Set Invariance Properties
Bisoffi, Andrea	University of Groningen
De Persis, Claudio	University of Groningen
Tesi, Pietro	University of Florence
Keywords: Data-based control, Control of constrained systems, Convex optimization Abstract: For a discrete-time linear system, we use data from an open-loop experiment to design directly a linear feedback controller enforcing that a given (polyhedral) set of the state is invariant and given (polyhedral) constraints on the control are satisfied. By building on classical results from model-based set invariance and a fundamental result from Willems et al., the controller designed from data has the following desirable features. The satisfaction of the above properties is guaranteed only from data, it can be assessed by solving a numerically-efficient linear program, and, under a certain rank condition, a data-based solution is feasible if and only if a model-based solution is feasible.
Paper VI121-05.6
PDF · Video · Data-Driven Iterative Tuning for Rejecting Spatial Periodic Disturbances Combined with LESO
Huo, Xin	Harbin Institute of Technology
Wu, Aijing	Harbin Institute of Technology
Wang, Ruichao	Texas A&M University
Ma, Kemao	Harbin Institute of Technology
Keywords: Data-based control, Disturbance rejection, Tracking Abstract: Iterative learning control (ILC) scheme is known as an effective technique focused on problems which involve repeating tasks, using the error signal from the previous cycle to update the control input. In this paper, a compound control which combines a data-driven iterative turning feedforward controller with a linear extended state observer (LESO) is proposed for spatial periodic disturbances suppression. Due to the problem of feedforward parameter identication in servo system, an algorithm of orthogonal projection is introduced. The error signals caused by the reference trajectory and the disturbances are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the plant as well as the model of the disturbances. Moreover, a data-driven approach is proposed to design the learning gain. Furthermore, a 4th-order LESO is designed to estimate non-periodic disturbances and uncertain dynamics so as to reduce the steady state error. Simulation results validate the proposed method and conrm its effectiveness and superiority.
Paper VI121-05.7
PDF · Video · Data-Driven Quadratic Stabilization of Continuous LTI Systems
Dai, Tianyu	Northeastern University
Sznaier, Mario	Northeastern University
Roig-Solvas, Biel	Northeastern University
Keywords: Data-based control, Linear systems, Convex optimization Abstract: This paper introduces a simple data-driven quadratic stabilization control (DDQSC) method to design a state feedback controller based solely on experimental measurements while avoiding explicitly identifying the plant. Rather, we seek a controller guaranteed to quadratically stabilize all plants that could have possibly generated the observed data. While in principle this leads to a very challenging non-convex robust optimization problem, our main result provides a convex, albeit infinite-dimensional, necessary and sufficient condition for the existence of such a controller and its associated Lyapunov function. In the second part of the paper, we provide a tractable finite-dimensional convex relaxation of this condition and illustrate its effectiveness with several examples.
Paper VI121-05.8
PDF · Video · A New Data-Driven Approach of Reference Shaping
Kuwabara, Keisuke	The University of Electro-Communication
Sadamoto, Tomonori	The University of Electro-Communications
Kaneko, Osamu	The University of Electro-Communications
Keywords: Data-based control, Linear systems, Time-invariant systems Abstract: In this paper, we propose a data-driven method of reference shaping to improve the tracking performance of uncertain linear systems. The proposed method can be implemented on a system based on its input-output data; the finite-time L2-norm of the tracking error, estimated using the data, can be minimized. Moreover, the proposed algorithm can be extended for cases where the control inputs are constrained owing to actuation limits. The effectiveness of the proposed method is demonstrated through a numerical simulation and an experiment conducted using the cart system.
Paper VI121-05.9
PDF · Video · Multivariable Correlation-Based Tuning for Load Disturbance Rejection
Pinto da Silva, Roger Willian	Universidade Federal Do Rio Grande Do Sul
Eckhard, Diego	UFRGS
Keywords: Data-based control, Model following control, Disturbance rejection (linear case) Abstract: In many industrial processes, the setpoint signals present few changes and variations in the output are due mainly to the disturbances that enter the closed-loop and may be understood as load disturbances. Even though this is a common problem, the response to load disturbances is a topic not well covered in the direct data-driven control literature. This work seeks to fill that gap presenting a direct data-driven method to tune a multivariable controller in order to achieve certain load disturbance response described by some reference model. This work extends a previous one dealing with the monovariable case and uses the same correlation approach employed before in the Correlation-based Tuning (CbT).
Paper VI121-05.10
PDF · Video · The Constrained Total Least Squares Solution for Virtual Reference Feedback Tuning
Silva Garcia, Cristiane	Universidade Federal Do Rio Grande Do Sul
Bazanella, Alexandre S.	Univ. Federal Do Rio Grande Do Sul
Keywords: Data-based control, Model following control, Linear systems Abstract: Virtual Reference Feedback Tuning (VRFT) is a direct data-driven control design method employed to tune a controller's parameters aiming to achieve a prescribed closed-loop performance. Its primary formulation leads to a biased estimate in the presence of noise, so an instrumental variable (IV) alternative has been proposed and this alternative has been favoured whenever the noise level is significant. Even though VRFT thus formulated has been very successful, the bias reduction through the IV approach comes at the cost of an important increase in the variance of the parameters' estimate. In this work we propose a different solution for the parameters estimation in VRFT which reduces bias without increasing the variance --- the Constrained Total Least Squares (CTLS). The effectiveness of the proposed solution is illustrated by three case studies, showing that the mean square error of the parameters' estimate is smaller when compared to previously proposed solutions and, most importantly, that the closed-loop performance is significantly better.
Paper VI121-05.11
PDF · Video · A Youla-Kucera Parametrization for Data-Driven Controllers Tuning
Valderrama, Freddy	Pontificia Universidad Javeriana
Ruiz, Fredy	Politecnico Di Milano
Vicino, Antonio	Universita' Di Siena
Garulli, Andrea	Universita' Di Siena
Keywords: Data-based control, Parametric optimization, Controller constraints and structure Abstract: The Youla-Kucera parametrization is a fundamental result in system theory, very useful when designing model-based controllers. In this paper, this parametrization is employed to solve the controller design from data problem, without requiring a process model. It is shown that employing the proposed controller structure it is possible to achieve more stringent closed-loop performances than previous works in literature, maintaining a criterion to estimate the closed-loop stability. The developed design methodology does not imply a plant identification step and the solution can be obtained by least-squares algorithms in the case of stochastic additive noise. The designed solution is evaluated through Monte Carlo simulations for the regulation problem of an under-damped system.
Paper VI121-05.12
PDF · Video · Data-Driven Linear Quadratic Regulation Via Semidefinite Programming
Rotulo, Monica	University of Groningen
De Persis, Claudio	University of Groningen
Tesi, Pietro	University of Florence
Keywords: Data-based control, Regulation (linear case), Convex optimization Abstract: This paper studies the finite-horizon linear quadratic regulation problem where the dynamics of the system are assumed to be unknown and the state is accessible. Information on the system is given by a finite set of input-state data, where the input injected in the system is persistently exciting of a sufficiently high order. Using data, the optimal control law is then obtained as the solution of a suitable semidefinite program. The effectiveness of the approach is illustrated via numerical examples.
Paper VI121-05.13
PDF · Video · Data-Driven Model-Free Adaptive Control with Prescribed Performance: A Rigorous Sliding-Mode Based Approach
Corradini, Maria Letizia	Università Di Camerino
Ippoliti, Gianluca	Università Politecnica Delle Marche
Orlando, Giuseppe	Univ. Politecnica Delle Marche
Keywords: Data-based control, Sliding mode control, Adaptive control Abstract: In this paper, the data-driven control approach known as Model-Free Adaptive Control technique is applied to the control of a class of general discrete-time Single-Input Single-Output nonlinear systems, making use of model obtained adopting a dynamic linearization technique based on pseudo-partial derivatives. The present study is inspired by the very recent paper [Liu and Yang, 2019], where a data-driven adaptive sliding mode controller has been proposed able to account also for prescribed performance constraints. In particular, a rigorous stability analysis is here proposed, achieved modifying the forms of the sliding surface and of the control law but still retaining the main setup presented in the source paper. The careful analysis of the closed loop system here provided is shown to lead to the definition of suitable constraints on the gain of the sliding-mode based control term. A comparative study, by simulation, is also provided, performed using a test taken from the literature. Results show a remarkable improvement of control accuracy.

VI121-06
Decentralised and Distributed Control	Regular Session
Chair: Lygeros, John	ETH Zurich
Co-Chair: Werner, Herbert	Hamburg Univ of Technology
Paper VI121-06.1
PDF · Video · Self-Triggered Adaptive Control for Multi-Agent Systems with Timed Constraints and Connectivity Maintenance
Guinaldo, Maria	UNED
Dimarogonas, Dimos V.	KTH Royal Institute of Technology
Keywords: Decentralized control, Adaptive control, Networked systems Abstract: This paper presents a distributed control strategy for a multi-agent system commanded by a set of leaders that has to accomplish a high-level plan consisting of a sequence of tasks specified by a state-space region and a timed constraint. The agents are also subject to relative-distance constraints with its neighbors. The solution consists in an adaptive distributed mechanism to update the feedback gains for the leader agents, which is executed following a self-triggered algorithm. The results show how the proposed approach provides less conservative results than if feedback gains are held constant, and are illustrated with a simulation example.
Paper VI121-06.2
PDF · Video · Spatio-Temporal Loop Shaping for Distributed Control of PDE Systems
Schug, Ann-Kathrin	Hamburg University of Technology
Werner, Herbert	Hamburg Univ of Technology
Keywords: Decentralized control, Complex systems, Distributed robust controller synthesis Abstract: The systems of interest in this paper are described by a possibly large number of interconnected subsystems, where the spatial discretization into subsystems is induced by applying an array of collocated actuator/sensor pairs. When considering these types of systems in a classical centralized fashion, they have a high number of input/output signals on one hand, and usually a sparse structure on the other. While the method of loop-shaping in classical control is well-established, the notion of spatially distributed systems makes it possible to extend frequency domain loop shaping to spatial frequencies and to include weighting filters with spatio-temporal dynamics. By using a Fourier transform, controller synthesis can be done for each spatial frequency at a time. This method is applied to the control of the temperature distribution of a thin metal rod.
Paper VI121-06.3
PDF · Video · A Modular Feedback Approach for Distributed Control
López Rodríguez, Francisco	Department of Systems and Automation, University of Seville
Maestre, Jose M.	University of Seville
Muros, Francisco Javier	University of Seville
Camacho, Eduardo F.	University of Seville
Keywords: Decentralized control, Controller constraints and structure, Time-invariant systems Abstract: This work presents a method based on linear matrix inequalities (LMIs) to design a feedback controller that guarantees stability regardless of the network topology considered. The proposed controller has a modular structure, that is, it is composed of blocks associated with communication links in a control network, obtaining the feedback of each topology by inserting zeros in the blocks related to disabled links. Conditions to obtain the desired modular structure are provided, as well as a numerical example to assess the feasibility of the design method.
Paper VI121-06.4
PDF · Video · Optimal Energy Management in Combined Heat and Power System Via a Decentralized Consensus-Based ADMM
Zhou, Xu	Beijing Institute of Technology
Zou, Suli	Beijing Institute of Technology
Wang, Peng	Beijing Institute of Technology
Ma, Zhongjing	Beijing Institute of Technology
Keywords: Decentralized control, Energy systems, Large scale optimization problems Abstract: This paper proposes a comprehensive optimization model that considers not only the economic dispatch (ED) of the combined heat and power (CHP) units, but also the demand response (DR) of consuming units in the energy management system, where each individual unit can exchange the information with its neighbours. In this optimization problem, there are energy balance constraints and individual local constraints. Particularly, the progresses of the power dispatch and the heat dispatch of each CHP unit are coupled through a feasible polygon region constraint, and the power demands of each consumer among different periods are also coupled due to the requirement of the total power consumption. To achieve the optimal energy coordination of the underlying system, we propose a decentralized alternating direction method of multipliers (ADMM), under connected communication network of individuals, such that each CHP unit and consumer can simultaneously implement their own optimal strategies based on an agreed energy price derived by a consensus protocol. The convergence and optimality of the proposed method are guaranteed under certain conditions. Simulation results are shown to demonstrate the developed results.
Paper VI121-06.5
PDF · Video · Relative Normalized Gain Array-Based Interaction Indicator for Non-Square Multivariable Control Systems: Properties and Application
Nagarsheth, Shaival	Sardar Vallabhbhai National Institute of Technology, Surat
Sharma, Shambhu N.	National Institute of Technology, Surat, Gujarat
Keywords: Decentralized control, Linear multivariable systems, Process control Abstract: This paper extends the square Relative Normalized Gain Array (RNGA) to non-square multivariable systems with the detailed derivation of non-square RNGA λRN properties with column-major, i.e. λRN Є Rr×n,r<n. Non-square RNGA in this paper has a row-column inequality. The developed interaction indicator is applied to a non-square multivariable radiator laboratory test setup for evaluating control-loop interactions. Closed-loop results, as well as sensitivity analysis for the RNGA-based control-loop pairing in comparison to the RGA-based control-loop pairing, are presented in the paper. The results demonstrate the effectiveness of the proposed non-square RNGA over RGA for non-square multivariable systems to have minimum interactions and better control.
Paper VI121-06.6
PDF · Video · Derivative-Free Method for Composite Optimization with Applications to Decentralized Distributed Optimization
Beznosikov, Aleksandr	Moscow Institute of Physics and Technology
Gorbunov, Eduard	Moscow Institute of Physics and Technology
Gasnikov, Alexander	Moscow Institute of Physics and Technology
Keywords: Decentralized control, Networked systems, Control under communication constraints (nonliearity) Abstract: In this paper, we propose a new method based on the Sliding Algorithm from Lan (2016, 2019) for the convex composite optimization problem that includes two terms: smooth one and non-smooth one. Our method uses the stochastic noised zeroth-order oracle for the non-smooth part and the first-order oracle for the smooth part and it is the first method in the literature that uses such a mixed oracle for the composite optimization. We prove the convergence rate for the new method that matches the corresponding rate for the first-order method up to a factor proportional to the dimension of the space or, in some cases, its squared logarithm. We apply this method for the decentralized distributed optimization and derive upper bounds for the number of communication rounds for this method that matches known lower bounds. Moreover, our bound for the number of zeroth-order oracle calls per node matches the similar state-of-the-art bound for the first-order decentralized distributed optimization up to to the factor proportional to the dimension of the space or, in some cases, its squared logarithm.
Paper VI121-06.7
PDF · Video · Adaptive Cooperative Control for High-Order Nonlinear Multiagent Time-Delay Systems Using Barrier Functions
Song, Jiacheng	Chang'an University
Ju, Yongfeng	Chang'an University
Yan, Maode	Chang'an University
Yang, Panpan	Chang'an University
Zuo, Lei	Chang'an University
Keywords: Decentralized control, Nonlinear cooperative control, Adaptive control Abstract: A novel adaptive backstepping controller is developed to achieve the asymptotic synchronization. The designed controller only contains the values of system states, and doesn't contain any other prior knowledge of system. Firstly, the designed controller regards the unknown system nonlinearities and the disturbance of state time-delay as ``disturbance-like'' terms, which are guaranteed to be bounded by using the pre-set barrier functions, such that any prior knowledge of system nonlinearities and state time-delay are released. Then, the ``disturbance-like'' terms are compensated adaptively by designing the novel compensator at each step, such that the synchronization errors are eliminated to zero eventually for each agent. It is proved that our developed controller guarantees the convergence on the basis of Lyapunov stability theory. Some simulations are shown to demonstrate the effectiveness and advantages of the developed method.
Paper VI121-06.8
PDF · Video · Transformed Manipulated Variables for Linearization, Decoupling and Perfect Disturbance Rejection
Zotica, Cristina	Norwegian University of Science and Technology
Alsop, Nicholas	Borealis AB
Skogestad, Sigurd	Norwegian Univ. of Science & Tech
Keywords: Decentralized control, Process control, Disturbance rejection Abstract: The objective of this work is to find new transformed manipulated variables (MVs) for nonlinear systems which linearize and decouple the system, and gives perfect disturbance rejection (at least at steady-state). The proposed new input transformation is more general than feedback linearization in that it also allows for multiple-inputs multiple-outputs (MIMO) systems, disturbances, a more general class of models, and introduces a tuning parameter τ0. The key idea is to use decentralized SISO controllers for the output y using the new transformed inputs v as MVs. The SISO controllers give v, and a nonlinear calculation block solves algebraic equations which explicitly gives the original input u as a function of the controller output v, output y and disturbances d. The calculation block also handles decoupling, and feedforward action from the disturbance d. This new procedure can be applied both for static and dynamic processes, which is typical in process control.
Paper VI121-06.9
PDF · Video · An LMI Approach for Structured H-Infinity State Feedback Control
Ferrante, Francesco	Université Grenoble Alpes
Ravazzi, Chiara	National Research Council of Italy (CNR)
Dabbene, Fabrizio	CNR
Keywords: Decentralized control, Robust linear matrix inequalities, Robust control (linear case) Abstract: In this paper we consider the problem of designing optimal H_infty static state feedback control in the presence of additional structural constraints. This problem arises in many applications, such as Network Decentralized Control and Overlapping Control, where the controller is constrained to have a specific nonzero patterns. Building upon previous results on S-variable approach for LMI-based robust control, we derive a novel solution to the design of H_infty state feedback controllers when the controller gain is constrained to belong to a given linear space. Through numerical examples we demonstrate the simplicity of the method and performance of the optimal control law.
Paper VI121-06.10
PDF · Video · Decentralised Sliding Mode Control for Nonlinear Interconnected Systems with Unknown Interconnections
Ji, Nan	University of Kent
Yan, Xing-Gang	University of Kent
Mao, Zehui	Nanjing University of Aeronautics and Astronautics
Zhao, Dongya	China University of Petroleum (East China)
Jiang, Bin	Nanjing University of Aeronautics and Astronautics
Keywords: Decentralized control, Sliding mode control, Control of interconnected systems Abstract: In this paper, a novel decentralised robust state feedback sliding mode control is presented to stabilise a class of fully nonlinear interconnected systems with matched uncertainty and unknown interconnections. An essential transformation is applied to transform all the nominal isolated subsystems into regular forms to facilitate system analysis and control design. A composite sliding surface is designed, and a set of conditions are developed to guarantee that the corresponding sliding motion is uniformly asymptotically stable. Then, a decentralised state feedback sliding mode control is proposed to drive the interconnected systems to the designed sliding surface in finite time, and sliding motion occurs thereafter. The bounds on the uncertainties and interconnections are known nonlinear functions, which are employed in the control design to reject the effects of uncertainties and unknown interconnections to enhance the robustness. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed control strategy.
Paper VI121-06.11
PDF · Video · Game Theoretic Stochastic Energy Coordination under a Distributed Zeroth-Order Algorithm
Chen, Yuwen	ETH Zurich
Zou, Suli	Beijing Institute of Technology
Lygeros, John	ETH Zurich
Keywords: Decentralized control, Stochastic optimal control problems, Power systems Abstract: Dealing with the effects from uncertainties properly is a key problem in stochastic energy management problems to achieve safe and efficient operation of the system. In this paper, we study the problem of coordinating multi-period electric vehicles charging amidst uncertainty from the embedded renewable generation in a local distribution network under transformer capacity limits. A stochastic generalized game is presented to formulate the underlying electric vehicle coordination problem wherein the cost function of each player is affected by the intermittent renewable energy supply. Existing algorithms for seeking the equilibrium rely on conditions on the form of the cost functions. In our setting, however, stochastic effects are not known in advance which results in an unknown form of the cost functions. We propose a distributed iterative zeroth-order algorithm, which only relies on the observations of costs, to achieve a stochastic generalized Nash equilibrium of the game under the concept of Gaussian smoothing. Under certain mild assumptions, the proposed algorithm is guaranteed to converge to the neighborhood of the stochastic generalized Nash equilibrium. We demonstrate the algorithm for a distribution network energy management problem with 3 heterogeneous subgroups of electric vehicles.

VI121-07
Fault Tolerant Control Design	Regular Session
Chair: Costa, Oswaldo Luiz V.	Univ. of Sao Paulo
Co-Chair: Gopaluni, Bhushan	University of British Columbia
Paper VI121-07.1
PDF · Video · Fault-Tolerant Fully Distributed Leader-Following Consensus for Linear Multi-Agent Systems with Non-Cooperative Leader
Hajshirmohamadi, Shahram	Isfahan University of Technology
Sheikholeslam, Farid	Isfahan Univrsity of Technology (IUT)
Meskin, Nader	Qatar University
Ghommam, Jawhar	CEM-GREPCI
Keywords: Adaptive control, Observer design Abstract: In this paper,the problem of distributed fault-tolerant control for multi-agent systems is studied. In the proposed method, the communication graph of the network is not needed to be known by the agents. The leader agent is active with a bounded non-zero control input. The control input of the leader and its bound is not known by any follower. Moreover, it is assumed that the leader is non-cooperative and does not communicate with any other agent. By considering all these limitations, the control input of the followers are designed such that the followers can track the leader in the presence of bounded additive actuator faults. A numerical simulation is provided to illustrate the effectiveness of the proposed approach.
Paper VI121-07.2
PDF · Video · Fault Prognostics of Rolling Bearings Using a Hybrid Approach
Camargos, Murilo	Universidade Estadual De Montes Claros
Bessa, Iury	Universidade Federal Do Amazonas
D'Angelo, Marcos	UNIMONTES
Palhares, Reinaldo Martinez	Federal University of Minas Gerais
Keywords: Fault-tolerant Abstract: This paper presents a two-phase hybrid prognostics approach; in the first phase, the model’s parameters are estimated using available training data in the least squares sense using the Levenberg-Marquardt algorithm. The second phase consists of using a particle filter to update the knowledge acquired so far and to predict future states of the system using in the Bayesian sense. The approach is used for an accelerated ball bearing data set, the PRONOSTIA platform, where a general fractional polynomial model is proposed as degradation model. The results of the Remaining Useful Life estimation are compared with another work in the literature, indicating its suitability and competitiveness for prognostics in this data set.
Paper VI121-07.3
PDF · Video · Software Rejuvenation under Persistent Attacks in Constrained Environments
Romagnoli, Raffaele	Carnegie Mellon University
Griffioen, Paul	Carnegie Mellon University
Krogh, Bruce H.	Carnegie Mellon Univ
Sinopoli, Bruno	Washington University in St Louis
Keywords: Fault-tolerant, Constrained control, Lyapunov methods Abstract: Software rejuvenation has been proposed to guarantee safety of cyber-physical systems (CPSs) against cyber-attacks. Recent work has demonstrated how this method can be applied to more general control problems such as tracking control. Despite this progress, there are still limitations in applying software rejuvenation to real situations where the presence of persistent attacks and physical environment constraints exist. In this paper we address these issues and propose a secure recovery algorithm that can be deployed not only for recovery against persistent attacks but also in situations where physical environment constraints do not allow the system to tolerate any attack. The effectiveness of the approach is illustrated with a simulation of a quadrotor landing on the ground during recovery from a persistent attack.
Paper VI121-07.4
PDF · Video · Actuator Fault Tolerant Control of Variable Pitch Quadrotor Vehicles
Baldini, Alessandro	Università Politecnica Delle Marche
Felicetti, Riccardo	Università Politecnica Delle Marche
Freddi, Alessandro	Universita' Politecnica Delle Marche
Longhi, Sauro	Università Politecnica Delle Marche
Monteriù, Andrea	Università Politecnica Delle Marche
Keywords: Fault-tolerant, Diagnosis, UAVs Abstract: Variable pitch quadrotors can experience actuation faults and failures of two main types: one type related to the rotor system and the other one related to the blade pitch servo. In this paper, we face the fault tolerant attitude tracking problem for a variable pitch quadrotor, in case of partial loss of effectiveness of the rotor system or lock-in-place of the blade pitch servo. The proposed solution is based on the combination of the Disturbance Observer Based Control design paradigm together with that of Active Fault Diagnosis. In detail, an observer is designed for estimating the thrust produced by each rotor. An active diagnosis scheme is adopted to discriminate which fault/failure is affecting the system. Finally, a control allocation algorithm solves the optimal redistribution problem of the control effort among the rotors, subject to different constraints. The proposed overall optimal fault tolerant control scheme can be coupled with most of the nonlinear control laws commonly applied to conventional, fixed pitch, quadrotor systems. Numerical simulations show the capability of the proposed scheme to handle both loss of effectiveness of the rotor system or lock-in-place of the blade pitch servo.
Paper VI121-07.5
PDF · Video · Fault Compensation Controller for Markovian Jump Linear Systems
Carvalho, Leonardo de Paula	Universidade De São Paulo
Rosa, Tábitha E.	University of Groningen
Jayawardhana, Bayu	University of Groningen
Costa, Oswaldo Luiz V.	Univ. of Sao Paulo
Keywords: Fault-tolerant, Networked systems, Robust linear matrix inequalities Abstract: In this paper, we tackle the fault-compensation controller in the context of Markovian Jump Linear Systems (MJLS). More specifically, we propose the design of Hoo Fault-Compensation Controllers under the MJLS formulation, which is provided in terms of linear matrices inequalities optimization problems. These particular controllers have as the main motivation the network communication loss which is inherent to any automation process. We present a numerical example of a coupled tank system, where a Monte Carlo simulation illustrates the feasibility of the proposed solution. The results show that the proposed approach is indeed a valuable alternative to compensate for the fault occurrence.
Paper VI121-07.6
PDF · Video · A Cooperative Fault-Tolerant Control Method for the Coupled System Based on Interaction Effect Utilization
Chang, Jing	Xidian University
Cieslak, Jérôme	University of Bordeaux
Guo, Zongyi	Northwestern Polytechnical University
Henry, David	Université De Bordeaux
Keywords: Fault-tolerant, Nonlinear cooperative control, Lyapunov methods Abstract: An active fault-tolerant control scheme is proposed in this paper for the strongly coupled MIMO systems which subject to total actuator failures. A control-oriented interaction indicator is defined in the Lyapunov stability sense and then is utilized to design the cooperative fault-tolerant control law. The proposed scheme can achieve robust tracking performance with globally uniformly ultimate boundlessness and is capable of improving transient performance (fault-tolerant ability) by wisely using the interactions. Simulation results obtained on a flight attitude control system illustrates the benefit of the proposed techniques.
Paper VI121-07.7
PDF · Video · Fault-Tolerant Optimal Control Scheme for Satellite Micro-Launchers
Reitu, Alexandra	Faculty of Automatic Control and Computers, University Politehni
Sperila, Andrei	Faculty of Automatic Control and Computers, University Politehni
Ciubotaru, Bogdan D.	Faculty of Automatic Control and Computers, Polytechnic Universi
Keywords: Fault-tolerant, Optimal control theory, Aerospace Abstract: An integration of Fault Detection, Isolation and Recovery (FDIR) with the Linear Quadratic Gaussian (LQG) technique is presented, which achieves fault tolerance while maintaining control optimality. The FDIR scheme is tested on a space micro-launcher model, and simulation results show successful accommodation of both sensor and actuator faults.
Paper VI121-07.8
PDF · Video · Dissipativity and Stability Recovery by Fault Hiding
Bessa, Iury	Universidade Federal Do Amazonas
Camargos, Murilo	Universidade Estadual De Montes Claros
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Palhares, Reinaldo Martinez	Federal University of Minas Gerais
Keywords: Fault-tolerant, Stability of nonlinear systems, Passivity-based control Abstract: This paper addresses the problem of dissipativity-based fault tolerant control (FTC) based on fault hiding approach. In particular, a static reconfiguration block (RB) is used for reconfiguration of faulty systems. Such block performs a loop transformation by inserting series, feedback, and feedforward gains to a system including plant, sensor or actuator faults. The proposed approach consists in recovering dissipativity and passivity conditions of a previously dissipative system, ensuring that the reconfigured system has the same supply function of the nominal system. Numerical examples illustrate how such approach can be used to recover the asymptotic stability by fault hiding even for nonlinear systems. Furthermore, LMI-based conditions for designing the proposed RB are provided for stability recovery for linear systems.
Paper VI121-07.9
PDF · Video · Recent Advances in Fault Diagnosis and Control of Cyber-Physical System
Yu, Jiafeng	Jiangsu Maritime Institute
Shi, Peng	University of Adelaide
Li, Qinsheng	Jiangsu Maritime Institute
Xing, Wen	Harbin Engineering University
Chadli, Mohammed	University of Paris-Saclay, IBISC Lab - UEVE
Dimirovski, Georgi Marko	Dogus University of Istanbul
Keywords: Nonlinear cooperative control, Passivity-based control, Sum-of-squares Abstract: In this paper, the dissipativity-based consensus problem for polynomial fuzzy multi-agent systems is considered. First, a novel fuzzy modeling method is proposed to describe the error dynamics. By establishing the changing topologies by Markov process, a new consensus protocols are designed. By polynomial Lyapunov function and sum of squares, sufficient condition is given to assure even-square consensus with dissipative performance. Finally, an illustrative example is employed to verify the proposed dissipativity-based even-square consensus design schemes.

VI121-08
Observer and Estimator Design	Regular Session
Chair: Zhu, Fanglai	Tongji University
Co-Chair: Nesic, Dragan	Univ of Melbourne
Paper VI121-08.1
PDF · Video · Thermal Monitoring of Buildings by Aggregated Temperature Estimation
Niazi, Muhammad Umar B.	Gipsa-Lab, CNRS
Canudas de Wit, Carlos	CNRS-GIPSA-Lab
Kibangou, Alain	GIPSA-Lab, Univ. Grenoble Alpes, CNRS
Keywords: Observer design, Complex systems, Networked systems Abstract: Thermal monitoring is important not only to ensure the comfort of building inhabitants but also to reduce energy consumption and greenhouse gas emissions. It can be, however, a challenging task because of limited computational and sensing resources at hand. This paper provides an efficient technique to estimate average (or mean operative) temperatures of rooms in a building. The proposed average observer is of minimum order whose parameters are chosen to minimize the asymptotic estimation error. The results show the effectiveness of the approach in the estimation-based temperature regulation.
Paper VI121-08.2
PDF · Video · Formation Control of Euler-Lagrange Systems of Leaders with Bounded Unknown Inputs
Zhou, Panpan	The Chinese University of Hong Kong
Xi, Lele	Beijing Institute of Technology
Chen, Ben M.	Chinese University of Hong Kong
Keywords: Observer design, Decentralized control, Tracking Abstract: In this paper, we study the formation control of multiple Euler-Lagrange systems with nonautonomous leaders, which means the leaders have bounded unknown inputs. Firstly, adaptive distributed observers to the leaders' input bounds and states are designed for every follower. In addition, a discontinuous function in the adaptive distributed observer is applied to make up for the influence of the leaders' unknown inputs. Secondly, a distributed control law is constructed using the distributed observer to accomplish the formation control. Our control law achieves not only affine maneuver control but also containment control performance. All agents as a whole can rotate, shear and scale, and maneuver to destination safely.
Paper VI121-08.3
PDF · Video · State Estimation and Sliding Mode Control for Non-Linear Singular Systems with Time-Varying Delay
Kchaou, Mourad	University of Hail Saudi Arabia
El Hajjaji, Ahmed	Univ. De Picardie Jules Verne
Keywords: Observer design, Delay systems, Sliding mode control Abstract: This paper deals with the sliding mode control (SMC) problem for a class of non- linear discrete-time singular systems with external disturbances and time-varying delay. The main contribution of this paper is to design an observer-based sliding mode control scheme for the system under consideration. First, a delay dependent criterion is built to guarantee the sliding mode dynamics to be robustly admissible. Then, a (SMC) law is synthesized to guarantee the state trajectories of the closed-loop systems to be stable, and ensure the reachability of the specified sliding surface in a short time interval. An illustrative example is given to numerically demonstrate the effectiveness of the proposed control scheme.
Paper VI121-08.4
PDF · Video · Anti-Disturbance State Feedback Controller Based on Disturbance Reconstruction for Underactuated Overhead Crane
Zhu, Fanglai	Tongji University
Shan, Yu	Tongji University
Keywords: Observer design, Fault-tolerant, Disturbance rejection (linear case) Abstract: The paper deals with the control problems for the underactuated overhead crane system with lumped disturbance. First, two-stage state transformations are made and the system is eventually transformed into a linear-like cascade system under the transformations. In order to cope with the lumped unknown inputs, an identical unknown input reconstruction method is developed and the reconstruction is based on an interval observer. And then, for the equivalent linear-like cascade system, an anti-disturbance (or anti-unknown input) state feedback controller is designed by introducing the unknown input reconstruction into the controller. Simulation results are given to show the effectiveness of our methods.
Paper VI121-08.5
PDF · Video · A Distributed Set-Membership Estimator for Linear Systems Considering Multi-Hop Subspace Decomposition
Orihuela Espina, Luis	Universidad Loyola Andalucía
Ierardi, Carmelina	Loyola Andalucia University
Jurado, Isabel	Universidad Loyola Andalucía
Keywords: Observer design, Linear systems, Observers for linear systems Abstract: This paper presents a distributed set-membership estimator for linear full-coupled systems affected by bounded disturbances. The estimator makes use of a recently developed multi-hop subspace decomposition of the system that allows to transform the dynamic matrix into an upper triangular matrix, decoupling the influence of the non-observable modes to the observable ones. This way, each agent has to compute sets to encompass the observable dynamics on the one hand, and the unobservable dynamics on the other. The sets are mathematically described by zonotopes. Due to the multi-hop decomposition, the agents are able to design different gains for the observable and the unobservable part, pursuing the reduction in volume of the corresponding sets. The paper presents the solution for the two-agents case. Simulations are given to compare the proposed solution with existing ones in the field.
Paper VI121-08.6
PDF · Video · Simplifying the Design of Lipschitz Observers by Applying a Novel Batch Pole-Assignment Approach
Papageorgiou, Panos	University of Patras
Alexandridis, Antonis	University of Patras, Power Systems, Greece
Keywords: Observer design, Lyapunov methods, Observers for linear systems Abstract: A novel, analytic design method for full state observers of nonlinear Lipschitz systems with their nonlinear term bounded, is considered. In standard procedures, the Lipschitz constant of the nonlinear term imposes strict restrictions on the observer gain matrix stable selection and introduces a further uncertainty in the design, caused by the heuristic manner of this selection. As shown in the paper, when the system nonlinear term is additionally bounded, which is a common situation for many real world systems such as manipulators in robotics and generators in power systems, the Lipschitz constant restriction is fully relaxed. Under these circumstances, a direct design approach is proposed that assigns the observer linear part eigenvalues at a common, specific, negative real position on the left of the system poles. The whole procedure is conducted by simply solving a Lyapunov-type equation that simultaneously constructs the suitable corresponding gain matrix of the observer. The validity of the method and the enhanced observer performance are verified by simulation results conducted on a fundamental power system example.
Paper VI121-08.7
PDF · Video · Observer Design for Interconnected Systems with Model Reduction and Unknown Inputs
Steiner, Tim	University of Kaiserslautern
Liu, Steven	University of Kaiserslautern
Keywords: Observer design, model reduction of distributed parameter systems, thermal and process control applications of distributed parameter systems Abstract: In this paper a combination of distributed parameter systems and lumped parameter systems is investigated, also known as interconnected system. In particular, the heat distribution and the influence of single chips on a base plate is of interest, here in context of insulated-gate bipolar transistors. Only temperature measurements on the base plate are available. A method is presented with which the temperature inside the chip can be estimated. A combination of model reduction and unknown input observer is utilized.
Paper VI121-08.8
PDF · Video · A Two-Step Approach to Interval Estimation for Continuous-Time Switched Linear Systems
Li, Jitao	Harbin Institute of Technology
Wang, Zhenhua	Harbin Institute of Technology
Fei, Zhongyang	Harbin Institute of Technology
Dimirovski, Georgi Marko	Dogus University of Istanbul
Shen, Yi	Harbin Institute of Technology
Keywords: Observer design, Nonlinear observers and filter design Abstract: This paper proposes a two-step interval estimation method for continuous-time switched linear systems subject to unknown but bounded disturbance and measurement noise. We first use an L∞ norm-based approach to attenuate the effect of uncertainties in observer design. Then, based on the obtained observer, interval estimation can be achieved via analyzing the bounds of estimation error. The proposed method is intuitive and independent of cooperativity constraint, which is main restriction of interval observer theory. The performance of the proposed method is demonstrated through a numerical simulation.
Paper VI121-08.9
PDF · Video · An Observer for the Electrically Heated Vertical Rijke Tube with Nonlinear Heat Release
Wilhelmsen, Nils Christian Aars	MINES ParisTech
Di Meglio, Florent	MINES ParisTech
Keywords: Observer design, Nonlinear observers and filter design, thermal and process control applications of distributed parameter systems Abstract: This paper proposes an observer for the electrically heated vertical Rijke tube, using a model capable of inciting thermoacoustic instabilities. The model consists of linear, distributed acoustics coupled with nonlinear, lumped heat release. Using a boundary pressure measurement taken at the bottom end of the tube, the observer is designed by copying the system model and reconstructing both the bottom and top boundary conditions, the former exactly and the latter with an error that is shown to be converge to zero exponentially. It is proven that the observer produces state estimates that converge to their correct values asymptotically. Furthermore, it is shown the state estimation errors stay bounded when there is a modelling error in the boundary acoustic impedance. The proposed observer is simulated and compared to two alternative observers.
Paper VI121-08.10
PDF · Video · Stable Force Reconstruction from Acceleration Measurements - Theory and Experiment
Falkensteiner, Roland	Graz University of Technology
Seeber, Richard	Graz University of Technology
Horn, Martin	Graz University of Technology
Tafner, Robert	AVL DiTEST GmbH
Keywords: Observer design, Observers for linear systems Abstract: This paper presents an unknown input observer for the estimation of external forces acting on mechanical systems from only acceleration measurements. To circumvent arising stability issues, a classical unknown input observer augmented with an additional filter is proposed. The influence of the design parameter of the filter is analyzed. A guideline for the parameter tuning depending on predefined estimation goals is given. In contrast to existing methods, no prior knowledge about the unknown acting force is assumed in the design process. The performance of the presented concept is compared to a state-of-the-art approach in both simulation studies and on a experimental test setup.
Paper VI121-08.11
PDF · Video · Non-Asymptotic State Estimation of Linear Reaction Diffusion Equation Using Modulating Functions
Ghaffour, Lilia	Computer, Electrical and Mathematical Science and Engineering Di
Noack, Matti	TU Ilmenau
Reger, Johann	TU Ilmenau
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Observer design, Observers for linear systems Abstract: In this paper, we propose a non-asymptotic state estimation method for the linear reaction diffusion equation with general boundary conditions. The method is based on the modulating function approach utilizing a modulation functional in time and space. This results in a signal model control problem for a system of auxiliary PDEs in order to determine the modulation kernels. First, the algorithm is mathematically derived and then numerical simulations are presented for illustrating the good performance of the proposed approach and demonstrating the efficient implementation scheme.
Paper VI121-08.12
PDF · Video · Distributed Global Actuator Fault-Detection Scheme for a Class of Linear Multi-Agent Systems with Disturbances
Taoufik, Anass	Northumbria University
Defoort, Michael	University of Valenciennes
Djemai, Mohamed	UVHC
Busawon, Krishna K.	Northumbria University
Sanchez-Torres, Juan Diego	ITESO
Keywords: Observer design, Observers for linear systems, Nonlinear observers and filter design Abstract: This paper proposes a distributed methodology for the detection of actuator faults in a class of linear multi-agent systems in the presence of disturbances. A cascade of fixedtime observers is introduced to give an exact estimate of the global system state for each agent whereby the convergence time is estimated regardless of the initial conditions. Distributed observers are then designed using Linear Matrix Inequalities (LMI), by employing the H and H∞ norms. The proposed method ensures global actuator fault detection, where each agent is capable of detecting not only its faults but also those that occur at any other part of the system. Numerical simulation results are carried out to show the effectiveness of the proposed approach.
Paper VI121-08.13
PDF · Video · A Multi-Observer Approach for Parameter and State Estimation of Nonlinear Systems with Slowly Varying Parameters
Cuevas Ramirez, Luis Angel	The University of Melbourne
Nesic, Dragan	Univ of Melbourne
Manzie, Chris	The University of Melbourne
Postoyan, Romain	CRAN, CNRS, Université De Lorraine
Keywords: Observer design, Parameter-varying systems Abstract: This manuscript addresses the parameter and state estimation problem for continuous time nonlinear systems with unknown slowly time-varying parameters, which are assumed to belong to a known compact set. The problem is tackled by using the multi-observer approach under the supervisory framework, which generates parameter and state estimates by using a finite number of sample points of the parameter set, a bank of observers, a set of monitoring signals and a selection criterion. This note proposes a novel dynamic sampling policy for the multi-observer technique and studies its convergence properties. We prove that the parameter and state estimation errors are ultimately bounded where the ultimate bounds can be made arbitrarily small if the parameter varies sufficiently slowly, and the number of samples is sufficiently large.
Paper VI121-08.14
PDF · Video · Impact of Sensor Placement on Mode Observability and LQG Control of a Thermoacoustic System
Chen, Xiaoling	Pennsylvania State University
Fathy, Hosam K.	Penn State University
O'Connor, Jacqueline	Pennsylvania State University
Keywords: Observer design, Robust time-delay systems, Model reduction Abstract: This paper investigates the effect of sensor placement on the observability and LQG control of a thermoacoustic model. This model describes combustion instability in a one-dimensional combustor, called a Rijke tube. The transfer function describing this model is transcendental because of the time delay terms in the heat release dynamics. We apply Padé approximation to achieve a finite-dimensional transfer function and truncate the system by neglecting states with low Hankel singular values. We then analyze the impact of the placement and number of sensors on the observability of each mode of the resulting reduced-order model. Next, we design an LQG controller for suppressing pressure oscillations in the simplified thermoacoustic system. We find that placing sensors near the model's pressure nodes slows down the rate at which LQG control attenuates pressure oscillations, increases the control effort required for this attenuation, and worsens the controller's robustness.

VI121-09
Optimal and Predictive Controller Design and Optimization	Regular Session
Chair: Korda, Milan	école Polytechnique Fédérale De Lausanne
Co-Chair: Borrelli, Francesco	University of California
Paper VI121-09.1
PDF · Video · Robust Adaptive Model Predictive Control with Worst-Case Cost
Parsi, Anilkumar	ETH Zurich
Iannelli, Andrea	ETH Zurich
Yin, Mingzhou	ETH Zurich
Khosravi, Mohammad	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Adaptive control, Robust control (linear case), Predictive control Abstract: In this paper, a robust adaptive model predictive control (MPC) algorithm is presented for linear, time invariant systems with unknown dynamics and subject to bounded measurement noise. The system is characterized by an impulse response model, which is assumed to lie within a bounded set called the feasible system set. Online set-membership identification is used to reduce uncertainty in the impulse response. In the MPC scheme, robust constraints are enforced to ensure constraint satisfaction for all the models in the feasible set. The performance objective is formulated as a worst-case cost with respect to the modeling uncertainties. That is, at each time step an optimization problem is solved in which the control input is optimized for the worst-case plant in the uncertainty set. The performance of the proposed algorithm is compared to an adaptive MPC algorithm from the literature using Monte-Carlo simulations.
Paper VI121-09.2
PDF · Video · Model Predictive Control of a Vehicle Using Koopman Operator
Cibulka, Vit	CTU in Prague
HaniŠ, TomáŠ	CTU in Prague, Faculty of ElectricalEngineering, Departmentfor Co
Korda, Milan	école Polytechnique Fédérale De Lausanne
Hromcik, Martin	Czech Technical Univ
Keywords: Data-based control, N-dimensional systems, Nonlinear predictive control Abstract: This paper continues in the work from Cibulka et al. (2019) where a nonlinear vehicle model was approximated in a purely data-driven manner by a linear predictor of higher order, namely the Koopman operator. The vehicle system typically features a lot of nonlinearities such as rigid-body dynamics, coordinate system transformations and most importantly the tire. These nonlinearities are approximated in a predefined subset of the state-space by the linear Koopman operator and used for a linear Model Predictive Control (MPC) design in the high-dimension state space where the nonlinear system dynamics evolve linearly. The result is a nonlinear MPC designed by linear methodologies.It is demonstrated that the Koopman-based controller is able to recover from a very unusual state of the vehicle where all the aforementioned nonlinearities are dominant. The controller is compared with a controller based on a classic local linearization and shortcomings of this approach are discussed.
Paper VI121-09.3
PDF · Video · Data-Driven Parameterizations of Suboptimal LQR and H-2 Controllers
van Waarde, Henk J.	University of Groningen
Mesbahi, Mehran	Univ of Washington
Keywords: Data-based control, Optimal control theory, Linear systems Abstract: In this paper we design suboptimal control laws for an unknown linear system on the basis of measured data. We focus on the suboptimal linear quadratic regulator problem and the suboptimal H2 control problem. For both problems, we establish conditions under which a given data set contains sufficient information for controller design. We follow up by providing a data-driven parameterization of all suboptimal controllers. We will illustrate our results by numerical simulations, which will reveal an interesting trade-off between the number of collected data samples and the achieved controller performance.
Paper VI121-09.4
PDF · Video · Task Decomposition for MPC: A Computationally Efficient Approach for Linear Time-Varying Systems
Vallon, Charlott	University of California, Berkeley
Borrelli, Francesco	University of California
Keywords: Data-based control, Predictive control, Convex optimization Abstract: A Task Decomposition method for iterative learning Model Predictive Control (TDMPC) for linear time-varying systems is presented. We consider the availability of state-input trajectories which solve an original task T1, and design a feasible MPC policy for a new task, T2, using stored data from T1. Our approach applies to tasks T2 which are composed of subtasks contained in T1. In this paper we formally define the task decomposition problem, and provide a feasibility proof for the resulting policy. The proposed algorithm reduces the computational burden for linear time-varying systems with piecewise convex constraints. Simulation results demonstrate the improved efficiency of the proposed method on a robotic path-planning task.
Paper VI121-09.5
PDF · Video · Data-Based Nonaffine Optimal Tracking Control Using Iterative DHP Approach
Ha, Mingming	University of Science and Technology Beijing
Wang, Ding	Beijing University of Technology
Liu, Derong	Chinese Academy of Sciences
Keywords: Data-based control, Tracking, Optimal control theory Abstract: In this paper, a data-based optimal tracking control approach is developed by involving the iterative dual heuristic dynamic programming algorithm for nonaffine systems. In order to gain the steady control corresponding to the desired trajectory, a novel strategy is established with regard to the unknown system function. Then, according to the iterative adaptive dynamic programming algorithm, the updating formula of the costate function and the new optimal control policy for unknown nonaffine systems are provided to solve the optimal tracking control problem. Moreover, three neural networks are used to facilitate the implementation of the proposed algorithm. In order to improve the accuracy of the steady control corresponding to the desired trajectory, we employ a model network to directly approximate the unknown system function instead of the error dynamics. Finally, the effectiveness of the proposed method is demonstrated through a simulation example.
Paper VI121-09.6
PDF · Video · A Distributed Algorithm for Nonconvex Quadratically Constrained Programs
Ashour, Mahmoud	The Pennsylvania State University
Lagoa, Constantino M.	Pennsylvania State Univ
Keywords: Decentralized control Abstract: This paper considers nonconvex quadratically constrained programs over undirected connected graphs. We focus on problems whose quadratic constraint forms have sparse hessians, i.e., each constraint only involves a small subset of variables. We present both centralized and distributed treatment of the problem, where the centralized method is used as a benchmark with which we compare the performance of the proposed distributed algorithm. Towards this objective, we derive a lower bound on the optimal value of the problem using a semidefinite relaxation. Then, we develop a decentralized algorithm based on proximal gradient ADMM that exploits the structure of the constraints to distribute the computations among the graph nodes. Indeed, the proposed algorithm does away with a central node. Each node updates its local variables via solving a simple subproblem, then communicate with its immediate neighbors. An application of this work is the AC optimal power flow problem in power networks for which we provide preliminary numerical results to validate our findings.
Paper VI121-09.7
PDF · Video · Hierarchical Control of a Quadcopter under Stuck Actuator Fault
Nguyen, Ngoc Thinh	University of Luebeck
Prodan, Ionela	INP Grenoble
Petzke, Felix	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Lefevre, Laurent	Univ. Grenoble Alpes
Keywords: Fault-tolerant, Nonlinear predictive control, UAVs Abstract: We propose a hierarchical FTC (Fault Tolerant Control) scheme for trajectory tracking by a quadcopter system under stuck actuator fault and actuator saturation. Both the FDI (Fault Detection and Isolation) and control reconfiguration modules are implemented at the low-level associated with the rotation dynamics through a NMPC (Nonlinear Model Predictive Control) strategy. The uncontrolled (when under fault) yaw torque is predicted and compensated by the NMPC. It is shown that the overall control scheme succeeds in maintaining trajectory tracking for various fault events (both in the sense of having various stuck values and in the sense of changing the actuator under fault).
Paper VI121-09.8
PDF · Video · Observer Based Restricted Structure Generalized Predictive Control for Quasi-LPV Nonlinear Systems
Grimble, Michael	University of Strathclyde, Industrial Control Centre
Majecki, Pawel	Univ of Strathclyde
Keywords: Observer design, Predictive control, Linear parameter-varying systems Abstract: An observer based Restricted Structure Generalized Predictive Control (RS-GPC) algorithm is proposed. The novel feature is to assume the state-observer within the feedback loop is of reduced order. The aim is to inherit the natural robustness of low-order controllers and to provide a solution that may be easily simplified for real-time implementation. The nonlinear discrete-time, multivariable plant model is represented by a state-space system that may be in Linear Parameter Varying or State-Dependent forms. The controller gains are computed to minimize the type of cost-function that is found in traditional model predictive control but with some additional terms that enable gain magnitudes and the rate of change of control gains to be minimized. The cost-function also includes dynamically weighted tracking-error and control signal costing terms. The optimal controller includes a reduced order observer and a time-varying control gain matrix within the loop and background processing for the gain computations. Hard constraints may be imposed on the gain and rate of change of gain and on the control and output signals.

VI121-10
Singular and Descriptor Systems	Regular Session
Chair: Trenn, Stephan	University of Groningen
Co-Chair: Schwerdtner, Paul	Technische Universität Berlin
Paper VI121-10.1
PDF · Video · Fault Estimation Methods in Descriptor System with Partially Decoupled Disturbances
Do, Manh-Hung	Université Grenoble Alpes, GIPSA-Lab
Koenig, D.	Inpg - Esisar
Theilliol, Didier	University of Lorraine
Keywords: Descriptor systems, Observers for linear systems, Decoupling problems Abstract: The main contribution of this paper consists of the development of two methods for actuator fault estimation in dealing with the partially decoupled disturbances of the descriptor system, which is divided into decoupled and non-decoupled unknown inputs (UI). Based on the conventional UI observer, both of the solutions decouples the fault estimation with the first group of UI, while the second UI group is handled differently by each method. Finally, a numerical example with comparisons points out the performance of each approach
Paper VI121-10.2
PDF · Video · Certifying Global Optimality for the L-Infinity-Norm Computation of Large-Scale Descriptor Systems
Schwerdtner, Paul	Technische Universität Berlin
Mengi, Emre	Koc University, Istanbul
Voigt, Matthias	TU Berlin
Keywords: Descriptor systems, Robust control (linear case), Robustness analysis Abstract: We present a method for the certification of algorithms that approximate the L-infinity- or H-infinity-norm of transfer functions of large-scale (descriptor) systems. This certification is needed because such algorithms depend heavily on user input, and may converge to a local maximizer of the related singular value function leading to an incorrect value, much lower than the actual norm. Hence, we design an algorithm that determines whether a given value is less than the L-infinity-norm of the transfer function under consideration, and that does not require user input other than the system matrices. In the algorithm, we check whether a certain structured matrix pencil has any purely imaginary eigenvalues by repeatedly applying a structure-preserving shift-and-invert Arnoldi iteration combined with an appropriate shifting strategy. Our algorithm consists of two stages. First, an interval on the imaginary axis which may contain imaginary eigenvalues is determined. Then, in the second stage, a shift is chosen on this interval and the eigenvalues closest to this shift are computed. If none of these eigenvalues is purely imaginary, then an imaginary interval around the shift of appropriate length is removed such that two subintervals remain. This second stage is then repeated on the remaining two subintervals until either a purely imaginary eigenvalue is found or no critical subintervals are left. We show the effectiveness of our method by testing it without any parameter adaptation on a benchmark collection of large-scale systems.
Paper VI121-10.3
PDF · Video · H-Infinity Control for Differential-Algebraic Systems
Sperila, Andrei	Faculty of Automatic Control and Computers, University Politehni
Tudor, Sebastian Florin	Stevens Institute of Technology
Ciubotaru, Bogdan D.	Faculty of Automatic Control and Computers, Polytechnic Universi
Oara, Cristian	Politehnica University of Bucharest
Keywords: Descriptor systems, Robust controller synthesis, Output feedback control (linear case) Abstract: For a differential-algebraic system, we construct the class of proper suboptimal H-infinity stabilizing controllers and give formulas in terms of realizations and solutions to appropriate Riccati equations.
Paper VI121-10.4
PDF · Video · Set-Based State Estimation and Fault Diagnosis of Linear Discrete-Time Descriptor Systems Using Constrained Zonotopes
Rego, Brenner Santana	Federal University of Minas Gerais
Raimondo, Davide Martino	Università Degli Studi Di Pavia
Raffo, Guilherme Vianna	Federal University of Minas Gerais
Keywords: Descriptor systems, Robust estimation, Diagnosis Abstract: This paper presents new methods for set-valued state estimation and active fault diagnosis of linear descriptor systems. The algorithms are based on constrained zonotopes, a generalization of zonotopes capable of describing strongly asymmetric convex sets, while retaining the computational advantages of zonotopes. Additionally, unlike other set representations like intervals, zonotopes, ellipsoids, paralletopes, among others, linear static constraints on the state variables, typical of descriptor systems, can be directly incorporated in the mathematical description of constrained zonotopes. Therefore, the proposed methods lead to more accurate results in state estimation in comparison to existing methods based on the previous sets without requiring rank assumptions on the structure of the descriptor system and with a fair trade-off between accuracy and efficiency. These advantages are highlighted in two numerical examples.
Paper VI121-10.5
PDF · Video · Finite-Time Decentralized H∞ Control for Singular Large-Scale Systems
Li, Bo	Jiangsu University of Technology
Zhao, Junjie	Jiangsu University of Technology
Wo, Songlin	Jiangsu University of Technology
Ren, Xuejing	Changzhou Institute of Technology
Keywords: Descriptor systems, Robust linear matrix inequalities, Disturbance rejection (linear case) Abstract: In this paper, the definition of finite-time robust H∞ control for linear continuous-time singular large-scale systems is presented. The main aim of this paper is to design a decentralized state feedback controller which ensures that the closed-loop system is finite-time bounded (FTB), and the effect of the disturbance input on the controller output, meanwhile, is reduced to a prescribed level. A sufficient condition is presented for the solvability of this problem, which can be reduced to a feasibility problem involving linear matrix inequalities (LMIs). A detailed solving method is proposed for the restricted linear matrix inequalities. Finally, examples are given to show the validity of the methodology.
Paper VI121-10.6
PDF · Video · On Stabilizability of Switched Differential Algebraic Equations
Wijnbergen, Paul	University of Groningen
Jeeninga, Mark	University of Groningen
Trenn, Stephan	University of Groningen
Keywords: Time-varying systems, Linear systems, Descriptor systems Abstract: This paper considers stabilizability of switched differential algebraic equations (DAEs). We first introduce the notion of interval stabilizability and show that under a certain uniformity assumption, stabilizability can be concluded from interval stabilizability. A geometric approach is taken to find necessary and sufficient conditions for interval stabilizability. Then the analysis is extended resulting in a characterization of controllability.

VI122
Design Methods - Linear Control Systems
VI122-01 Algebraic and Symbolic Methods in Mathematical Systems Theory   Invited Session, 5 papers
VI122-02 Frequency Domain Techniques for Analysis and Design of Time-Delay Systems with Applications   Open Invited Session, 10 papers
VI122-03 Advances in Linear Systems   Regular Session, 19 papers
VI122-04 Observer Design and Output Feedback (Linear Systems)   Regular Session, 13 papers
VI122-05 Robust Control (Linear Case)   Regular Session, 9 papers
VI122-06 Structural Properties and Positive Systems   Regular Session, 9 papers
VI122-07 Switched Linear Systems   Regular Session, 5 papers
VI122-08 Time Varying Systems and Polynomial Methods   Regular Session, 6 papers
VI122-09 Time-Delay Systems   Regular Session, 15 papers

VI122-01
Algebraic and Symbolic Methods in Mathematical Systems Theory	Invited Session
Chair: Quadrat, Alban	Inria Lille - Nord Europe
Co-Chair: Zerz, Eva	RWTH Aachen Univ
Organizer: Quadrat, Alban	Inria Lille - Nord Europe
Organizer: Zerz, Eva	RWTH Aachen Univ
Paper VI122-01.1
PDF · Video · A Behavioral Approach to Estimation in nD Systems (I)
Pereira, Ricardo	University of Aveiro
Rocha, Paula	Univ of Porto
Keywords: N-dimensional systems, Observers for linear systems Abstract: In this paper we study the problem of estimation for multidimensional systems within the context of the behavioral approach. We consider the case where there are no disturbances as well as the case where the system dynamics is perturbed, and provide necessary conditions for the solvability of the corresponding estimation problems together with the construction of a solution, if it exists. Such solution is an estimator that is asymptotic, in the sense that the error trajectories are stable with respect to a pre-specified nD stability cone.
Paper VI122-01.2
PDF · Video · Computing the Cycle Structure of Finite Linear Systems (I)
Zerz, Eva	RWTH Aachen Univ
Giese, Hermann	RWTH Aachen University
Keywords: Linear systems, Structural properties, Polynomial methods Abstract: Consider a linear difference equation with constant coefficients in the ring of integers modulo m. If the leading coefficient and the constant term are both units, then all trajectories are (purely) periodic. Moreover, the finite state set can be decomposed into disjoint cycles of various lengths. The following problems will be addressed: computing the cycle partition and determining the period w.r.t. a specific initial state. The latter question can often be reduced to calculating the order of an invertible matrix. If the prime factorization of m is known, then it suffices to consider prime powers, by the Chinese remainder theorem. For primes, an efficient algorithm due to Leedham-Green may be used, which is available in group-theoretic computer algebra systems such as MAGMA or GAP. This approach will be extended to prime powers. Finally, we will discuss how to relax the assumptions guaranteeing periodicity.
Paper VI122-01.3
PDF · Video · On a Rank Factorisation Problem Arising in Gearbox Vibration Analysis (I)
Hubert, Elisa	University of Lyon
Barrau, Axel	Safran
Bouzidi, Yacine	INRIA
Dagher, Roudy	Inria Lille, Inria Chile
Quadrat, Alban	Inria Lille - Nord Europe
Keywords: N-dimensional systems, Linear systems, Polynomial methods Abstract: Given a field K, r matrices D_i belonging to K^{n*n}, a matrix M belonging to K^{n * m} of rank at most r, in this paper, we study the problem of factoring M as follows M=sum_{i=1}^r D_i u v_i, where u belongs to K^{n * 1} and v_i belongs to K^{1 * m} for i=1, ..., r. This problem arises in modulation-based mechanical models studied in gearbox vibration analysis (e.g., amplitude and phase modulation). We show how linear algebra methods combined by linear system theory ideas can be used to characterize when this polynomial problem is solvable and if so, how to explicitly compute the solutions.
Paper VI122-01.4
PDF · Video · On Constructing Boundaries for Boundary Value Problems Defined by Continuous 2-D Autonomous Systems (I)
Mukherjee, Mousumi	Indian Institute of Technology Bombay
Pal, Debasattam	Indian Institute of Technology Bombay
Keywords: N-dimensional systems, Infinite-dimensional systems, Polynomial methods Abstract: In this paper, we provide a constructive way of specifying initial/boundary data for a given continuous 2-D autonomous system described by a set of linear partial differential equations (PDEs) with real constant coefficients. One of the ways of specifying initial/boundary data is by specifying the values of various derivatives of the solution trajectories at the origin; the derivatives correspond to a standard monomial set obtained using Groebner basis. However, such an initial/boundary data often lacks physical interpretation. In this paper, we consider subsets of the domain having some algebraic structure (in the form of subspaces and strips of finite width around such subspaces) such that trajectories restricted to these subsets, often called characteristic sets, serve as initial/boundary conditions for the given autonomous system of linear PDEs. We provide a systematic way to construct such characteristic sets with the help of Groebner bases and Oberst-Riquier algorithm. Thus we bridge the gap between initial/boundary conditions involving standard monomials and more conventional initial/boundary conditions in the form of restrictions on characteristic sets. We also show that every scalar system of PDEs admits such a characteristic set given by a rectangular strip of finite width around a subspace whose dimension equals the Krull dimension of the system's quotient ring.
Paper VI122-01.5
PDF · Video · On Sensor Selection for Differential Algebraic Systems Observability (I)
Diop, Sette	CNRS
Keywords: Nonlinear observers and filter design, Observers for linear systems, Observer design Abstract: We address the problem of selecting sensors, that is, output equations, in order to endow with some properties. Among all such desirable properties is the basic one of observability and/or identifiability. Once such a problem is solved one may ask how to choose sensors in order to improve estimation algorithms in terms of reliability, robustness, or simply, low complexity. First, what is the minimal number of sensors that make the dynamics observable? Second, when the sensors are bound to measure state components, what is their minimum number? Third, how may the observability margin be improved by selecting the sensors? In this communication we provide an overview of these questions in the differential algebraic approach of observation problems.

VI122-02
Frequency Domain Techniques for Analysis and Design of Time-Delay Systems with Applications	Open Invited Session
Chair: Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Co-Chair: Sipahi, Rifat	Northeastern University
Organizer: Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Organizer: Sipahi, Rifat	Northeastern University
Paper VI122-02.1
PDF · Video · Stability by the First Approximation of a Water Hammer Model (I)
Danciu, Daniela	University of Craiova
Rasvan, Vladimir	Univ. of Craiova
Keywords: Infinite-dimensional systems, Linear systems, stability of distributed parameter systems Abstract: Usually the water hammer models in hydroelectric engineering are described by the adapted Saint-Venant Partial Differential Equations with linear and nonlinear boundary conditions. If the dynamic head and the Darcy-Weisbach losses are neglected the PDEs are linear hyperbolic and can be tackled by associating a system of Neutral Functional Differential Equations with two delays - there are two conduits (the tunnel and the penstock). The time scale analysis shows that in certain cases arising from practice the dynamics of the penstock can be considered as described by ordinary differential equations. Consequently the water hammer dynamics has now a single time delay. The stability is then discussed by analyzing the characteristic equation: frequency domain methods combined with algebraic ones are implied. In this way stability by the first approximation is obtained. From the engineering point of view the results display the stabilizing role of the surge tank.
Paper VI122-02.2
PDF · Video · On Qualitative Properties of Single-Delay Linear Retarded Differential Equations: Characteristic Roots of Maximal Multiplicity Are Necessarily Dominant (I)
Mazanti, Guilherme	CentraleSupélec
Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Time-invariant systems Abstract: This paper presents necessary and sufficient conditions for the existence of a real root of maximal multiplicity in the spectrum of a linear time-invariant single-delay equation of retarded type. We also prove that this root is always strictly dominant, and hence determines the asymptotic behavior of the system. These results are based on improved a priori bounds on the imaginary part of roots on the complex right half-plane.
Paper VI122-02.3
PDF · Video · Spectral Properties and Lyapunov Matrices of Primal-Dual Periodic Time-Delay Systems, with Application to Balancing (I)
Gomez, Marco Antonio	KU Leuven
Michiels, Wim	KU Leuven
Keywords: Systems with time-delays, Lyapunov methods, Model reduction Abstract: In the paper we establish connections between the spectral properties of linear periodic systems with multiple delays with those of a dual system, obtained by transposition of the systems matrices and affine transformations of their arguments. The dual system also allows to introduce the dual Lyapunov matrix associated with the original system. We provide various energy interpretations of the primal-dual Lyapunov matrices, which allow us to generalize the concept of position balancing and explore its potential for model reduction.
Paper VI122-02.4
PDF · Video · Computing and Optimizing the Robust Strong H-Infinity Norm of Uncertain Time-Delay Systems (I)
Appeltans, Pieter	KU Leuven
Michiels, Wim	KU Leuven
Keywords: Systems with time-delays, Robust control (linear case), Robust time-delay systems Abstract: This short paper presents a method to compute and optimize the robust strong H-infinity norm of linear time-invariant systems with discrete delays and uncertainties on the system matrices. Special attention will be paid to a fragility problem of the H-infinity norm for systems with discrete delays in the direct feed-through terms. More specifically, for such systems the H-infinity norm might be sensitive to arbitrary small delay changes. This fragility problem can be resolved by considering the strong H-infinity norm, which takes into account infinitesimal delay perturbations. The robust strong H-infinity norm is subsequently defined as the worst-case strong H-infinity norm over all instances of the uncertainties and is a measure for robust performance. It can be shown that this robust strong H-infinity norm is related to the robust distance to instability of an associated uncertain system described by delay differential-algebraic equations. Using this relation, the robust strong H-infinity norm can be computed efficiently. This efficient computation of the robust strong H-infinity norm will be used for controller design by direct minimization of the robust strong H-infinity norm as function of the controller parameters.
Paper VI122-02.5
PDF · Video · Spectral Dominance of Complex Roots for Single-Delay Linear Equations (I)
Mazanti, Guilherme	CentraleSupélec
Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Vyhlidal, Tomas	Czech Technical Univ in Prague, Faculty of Mechanical Engineerin
Keywords: Systems with time-delays, Time-invariant systems Abstract: This paper provides necessary and sufficient conditions for the existence of a pair of complex conjugate roots, each of multiplicity two, in the spectrum of a linear time-invariant single-delay equation of retarded type. This pair of roots is also shown to be always strictly dominant, determining thus the asymptotic behavior of the system. The proof of this result is based on the corresponding result for real roots of multiplicity four, continuous dependence of roots with respect to parameters, and the study of crossing imaginary roots. We also present how this design can be applied to vibration suppression and flexible mode compensation.
Paper VI122-02.6
PDF · Video · Robust Stabilization of an Elementary Logistic System with an Input Delay (I)
Bou Farraa, Berna	Ecole Centrale De Nantes
Abbou, Rosa	LS2N University/ IUT of Nantes
Loiseau, Jean Jacques	Lab. Sciences Du Numérique De Nantes - LS2N CNRS
Keywords: Robust time-delay systems, Robustness analysis, Control of constrained systems Abstract: In this paper, we are interested in the robustness analysis of an elementary logistic system having a fixed loss factor on the inventory level and uncertainties on the production delay. The problem is treated in control theory domain, where the model is considered as an input time delay system characterized by positivity and saturation constraints, and an external disturbance. Indeed, we apply a prediction state feedback control strategy using an affine control law, where the prediction of the future inventory level is based on a delay estimation of the delay uncertainty. Hence, the objective of the study is to quantify the impact of the uncertainty induced by this estimation on the performance of the controlled system. First, we use a frequency-domain technique to identify the robust stability condition in the set of parameters. In particular, we specify the range of the delay deviation such that the closed-loop system stability is guaranteed. Then, we move on to define the input-output flow variations that allows to check the system constraints, based on the invariance properties. Finally, a comparative simulation is provided to highlight the advantages of this study.
Paper VI122-02.7
PDF · Video · Some Insights on the Asymptotic Stabilization of a Class of SISO Marginally Stable Systems Using One Delay Block (I)
Hernandez-Diez, José	Université De Paris-Saclay (CentraléSupelec)
Mendez-Barrios, Cesar Fernando	Universidad Autónoma De San Luis Potosí
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Linear systems, Asymptotic stabilization Abstract: In this paper, the stability of a class of marginally stable SISO systems is studied by applying a single one delay block as a feedback controller. More precisely, we consider an open-loop system with no zeros and whose poles are located exactly on the imaginary axis. Furthermore, a control law formed uniquely by a proportional gain and a delayed behavior is proposed for its closed-loop stabilization. The main ideas are based on a detailed analysis of the characteristic quasi polynomial of the closed-loop system as the controller parameters (gain, delay) are varied. More precisely, by using the Mikhailov stability criterion, for a fixed delay value, we compute some gain margin guaranteeing the closed-loop stability. The particular case when the characteristic roots of the open-loop system are equidistantly distributed on the imaginary axis is also addressed. Finally, an illustrative example shows the effectiveness of the approach.
Paper VI122-02.8
PDF · Video · Towards an MID-Based Delayed Design for Arbitrary-Order Dynamical Systems with a Mechanical Application (I)
Balogh, Tamas	Budapest University of Technology and Economics and MTA-BME Lend
Insperger, Tamas	Budapest Univ of Technology and Economics
Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Asymptotic stabilization, Output feedback control Abstract: In this study we consider the stabilization of nth-order linear time-invariant (LTI) dynamical systems using multiplicity-induced-dominancy (MID)-based controller design in the presence of delays in the input/output channels. A sufficient condition is given for the dominancy of a real root with multiplicity n+1 using an integral representation of the corresponding characteristic function. Furthermore, this sufficient condition is analyzed in the case when the characteristic function of the open-loop system is real-rooted, and delay intervals are derived for the set of parameters satisfying stabilizability and dominancy conditions. The efficiency of the proposed controller design is shown in the case of a multi-link inverted pendulum.
Paper VI122-02.9
PDF · Video · Some Insights on Real Rightmost Spectral Values Assignment for Time Delay Systems (I)
Amrane, Souad	Université Mouloud Mammeri De Tizi Ouzou
Boussaada, Islam	Laboratoire Des Signaux Et Systemes (L2S)
Bedouhene, Fazia	Laboratoire De Mathématiques Pures Et Appliquées(LMPA), Universi
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Linear systems, stability of delay systems Abstract: This paper investigates the stability and stabilization of some generic linear second-order time-invariant retarded system with single delay. It provides an appropriate stability criterion based on the manifold defined by the coexistence of the maximal number of negative spectral values. Next, such ideas are exploited in the context of delayed output feedback by an appropriate "partial" pole placement guaranteeing simultaneously the stability in closed-loop and an appropriate exponential decay rate. To perform such an analysis, the argument principle is explicitly used.
Paper VI122-02.10
PDF · Video · Some Remarks on the Regular Splitting of Quasi-Polynomials with Two Delays. Characterization of Double Roots in Degenerate Cases (I)
Martínez-González, Alejandro	Universidad Autónoma De San Luis Potosí
Mendez-Barrios, Cesar Fernando	Universidad Autónoma De San Luis Potosí
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Time-invariant systems Abstract: This paper addresses the classification of multiple critical roots of dynamical continuous linear time-invariant systems including two constant delays in their mathematical representation. By considering the associated Weierstrass polynomial and its algebraic properties, we investigate the splitting behavior of such critical roots when the delays are subject to small variations. Some degenerate cases are also considered. The effectiveness of the proposed approach is illustrated through several numerical examples.

VI122-03
Advances in Linear Systems	Regular Session
Chair: Hauksdottir, Anna Soffia	Univ of Iceland
Co-Chair: Menini, Laura	University of Rome Tor Vergata
Paper VI122-03.1
PDF · Video · Dual Lattices for Non-Strictly Proper Systems
Padula, Fabrizio	Curtin University
Ntogramatzidis, Lorenzo	Curtin University
Loxton, Ryan	Curtin University
Keywords: Linear multivariable systems, Structural properties Abstract: This paper investigates the dual lattice structures of self-bounded and self-hidden subspaces of linear time-invariant systems arising in the solution of disturbance decoupling, regulator and unknown input observation problems. The case that we are addressing in this paper is the one where the algebraic feedthrough matrices are allowed to be nonzero. We show that, in this general case, the additional constraints that need to be taken into account for the solution of the aforementioned control/estimation problems are no longer simple subspace inclusions as in the strictly proper case. As a consequence, mathematical apparatus underpinning the structure of the dual lattices of self bounded and self hidden subspaces in this more general framework becomes more challenging and richer.
Paper VI122-03.2
PDF · Video · Phase Analysis for Discrete-Time LTI Multivariable Systems
Mao, Xin	Hong Kong University of Science and Technology
Chen, Wei	Peking University
Qiu, Li	Hong Kong Univ. of Sci. & Tech
Keywords: Linear multivariable systems, Uncertainty descriptions, Robustness analysis Abstract: In contrast to the well-developed gain analysis for multi-input-multi-output (MIMO) linear time-invariant (LTI) systems, the research on the phase analysis does not share the same status. In this paper, we introduce the phase response of a class of discrete-time (DT) LTI multivariable system by exploiting a definition of matrix phases based on the numerical range. Half-sectorial transfer matrices are defined, which can generalize the positive real and negative imaginary systems. A sectored real lemma is obtained to characterize the phase information of a half-sectorial system from a state-space realization. Motivated by finding a phasic counterpart to the small gain theorem, we develop a small phase theorem for the internal stability of closed-loop systems.
Paper VI122-03.3
PDF · Video · Numerical Pitfalls in Q-Design
Kjellqvist, Olle	Lund University
Troeng, Olof	Lund University
Keywords: Linear systems, Convex optimization, Robust control (linear case) Abstract: Q-design is a powerful method for designing approximately optimal LTI controllers and assessing the achievable control performance. Unfortunately, numerical issues are often encountered in Q-design which limits its applicability. This paper warns about two numerical pitfalls in Q-design when using H 2 norm penalties and Laguerre-type basis functions.
Paper VI122-03.4
PDF · Video · Resilient Reachability for Linear Systems
Bouvier, Jean-Baptiste	University of Illinois at Urbana-Champaign
Ornik, Melkior	Univ. of Illinois at Urbana-Champaign
Keywords: Linear systems, Fault-tolerant, Robust control (linear case) Abstract: A fault-tolerant system is able to reach its goal even when some of its components are malfunctioning. This paper examines tolerance to a specific type of malfunction: the loss of control authority over actuators. Namely, we investigate whether the desired target set for a linear system remains reachable under any undesirable input. Contrary to robust control, we assume that the undesirable inputs can be observed in real time, and subsequently allow the control inputs to depend on these undesirable inputs. Building on previous work on reachability with undesirable inputs, this paper develops a reachability condition for linear systems, and obtains a formula that describes reachability of the goal set for driftless linear systems by computing the minimum of a concave-convex objective function. From this formulation we establish two novel sufficient conditions for resilient reachability.
Paper VI122-03.5
PDF · Video · Unimodular Completion for Computation of Fractionally Flat Outputs for Linear Fractionally Flat Systems
Rammal, Rim	University of Bordeaux
Airimitoaie, Tudor-Bogdan	Univ. Bordeaux
Melchior, Pierre	Université De Bordeaux - Bordeaux INP/ENSEIRB-MATMECA
Cazaurang, Franck	Univ. Bordeaux I
Keywords: Linear systems, Fractional systems, Polynomial methods Abstract: The current paper presents a method for the computation of fractionally flat outputs for linear fractionally flat systems based on the notion of unimodular completion. This calculation method, which already exists for integer order non-linear flat systems, is extended for the class of fractionally linear flat systems by employing some fractional calculation properties. Two examples are used to validate the proposed extension.
Paper VI122-03.6
PDF · Video · Feedback Stabilization: The Algebraic View
Szabo, Zoltan	MTA SZTAKI
Bokor, Jozsef	Hungarian Academy of Sciences
Keywords: Linear systems, Infinite-dimensional systems, Structural properties Abstract: Based on an abstract algebraic setting we provide an elementary derivation of the Youla-Kucera parametrization of stabilizing controllers and also an alternative, coordinate free, approach of the problem. For this latter case, in contrast to the Youla-Kucera approach, the parameter set is not universal but its elements can be generated by a universal algorithm. We also emphasise the natural continuity property of this parametrization compared to the Youla-Kucera case. Extending the framework to the LFT loops we show by using elementary tools that every controller which stabilizes the interior loop of the generalized plant also stabilizes the LFT loop.
Paper VI122-03.7
PDF · Video · Parallel-Triggered Observer-Based Output Feedback Stabilization of Linear Systems
Wu, Zhiying	Department of Automation, University of Science and Technology O
Ren, Wei	KTH Royal Institute of Technology
Xiong, Junlin	University of Science and Technology of China
Xie, Min	City University of Hong Kong
Keywords: Linear systems, Observer design, Time-invariant systems Abstract: The parallel-triggered stabilization problem is investigated for linear systems in this paper. By using both the relative and absolute errors, a continuous parallel-triggered scheme is proposed. The proposed parallel-triggered scheme reduces the number of transmitted signals as well as maintains control performance. Under the proposed scheme, Zeno behavior can be excluded. Based on Lyapunov theory, sufficient conditions are established for the existence of state feedback controller and the observer-based controller. Then, a co-design approach is developed to obtain both weighting matrix of the triggered scheme and controller gain. Finally, the superiority of the proposed scheme is illustrated by a numerical example.
Paper VI122-03.8
PDF · Video · Algebraic Tests for the Asymptotic Stability of Parametric Linear Systems
Menini, Laura	University of Rome Tor Vergata
Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Tornambe, Antonio	Univ. Di Roma Tor Vergata
Keywords: Linear systems, Polynomial methods, Robust control (linear case) Abstract: In this paper, algebraic tests are proposed to establish asymptotic stability of parametric linear systems assuming that the parameters lie in a given variety. In particular, by using tools borrowed from algebraic geometry, necessary and sufficient condition are proposed to test whether a continuous-time or a discrete-time linear parametric system is asymptotically stable for all the specializations belonging to a given variety. Both the cases of zero dimensional and non-zero dimensional varieties are considered.
Paper VI122-03.9
PDF · Video · A Design Method of High Order Repetitive Controllers
Guo, Hai-jiao	Tohoku Gakuin University
Otomo, Kazuki	Tohoku Gakuin University
Ishihara, Tadashi	Fukushima University
Keywords: Linear systems, Robust control (linear case), Disturbance rejection (linear case) Abstract: It turns out that higher-order RC is useful for improving the robustness of the entire control system, and its importance is only increasing. In this paper, we propose a new high-order RC design method. The proposed high-order RC design method includes more design parameters than the same order conventional high-order RC, which increases design flexibility. Further improvement of robustness can be expected. It will also prove useful for improving time response. Further, it is possible to suppress a disturbance having a frequency different from the frequency of the target periodic signal. This is not possible with conventional high-order RC.
Paper VI122-03.10
PDF · Video · On the Reachable Set of Uncertain Closed Loop Discrete-Time Linear Systems
Meslem, Nacim	INP De Grenoble
Dang, Thao	VERIMAG
Keywords: Linear systems, Robust estimation Abstract: This work tackles the reachability problem of uncertain discrete-time linear systems controlled by estimated state feedback regulators. First an augmented system is considered in order to include the effect of the estimation error on the behavior of the closed loop system. Then, based on interval analysis, an interval predictor is proposed to compute tight trajectory tubes that contain in a guaranteed way the actual state trajectory of the augmented system. Moreover, under the standard controllability and observability assumptions of linear systems, the convergence of the width of these trajectory tubes is shown.
Paper VI122-03.11
PDF · Video · Security of Control Systems: Prevention of Aging Attacks by Means of Convex Robust Simulation Forecasts
Escudero, Cédric	Univ. Grenoble Alpes, CNRS, Grenoble INP Univ. Grenoble Alpes, G
Massioni, Paolo	INSA De Lyon
Scorletti, Gerard	Ecole Centrale De Lyon
Zamai, Eric	Institut National Polytechnique De Grenoble
Keywords: Linear systems, Supervision and testing, Lyapunov methods Abstract: Aging attacks are a class of attacks targeting closed-loop control systems connected to a network. Such attacks consist in slightly modifying the control signals to increase the wear and tear of the physical system while maintaining the delivered service. In this paper, we exploit the technique of robust simulation of linear systems for forecasting and preventing these attacks by means of convex optimization. Besides, this technique allows the computation of the time at which the normal aging is not guaranteed anymore for a given control input set. The paper end highlights an example application upon an electrical machine.
Paper VI122-03.12
PDF · Video · Proving Routh's Theorem Using the Euclidean Algorithm and Cauchy's Theorem
Hauksdottir, Anna Soffia	Univ of Iceland
Sigurdsson, Sven Th.	Univ of Iceland
Keywords: Linear systems, Time-invariant systems Abstract: This paper presents a proof of Routh's theorem for polynomials with real coefficients, determining the number of roots in the right half plane (RHP). The proof exploits the relationship of the Routh array to the Euclidean algorithm and applies Cauchy's theorem in an analogous way to that of applying the Nyquist criterion to investigate the stability of a control system. While a number of papers have been published over the years with different proofs of Routh's stability criterion or Routh's theorem, the aim in this paper is to present a proof that may offer most insight to undergraduate students of engineering. Routh's theorem and his array are introduced without any proof in most undergraduate texts on control theory, whereas the Nyquist criterion is typically treated quite extensively in such texts. As well as presenting a proof for the regular case when all the coefficients in the first column of the Routh array are non-zero, analogous proofs are given for the singular cases when some of the leading coefficients in a row, or the coefficients of the entire row, become zero. In the first case, these result in a statement on the number of roots in the RHP, more explicit than those typically presented in papers on Routh's theorem. In the second case, the only case where there may be roots on the imaginary axis, use is made of the modified array introduced by Routh, often referred to as the Q-method, to determine the number of such roots, differentiating between simple and multiple roots. One can thus distinguish between exponential stability, marginal stability and polynomial instability, when there are no roots in the RHP, with these results.
Paper VI122-03.13
PDF · Video · Simultaneous Update of Controller and Model by Using Virtual Internal Model Tuning
Ikezaki, Taichi	The University of Electro-Communications
Kaneko, Osamu	The University of Electro-Communications
Keywords: Linear systems, Time-invariant systems Abstract: In this paper, we consider data-driven approach to the simultaneous attainment of a controller and a model. Here, we utilize Virtual Internal Model Tuning (VIMT), which is proposed by the same authors, to update a controller with a virtual internal model. We clarify that the VIMT is effective for not only the update of a controller but also the attainment of the plant model so as to reflect a given tracking specification.
Paper VI122-03.14
PDF · Video · An Assumption-Free Theorem on Discrete-Time Positive Real Systems
Branford, Edward Hugh	University of Exeter
Hughes, Timothy H.	University of Exeter
Keywords: Linear systems, Time-invariant systems, Linear multivariable systems Abstract: The discrete-time positive real lemma is examined and the assumptions of controllability and observability are removed. An intermediate theorem is proved that removes only the assumption of controllability. This work is intended to be the counterpart - and is inspired by - recent work on the continuous-time positive real lemma, and does not assume asymptotic stability unlike the recent results of Ferrante and Ntogramatzidis (2017).
Paper VI122-03.15
PDF · Video · A Geometric Description of the Set of Stabilizing PID Controllers
Gu, Keqin	Southern Illinois Univ Edwardsville
Ma, Qian	Nanjing University of Science and Technology
Zhou, Huiqing	Southern Illinois University Edwardsville
Mahzoon, Salma	Southern Illinois University
Yang, Xingzi	University of Texas at San Antonio
Keywords: Linear systems, Time-invariant systems, Parametric optimization Abstract: This article presents a geometric description of the set of stabilizing PID controllers. The three-dimensional parameter space is partitioned by the stability crossing surface into regions such that the number of characteristic roots on the right half-plane (RHP) remains constant within each region. The set of stabilizing PID parameters consists those regions with no RHP root. The stability crossing surface is a ruled surface, and it is completely determined by a curve known as the discriminant. The discriminant may be divided into sectors between its cusps, and each sector corresponds to a positive patch and negative patch. The stability crossing surface is composed of these patches. The projection of the boundary of these patches to the horizontal plane allows us to partition this plane into regions such that there are a fixed number of patches in each such region. The regions are further divided such that these patches are in the same vertical order within each region. By identifying the crossing directions, we may determine the number of RHP characteristic roots between any two patches.
Paper VI122-03.16
PDF · Video · Covert Attack Detection Based on Hi/H∞ Optimization for Cyber-Physical Systems
Qin, Jiao	Shandong University of Science and Technology
Zhong, Maiying	Shandong University of Science and Technology
Liu, Yang	Shandong University of Science and Technology
Wang, Xianghua	Shandong University of Science and Technology
Zhou, Donghua	Shandong Univ. of Science and Technology
Keywords: Linear systems, Time-varying systems Abstract: In this paper, a new detection scheme is proposed to detect covert attack in the framework of Hi/H∞ index optimization for cyber-physical system (CPS) which is modeled as a linear discrete time-varying (LDTV) system. First, a random modulation matrix that the attacker cannot know is inserted into the path of the control variables to destroy the stealthiness of covert attacks. Second, a detection filter is constructed which transforms the detection problem into an H-/H∞ or H∞/H∞ index optimization problem. The optimal solution is obtained by solving the Riccati equation. Third, a decision making mechanism is presented to trigger an alarm and further determine whether the cause of alarm is a covert attack or a fault. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.
Paper VI122-03.17
PDF · Video · Interval Observer for Discrete Periodic Time-Varying Descriptor Systems
Xu, Feng	Tsinghua Univerisity
Yang, Songlin	Graduate School at Shenzhen, Tsinghua University
Wang, Xueqian	Tsinghua University
Wang, Ye	The University of Melbourne
Keywords: Linear systems, Time-varying systems, Observers for linear systems Abstract: This paper designs an interval observer for discrete linear periodic time-varying descriptor (LPTVD) systems. First, the discrete LPTVD system is transformed into a linear time-invariant (LTI) descriptor system by using a stacked form of periodic systems. Then, in order to reduce complexity, we further transform the equivalent LTI descriptor system into a minimal-order form. Finally, by using the obtained minimal-order implementation of the discrete LPTVD system, an interval observer is designed to estimate the system state interval at each step. At the end, an example is used to illustrate the effectiveness of the proposed results.
Paper VI122-03.18
PDF · Video · Two-Degree-Of-Freedom Design between Intersample and Sample Responses: Closed-Loop State-Space Approach Based on Steady-State Characteristic
Yasui, Ryota	University of Hyogo
Kawaguchi, Natsuki	University of Hyogo
Sato, Takao	University of Hyogo
Araki, Nozomu	University of Hyogo
Konishi, Yasuo	University of Hyogo
Keywords: Linear systems, Controller constraints and structure, Digital implementation Abstract: A dual-rate sampled-data control system is designed, where the sampling interval of measured signals is twice as long as the holding interval of a control input. In the proposed method, a control law is extended based on the null-space, and intersample ripples are eliminated without changing the sampled output trajectory in the steady state. As the conventional open-loop design method based on the null-space, there are a polynomial approach and a state-space approach. However, the conventional methods are ineffective for unstable systems and are also unavailable when the null-space of the plant model is only the zero vector because the controlled plant is not arbitrary selectable. On the other hand, the proposed method is effective for unstable systems as well as the stable system even when the null-space of the plant model is only the zero vector because the proposed controller is designed based on the closed-loop system.
Paper VI122-03.19
PDF · Video · The AAA Framework for Modeling Linear Dynamical Systems with Quadratic Output
Gosea, Ion Victor	Max Planck Institute for Dynamics of Complex Technical Systems
Gugercin, Serkan	Virginia Tech
Keywords: Model reduction, Complex systems, Time-invariant systems Abstract: We consider linear dynamical systems with quadratic output. We first define the two transfer functions, a single-variable and a multivariate one, that fully describe the dynamics of these special nonlinear systems. Then, using the samples of these two transfer functions, we extend the AAA algorithm to model linear systems with quadratic output from data.

VI122-04
Observer Design and Output Feedback (Linear Systems)	Regular Session
Chair: Krokavec, Dusan	Technical University of Kosice
Co-Chair: Bullinger, Eric	Otto-von-Guericke-Universität Magdeburg
Paper VI122-04.1
PDF · Video · New Passivity Conditions for Linear Time Varying Output Feedback Systems
Weiss, Haim M.	Rafael
Keywords: Adaptive control, Output feedback control (linear case), Passivity-based control Abstract: The paper presents new passivity conditions for square linear time varying (LTV) output feedback systems. The new conditions enable the formulation of a new simple test for almost strict passivity, which is necessary for the closed loop to be output strictly passive. The new test requires the solution of an algebraic Riccati equation in the linear time invariant (LTI) case and the solution of a forward differential Riccati equation in the LTV case. The proposed test simplifies the synthesis and design of output strictly passive systems. The examples discussed in the paper demonstrate the efficiency of the test.
Paper VI122-04.2
PDF · Video · Skyhook Controller Design Using Bilinear Matrix Inequalities
Canevi, Mehmet	Istanbul Technical University
Söylemez, Mehmet Turan	Istanbul Technical University
Keywords: Disturbance rejection (linear case), Robust control, Output feedback control (linear case) Abstract: This paper focuses on the design of the so called sky-hook controller, which is used to isolate vibrations on suspension systems. The design of the sky-hook controller is posed as a static output feedback control problem, in fact the sky-hook controller is a single input-single output controller. The design of the sky-hook controller is posed using the generalized plant using the sparse structure of the sky-hook controller. It is pointed out that, root-locus plot for visualization and well known stability analysis methods can be used to acquire a stability interval for the sky-hook controller. Via gridding the stability interval, it has been shown that there may exist convex sub intervals and posing a BMI problem with the corresponding D region, it is possible to solve the skyhook design problem, regarding H2 or H∞ optimality. The sky-hook design is simulated using two different suspension systems and an experiment is carried out on a system for three different road profiles. It has been sown that using a sky-hook controller instead of an LQR controller is plausible, since the required sensor amount is reduced, therefore the cost is reduced and the performance is almost equal for both controllers.
Paper VI122-04.3
PDF · Video · Anisotropy-Based Finite-Horizon Estimation with Packet Dropouts
Kustov, Arkadiy	Institute of Control Sciences, Russian Academy of Sciences
Yurchenkov, Alexander	V. A. Trapeznikov Institute of Control Sciences of the Russian A
Keywords: Observers for linear systems, Time-varying systems, Fault-tolerant Abstract: In this paper, the estimation problem is studied for a class of linear discrete time-varying system with packet dropout in the framework of anisotropy-based theory. The extended vector of fragment of the disturbance sequence is from the set of random vectors with bounded anisotropy. The packet dropout effect is considered to be random and described by a binary switching sequence with Bernoulli distribution. The input-to-error dynamics is obtained for multiplicative noise system with mutually independent matrix noise and input disturbance. By using anisotropy-based approach, the estimation problem is reduced to optimization problem with convex constraints. The developed method provides the (sub)optimal estimator ensuring the boundedness of anisotropic norm for input-to-output error system. Numerical example is provided to demonstrate efficiency of proposed approach.
Paper VI122-04.4
PDF · Video · Minimal Control of Constrained, Partially Controllable & Observable Linear Systems
Mora Gil, Edwin Camilo	Technische Universität Darmstadt
Steinke, Florian	Max-Planck-Inst. Bio. Cybernetics
Keywords: Output feedback control (linear case), Controller constraints and structure, Convex optimization Abstract: We aim at developing control strategies for constrained linear systems without requiring full system controllability and observability. Given a fixed, potentially small set of actuators and sensors, we first design a static affine-linear output feedback controller that guarantees both the asymptotic stability of the closed-loop system and the adherence of the steady state to a set of linear inequality constraints in the presence of interval-bounded, constant inputs. Subsequently, the derived method is used to find the minimum number of actuators and sensors with which one can fulfill such partial controllability and observability requirements. The approach is applied to electrical power networks modeled as a set of linearly coupled oscillators.
Paper VI122-04.5
PDF · Video · Partial Pole Placement Using Static Output Feedback
Pusch, Manuel	German Aerospace Center
Theis, Julian	Hamburg University of Technology
Ossmann, Daniel	Munich University of Applied Sciences
Keywords: Output feedback control (linear case), Linear multivariable systems, Decoupling problems Abstract: For many dynamical systems it is required to specifically shift individual poles, especially when these poles are lightly damped or even unstable. To achieve that, a preferably large number of effectors and measurements are installed leading to multivariable control problems. In this paper, a novel control approach is presented for placing either a single pole or a conjugate complex pole pair at a predefined location using rank-one static output feedback. Rank-one feedback can be interpreted as blending inputs and outputs to define a single input and single output loop with a desirable root locus along which the pole is moved. The corresponding controller synthesis is reduced to an unconstrained optimization problem in a single variable that aims at minimizing the feedback gain. Although the approach is derived for a single pole or conjugate complex pole pair, it is easily extended to multiple poles. To this end, a repeated design and superposition of rank-one feedback gains is proposed. It is further shown how residual system dynamics as well as subsequently designed gains can be efficiently decoupled from each other in order to avoid undesired interactions and spillover effects. The effectiveness of the proposed control approach is demonstrated by means of a numerical example.
Paper VI122-04.6
PDF · Video · Output Control of Linear Time-Invariant Systems under Input and Output Disturbances
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Gushchin, Pavel	Gubkin Russian State University of Oil and Gas
Nekhoroshikh, Artem	ITMO University
Peregudin, Alexey	ITMO University
Keywords: Output feedback control (linear case), Robust control (linear case) Abstract: The novel control algorithm for linear time-invariant systems under disturbances and measurement noises is proposed. The designed control law, based on the noise and disturbance estimation, ensures the accuracy in steady state depending on the disturbance, only one component of noise vector and its first derivatives. Sufficient conditions in terms of linear matrix inequality (LMI) providing stability of the closed-loop system are obtained. The simulations show efficiency of the proposed method compared with existing ones.
Paper VI122-04.7
PDF · Video · Robust Static Output Feedback Stabilization of Continuous-Time Linear Systems Via Enhanced LMI Conditions
Gritli, Hassène	Institut Supérieur Des Technologies De l'Information Et De La Co
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Belghith, Safya	ENIT
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Output feedback control (linear case), Robust linear matrix inequalities, Robust controller synthesis Abstract: This paper addresses the problem of Static Output Feedback (SOF) stabilization for continuous-time linear systems subject to norm-bounded parameter uncertainties. Usually this issue leads to the feasibility of a Bilinear Matrix Inequality (BMI), which is difficult to linearize to get non conservative Linear matrix inequality (LMI) conditions. In this paper, by means of some technical lemmas, we transform the BMI into a new LMI with a line search over two scalar variables. The obtained LMI conditions are less conservative than those existing in the literature. Numerical evaluations are presented to show the superiority of the proposed method.
Paper VI122-04.8
PDF · Video · On Real Stable Pole Placement for Structured Systems Using Sturm and Sturm-Habicht Sequences
Röbenack, Klaus	TU Dresden
Voßwinkel, Rick	IAV GmbH
Keywords: Polynomial methods, Time-invariant systems, Output feedback control (linear case) Abstract: During the last decades, many approaches for controller design of linear time-invariant systems have been developed. However, if a prescribed controller structure is desired, controller design may become more complicated. Typical examples include PID controllers and static output feedback. We propose a method for purely real pole or eigenvalue placement. Our approach is based on the closed-loop characteristic polynomial whose coefficients are polynomials in the controller parameters. We employ quantifier elimination to verify the existence conditions and to compute the controller gain.
Paper VI122-04.9
PDF · Video · Reduced-Order Observers for Linear Metzlerian Systems
Krokavec, Dusan	Technical University of Kosice
Filasova, Anna	Technical University of Kosice
Keywords: Positive systems, Observer design, Linear multivariable systems Abstract: For linear time-invariant Metzlerian systems this paper proposes an original approach required to reflect structural system constraints and positiveness in solving the problem of reduced-order Metzlerian observer design. Three forms of design conditions are proposed, all of them exploiting a set of common system parameter constraint representation in the form of linear matrix inequalities, while a systematic H∞ norm performance strategy is focused on to guarantee the observer asymptotic stability. To serve as a potential estimator of the plant state vector, the impact of strictness and non strictness Metzler matrix structure in design is clarified and reflected in adaptation of the design conditions. A numerical example is included to assess the feasibility of the technique and its applicability.
Paper VI122-04.10
PDF · Video · An LMI-Based Algorithm for Static Output-Feedback Stabilization of Continuous-Time Positive Polytopic Linear Systems
Arnanz, Alvaro	University of Campinas
Spagolla, Amanda	University of Campinas
Morais, Cecília F.	University of Campinas
Oliveira, Ricardo C. L. F.	University of Campinas
Peres, Pedro L. D.	Univ. of Campinas
Keywords: Positive systems, Output feedback control (linear case), Robust linear matrix inequalities Abstract: This paper presents a new technique to design static output-feedback controllers for continuous-time positive uncertain linear systems. The design is performed through an iterative algorithm based on parameter-dependent linear matrix inequality conditions, solved by means of relaxations, with local convergence guaranteed. A qualified feasible solution provides a stabilizing output-feedback controller that also assures the positivity of the closed-loop system. The main advantage of the proposed methodology is that the control gain is handled directly as an optimization variable, that is, no change of variables is needed to recover the gain and no particular structure (e.g., diagonal) is imposed on the Lyapunov or slack variable matrix to guarantee closed-loop positivity. This particular feature also facilitates the design of decentralized or element-wise bounded gains, as illustrated by numerical experiments.
Paper VI122-04.11
PDF · Video · Event-Triggered Tracking Control: A Discrete-Time Approach
Sbarbaro, Daniel G.	Universidad De Concepción
Gomes Da Silva Jr, Joao Manoel	Universidade Federal Do Rio Grande Do Sul (UFRGS)
Moreira, Luciano Gonçalves	IFSUL
Keywords: Regulation (linear case), Disturbance rejection (linear case), Observers for linear systems Abstract: In this work, the problem of designing event-triggered control strategies for disturbance rejection and reference tracking for discrete-time linear systems is addressed. Based on the Lyapunov theory, LMI-based conditions for the guarantee of perfect reference tracking/disturbance rejection under the proposed event-trigger strategy are derived. Furthermore, to avoid that the ETC strategy degenerates to a periodic one (in the case of non constant signals), a practical tracking/rejection solution considering a trade-off between the reduction of the control updates and the tolerance to a small error in steady state is proposed. The conditions are then casted in LMI-based optimization problems to compute the triggering functions aiming at reducing the control updates while ensuring the perfect or the practical tracking.
Paper VI122-04.12
PDF · Video · Fast Interval Estimation for Discrete-Time Systems Based on Fixed-Time Convergence
Wang, Zhenhua	Harbin Institute of Technology
Dinh, Thach Ngoc	Conservatoire National Des Arts Et Métiers
Zhang, Qinghua	INRIA
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Shen, Yi	Harbin Institute of Technology
Keywords: Time-invariant systems, Observer design, Robust estimation Abstract: This paper studies interval estimation for discrete-time linear systems with unknown but bounded disturbance and measurement noise. Inspired by the well-known parity space approach in the field of fault diagnosis, we propose a fast interval estimation method with fixed-time convergence property. A singular value decomposition-based parameter optimization algorithm is used to attenuate the effect of uncertainties on the estimation error. Comparison study illustrates the superiority of the proposed method over existing technique.
Paper VI122-04.13
PDF · Video · Homogeneous Observer Design for Linear MIMO Systems
Zimenko, Konstantin	ITMO University
Polyakov, Andrey	INRIA Lille Nord-Europe
Efimov, Denis	Inria
Kremlev, Artem	ITMO University
Keywords: Nonlinear observers and filter design, Observers for linear systems, Observer design Abstract: The paper is devoted to the problem of state observation (particularly, in finite time) of linear MIMO systems. The presented nonlinear observer does not require system transformation to a canonical form and guarantees finite-time (asymptotic with a fixed-time attraction of any compact set containing the origin) stability of observation error equation if homogeneity degree is negative (positive). The proposed observer is robust in input-to-state sense with respect to disturbances and measurement noises. Performance of the observer is illustrated by a numerical example.

VI122-05
Robust Control (Linear Case)	Regular Session
Chair: Streif, Stefan	Technische Universität Chemnitz
Co-Chair: Taiwo, Oluwafemi	Obafemi Awolowo University, Ile-Ife, Nigeria
Paper VI122-05.1
PDF · Video · Towards a Simple Sampled-Data Control Law for Stably Invertible Linear Systems
Sanchez, Claudia	Universidad Tecnica Federico Santa Maria
Goodwin, Graham C.	University of Newcastle
Yuz, Juan I.	Universidad Técnica Federico Santa María
Seron, Maria	The Univ of Newcastle
Carrasco, Diego S.	University of Newcastle
Keywords: Analytic design, Robust control, Robustness analysis Abstract: A new high gain control law is proposed for stably invertible linear systems. The continuous-time case is first studied to set ideas. The extension to the sampled-data case is made difficult by the presence of sampling zeros. For continuous-time systems having relative degree greater than or equal to two, these zeros converge, as the sampling rate approaches zero, to either marginally stable or unstable locations. A methodology which specifically addresses the sampling zero issue is developed. The methodology uses an approximate model which includes, when appropriate, the asymptotic sampling zeros. The core idea is supported by simulation studies. Also, a preliminary theoretical analysis is provided for degree two, showing that the design based on the approximate model stabilizes the true system for the continuous and sampled-data cases.
Paper VI122-05.2
PDF · Video · L_2-Gain Performance Analysis for Discrete-Time Systems with Input Saturation: An LPV Approach
Nguyen, Hoai-Nam	IFP Energies Nouvelles
Keywords: Disturbance rejection (linear case), Constrained control, Convex optimization Abstract: In this paper, we consider the problem of estimating the L_2-gain under a given feedback law for linear discrete-time systems subject to actuator saturation. The basic idea is to use the linear parameter varying system framework to model the saturation nonlinearity. It is shown that the conditions can be expressed as a set of linear matrix inequalities. Furthermore, it is proved that the conditions are guaranteed to be less conservative than several existing solutions in the literature. One numerical example is presented to illustrate the effectiveness of the proposed method.
Paper VI122-05.3
PDF · Video · Feedback Control in the Presence of Input and Output Disturbances
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Fridman, Emilia	Tel-Aviv Univ
Keywords: Disturbance rejection (linear case), Decoupling problems Abstract: A novel control law is proposed to attenuate the influence of input and output disturbances for systems with vector output and sector bounded nonlinearities. The control law is based on estimation of the disturbance in the output. Differently from the existing results, the ultimate bound of the closed-loop system depends on only one component of the output disturbance vector (as well as, on the input disturbance). The results are formulated in terms of LMIs. The efficiency and advantages of the results over the existing methods are demonstrated by numerical examples.
Paper VI122-05.4
PDF · Video · On the Selection of Lambda in Lambda Tuning for PI(D) Controllers
Veronesi, Massimiliano	Yokogawa Italy
Visioli, Antonio	University of Brescia
Keywords: Process control Abstract: Lambda tuning is frequently employed for PI(D) controllers in the process industry because of its simplicity and intuitiveness for the user. In this paper we analyze the fundamental choice of the tuning parameter lambda, that is, of the desired closed-loop time constant, by considering different trade-offs that can be posed by the user in the controller design. In particular, we consider the trade-off between bandwidth and gain or phase margin and that between performance and maximum sensitivity. The achievement of a specified maximum sensitivity is also addressed. Simple analytical formulas are determined so that they can be used in order to provide an optimized tuning in different contexts.
Paper VI122-05.5
PDF · Video · The Generalized Internal Model Control Method
Taiwo, Oluwafemi	Obafemi Awolowo University, Ile-Ife, Nigeria
Fasiku, Damilola	Obafemi Awolowo University
Keywords: Process control, Linear multivariable systems, Robust control (linear case) Abstract: The work deals with a generalization of the internal model control method whereby the original process model is suitably simplified to facilitate direct parameterization of feedback controllers. Here, the m/n moment approximant is adopted as the simplified model. The parameterized feedback controller contains a filter that can the tuned for closed loop system acceptable characteristics. The method facilitates cheap computation of controllers based on desired performance and user’s preference.
Paper VI122-05.6
PDF · Video · H-Infinity Control Tunning to Guarantee the Output Performance of LTI Second-Order Systems
Verdés Kairuz, Ramón Imad	Instituto Politécnico Nacional
Aguilar, Luis T.	Instituto Politecnico Nacional
Orlov, Yury	CICESE
Keywords: Robust control (linear case), Analytic design, Time-invariant systems Abstract: Settling time and input/output specifications are general for optimal operation of control systems and for their avoiding irreversible damages. We present an H-infinity control design whose parameters are tuned, not only to achieve the robustness property but also to meet the step time response characteristic of a linear time-invariant second-order system. We present explicit formulas in terms of the settling time and overshoot response. Simulation and experimental evidence corroborate the results.
Paper VI122-05.7
PDF · Video · Robust Anticipative Controller Design with Application to a High Dynamic Engine Testbed
Airimitoaie, Tudor-Bogdan	Univ. Bordeaux
Lanusse, Patrick	Bordeaux INP - Université De Bordeaux
Achnib, Asma	University of Gabes, National Engineering School of Gabes, Tunis
Keywords: Robust control (linear case), Controller constraints and structure, Parametric optimization Abstract: This paper presents a robust controller design method for reference tracking in multi-input multi-output preview systems. In the context of preview systems, it is supposed that future values of the reference signal are available a number of time steps ahead. The objective of the controller being to minimize a quadratic error between the reference and the system's output, the optimal solution needs to take into account the known future values of the reference. Furthermore, it is desired to maintain the control signal at an acceptable level. The feedforward preview is obtained by solving a mixed L_2/L_infty optimisation, where the L_infty constraint is used to reduce the level of the control. The proposed solution combines a robust feedback controller with a feedforward preview filter. The feedback controller's purpose is to assure robustness of the closed-loop system to model uncertainties and is not detailed here. The focus of this paper is on the design of the feedforward preview filter taking into account that a feedback controller is present. The proposed solution is validated in simulation on a high dynamic engine testbed.
Paper VI122-05.8
PDF · Video · Prototypical Description and Controller Design for a Set of Systems Using V-Gap Based Clustering
Munser, Lukas	Technische Universität Chemnitz
Hempel, Arne-Jens	Technische Universität Chemnitz
Devadze, Grigory	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Robust control (linear case), Linear multivariable systems, Time-invariant systems Abstract: We present an approach to design stabilizing controllers for a set of linear systems without restrictions regarding their modeling order. To this end, the systems are treated as abstract objects in the space of the v-gap metric. Via a cluster analysis the set of systems is split into v-gap similar clusters which are treated separately. For this purpose we provide an algorithm that constructs an explicit prototype system by generalizing the information of a given set of systems. Applying this algorithm to each cluster a set of prototype systems is obtained. Given these prototypes we design controllers in such a way that all systems assigned to a cluster will be stabilized by a corresponding controller. The approach is demonstrated for a set of 80 linear systems.
Paper VI122-05.9
PDF · Video · Sensor Blending and Control Allocation for Non-Square Linear Systems to Achieve Negative Imaginary Dynamics
Bhowmick, Parijat	University of Manchester
Lanzon, Alexander	University of Manchester
Keywords: Robust control (linear case), Output feedback control (linear case), Decentralized control Abstract: This paper deals with the design of static pre- and post- compensators to transform stable, non-square LTI systems into the class of strongly strict negative imaginary systems. The pre-compensator plays the role of a control allocator while the post-compensator does sensor blending in order to make a non-square system square along with satisfying the strongly strict negative imaginary property. A specific structure of the post-compensator is also given that guarantees a feasible solution of the LMI conditions when applied to systems with number of outputs greater than or equal to number of inputs. The proposed pre- and post- compensators can also stabilize a non-square plant in closed-loop upon satisfying a particular DC-gain condition and furthermore, they can be utilized to develop a simple constant input tracking framework for non-square systems. The LMI-based design methodology offers a numerically tractable solution framework and hence the easy implementation of the proposed scheme in practical applications. Illustrative examples are provided throughout the paper to demonstrate the usefulness of the proposed results in widening the scope of the negative imaginary theory to non-square LTI systems (e.g. safety-critical systems having redundant sensors and actuators).

VI122-06
Structural Properties and Positive Systems	Regular Session
Chair: Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Co-Chair: Zattoni, Elena	Alma Mater Studiorum - University of Bologna
Paper VI122-06.1
PDF · Video · An Optimization Approach to Verifying and Synthesizing K-Cooperative Systems
Kousoulidis, Dimitris	University of Cambridge
Forni, Fulvio	University of Cambridge
Keywords: Positive systems, Robust control, Nonlinear cooperative control Abstract: Differential positivity and K-cooperativity, a special case of differential positivity, extend differential approaches to control to nonlinear systems with multiple equilibria, such as switches or multi-agent consensus. To apply this theory, we reframe conditions for strict K-cooperativity as an optimization problem. Geometrically, the conditions correspond to finding a cone that a set of linear operators leave invariant. Even though solving the optimization problem is hard, we combine the optimization perspective with the geometric intuition to construct a heuristic cone-finding algorithm centered around Linear Programming (LP). The algorithm we obtain is unique in that it modifies existing rays of a candidate cone instead of adding new ones. This enables us to also take a first step in tackling the synthesis problem for K-cooperative systems. We demonstrate our approach on some examples, including one in which we repurpose our algorithm to obtain a novel alternative tool for computing polyhedral Lyapunov functions of bounded complexity.
Paper VI122-06.2
PDF · Video · Robust Finite-Time Control of Impulsive Positive Systems under L1-Gain Performance
Hu, Mengjie	Yeungnam University
Park, Ju H.	Yeungnam University
Jung, Ho Youl	Yeungnam University
Keywords: Positive systems, Robustness analysis, Robust control (linear case) Abstract: This paper is concerned with robust finite-time L1-gain control problem for impulsive positive systems (IPSs). By adopting the average impulsive interval technique, sufficient conditions ensuring the finite-time boundedness of IPSs under L1-gain characterization are formulated. The design of a feedback controller is also addressed to make the closed-loop system be positive, finite-time bounded (FTB), and have L1-gain characterization. Results are presented in the form of linear programming (LP) inequalities. Finally, a numerical example is given to demonstrate the efficiency of the proposed design.
Paper VI122-06.3
PDF · Video · Model Matching Problems for Positive Systems
Conte, Giuseppe	Universita' Politecnica Delle Marche
Perdon, Anna Maria	Universita' Politecnica Delle Marche
Zattoni, Elena	Alma Mater Studiorum - University of Bologna
Keywords: Positive systems, Structural properties, Disturbance rejection (linear case) Abstract: The problem of compensating a given plant by means of a static compensator in such a way that, for any input, the output of the compensated system matches that of a given positive model, when both are initialized at 0, and its state evolves in the positive cone for positive initial conditions and inputs is considered. Under a mild structural assumption for the output-difference system between the plant and the model, a complete characterization of solvability of the problem in terms of necessary and sufficient conditions is obtained by means of structural geometric methods. Solvability conditions are practically checkable by algorithmic procedures and by solving a set of linear inequalities. The problem of asymptotic matching for any initial condition is then considered and solvability is characterized by necessary and sufficient conditions. A necessary condition that is practically checkable is given. Solvability by a dynamic compensator is also studied and a sufficient condition to characterize it is given
Paper VI122-06.4
PDF · Video · On Strongly Unimodal Third-Order SISO Linear Systems with Applications to Pharmacokinetics
Weller, Steven R.	University of Newcastle
Martin, Jennifer	University of Newcastle
Keywords: Positive systems, Time-invariant systems Abstract: This paper addresses the problem of characterizing external positivity (equivalently, non-negative impulse response) of third-order single-input, single-output (SISO) linear systems. We show how an exact, geometric solution to this problem follows by first identifying an equivalence between the impulse response of an externally positive system on the one hand, and the probability density function of a non-negative random variable on the other, then drawing on the characterization of matrix exponential distributions, defined as probability distributions for which the Laplace transform is a rational function. The results are then extended to the characterization of strongly unimodal systems, defined as systems in which input signals with a time-derivative that has at most one sign variation (namely, are pulse-like) are mapped to output signals with the same property. The results are applied to a third-order compartmental system arising in pharmacokinetics, in which the properties of non-negativity of the impulse response and the preservation of unimodality from drug adminstration (input) to compartmental drug concentration (output) are of clinical relevance.
Paper VI122-06.5
PDF · Video · A New Controllability Index Based on Hankel Singular Value
Yang, Shuang-Hua	Zhejiang University
Birk, Wolfgang	Luleå University of Technology
Cao, Yi	Zhejiang University
Keywords: Process control, Structural properties, Controller constraints and structure Abstract: This paper proposes a new controllability index based on the Hankel singular values (HSV) which is applicable for both single-input single-output (SISO) and multivariable processes. The new index quantifies the inherent performance limitation in terms of closed-loop response speed by associating it with the control effort, which is directly related to the inverse of the HSVs. It is also shown that for specific system there is a direct linear relationship between the inverse of the minimum Hankel singular value and desired closed loop pole locations. The controllability index is thereafter exemplified on several SISO examples systems to show some of its properties. Thereafter two well-known multivariable benchmark processes, quadruple tank and two-continuous-stirring-tank-reactor are used to show the effectiveness of the index. It is concluded that the index provides valuable insights to practitioners on the achievable performance of processes with actuator constraints, while being easy to use and requiring little computational effort.
Paper VI122-06.6
PDF · Video · A Generalized Minimum Phase Property for Finite-Dimensional Continuous-Time MIMO LTI Systems with Additive Disturbances
Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Pan, Zigang	N/A
Keywords: Structural properties, Linear multivariable systems, Adaptive control Abstract: In this paper, we further generalize the definition of the extended zero dynamics to finite-dimensional continuous-time MIMO LTI systems with additive disturbances; and then introduce the concept of minimum phase for this class of systems. We show that the extended zero dynamics is invariant under the application of dynamic extension to its input, and therefore, a minimum phase system remains minimum phase after a finite number of steps of dynamic extension. We further introduce the extended zero dynamics canonical form for square MIMO LTI systems with uniform vector relative degree. We prove that a system is minimum phase according to our definition if its zero dynamics is asymptotically stable. The converse of the statement holds if the system is stabilizable from the control input. The objective of this research is to solve the model reference robust adaptive control problem for finite-dimensional continuous-time square MIMO LTI systems that is minimum phase according to the generalized definition using an appropriately vectorized version of Pan and Basar (2000), and results here constitute important building blocks. In a subsequent paper, Ba ̧sar and Pan (2019), we further connect the dots: starting with a square MIMO LTI system that is minimum phase with respect to admissible initial conditions and admissible disturbance waveforms, we must obtain a true system representation that admits both the extended zero dynamics canonical form representation and the strict observer canonical form representation. Toward this end, we need to be able to extend the given system to one with uniform vector relative degree and with uniform observability indices without changing its minimum phase property, and this has been done in Basar and Pan (2019), fully resolving this issue.
Paper VI122-06.7
PDF · Video · Algebraic Certificates for the Structural Properties of Parametric Linear Systems
Menini, Laura	University of Rome Tor Vergata
Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Tornambe, Antonio	Univ. Di Roma Tor Vergata
Keywords: Structural properties, Linear systems, Time-invariant systems Abstract: In this paper, by exploiting the concept of polynomial greatest common divisor, some algebraic tests are proposed to certify the structural properties of both discrete-time and continuous-time linear systems. Furthermore, by exploiting the concept of parametric greatest common divisor, such results are extended to certify the structural properties of systems whose dynamical matrices depend polynomially on some parameters.
Paper VI122-06.8
PDF · Video · Fixed-Order Controller Synthesis for Monotonic Closed-Loop Responses: A Linear Programming Approach
Taghavian, Hamed	Royal Institute of Technology
Johansson, Mikael	Royal Institute of Technology
Keywords: Time-invariant systems, Positive systems, Linear systems Abstract: We consider the problem of synthesizing dynamic controllers to guarantee monotonic closed-loop step responses. Restricting our attention to controllers which yield positive closed-loop systems, we derive synthesis conditions that are linear in the controller parameters. A linear programming formulation that attempts to optimize the decay rate of the closed-loop system while ensuring asymptotic stability and monotonic step response is developed. An alternative approach which guarantees closed-loop stability and a near-monotonic response is also introduced. Several illustrative examples demonstrate the effectiveness of the approach.
Paper VI122-06.9
PDF · Video · Control Reconfiguration for Improved Performance Via Reverse-Engineering and Forward-Engineering
Shu, Han	Tsinghua University
Zhang, Xuan	Tsinghua-Berkeley Shenzhen Institute
Li, Na (Lina)	SEAS Harvard
Papachristodoulou, Antonis	Univ of Oxford
Keywords: Analytic design, Networked systems, Convex optimization Abstract: This paper presents a control redesign approach to improve the performance of a certain class of dynamical systems. Motivated by recent research on re-engineering cyber-physical systems, we propose a three-step control retrofit procedure. First, we reverse-engineer a dynamical system to dig out an optimization problem it actually solves. Second, we apply an augmented Lagrangian or a hat-x method to solve this optimization problem. Finally, by comparing the original and new dynamics, we obtain the implementation of the redesigned part (i.e., the extra dynamics). As a result, the convergence rate/speed or transient behavior of the given system can be improved while the system structure remains. To show the effectiveness of the proposed approach and its potential applications, we present two practical examples including Internet congestion control and distributed proportional-integral (PI) control.

VI122-07
Switched Linear Systems	Regular Session
Chair: Bajcinca, Naim	University of Kaiserslautern
Co-Chair: Peaucelle, Dimitri	LAAS-CNRS
Paper VI122-07.1
PDF · Video · Fault Detection for Switched Systems Based on Pole Assignment and Zonotopic Residual Evaluation
Zammali, Chaima	Conservatoire National Des Arts Et Métiers (CNAM), Cedric Lab
Wang, Zhenhua	Harbin Institute of Technology
Van Gorp, Jeremy	CNAM
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Keywords: Diagnosis, Observers for linear systems, Robust estimation Abstract: This paper considers fault detection problem for a class of discrete-time switched systems with actuator faults. Pole assignment technique and H_infty design are used to develop the fault sensitivity and the disturbance attenuation condition of the residual, respectively. The design conditions of the observer are given in terms of Linear Matrix Inequalities (LMIs). In addition, the disturbances and measurement noises are supposed to be unknown but bounded by zonotopes. A zonotopic method is then presented to evaluate the residual. A numerical example is performed to illustrate the effectiveness of the proposed method through a comparison with the results obtained without considering sensitivity and robustness analysis.
Paper VI122-07.2
PDF · Video · Estimation in Uncertain Switched Systems Using a Bank of Interval Observers: Local vs Glocal Approach
Rotondo, Damiano	Universitat Politecnica De Catalunya (UPC)
Efimov, Denis	Inria
Cristofaro, Andrea	Sapienza University of Rome
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Observers for linear systems, Robust estimation Abstract: This paper discusses some issues related with the design of a bank of interval observers for uncertain switched systems, in which several sources of uncertainty are considered: parametric uncertainties, unknown disturbances, measurement noise, and unknown switching signal. More specifically, this paper focuses on analyzing the interval estimation accuracy when changes of active mode induce non-positivity of the interval state estimation errors. In particular, it is shown that by combining two types of interval observers, referred to as local and global, the accuracy and reliability of the estimation can be improved. The properties of the obtained so-called glocal observer are investigated and illustrated by means of numerical simulations.
Paper VI122-07.3
PDF · Video · Zonotope-Based Interval Estimation for Discrete-Time Linear Switched Systems
Zhang, Wenhan	Harbin Institute of Technology
Wang, Zhenhua	Harbin Institute of Technology
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Dinh, Thach Ngoc	Conservatoire National Des Arts Et Métiers
Dimirovski, Georgi Marko	Dogus University of Istanbul
Keywords: Observers for linear systems, Robust estimation Abstract: This paper is concerned with the interval estimation for discrete-time linear switched systems affected by unknown disturbances and noises. A novel interval estimation approach is proposed by integrating robust observer design with zonotopic techniques. By introducing L_infty technique into observer design, the proposed approach is effective in attenuating the influence of unknown disturbances and noises, and improving the accuracy of interval estimation. Based on the designed observer, the interval estimation can be obtained by using zonotopic analysis. Numerical simulation results are conducted to demonstrate the feasibility and effectiveness of the proposed approach.
Paper VI122-07.4
PDF · Video · On Output Feedback Stabilization of Time-Varying Decomposable Systems with Switching Topology and Delay
Zakwan, Muhammad	Bilkent University, Ankara
Ahmed, Saeed	University of Kaiserslautern
Bajcinca, Naim	University of Kaiserslautern
Keywords: Output feedback control (linear case), Systems with time-delays, Control of switched systems Abstract: This paper presents a new method for dynamic output feedback stabilizing controller design for decomposable systems with switching topology and delay. Our approach consists of two steps. In the first step, we model the decomposable systems with switching topology as equivalent LPV systems with a piecewise constant parameter. In the second step, we design stabilizing output feedbacks for these LPV systems in the presence of a time-varying output delay using a trajectory-based stability analysis approach. We do not impose any constraint on the delay derivative. Finally, we illustrate our approach by applying it to the consensus problem of non-holonomic agents.
Paper VI122-07.5
PDF · Video · The Hankel-Type L_q/L_p Induced Norms of Positive Systems across Switching
Ebihara, Yoshio	Kyushu University
Peaucelle, Dimitri	LAAS-CNRS
Arzelier, Denis	LAAS-CNRS
Keywords: Positive systems, Control of switched systems, Robustness analysis Abstract: The Hankel-type L_q/L_p induced norms across a single switching over two linear time-invariant (LTI) positive systems are discussed. The norms are defined as the induced norms from vector-valued L_p-past inputs to vector valued L_q-future outputs across a switching at the time instant zero. The Hankel-type L_2/L_2 induced norm across a single switching for general LTI systems is studied in details to evaluate the performance deterioration caused by switching. Thanks to the strong positivity property, we successfully characterize the Hankel-type L_q/L_p induced norms for the positive system switching even for p,q being 1, 2, infinity. In particular, we will show that some of them are given in the form of linear program and semidefinite program (SDP). The SDP-based characterizations are useful for the analysis of the Hankel-type L_q/L_p induced norms where the systems of interest are affected by parametric uncertainties.

VI122-08
Time Varying Systems and Polynomial Methods	Regular Session
Chair: Verriest, Erik I.	Georgia Inst. of Tech
Co-Chair: Jeinsch, Torsten	University of Rostock
Paper VI122-08.1
PDF · Video · Guaranteeing the Accuracy of Digital Control of a Linear Periodic Object within the Set of Stabilizing Regulators
Rybinskii, Vladislav	SMTU
Rosenwasser, Efim N.	Marine Technical Univ of Saint Petersburg
Ladisch, Jens	University of Rostock
Drewelow, Wolfgang	University of Rostock
Jeinsch, Torsten	University of Rostock
Keywords: Polynomial methods, Linear systems Abstract: The article considers the task of optimization of a digital control system for a linear continuous periodic object. It is supposed that the system operates under the conditions of uncertainty of an external stationary stochastic disturbance applied directly to the periodic object. For the description of the system dynamics in continuous time the apparatus of the parametric transfer function is used. As an optimization criterion the score of guaranteed accuracy is used, which is an estimate of the H2-norm of the system on the class of perturbations. The optimization is performed on the set of stabilizing causal regulators. An example is given.
Paper VI122-08.2
PDF · Video · Modeling and Manipulating Dynamic Font-Based Hairy Brush Characters Using Control-Theoretic B-Spline Approach
Xie, Zhenyu	Fukuoka Institute of Technology
Fujioka, Hiroyuki	Fukuoka Institute of Technology
Hidaka, Akinori	Tokyo Denki University
Kano, Hiroyuki	Tokyo Denki Univ
Keywords: Polynomial methods, Optimal control theory, Industrial applications of optimal control Abstract: In this study, we consider a problem of modeling and manipulating hairy-brush characters based on the so-called `dynamic font' method with control-theoretic B-spline approach, in which the characters are constituted as a result of trajectory curves using normalized uniform B-splines as basis function. First, typefaces of pre-designed dynamic font characters with one-pixel thickness are transformed to hairy-brush ones by introducing a deep learning method `Pix2Pix'. We then develop a method for modeling hairy-brush characters by formulating the problem as an optimal function-approximation problem, which minimizes an input energy of writing trajectory. Also, manipulations for generating cursive words as seen in Japanese calligraphy in a systematic way are described. A design example of cursive words is included.
Paper VI122-08.3
PDF · Video · Linear Parameter-Varying Embedding of Nonlinear Models with Reduced Conservativeness
Sadeghzadeh, Arash	Eindhoven University of Technology
Tóth, Roland	Eindhoven University of Technology
Keywords: Polynomial methods, Parameter-varying systems Abstract: In this paper, a systematic approach is developed to embed the dynamical description of a nonlinear system into a linear parameter-varying (LPV) system representation. Initially, the nonlinear functions in the model representation are approximated using multivariate polynomial regression. Taking into account the residuals of the approximation as the potential scheduling parameters, a principle component analysis (PCA) is conducted to introduce a limited set of auxiliary scheduling parameters in coping with the trade-off between model accuracy and complexity. In this way, LPV embedding of the nonlinear systems and scheduling variable selection are jointly performed such that a good trade-off between complexity and conservativeness can be found. The developed LPV model depends polynomially on some of the state variables and affinely on the introduced auxiliary scheduling variables, which all together comprise the overall scheduling vector. The methodology is applied to a two-degree of freedom (2-DOf) robotic manipulator in addition to an academic example to reveal the effectiveness of the proposed method and to show the merits of the presented approach compared with some available results in the literature.
Paper VI122-08.4
PDF · Video · Exponential Stabilization of Discrete Nonlinear Time-Varying Systems
Czornik, Adam	Faculty of Automatic Control, Electronics and Computer Science,
Makarov, Evgenii	Institute of Mathematics, National Academy of Sciences of Belaru
Niezabitowski, Michal	Silesian University of Technology, Faculty of Automatic Control
Popova, Svetlana Nikolaevna	Udmurt State University
Zaitsev, Vasilii	Udmurt State University
Keywords: Time-varying systems, Asymptotic stabilization, Stability of nonlinear systems Abstract: We consider a discrete nonlinear control time-varying system on the natural axis. A control process of this system is a pair of sequences consisting of a control sequence and some solution sequence of the system with this control. We assume that the control process is defined on the whole natural axis. We have obtained sufficient conditions for uniform and non-uniform (with respect to the initial moment) exponential stabilization of the control process with any pregiven decay of rate. Exponential convergence to zero of the deviation of both the state vector and the control vector is guaranteed. The result is based on the property of uniform complete controllability (in the sense of Kalman) for a system of linear approximation.
Paper VI122-08.5
PDF · Video · Time-Varying Realization for Arbritary Functions
Verriest, Erik I.	Georgia Inst. of Tech
Keywords: Time-varying systems, Linear systems, Model reduction Abstract: We solve an extension of the inverse problem: Given a function, x, which differential equation does it solve. This extends the well known solution for Bohl-functions, where an LTI-ODE is the solution. First we show that for functions analytic in an open interval, a regular time-variant differential polynomial annihilates the given function. Its order is determined by the highest multiplicity of a real zero of the given function. This is then extended to a class of functions that are real-analytic in R, and further to a class of meromorphic functions, but without real poles. The solution is based on the theory of entire functions, for which essential notions are summarized. Applications in reduced-modeling and computer algebra are mentioned.
Paper VI122-08.6
PDF · Video · Robust Finite-Time Boundedness for Linear Time-Varying Systems
Agulhari, Cristiano M.	Federal University of Technology - Paraná
Peres, Pedro L. D.	Univ. of Campinas
Keywords: Time-varying systems, Robust control (linear case) Abstract: A method for the synthesis of time-varying state-feedback gains, capable of guaranteeing robust finite-time boundedness properties for linear time-varying continuous-time systems, is proposed in this paper. The strategy relies on the computation of discrete-time gains for a discretized version of the open-loop system. If some sufficient conditions are satisfied, the desired continuous-time gain is obtained. A numerical example illustrates the validity of the technique.

VI122-09
Time-Delay Systems	Regular Session
Chair: Seuret, Alexandre	Cnrs / Laas
Co-Chair: Fridman, Emilia	Tel-Aviv Univ
Paper VI122-09.1
PDF · Video · Solutions of Stable Difference Equations Probably Experience Peak
Shcherbakov, P.S.	Moscow Inst. of Control Sciences
Dabbene, Fabrizio	CNR
Polyak, Boris T.	Moscow Inst. of Control Sciences
Keywords: Linear systems, Time-invariant systems, Systems with time-delays Abstract: From the literature, it is known that solutions of homogenous linear stable difference equations may experience large deviations, or peaks, from the nonzero initial conditions at finite time instants. In this paper we take a probabilistic standpoint to analyze these phenomena by assuming that both the initial conditions and the coefficients of the equation have random nature. Under these assumptions we find the probability for deviations to occur, which turns out very close to unity even for equations of low degree, which means that peak is typical. We also address other issues such as evaluation of the mean magnitude and maximum value of peak.
Paper VI122-09.2
PDF · Video · Approximation of the Disturbance Dynamics by Extended State Observer Using an Artificial Delay
Lechappe, Vincent	INSA Lyon - Laboratoire Ampère
Cirrincione, Maurizio	School of Engineering, University of the South Pacific,
Han, Qing-Long	Swinburne University of Technology
Keywords: Observers for linear systems, Systems with time-delays Abstract: A disturbance estimator based on the design of an extended state observer (ESO) often considers that the time-derivative of the perturbation (or higher order time-derivatives) is very small and can be taken equal to zero in the observer design (standard extended system). In this paper, a better approximation of the disturbance dynamics is proposed using a backward difference method. A new extended system is designed based on this approximation. Any observer that makes the error dynamics exponentially stable for the standard extended system can then be used to estimate the state of the new extended system. The efficiency of the method is illustrated through an example.
Paper VI122-09.3
PDF · Video · Analytical Triangular Decoupling Internal Model Control of a Class of Two-Input, Two-Output (TITO) Systems with Delays
Ogunba, Kolawole	Obafemi Awolowo University
Fasiku, Damilola	Obafemi Awolowo University
Fakunle, Afeez Abiodun	Obafemi Awolowo University
Taiwo, Oluwafemi	Obafemi Awolowo University, Ile-Ife, Nigeria
Keywords: Systems with time-delays Abstract: The Decoupling Internal Model Control (DIMC) technique is modified to achieve triangular decoupling for a class of two-input, two-output systems with delays. The closed-loop transfer function matrix that guarantees stability and triangular decoupling within the IMC framework is mathematically developed, and the corresponding centralized decoupling internal model controller calculated for systems with delays and right-half-plane zeros. The shifting of inverse responses and interactions is achieved to a single least-desired output so that for non-minimum-phase (NMP) two-input, two-output (TITO) systems with delays, one output has some delay but has no interacting behavior or inverse response behavior, while the less-desired output has substantial interaction and inverse response behavior, with asymptotic tracking of setpoints for both outputs. A simulation example shows the effectiveness of the proposed method.
Paper VI122-09.4
PDF · Video · Stabilization and Adaptive Output Tracking for MIMO Systems with Distinct Input Delays
Nikiforov, Vladimir O.	ITMO University
Gerasimov, Dmitry	ITMO University
Paramonov, Aleksei	ITMO University
Keywords: Systems with time-delays, Adaptive control, Linear multivariable systems Abstract: In the paper the twofold problem of stabilization and output adaptive tracking is addressed for the class of multi-input multi-output (MIMO) linear time-invariant (LTI) unstable plants with known parameters, unmeasurable state, and known distinct input delays. The reference is represented by the vector of multi-harmonic time functions and is generated by an autonomous linear dynamic model (exosystem) with known order but unknown parameters. The amplitudes, phase shifts, and frequencies of the harmonics of these functions are unknown. The solution proposed is based on a robust predictor-feedback stabilizing control law, suitable parameterization of the tracking error, special implementation of the augmented error scheme, and direct adaptation algorithm providing asymptotic tracking without identification of the exosystem parameters. The stabilizing part of control palliates negative influence of distinct input delays. Regardless of the values of input delays, the adaptive control law designed ensures boundedness of all signals in the closed-loop system and drives the tracking error to zero.
Paper VI122-09.5
PDF · Video · Controller Design for Large-Scale Neutral Time-Delay Systems Using Overlapping Decompositions
Iftar, Altug	Eskisehir Tech. Univ
Keywords: Systems with time-delays, Decentralized control, stability of delay systems Abstract: Decentralized controller design for large-scale linear time-invariant (LTI) neutral time-delay systems, using the approach of overlapping decompositions, is presented. The approach is based on the principle of restriction, which is a special case of inclusion. The considered controllers have the most general form of LTI neutral time-delay controllers. However, they also include LTI retarded time-delay, as well as finite-dimensional, controllers as special cases.
Paper VI122-09.6
PDF · Video · Global Exponential Stability Criteria for Proportional Delay High-Order Neural Networks: A Hyper-Exponential Stability Technique
Shen, Wenqi	Heilongjiang University
Wang, Xin	Heilongjiang University
Liu, Heng	Heilongjiang University
Zhang, Xian	Heilongjiang University
Cai, Bo	Harbin Institute of Technology
Keywords: Systems with time-delays, Delay systems, Robust linear matrix inequalities Abstract: A new method is presented for stability analysis of proportional delay high-order neural networks. The network model is first transformed into a system with a constant time delay and unbounded time-varying coefficients, and then it is proven that the former is globally exponentially stable if and only if the laster is globally hyper-exponentially stable. The global hyper-exponential stability criteria of the laster are investigated by employing the generalized Halanay inequality and constructing a novel Lyapunov function that can avoid the computation of upper-right derivative. From which, the global exponential stability criteria of the former are derived. To illustrate the advantages of this proposed method, numerical simulation examples are given. Compared with the existing results, the contributions of this paper lie in: (i) An Lyapunov function different from ones in literature is constructed; (ii) The derived global exponential stability criteria possess simple forms, which are easy to verify; and (iii) The concept of hyper-exponential stability is proposed. The proposed method is also available to multi-proportional delay neural networks.
Paper VI122-09.7
PDF · Video · Interval Estimation for Linear Discrete-Time Delay Systems
Sehli, Naima	National Engineering School of Tunis
Wang, Zhenhua	Harbin Institute of Technology
Kaouther, Ibn Taarit	ENIT
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Ksouri, Moufida	National Engineering School of Tunis
Keywords: Systems with time-delays, Linear systems, Observer design Abstract: This paper deals with the problem of interval estimation for linear discrete-time systems with a constant time delay. First, an interval observer is designed based on cooperativity and Lyapunov- Krasovskii stability analysis. Second, a zonotope-based interval estimation, which is independent of cooperativity constraint, is proposed. It integrates robust observer design, based on multiple feedbacks, with reachability analysis via zonotopes. In order to enhance the accuracy of interval estimation, an H-infinity technique is introduced into observer design to reduce the effects of disturbances and noises. Finally, simulation results are given to illustrate the efficiency of the proposed method.
Paper VI122-09.8
PDF · Video · A New Control Scheme for Time-Delay Compensation for Structural Vibration
Vite Hernández, Leopoldo	CINVESTAV-IPN
Gomez, Marco Antonio	KU Leuven
Morales Valdez, Jesús	CINVESTAV-IPN
Mondie, Sabine	CINVESTAV-IPN
Keywords: Systems with time-delays, Robust time-delay systems, delay compensation for linear and nonlinear systems Abstract: This paper addresses the vibration control of seismic-excited building structures in the presence of input time-delay. The control scheme is based on a prediction approach for input delay compensation and H_infty theory. The prediction scheme, which relies on state observers, is tuned by means of the optimization of the smoothed spectral abscissa, that is a suitable robust stability measure since it provides a trade-off between the optimization of the spectral abscissa and the H_2 of the system. The effectiveness of the proposed control scheme is illustrated with simulation results of a reduced scale two-storey building structure.
Paper VI122-09.9
PDF · Video · Constructive Backstepping for a Class of Delay Systems Based on Functionals of Complete Type
Pereyra, Javier	CINVESTAV-IPN
Mondie, Sabine	CINVESTAV-IPN
Mazenc, Frederic	INRIA-L2S-CNRS-CentraleSupelec,
Keywords: Systems with time-delays, stability of delay systems, Lyapunov methods Abstract: In this paper we consider an alternative approach of the backstepping control strategy with the introduction of artificial delays combined with Lyapunov-Krasovskii functionals of complete type, thus allowing a constructive approach for the design of asymptotically stabilizing controls of linear systems with delay in the input and state that are too long for being neglected.
Paper VI122-09.10
PDF · Video · Insight into Stability Analysis of Time-Delay Systems Using Legendre Polynomials
Bajodek, Mathieu	LAAS-CNRS
Seuret, Alexandre	Cnrs / Laas
Gouaisbaut, Frederic	LAAS CNRS
Keywords: Systems with time-delays, stability of delay systems, Robust time-delay systems Abstract: In this paper, a numerical analysis to assess stability of time-delay systems is investigated. The proposed approach is based on the design of a finite-dimensional approximation of the infinite-dimensional space of solutions of the system. Indeed, based on the dynamical coefficients on the sequence made of the first Legendre polynomials, the original time-delay system is modelled by a finite-dimensional model interconnected to a modelling error. Putting aside the interconnection, the resulting finite-dimensional system turns out to be a nice approximation of the time-delay system. Using Pade arguments, the eigenvalues of this finite-dimensional system are proven to converge towards a set of characteristic roots of the original time-delay system. Furthermore, considering now the whole interconnected system and having a deeper look at the interconnection, an enriched Lyapunov-Krasovskii functional is proposed to develop a sufficient condition expressed in terms of linear matrix inequalities for the stability of the time-delay system. Both results are illustrated on a toy example.
Paper VI122-09.11
PDF · Video · Controllability of Linear Delay Systems and of Their Sampled Versions
Mounier, Hugues	Laboratoire Des Signaux Et Systèmes, CNRS SUPELECUniversité Pari
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Systems with time-delays, Structural properties, Digital implementation Abstract: This paper focuses on the controllability preservation through sampling of linear time-delay systems. We make use of a module theoretic framework acting as a unifying one for most of the existing delay system controllability notions. The controllability properties are envisioned through ring theoretic properties. Some illustrative examples complete the presentation.
Paper VI122-09.12
PDF · Video · Systems with Vanishing Time-Variant Delay: Structural Properties Based on the Pantograph (Scale-Delay) Equation
Verriest, Erik I.	Georgia Inst. of Tech
Keywords: Systems with time-delays, Time-varying systems, Structural properties Abstract: This paper studies the scale-delay system as a paradigm for systems with vanishing time-variant delay. After a brief review of the scale-delay equation and its associated solution, we derive new identities for the zeros of the deformed exponential. A solution method for the higher order scale-delay equation is given in terms of these deformed exponentials. We then consider inverse problem: ``Given a function x, which differential equation does it solve," but with a twist: We are interested in time-variant realizations of the solution, as described in a companion paper. This extends the well known solution for Bohl-functions, where an LTI-ODE results. Finally this is applied to obtain a second order time-variant approximation of the SD-equation.
Paper VI122-09.13
PDF · Video · Stability Analysis by Averaging: A Time-Delay Approach
Fridman, Emilia	Tel-Aviv Univ
Zhang, Jin	Tel Aviv University
Keywords: Time-varying systems, Lyapunov methods, Switching stability and control Abstract: We study stability of linear systems with fast time-varying coefficients. The classical averaging method guarantees the stability of such systems for small enough values of parameter provided the corresponding averaged system is stable. However, it is difficult to find an upper bound on the small parameter by using classical tools for asymptotic analysis. In this paper we introduce an efficient constructive method for finding an upper bound on the value of the small parameter that guarantees a desired exponential decay rate. We transform the system to a model with time-delays of the length of the small parameter. The resulting time-delay system is a perturbation of the averaged LTI system which is assumed to be exponentially stable. The stability of the time-delay system guarantees the stability of the original one. We construct an appropriate Lyapunov functional for finding sufficient stability conditions in the form of linear matrix inequalities (LMIs). The upper bound on the small parameter that preserves the exponential stability is found from LMIs. Two numerical examples (stabilization by vibrational control and by time-dependent switching) illustrate the efficiency of the method.
Paper VI122-09.14
PDF · Video · State Predictive Control with Multiple Modification Terms and Robust Stability Analysis Based on Complementary Sensitivity Functions
Yanase, Shotaro	Kyoto Univ
Masui, Yoichiro	National Institute of Technology, Oshima College
Hirata, Kentaro	Okayama University
Hagiwara, Tomomichi	Kyoto Univ
Keywords: Systems with time-delays, Robustness analysis, Robust time-delay systems Abstract: As an effective control method for systems with time delay in the input, state predictive control is well known. An idea of adding a single modification term to its control law was presented recently, and it was suggested that an appropriate modification term could contribute to improving robust stability of the control system to some parametric uncertainties. This extended control method is called modified state predictive control. Motivated by the preceding study, this paper considers introducing multiple modification terms into the control law of state predictive control, aiming at improving robust stability for non-parametric uncertainties. We first derive the characteristic equation of the modified state predictive control systems with multiple modification terms, and give a necessary and sufficient condition for stability. We then derive an explicit representation of the complementary sensitivity function associated with the robust stability analysis problem for multiplicative uncertainties. Finally, we demonstrate through numerical examples that state predictive control with appropriate multiple modification terms could be useful in improving robust stability compared with that with a single modification term or no such a term.
Paper VI122-09.15
PDF · Video · Model-Based Higher-Order PID Control Design
Huba, Mikulas	Slovak Univ. of Tech
Keywords: Systems with time-delays, Disturbance rejection (linear case), delay compensation for linear and nonlinear systems Abstract: Higher order (HO) proportional-integrative-derivative (PID) control aims to fill the gap between traditional and fractional order PID control. Thereby, it allows to fulfill more complex requirements on the target loop performance than it is possible in traditional PID control. This paper illustrates, how HO PID controllers may be derived by generalizing the constructive simple/Skogestad (SIMC) method for analytical model-based controller tuning. Controllers with HO derivative actions are necessarily based on improved design of noise attenuation filters. To evaluate their impact, shape related performance measures of the input and output step responses will be used based on concept of piece wise monotonic signals. Deviations from the ideal shapes due to the noise, design imperfections and plant-model mismatch, establishing additional constraints in designing as fast as possible transients, are quantified in terms of modified total variations. Tuning scenarios based on modified ``half-rule'' and their superiority in comparison to the IAE optimization based controller design are demonstrated by simulation and by real time experiments. Pros and cons of more complex HO PID controllers are discussed.

VI123
Design Methods - Non-Linear Control Systems
VI123- Nonlinear Robust Control   Regular Session, 9 papers
VI123-01 Advances in Nonlinear Observers   Open Invited Session, 9 papers
VI123-02 Control of Nonlinear Stochastic Systems   Open Invited Session, 7 papers
VI123-03 Estimation and Observer Design Methods in Nonlinear Systems   Open Invited Session, 10 papers
VI123-04 Finite-Time Control and Estimation of Uncertain Systems   Open Invited Session, 18 papers
VI123-05 Machine Learning and Model Predictive Control   Open Invited Session, 20 papers
VI123-06 On Nonlinear Infinite Dimensional Systems   Open Invited Session, 8 papers
VI123-07 Theory and Applications of Extremum Seeking Control   Open Invited Session, 14 papers
VI123-08 Application of Nonlinear Analysis and Design   Regular Session, 8 papers
VI123-09 Constrained Control   Regular Session, 14 papers
VI123-10 Lagrangian and Hamiltonian Systems   Regular Session, 5 papers
VI123-11 Model Reduction   Regular Session, 5 papers
VI123-12 Networked, Interconnected, and Distributed Nonlinear Systems   Regular Session, 9 papers
VI123-13 Nonlinear Control for Aerospace Systems   Regular Session, 12 papers
VI123-15 Nonlinear Systems   Regular Session, 14 papers
VI123-16 Stabilization of Nonlinear Systems   Regular Session, 7 papers
VI123-17 Nonlinear Observers and Applications   Regular Session, 14 papers
VI123-18 Nonlinear Output Feedback   Regular Session, 6 papers
VI123-19 Nonlinear Predictive Control   Regular Session, 16 papers
VI123-20 Nonlinear Switched Systems   Regular Session, 5 papers
VI123-21 Nonlinear Tracking   Regular Session, 8 papers
VI123-22 Sliding Mode Control   Regular Session, 10 papers
VI123-23 Stability of Nonlinear Systems   Regular Session, 27 papers
VI123-24 Switching - Stability and Control   Regular Session, 9 papers

VI123
Nonlinear Robust Control	Regular Session
Chair: Gruene, Lars	Univ of Bayreuth
Co-Chair: Zuev, Alexander	Far Eastern Federal University
Paper VI123.1
PDF · Video · Decision Making Method for Nonparametric Diagnosis in Nonlinear Dynamic Systems
Shumsky, Alexey	Far Eastern Federal University
Zhirabok, Alexey N.	Far Eastern Federal Univ
Zuev, Alexander	Far Eastern Federal University
Keywords: Disturbance rejection, Diagnosis, Robust control applications Abstract: The problem of robust fault diagnosis in nonlinear dynamic systems under presence of disturbances is studied within the scope of analytical redundancy conception. Solution of the problem assumes residual generation by checking redundancy relations existing among system inputs and outputs measured over a finite time window followed by decision making through evaluation of the residuals. Nonparametric method is considered for residual generation. To make decision, the unified method is developed whose feature is it combines the threshold logic of decision making and the residuals comparing with the fault syndromes evaluated on-line. Joint application of both nonparametric method for residual generation and unified method for decision making gives the possibility to develop the universal diagnostic platform for different systems described by ordinary nonlinear differential equations of the same structure but distinguished by these equations coefficients values.
Paper VI123.2
PDF · Video · An Adaptive Robust Guidance Strategy for Interceptor with Input Quantization
Banerjee, Arunava	Indian Institute of Technology Delhi
Amrr, Syed Muhammad	Indian Institute of Technology Delhi
Nabi, Mashuq-un	Indian Institute of Technology, New Delhi
Keywords: Quantized control, Robust control, Aerospace Abstract: The computational capabilities of processors have increased many folds over the last few decades. However, due to constraint on space, weight, and cost, the state-of-art onboard processors cannot be generally installed in a missile, which is required to perform multiple parallel computations for a successful interception. An efficient way of minimizing the computational burden can be ensured by reducing the number of updates of the control input, thereby minimizing the load on the onboard processors. A logarithmic quantizer technique is explored in this work for designing a guidance strategy for a two-dimensional interceptor problem. The proposed guidance strategy is capable of tackling disturbances and quantization errors while achieving the primary objective of capturing the target. An adaptive law has also been incorporated to eliminate the need of apriori knowledge about the disturbance bound. Lyapunov theory has been used to show Uniformly Ultimately Bounded (UUB) convergence of the closed-loop system states under the application of the quantized control approach. The proposed scheme is implemented through numerical simulations for the tail-chase and head-on engagement scenarios. A comparative analysis of the proposed guidance strategy with the periodic sampling time technique is also included in this work.
Paper VI123.3
PDF · Video · Robust Backstepping Control of Uncertain Nonlinear Systems with Unknown Time-Varying Input Delay
Jain, Ashish	Indian Institute of Technology, Delhi
Bhasin, Shubhendu	Indian Institute of Technology Delhi
Keywords: Robust control, Delay systems, Lyapunov methods Abstract: A robust compensator is developed for a class of strict-feedback uncertain nonlinear systems with additive disturbance and unknown time-varying input delay. The compensator is composed of a Proportional-Inegral (PI) control and delay compensation term based on a finite integral of the past control values. The sufficient inequality conditions on controller gains and upper bound of input delay are derived using a Lyapunov-based stability analysis by choosing suitable L-K functionals, which guarantee a global uniformly ultimately bounded (GUUB) tracking result. Simulation results show the performance and robustness of controller for different values of time-varying input delay.
Paper VI123.4
PDF · Video · Improved Event-Triggering Scheme for Uncertain Systems
Mahmoud, Magdi Sadek Mostafa	KFUPM
Karaki, Bilal J.	King Fahd University of Petroleum and Minerals
Keywords: Robust control, Delay systems, Networked systems Abstract: This paper develops a new event-triggering approach for a class of nonlinear systems. This approach goes beyond the control of certain systems by developing sporadic feedback control laws to solve unstructured uncertainty problem. It guarantees asymptotic stability of a broad range of uncertain systems under sample and hold implementation while it efficiently reduces the communication samples. Under the proposed scheme, in order to handle the uncertain dynamics, the sampling time might become smaller than that in the approach of the certain systems. Using linear matrix inequalities, the controller gains and the event triggering parameters are obtained simultaneously. In addition to addressing new scheme for uncertain systems, we propose another triggering mechanism for affine nonlinear systems. Simulation results illustrate that the increase of triggered messages due to the nonlinearity and uncertainty is kept small enough that can be neglected when compared with conventional event-triggering policy.
Paper VI123.5
PDF · Video · Efficient Non-Conservative Realization of Dynamic Scaling-Based Output-Feedback Controllers Via a Matrix Pencil Approach
Krishnamurthy, Prashanth	NYU Polytechnic School of Engineering
Khorrami, Farshad	NYU Polytechnic School of Engineering
Keywords: Robust control, Nonlinear observers and filter design, Uncertainty descriptions Abstract: A general matrix pencil based approach is developed for efficient non-conservative realization of dual dynamic high-gain scaling based control designs. A general class of uncertain feedforward-like nonlinear systems is considered and it is shown that the output-feedback control design procedure can be cast into a set of matrix pencil based sub-problems that capture the detailed system structure, state dependence structure of uncertain terms, and the precise roles of the design freedoms in the context of the detailed structure of the Lyapunov inequalities. The design freedoms in the dynamic high-gain scaling based design are extracted in terms of generalized eigenvalues of the formulated matrix pencil structures. It is seen that the proposed matrix pencil based approach greatly reduces design conservatism and algebraic complexity compared to prior results on dynamic high-gain scaling based control designs.
Paper VI123.6
PDF · Video · Robust Output Regulation of Permanent Magnet Synchronous Motors by Enhanced Extended Observer
Borisov, Oleg	ITMO University
Pyrkin, Anton	ITMO University
Isidori, Alberto	University of Rome "La Sapienza"
Keywords: Robust control, Output regulation, Robust control applications Abstract: This paper presents an application of the enhanced extended observer design with regard to the problem of robust output regulation of permanent magnet synchronous motors. The control framework is further advanced by means of the internal model so as to cope with disturbances represented by the time-varying load torque. The paper shows simulation of regulating a motor for different cases of torque loads and references and provides an explicit procedure of the recursive calculation of the enhanced extended observer coefficients.
Paper VI123.7
PDF · Video · Sliding Mode Tracking Control for Nonlinear Sampled-Data Systems with Unmatched Perturbation
Zapata-Zuluaga, Cristian Camilo	Centro De Investigación De Estudios Avanzados Del IPN
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Utkin, Victor	ICS
Keywords: Robust control, Robust controller synthesis, Tracking Abstract: The output tracking problem for a class of sampled-data nonlinear systems exposed in Nonlinear Block Controllable (NBC) form is faced. This paper considers both matched and unmatched perturbations. To formulate a desired sliding manifold on which the impact of unmatched perturbation is attenuated, the Block Control technique combined with the perturbation estimation, is implemented. A discrete-time sliding mode non-switching controller is synthesized such that the system state is driven toward a vicinity of the designed sliding manifold and stays there for all sampled time instants, avoiding chattering and reducing the matched perturbation effect. The effectiveness of the proposed technique is confirmed by simulation.
Paper VI123.8
PDF · Video · Robust Error Feedback Sliding Mode Regulator for Nonlinear Systems in Regular Form
Martín del Campo, Maximiliano	CINVESTAV De IPN, Unidad Guadalajara
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Plestan, Franck	Ecole Centrale De Nantes-LS2N
Keywords: Sliding mode control, Output regulation, Nonlinear observers and filter design Abstract: In this paper, the problem of designing a nonlinear Sliding Mode (SM) regulator is addressed for nonlinear affine control systems in Regular form subject to unmodeled disturbance. In particular, the error feedback SM regulator problem is defined, taking the concepts related to the zero-output tracking submanifold as a starting point. Applying the internal model concept to the time-invariant SM equation, the solvability conditions to the problem are derived. A Proportional-Integral (PI) nonlinear observer is proposed, and using the observer states, a sliding manifold on which the tracking error is ultimately bounded, is formulated. A SM control algorithm is proposed to ensure the designed manifold to be attractive, achieving robustness with respect to certain allowed uncertainties. The effectiveness of the proposed method is demonstrated by the application to the Pendubot system.
Paper VI123.9
PDF · Video · Quadratic Stabilization of Discrete-Time Bilinear Control Systems Subjected to Exogenous Disturbances
Khlebnikov, Mikhail V.	Trapeznikov Institute of Control Sciences RAS
Keywords: Disturbance rejection, Lyapunov methods, Stability of nonlinear systems Abstract: We consider the design problem for discrete-time bilinear control systems subjected to arbitrary bounded exogenous disturbances. A procedure for the construction of the stabilizability ellipsoid and domain of stabilizability for discrete-time bilinear control systems is proposed and its efficiency is proved. The main tools are the linear matrix inequality technique and the apparatus of quadratic Lyapunov functions. This simple yet general approach is of great potential; for instance, it can be generalized to the various robust statements of the problem.

VI123-01
Advances in Nonlinear Observers	Open Invited Session
Chair: Marconi, Lorenzo	Univ. Di Bologna
Co-Chair: Dochain, Denis	Univ. Catholique De Louvain
Organizer: Astolfi, Daniele	CNRS - Univ Lyon 1
Organizer: Andrieu, Vincent	Université De Lyon
Organizer: Marconi, Lorenzo	Univ. Di Bologna
Paper VI123-01.1
PDF · Video · Adaptive Low-Power High-Gain Observers for Lower-Triangular Systems with Input-Dependent Lipschitz Constant (I)
Morfin, Elise	Grenoble INP - Ense3, Grenoble F-38031, France
Astolfi, Daniele	CNRS - Univ Lyon 1
Andrieu, Vincent	Université De Lyon
Keywords: Nonlinear observers and filter design, Observer design, Adaptive control Abstract: We combine the low-power high-gain observer recently proposed in Astolfi and Marconi (2015) with the updated-gain technique used in Andrieu et al. (2009). The resulting adaptive low-power high-gain observer inherits the advantages of both techniques and can be used to address the state-estimation problem for Lipschitz systems in lower triangular form with nonlinearities having a Lipschitz constant that depends on a known external input.
Paper VI123-01.2
PDF · Video · Port-Hamiltonian Sliding Mode Observer Design for a Counter-Current Heat Exchanger (I)
Kadima Kazaku, Jacques	Université De Lubumbashi, Université Catholique De Louvain
Dochain, Denis	Univ. Catholique De Louvain
Winkin, Joseph J.	University of Namur
Mukepe Kahilu, Moïse	Université De Lubumbashi
Kalenga Kaunde Kasongo, Jimmy	Université De Lubumbashi
Keywords: Nonlinear observers and filter design, Control of interconnected systems, Lagrangian and Hamiltonian systems Abstract: This paper presents a sliding mode observer (SMO) for estimating temperatures in a heat exchanger. First a port-Hamiltonian formulation for a countercurrent heat exchanger is proposed. It is so as to guarantee convergence of the observer. It is shown that the Stokes-Dirac structure obtained by opening only the dissipation ports due to the convection phenomenon, is conservative. Secondly, a SMO based on an interconnected structure of port-Hamiltonian systems is designed. The convergence of the dynamics of the estimation error is proven. The simulation results illustrate the eectiveness of this estimation strategy.
Paper VI123-01.3
PDF · Video · A Minimum Energy Filter for Distributed Multirobot Localisation (I)
Henderson, Jack	Australian National University
Trumpf, Jochen	The Australian National University
Zamani, Mohammad	DST Group
Keywords: Distributed nonlinear control Abstract: We present a new approach to the cooperative localisation problem by applying the theory of minimum energy filtering. We consider the problem of estimating the pose of a group of mobile robots in an environment where robots can perceive fixed landmarks and neighbouring robots as well as share information with others over a communication channel. Whereas the vast majority of the existing literature applies some variant of a Kalman Filter, we derive a set of filter equations for the global state estimate based on the principle of minimum energy filtering. We show how the filter equations can be decoupled and the calculations distributed among the robots in the network without requiring a central processing node. Finally, we provide a demonstration of the filter's performance in simulation.
Paper VI123-01.4
PDF · Video · Dynamic Output Feedback Stabilization of Non-Uniformly Observable Dissipative Systems (I)
Sacchelli, Ludovic	Lehigh University, Bethlehem, PA
Brivadis, Lucas	LAGEPP, Université Lyon 1
Andrieu, Vincent	Université De Lyon
Serres, Ulysse	University of Lyon 1
Gauthier, Jean-Paul	Université De Toulon
Keywords: Output feedback control, Asymptotic stabilization Abstract: Output feedback stabilization of control systems is a crucial issue in engineering. Most of these systems are not uniformly observable, which proves to be a difficulty to move from state feedback stabilization to dynamic output feedback stabilization. In this paper, we present a methodology to overcome this challenge in the case of dissipative systems by requiring only target detectability. These systems appear in many physical systems and we provide various examples and applications of the result.
Paper VI123-01.5
PDF · Video · A New Extended State Observer with Low Sensitivity to High Frequency Noise and Low Gain Power (I)
Li, Xiaoyang	Dalian University of Technology
Xia, Hao	Dalian University of Technology
Keywords: Nonlinear observers and filter design, Disturbance rejection, Observer design Abstract: Linear Extended State Observer (LESO) with a large gain wo leads to faster estimation error convergence. But a high gain LESO is sensitive to high frequency measurement noise and its digital implementation is rather complex. To address the above issues, for a given n-th order plant, a new 2n-th order extended state observer is proposed. The proposed observer, while preserving the fast convergence property of LESO, has a lower gain power of 2 and is less sensitive to high frequency measurement noise. And the new observer can be easily tuned with gain wo.
Paper VI123-01.6
PDF · Video · State Observer Design Method for a Class of Nonlinear Systems (I)
Arezki, Hasni	Mouloud Mammeri Univetrsity of Tizi Ouzou
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Bedouhene, Fazia	Laboratoire De Mathématiques Pures Et Appliquées(LMPA), Universi
Alessandri, Angelo	Università Di Genova
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Observer design, Nonlinear observers and filter design, Linear parameter-varying systems Abstract: In this paper, we develop a new high gain observer design method for nonlinear systems. This new structure provides a lower gain compared to both the high gain and the enhanced high gain observer. The idea is to combine the improved high gain methodology with the LMI-based observer design technique to build a more general observer that allows us to exploit the benefits of both approaches.
Paper VI123-01.7
PDF · Video · A Switched-Gain Nonlinear Observer for LED Optical Communication (I)
N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Ding, Zhang	The Hong Kong University of Science and Technology, Clear Water
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Rajamani, Rajesh	Univ. of Minnesota
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Observer design, Nonlinear observers and filter design, Application of nonlinear analysis and design Abstract: Alignment for maintaining Line-of-Sight (LoS) between the receiver and the transmitter in a LED optical communication system is a challenging problem due to the constant movement of the underlying optical platform that is caused by vibration effects and atmospheric turbulence. In this paper, we propose a robust switched-gain nonlinear observer to estimate the angular position and velocity of the receiver orientation, which is used subsequently to follow the receiver orientation. The optical communication system model involves highly nonlinear and non-monotonic output measurement equations. Furthermore, tracking the receiver with perfect alignment results in loss of local observability. Hence, a two-receiver system is utilized to provide a robust tracking system that retains observability over the entire range of operation of the system. Lyapunov function-based analysis that ensures global stability is used to design the observer; then, a static feedback controller drives the receiver orientation based on the state estimate. Finally, numerical simulations are presented on the performance of the observer-based static feedback control in accurately estimating and tracking the angular position and velocity of the receiver orientation.
Paper VI123-01.8
PDF · Video · An Observer for Infinite Dimensional 3D Surface Reconstruction That Converges in Finite Time (I)
O'Brien, Sean	Australian National University
Ashton, Katrina	Australian National University
Trumpf, Jochen	The Australian National University
Keywords: Observer design, Nonlinear observers and filter design, Infinite-dimensional systems Abstract: This paper proposes a method of reconstructing the dense structure of scenes from visual or depth sensors that provably converges in finite time. We represent the scene as a superlevel set of a function that resides within some potentially infinite-dimensional function space. The observer state is determined by the parameters of the function that represents the scene. Preliminary experiments show that the observer exhibits convergence behaviour on a variety of different function spaces both in simulation and with real light-field camera data.
Paper VI123-01.9
PDF · Video · Data Rate Limits for the Remote State Estimation Problem (I)
Kawan, Christoph	Ludwig-Maximilians-Universität München
Matveev, Alexey S.	St.Petersburg Univ
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Keywords: Control under communication constraints, Networked systems, Lyapunov methods Abstract: In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which a system can be regularly observed. The observer here is assumed to receive its state information through a communication channel of a finite bit-rate capacity. In this paper, we provide a new characterization of restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding an adapted Riemannian metric on the state space that allows to ‘see’ the decisive quantity that determines the restoration entropy – a certain type of Lyapunov exponent – in only one step of time.

VI123-02
Control of Nonlinear Stochastic Systems	Open Invited Session
Chair: Scarciotti, Giordano	Imperial College London
Co-Chair: Mellone, Alberto	Imperial College London
Organizer: Scarciotti, Giordano	Imperial College London
Organizer: Mellone, Alberto	Imperial College London
Paper VI123-02.1
PDF · Video · The J-Orthogonal Square-Root Fifth-Degree Cubature Kalman Filtering Method for Nonlinear Stochastic Systems (I)
Kulikov, Gennady Yu.	Instituto Superior Tecnico, Universidade De Lisboa
Kulikova, Maria V.	Instituto Superior Técnico, Universidade De Lisboa
Keywords: Nonlinear observers and filter design, Robust estimation Abstract: This paper addresses the issue of square-rooting in the Fifth-Degree Cubature Kalman Filtering (5D-CKF) method grounded in the Ito-Taylor approximation of order 1.5 and designed by Santos-Diaz, Haykin and Hurd in 2018. That filter is rather accurate and efficient in treating nonlinear continuous-discrete stochastic systems of practical value and shown to outperform many other algorithms in a radar tacking scenario. However, the cited authors mention ``the lack of a square-root implementation'' of the filter under consideration as a principle shortcoming reducing its applied potential. Here, we address the reported lack and resolve it with a hyperbolic QR factorization used for devising the filter's J-orthogonal square-root version, which possesses an exceptional robustness to round-off and other disturbances. Our square-root implementation of the 5D-CKF technique is justified theoretically and examined and compared numerically to its non-square-root predecessor in a flight control scenario with ill-conditioned measurements.
Paper VI123-02.2
PDF · Video · The J-Orthogonal Square-Root MATLAB-Based Continuous-Discrete Unscented Kalman Filtering Method (I)
Kulikova, Maria V.	Instituto Superior Técnico, Universidade De Lisboa
Kulikov, Gennady Yu.	Instituto Superior Tecnico, Universidade De Lisboa
Keywords: Nonlinear observers and filter design, Robust estimation, Numerical methods for optimal control Abstract: The paper suggests a general solution to the square-rooting problem existed for the Unscented Kalman Filter (UKF) since its appearance in the late 1990s. As properly noted in engineering literature, the previously suggested Cholesky-based UKF implementations are, in fact, the 'pseudo' square-root versions. Their key feature is the utilization of one-rank Cholesky update procedure required at each filtering step because of the possibly negative sigma points' weights. In a finite precision arithmetic, the resulting downdated matrix might be not a positive definite matrix. This yields a failure of the UKF estimator in practice. We resolve this problem by suggesting a novel square-root approach based on the J-orthogonal matrix utilization for updating the required Cholesky factors. Additionally, we explain how the MATLAB language with built-in numerical integration schemes developed for solving ordinary differential equations can be easily and effectively used for accurate calculations when implementing the continuous-discrete UKF time update stage.
Paper VI123-02.3
PDF · Video · Towards a Solution of Mean-Field Control Problems Using Model Predictive Control (I)
Borzi, Alfio	Universität Würzburg
Gruene, Lars	Univ of Bayreuth
Keywords: Stochastic optimal control problems, Predictive control, Optimal control of partial differential equations Abstract: In this paper we propose a model predictive control (MPC) scheme for solving mean-field control problems. To this end, the MPC scheme is applied to a controlled Fokker-Planck equation. We test our algorithm by means of a numerical example, both with and without nonlinear coupling. We also provide numerical evidence that MPC indeed delivers approximately optimal trajectories for this example.
Paper VI123-02.4
PDF · Video · The Zero Dynamics of Nonlinear Stochastic Systems: Stabilisation and Output Tracking in the Ideal Case (I)
Mellone, Alberto	Imperial College London
Scarciotti, Giordano	Imperial College London
Keywords: Asymptotic stabilization, Tracking, Uncertainty descriptions Abstract: This paper introduces the notion of zero dynamics and presents results of local stabilisation and output tracking for single-input single-output nonlinear stochastic systems described by stochastic differential equations. For this class of systems we define the zero dynamics when the stochastic relative degree is strictly smaller than the order of the system. We show that, under suitable conditions on the zero dynamics, the equilibrium at the origin can be stabilised via a coordinate change and a nonlinear state feedback. In an analogous way, we show that it is possible to achieve local asymptotic output tracking of a reference signal. We validate the theory through a numerical example.
Paper VI123-02.5
PDF · Video · Approximate Feedback Linearisation and Stabilisation of Nonlinear Stochastic Systems (I)
Mellone, Alberto	Imperial College London
Scarciotti, Giordano	Imperial College London
Keywords: Asymptotic stabilization, Uncertainty descriptions Abstract: This paper addresses the design of a practically sound control architecture to solve the problem of feedback linearisation and stabilisation of single-input single-output nonlinear stochastic systems. We first present a causal method to obtain, from measurements of the state, a-posteriori estimates of the variations of the Brownian motion which affected the system. Then we employ these estimates to design a control law that approximately compensates for the diffusive dynamics of the system. We address the local stabilisation problem and we prove that the control law which performs the proposed stochastic compensations stabilises a broader class of systems with respect to feedback laws without compensation. We finally validate the theory through a numerical example.
Paper VI123-02.6
PDF · Video · Functional Reduced Order Hinfinity Decentralized Observer Based Control for Large Scale Interconnected~nonlinear~stochastic~systems (I)
Barbata, Asma	Université De Lorraine
Zasadzinski, Michel	CRAN
Souley Ali, Harouna	Cran Umr 7039 Cnrs
Keywords: Decentralized control, Control of interconnected systems, Output feedback control Abstract: In this work, the Hinfinity decentralized reduced order observer based control for a class of large scale nonlinear stochastic systems is concerned. In this context we consider subsystems which are interconnected by some nonlinear interconnections under quadratic boundedness and Lipschitz property of the system. The proposed control law is based on the resolution of some LMI.
Paper VI123-02.7
PDF · Video · Metaheuristics-Based Approximation of Two-Dimensional Probability Distributions for Stochastic Systems Control (I)
Osaki, Kenta	Kyoto Univ
Hosoe, Yohei	Kyoto University
Hagiwara, Tomomichi	Kyoto Univ
Keywords: Synthesis of stochastic systems, Realization theory Abstract: This paper is concerned with approximation of probability distributions behind discrete-time systems with stochastic dynamics. The aim is to facilitate advances in studies for control of such stochastic systems. An approach to approximating two-dimensional probability distributions using metaheuristics is suggested. Then, its effectiveness is demonstrated with a numerical example of stabilization synthesis.

VI123-03
Estimation and Observer Design Methods in Nonlinear Systems	Open Invited Session
Chair: N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Co-Chair: Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Organizer: N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Organizer: Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Organizer: Rajamani, Rajesh	Univ. of Minnesota
Organizer: Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Paper VI123-03.1
PDF · Video · Optimistic vs Pessimistic Moving-Horizon Estimation for Quasi-LPV Discrete-Time Systems (I)
Alessandri, Angelo	Università Di Genova
Zasadzinski, Michel	CRAN
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Keywords: Linear parameter-varying systems, Robust estimation, Nonlinear observers and filter design Abstract: In this paper we focus on estimation for nonlinear plants that can be rewritten under the form of quasi-linear parameter-varying systems with bounded unknown parameters. Moving-horizon estimators are proposed to estimate the state of such systems according to two different formulations, i.e., ``optimistic'' and ``pessimistic.'' In the former case, we perform estimation by minimizing the least-squares moving-horizon cost w.r.t. both state variables and parameters simultaneously. In the latter, we minimize such a cost w.r.t. the state variables after picking up the maximum w.r.t. the parameters. Under suitable assumptions, the stability analysis of the estimation is proved in both cases. A simple numerical example is provided to compare the proposed approaches.
Paper VI123-03.2
PDF · Video · Asymptotic and Tracking Guarantees in Interval Observer Design for Systems with Unmeasured Polytopic Nonlinearities (I)
Ito, Hiroshi	Kyushu Institute of Technology
Dinh, Thach Ngoc	Conservatoire National Des Arts Et Métiers
Keywords: Nonlinear observers and filter design, Observer design, Robust estimation Abstract: For a class of nonlinear systems subject to disturbances, an observer is proposed to estimate time-varying intervals in which their state variables are guaranteed to stay all the time. The objective is to effectively deal with nonlinearities depending on unmeasured variables which have been usually treated as uncertainty in observer design. Focusing on nonlinearities in a polytopic form, this paper shows how an interval observer can replace nonlinearities in unmeasured variables by nonlinearities in estimated intervals. Theoretical guarantees and simulation comparisons are presented to demonstrate that the use of interval-dependent nonlinearities gives better estimates than the use of an overbounding observer.
Paper VI123-03.3
PDF · Video · Optimal Sensing Precision in Ensemble and Unscented Kalman Filtering (I)
Das, Niladri	Texas A&M University
Bhattacharya, Raktim	Texas A&M
Keywords: Nonlinear observers and filter design, Parametric optimization, Robust estimation Abstract: We consider the problem of selecting an optimal set of sensor precisions to estimate the states of a non-linear dynamical system using an Ensemble Kalman filter and an Unscented Kalman filter, which uses random and deterministic ensembles, respectively. Specifically, the goal is to choose, at run-time, a sparse set of sensor precisions for active-sensing that satisfies certain constraints on the estimated state covariance. In this paper, we show that this sensor precision selection problem is a semidefinite programming problem when we use l1 norm over precision vector as the surrogate measure to induce sparsity. We formulate a sensor selection scheme over multiple time steps, for certain constraints on the terminal estimated state covariance.
Paper VI123-03.4
PDF · Video · Eigen Value Analysis in Lower Bounding Uncertainty of Kalman Filter Estimates (I)
Das, Niladri	Texas A&M University
Bhattacharya, Raktim	Texas A&M
Keywords: Nonlinear observers and filter design, Parametric optimization, Robust estimation Abstract: In this paper we are concerned with the error-covariance lower-bounding problem in Kalman filtering: a sensor releases a set of measurements to the data fusion/estimation center, which has a perfect knowledge of the dynamic model, to allow it to estimate the states, while preventing it to estimate the states beyond a given accuracy. We propose a measurement noise manipulation scheme to ensure lower-bound on the estimation accuracy of states. Our proposed method ensures lower-bound on the steady state estimation error of Kalman filter, using mathematical tools from eigen value analysis.
Paper VI123-03.5
PDF · Video · A Globally Convergent State Observer for Multimachine Power Systems with Lossy Lines (I)
Bobtsov, Alexey	ITMO University
Ortega, Romeo	Supelec
Nikolaev, Nikolay	ITMO University
Schiffer, Johannes	Brandenburg University of Technology
Keywords: Nonlinear observers and filter design, Power systems, Parameter-varying systems Abstract: We present the first solution to the problem of estimation of the state of multimachine power systems with lossy transmission lines. We consider the classical three-dimensional "flux-decay" model of the power system and assume that the active and reactive power and the rotor angle at each generator is available for measurement|a scenario that is feasible with current technology. The design of the observer relies on two recent developments proposed by the authors: a parameter estimation based approach to the problem of state estimation and the use of the dynamic regressor extension and mixing technique to estimate these parameters. Thanks to the combination of these techniques it is possible to overcome the problem of lack of persistent excitation that stymies the application of standard observer designs. Simulation results illustrate the performance of the proposed observer.
Paper VI123-03.6
PDF · Video · High-Gain Observer-Based Output Feedback Control with Sensor Dynamic Governed by Parabolic PDE (I)
Ahmed-Ali, Tarek	Université De Caen Normandie
Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Khalil, Hassan K.	Michigan State Univ
Keywords: Output feedback control, Observer design, stability of distributed parameter systems Abstract: In this paper it is proposed to extend the result described in Khalil and Praly (2014) and the references therein, regarding the high-gain observer-based nonlinear control to the case of systems with diffusion sensor dynamic. Based on some usual hypotheses, we provide sufficient conditions involving the high-gain parameter and the length on the PDE sensor. In fact it is brought into light an explicit trade off between them: the larger the observer gain, the smaller the length of the PDE sensor needs to be. The stability analysis of the closed loop is based on a Lyapunov functional.
Paper VI123-03.7
PDF · Video · A Continuous-Discrete Adaptive Observer Design for Nonlinear Systems Subject to Sensor Nonlinearities (I)
Ahmed-Ali, Sofiane	IRSEEM/ESIGELEC
Magarotto, Eric	Universite De Caen Normandie, Laboratoire d'Automatique De Caen
Massieu, Jean-Francois	Universite De Caen Normandie, Laboratoire d'Automatique De Caen
Keywords: Nonlinear observers and filter design, Lyapunov methods Abstract: In this paper, we address the problem of nonlinear continuous-discrete adaptive observer design for a class of system with sampled data measurements subject to sensor nonlinearities. The main difficulty of the considered class of system is coming from the fact that the output equation contains unknown parameters which renders the design of a classical sampled data observer difficult. To overcome this difficulty, we propose a new online continuous-discrete adaptive observer which ensures a simultaneous exponential convergence of both states and parameters. Comparing to other observer structures, our design is characterized by a simpler structure thanks to the introduction of a parametric adaptation law. To show the efficiency of our proposed approach, numerical simulations have been performed for different values of sampling time. In addition, the delayed-sampled measurements case is also illustrated.
Paper VI123-03.8
PDF · Video · Distributed State Estimation for a Class of Jointly Observable Nonlinear Systems (I)
Yang, Guitao	Imperial College London
Rezaee, Hamed	Imperial College London
Parisini, Thomas	Imperial College & Univ. of Trieste
Keywords: Nonlinear observers and filter design, Observer design, Networked systems Abstract: State estimation for a class of nonlinear systems using a network of distributed observers is dealt with in this paper. We propose a network of observers, each of which has its own local measurements which may not be sufficient for observability of the system, while the joint measurements of the sensors in the network guarantees the observability. We derive sufficient conditions on the proposed observers such that the estimated states of each observer asymptotically converge to the states of the system using local measurements and the estimates of a subset of observers in its neighborhood. Accordingly, it is assumed that each observer has access to the estimates of its neighbors via a communication network. The main problem of existing distributed state estimation strategies in the literature is their limitation to linear systems or to nonlinear systems with observable nonlinearities (by considering nonlinearities as states to be estimated). However, based on the proposed strategy, distributed state estimation of a more general class of nonlinear systems can be devised. A numerical example is provided to evaluate the accuracy of the obtained results.
Paper VI123-03.9
PDF · Video · Stator Flux and Load Torque Observers for PMSM (I)
Bobtsov, Alexey	ITMO University
Pyrkin, Anton	ITMO University
Aranovskiy, Stanislav	CentraleSupelec - IETR
Nikolaev, Nikolay	ITMO University
Slita, Olga	ITMO University
Kozachek, Olga	ITMO University
Vo Quoc, Dat	ITMO University
Keywords: Nonlinear observers and filter design Abstract: In this paper, a stator flux observer and constant load torque estimation method are developed for non-salient permanent magnet synchronous motors. The methods described here are based on implementation of LTI filters and linear regression. The motor resistance and inductance are assumed to be known.
Paper VI123-03.10
PDF · Video · High-Gain Observer Design for Nonlinear Systems with Delayed Outputs (I)
Ania, Adil	Mouloud Mammeri Univetrsity of Tizi Ouzou
Zemouche, Ali	CRAN UMR CNRS 7039, University of Lorraine
Hamaz, Abdelghani	University of Mouloud Mammeri Tizi-Ouzou
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Bedouhene, Fazia	Laboratoire De Mathématiques Pures Et Appliquées(LMPA), Universi
Keywords: Observer design, Lyapunov methods, Systems with time-delays Abstract: This paper deals with high-gain nonlinear observer design for a class of triangularsystems with delayed output measurements. Based on a recent high-gain like observer design method, called HG/LMI observer, a larger bound of the time-delay is allowed compared to that obtained by using the standard high-gain methodology. Such a HG/LMI observer leadsto a significantly lower tuning parameter, which reduces the values of the observer gains and increases the maximum bound of the delay allowed to ensure exponential convergence. Indeed, an explicit relation between the maximum bound of the delay and the observer tuning parameteris inferred by using a Lyapunov-Krasovskii functional jointly with the Halanay inequality. Such a relation shows clearly the superiority of the use of the HG/LMI observer design methodology.

VI123-04
Finite-Time Control and Estimation of Uncertain Systems	Open Invited Session
Chair: Efimov, Denis	Inria
Co-Chair: Fridman, Leonid M.	National Autonomous University of Mexico
Organizer: Efimov, Denis	Inria
Organizer: Fridman, Leonid M.	National Autonomous University of Mexico
Paper VI123-04.1
PDF · Video · Adaptive Continuous Controllers Ensuring Prescribed Ultimate Bound for Uncertain Dynamical Systems (I)
Cruz-Ancona, Christopher D.	CINVESTAV-IPN
Estrada, Manuel A.	Universidad Nacional Autonoma De México
Fridman, Leonid M.	National Autonomous University of Mexico
Obeid, Hussein	Université De Technologie De Belfort-Montbéliard (UTBM)
Laghrouche, Salah	UTBM
Keywords: Sliding mode control, Adaptive control, Robust control Abstract: Within the framework of the classical problem of Lyapunov redesign, the barrier function-based adaptation control is presented. The proposed approach does not require the knowledge of an upper bound of the uncertainty. However, producing a continuous control signal adjusts the chattering problem and ensures that the solution will converge in finite time to a region with a priori prescribed ultimate bound.
Paper VI123-04.2
PDF · Video · Finite-Time Sliding Mode Control under Dynamic Event-Triggered Scheme (I)
Li, Jiarui	East China University of Science & Technology
Niu, Yugang	East China Univ of Science & Technology
Chen, Bei	Shanghai University of Engineering Science
Keywords: Sliding mode control, Networked systems, Output feedback control Abstract: In this work, we investigate the finite-time boundedness (FTB) problem for a class of continuous-time uncertain systems via sliding mode control (SMC) method. A dynamic event-triggered scheme is introduced to determine whether the measurement output will be transmitted. And then, a state observer is designed by means of the transmitted output information, based on which a sliding surface in the estimation space is construct. It is shown that the corresponding SMC law can drive the system trajectories onto the specified sliding surface in a finite (possibly short) time. Meanwhile, a partitioning strategy is introduced to analyze the FTB over both reaching phase and the sliding motion, respectively. Finally, a numerical simulation is given.
Paper VI123-04.3
PDF · Video · Finite-Time Boundedness of T-S Fuzzy Systems Subject to Injection Attacks: A Sliding Mode Control Method (I)
Zhang, Zhina	East China University of Science and Technology
Song, Jun	East China University of Science & Technology
Zou, Yuanyuan	Shanghai Jiao Tong University
Niu, Yugang	East China Univ of Science & Technology
Keywords: Sliding mode control, Application of nonlinear analysis and design, Stability of nonlinear systems Abstract: This paper studies the sliding mode control for T-S fuzzy systems in the framework of finite-time boundedness. It is assumed that the control signals are transmitted via vulnerable channels, where injection attacks might happen. A fuzzy sliding mode controller is firstly synthesized to guarantee the finite-time reachability of the prescribed sliding surface and attenuate the effect of the injection attacks. By introducing a partitioning strategy, the finite-time boundedness over both the reaching phase and the sliding motion phase are analyzed. Furthermore, sufficient criteria are derived such that the closed-loop system is finite-time bounded over the whole specified finite-time interval despite of the injection attacks. An optimal algorithm is further provided for searching ideal control gains with fewer energy demands. Finally, a simulation example verifies the proposed sliding mode control approach.
Paper VI123-04.4
PDF · Video · Homogeneous Output-Feedback Control (I)
Hanan, Avi	Tel-Aviv University
Jbara, Adam	Tel-Aviv University
Levant, Arie	Tel - Aviv University
Keywords: Output feedback control, Nonlinear observers and filter design, Sliding mode control Abstract: New types of homogeneous and homogeneous-in-bilimit filtering observers and differentiators are proposed and applied for the global robust homogeneous asymptotic output-feedback stabilization of disturbed integrator chains. The type of convergence (finite-time, fixed-time to any ball or just asymptotic) is determined by the chosen system homogeneity degree (HD). Output-feedback sliding-mode control is an important particular case. Stabilization accuracy is calculated in the presence of noises representable as a sum of possibly unbounded noises, each having a bounded multiple integral. Successful stabilization is demonstrated for very large noises and different HDs.
Paper VI123-04.5
PDF · Video · On Homogeneous Lyapunov Function Theorem for Evolution Equations (I)
Polyakov, Andrey	INRIA Lille Nord-Europe
Keywords: stability of distributed parameter systems, semigroup and operator theory, Stability of nonlinear systems Abstract: The existence of homogeneous Lyapunov function for a stable homogeneous ordinary differential equation (ODE) is proven by V. Zubov in 1958 and by L. Rosier in 1992. The present paper extends this result to evolution equations in Banach spaces.
Paper VI123-04.6
PDF · Video · Mixing Sliding Mode and Linear Observers for Second and Third Order Systems (I)
Andrieu, Vincent	Université De Lyon
Astolfi, Daniele	CNRS - Univ Lyon 1
Bernard, Pauline	MINES ParisTech
Keywords: Sliding mode control, Nonlinear observers and filter design, Stability of nonlinear systems Abstract: High-gain observers and sliding mode observers are two of the most common techniques to design observers (or differentiators) for lower triangular nonlinear dynamics. While sliding mode observers can handle bounded nonlinearities, high-gain linear techniques can handle global Lipschitz nonlinearities. In this preliminary paper, we present a novel observer design for second and third order systems which benefits from both techniques. More precisely, the proposed observer converges in finite-time and handles nonlinearities satisfying an incremental affine bound.
Paper VI123-04.7
PDF · Video · A Consistent Discretisation Method for Stable Homogeneous Systems Based on Lyapunov Function (I)
Sanchez, Tonametl	IPICYT
Polyakov, Andrey	INRIA Lille Nord-Europe
Efimov, Denis	Inria
Keywords: Lyapunov methods Abstract: In this paper we propose a discretisation scheme for continuous and asymptotically stable homogeneous systems. This method is based on the dynamics of the system projected on a level surface of a homogeneous Lyapunov function. The discretisation method is explicit and preserves the convergence rate of the continuous-time system.
Paper VI123-04.8
PDF · Video · A Finite Time Convergent Least-Squares Modification of the Dynamic Regressor Extension and Mixing Algorithm (I)
Palmisano, Marijan	Graz University of Technology
Reichhartinger, Markus	Graz University of Technology
Keywords: Nonlinear observers and filter design Abstract: The recently proposed Dynamic Regressor Extension and Mixing (DREM) algorithm can be used to estimate the parameters of structured uncertainties contained in the mathematical model of a plant. In order to provide a less sensitive adaptation a modification of the parameter adaptation law is presented. Additionally, a least-squares based modification of the DREM estimator which is less sensitive to the unavoidable mismatch between a plant and its model is proposed in this paper. The modified estimator yields significantly better estimation results as illustrated by the conducted real-world experiment and its parameter estimates also converge within finite time.
Paper VI123-04.9
PDF · Video · Robust Global Stabilization of the Third Order Reaction Wheel Pendulum System (I)
Gutiérrez, Diego	Universidad Nacional Autónoma De México
Mercado Uribe, José ángel	Universidad Nacional Autonoma De Mexico-UNAM
Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Fridman, Leonid M.	National Autonomous University of Mexico
Keywords: Sliding mode control, Disturbance rejection, Stability of nonlinear systems Abstract: In this paper, the global stabilization of the Reaction Wheel Pendulum, without taking into account the wheel position, is addressed despite the presence of Lipschitz disturbances and/or uncertainties in the model. Using two Second Order Continuous Sliding Modes Algorithms, the control task is performed, reaching finite-time convergence in one part of the dynamics and generating a continuous control signal. Finally, some simulations and experiments in the real systems are presented to test the proposed algorithms and compare them with a linear feedback controller.
Paper VI123-04.10
PDF · Video · Control of Fully Actuated Mechanical Systems Via Super-Twisting Based Lyapunov Redesign (I)
Estrada, Manuel A.	Universidad Nacional Autonoma De México
Fridman, Leonid M.	National Autonomous University of Mexico
Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Keywords: Sliding mode control, Stability of nonlinear systems, Robust control Abstract: The problem control of fully actuated of mechanical systems under uncertainties is considered. With this aim a concept of Lyapunov redesign is revisited. The derivative of the Lyapunov function for a nominal model of the robot is used for the sliding surface design. This surface permits to design a super-twisting controller allowing to compensate the Lipschitz uncertainties, providing theoretically exact convergence of the states of uncertain system to the origin by means of a continuous control signal. The proposed result is illustrated for simulation example controlling an uncertain planar robot.
Paper VI123-04.11
PDF · Video · Analysis of Sliding-Mode Control Systems with Unmatched Disturbances Altering the Relative Degree (I)
Posielek, Tobias	German Aerospace Center (DLR)
Wulff, Kai	Tech. Univ. Ilmenau
Reger, Johann	TU Ilmenau
Keywords: Sliding mode control, Disturbance rejection, Discontinuous control Abstract: We consider sliding-mode control systems subject to unmatched disturbances. Classical first-order sliding-mode techniques are capable to compensate unmatched disturbances if differentiations of the output of sufficiently high order are included in the sliding variable. Commonly for such disturbances it is assumed that the relative degree of the system is not changed. In this contribution we study the impact of disturbances that alter the relative degree (of the process) on the closed-loop control system with the classical first-order sliding-mode design. We analyse the reaching and sliding phase of the resulting closed-loop system. We show that uniqueness of the solution may be lost and derive conditions for such behaviour. We present conditions for the stability of the sliding-mode dynamics and analyse the disturbance rejection properties. For a second-order example system we evaluate the obtained conditions explicitly and show that attractivity of the sliding manifold may be lost. Moreover, a simulation case study of a two-mass spring-damper system illustrates the various closed-loop behaviours.
Paper VI123-04.12
PDF · Video · Performance Preserving Integral Extension of Linear and Homogeneous State-Feedback Controllers (I)
Seeber, Richard	Graz University of Technology
Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Keywords: Sliding mode control, Lyapunov methods, Structural properties Abstract: The problem of extending an existing state-feedback controller by an integrator is considered. A structural insight into the design of such controllers is presented for the linear case, which allows to preserve the performance of the given controller in a certain sense. Using this insight, a second order homogeneous state feedback controller with discontinuous integral action is proposed, which can reject arbitrary slope bounded, i.e., Lipschitz continuous, perturbations. By means of Lyapunov methods, stability conditions for the closed loop system and a bound for its finite convergence time are derived. Numerical simulations illustrate the results and provide further insight into the tuning of the proposed approach.
Paper VI123-04.13
PDF · Video · Semi-Implicit Euler Discretization for Homogeneous Observer-Based Control: One Dimensional Case (I)
Michel, Loïc	Centrale Nantes
Ghanes, Malek	Centrale Nantes
Plestan, Franck	Ecole Centrale De Nantes-LS2N
Aoustin, Yannick	CNRS, Univ of Nantes
Barbot, Jean Pierre	ENSEA
Keywords: Sliding mode control, Observer design, Disturbance rejection Abstract: It is well known that the implicit Euler strategy is a chattering-free implementation of sliding mode algorithms. In this paper, we propose to mix explicit and implicit discretizations in order to deal with homogeneous sliding mode control. More precisely, a semi-implicit discretization for homogeneous observer-based sliding mode control is proposed in one dimensional case with a theoretical stability proof. The effectiveness of the proposed solution is illustrated in simulation by a comparison with explicit Euler discretization.
Paper VI123-04.14
PDF · Video · Parameter Preference for the Continuous Super-Twisting-Like Algorithm Based on H-Infinity Norm Analysis (I)
Zhang, Daipeng	TU Ilmenau
Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Reger, Johann	TU Ilmenau
Keywords: Sliding mode control, Robust control, Lyapunov methods Abstract: In variable structured systems, plenty of designs are built to be homogeneous. Such unperturbed homogeneous dynamics with negative homogeneous degree guarantee finite time convergence. Previous studies provide lower bounds for parameters that result in such finite-time convergence property. In this paper, we propose a new perspective on parameter preference, based on H-infinity norm analysis. Contrary to other studies, which propose such norm non-homogeneous or homogeneous, yet of non-zero degree, we build a homogeneous H-infinity norm of homogeneous degree zero, thus global and constant. Based on data collected of this norm on the continuous super-twisting-like algorithm, we give recommendations for choosing the parameters.
Paper VI123-04.15
PDF · Video · Sliding Mode Control with Chattering Attenuation and Hardware Constraints in Spacecraft Applications (I)
Mancini, Mauro	Politecnico Di Torino
Capello, Elisa	Politecnico Di Torino, CNR-IEIIT
Punta, Elisabetta	CNR-IEIIT
Keywords: Sliding mode control, Systems with saturation, Tracking Abstract: Many practical issues should be considered when synthesizing a control system for real applications. In this paper the main objective is the evaluation of the performance of a Sliding Model Controller (SMC) for spacecraft applications, in which implementation issues are included. The key features of the proposed practical design are: (i) chattering attenuation, in which an hyperbolic tangent is considered, and (ii) hardware constraints, in which the SMC update frequency is reduced and saturations on the actuation system are included. A comparison between a first order and a super-twisting SMC is performed, including disturbances on the mathematical model. Moreover, computational effort and error accuracy are evaluated for both the proposed strategies, showing the performance of the proposed implementation solutions.
Paper VI123-04.16
PDF · Video · On the Discretization of Robust Exact Filtering Differentiators (I)
Carvajal Rubio, Jose Eduardo	Cinvestav Ipn Gdl
Sánchez Torres, Juan Diego	CINVESTAV-IPN Unidad Guadalajara
Defoort, Michael	University of Valenciennes
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Keywords: Nonlinear observers and filter design, Sliding mode control, Observer design Abstract: The calculation of time derivatives has a state-space representation of the form of a perturbed linear system. This description enables the application of the so-called robust filtering differentiator, i.e. a non-linear state observer with extended state and homogeneous input injection terms. Therefore, given the practical importance of having an accurate discretization of such differentiator, this paper presents the design of two discrete-time implementation schemes. The first discrete-time realization is explicit, while the second one is implicit. The implicit allows reducing the numerical chattering phenomenon caused by the explicit discretization of discontinuous terms. Numerical comparisons between the presented scheme and an existing discrete-time representation show that the performance of the proposed explicit implementation scheme is similar to the most recent results from the literature. Finally, the proposed implicit discrete-time realization presents better accuracy, especially when considering large sampling periods.
Paper VI123-04.17
PDF · Video · Sliding Mode Strategies for Monitoring and Compensation of Cyber-Attacks to Cyber-Physical Systems (I)
Azevedo Filho, Jair Luiz	Federal University of Rio De Janeiro
Nunes, Eduardo Vieira Leao	COPPE - Federal Univ. of Rio De Janeiro
Hsu, Liu	COPPE - Federal Univ of Rio De Janeiro
Keywords: Sliding mode control, Disturbance rejection, Output feedback control Abstract: In this paper, the problem of detection and reconstruction of cyber-attacks in linear cyber-physical systems is considered. The class of cyber-attacks described in this paper can corrupt the states or the outputs of a cyber-physical system. An attack monitor based on High-Order sliding mode is proposed to reconstruct the cyber-attack. A First Order Approximation Filter is proposed to ensure global stability and convergence results. Using sliding mode techniques, an attack compensation is developed for square plants, guarateeing finite time convergence to the output tracking while rejecting the effects of the cyber-attack.
Paper VI123-04.18
PDF · Video · Dynamic Output Feedback Sliding Mode Control for Non-Minimum Phase Systems with Application to an Inverted Pendulum
Feng, Jiehua	China University of Petroleum (East China)
Gao, Shouli	China University of Petroleum (East China)
Zhao, Dongya	China University of Petroleum (East China)
Yan, Xing-Gang	University of Kent
Spurgeon, Sarah K.	University College London
Keywords: Decentralized control, Sliding mode control, Output feedback control Abstract: In this paper, a class of nonlinear systems is considered, where the nominal system representation is allowed to be non-minimum phase. A sliding surface is proposed which is a function of the measured system output and an estimated state. A linear coordinate transformation is introduced so that the stability analysis of the reduced order sliding mode dynamics can be conveniently performed. A robust output feedback sliding mode control (OFSMC) is then designed to drive the system states to the sliding surface in finite time and maintain a sliding motion thereafter. A simulation example is used to demonstrate the effectiveness of the proposed method and the method is successfully applied to an inverted pendulum.

VI123-05
Machine Learning and Model Predictive Control	Open Invited Session
Chair: Lucia, Sergio	TU Berlin
Co-Chair: Mesbah, Ali	University of California, Berkeley
Organizer: Lucia, Sergio	TU Berlin
Organizer: Mesbah, Ali	University of California, Berkeley
Paper VI123-05.1
PDF · Video · Tustin Neural Networks: A Class of Recurrent Nets for Adaptive MPC of Mechanical Systems (I)
Pozzoli, Simone	Politecnico Di Milano
Gallieri, Marco	University of Cambridge
Scattolini, Riccardo	Politecnico Di Milano
Keywords: Nonlinear predictive control, Data-based control, Adaptive control Abstract: The use of recurrent neural networks to represent the dynamics of unstable systems is difficult due to the need to properly initialize their internal states, which in most of the cases do not have any physical meaning, consequent to the non-smoothness of the optimization problem. For this reason, in this paper focus is placed on mechanical systems characterized by a number of degrees of freedom, each one represented by two states, namely position and velocity. For these systems, a new recurrent neural network is proposed: Tustin-Net. Inspired by second-order dynamics, the network hidden states can be straightforwardly estimated, as their differential relationships with the measured states are hard-coded in the forward pass. The proposed structure is used to model a double inverted pendulum and for model-based Reinforcement Learning, where an adaptive Model Predictive Controller scheme using the Unscented Kalman Filter is proposed to deal with parameter changes in the system.
Paper VI123-05.2
PDF · Video · Learning-Based Funnel-MPC for Output-Constrained Nonlinear Systems (I)
Berger, Thomas	Universität Paderborn
Kästner, Carolin	Technische Universität Ilmenau
Worthmann, Karl	Technische Universität Ilmenau
Keywords: Predictive control, Adaptive control, Digital implementation Abstract: We exploit an adaptive control technique, namely funnel control, to establish both initial and recursive feasibility in Model Predictive Control (MPC) for output-constrained nonlinear systems. Moreover, we show that the resulting feedback controller outperforms the funnel controller both w.r.t. the required sampling rate for a zero-order-hold implementation and required control action. We further propose a combination of funnel control and MPC, exploiting the performance guarantees of the model-free funnel controller during a learning phase and the advantages of the model-based MPC scheme thereafter.
Paper VI123-05.3
PDF · Video · Optimal Training of Echo State Networks Via Scenario Optimization (I)
Bugliari, Luca	Politecnico Di Milano
Fagiano, Lorenzo	Politecnico Di Milano
Terzi, Enrico	Politecnico Di Milano
Farina, Marcello	Politecnico Di Milano
Scattolini, Riccardo	Politecnico Di Milano
Keywords: Randomized algorithms, Robust estimation, Uncertainty descriptions Abstract: Echo State Networks (ESNs) are widely-used Recurrent Neural Networks. They are dynamical systems including, in state-space form, a nonlinear state equation and a linear output transformation. The common procedure to train ESNs is to randomly select the parameters of the state equation, and then to estimate those of the output equation via a standard least squares problem. Such a procedure is repeated for different instances of the random parameters characterizing the state equation, until satisfactory results are achieved. However, this trial-and-error procedure is not systematic and does not provide any guarantee about the optimality of the identification results. To solve this problem, we propose to complement the identification procedure of ESNs by applying results in scenario optimization. The resulting training procedure is theoretically sound and allows one to link precisely the number of identification instances to a guaranteed optimality bound on relevant performance indexes, such as the Root Mean Square error and the FIT index of the estimated model evaluated over a validation data-set. The proposed procedure is finally applied to the simulated model of a pH neutralization process: the obtained results confirm the validity of the approach.
Paper VI123-05.4
PDF · Video · Efficient Calibration of Embedded MPC (I)
Forgione, Marco	SUPSI-USI
Piga, Dario	SUPSI-USI
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Predictive control, Control of constrained systems Abstract: Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challenge for the practitioner applying MPC is the need of tuning a large number of parameters such as prediction and control horizons, weight matrices of the MPC cost function, and observer gains, according to different trade-offs. The MPC design task is even more involved when the control law has to be deployed to an embedded hardware unit endowed with limited computational resources. In this case, real-time implementation requirements limit the complexity of the applicable MPC configuration, giving rise to additional design tradeoffs and requiring to tune further parameters, such as the sampling time and the tolerances of the on-line numerical solver. To take into account closed-loop performance and real-time requirements, in this paper we tackle the embedded MPC design problem using a global, data-driven optimization approach. We showcase the potential of this approach by tuning an MPC controller on two hardware platforms characterized by largely different computational capabilities.
Paper VI123-05.5
PDF · Video · Machine Learning Assisted Solutions of Mixed Integer MPC on Embedded Platforms (I)
Löhr, Yannik	Ruhr-University Bochum
Klauco, Martin	Slovak University of Technology in Bratislava
Fikar, Miroslav	Slovak University of Technology in Bratislava
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Nonlinear predictive control, Data-based control, Energy systems Abstract: Many control applications, especially in the field of energy systems, require a simultaneous decision for continuous and binary values of control inputs. In optimal control methods like model predictive control (MPC), this leads to the problem of solving expensive mixed-integer programs online. As this solution in practice has to be calculated with low cost embedded hardware with a low energy demand, it is necessary to reduce the computational demand in advance. We present an approach to replacing the mixed-integer program by a simpler quadratic program by means of learning techniques. To be more specific, we design a neural network and a support vector machine to classify the optimal control policies for the binary inputs offline and evaluate this decision in the online step as basis for the solution of the quadratic program. As a result, we achieve a controller suitable for implementation on embedded hardware. We demonstrate its applicability for a domestic heating system. The results indicate a very high quality of the approximation of the primary optimal controller that solves mixed-integer programs online.
Paper VI123-05.6
PDF · Video · Robust Adaptive Control with Active Learning for Fed-Batch Process Based on Approximate Dynamic Programming (I)
Byun, Ha-Eun	KAIST
Kim, Boeun	University of Wisconsin – Madison
Lee, Jay H.	KAIST
Keywords: Stochastic optimal control problems, Adaptive control, Robust control Abstract: Batch process is often subject to a high degree of uncertainty in raw material quality and other initial feedstock conditions. One of the key objectives in operating a batch process is achieving consistent performance and constraint satisfaction in the presence of these uncertainties. This study presents a method for optimal control of a fed-batch process, which can actively and robustly cope with system uncertainty. As in dual control, the method aims to achieve an optimal balance between control actions (exploitation) and probing actions (exploration), leading to improved process performance by actively reducing system uncertainty. An optimal solution of the dual control problem can be found by stochastic dynamic programming but it is computationally intractable in most practical cases. In this study, an approximate dynamic programming (ADP) method for solving the dual control problem is tailored to a batch process which involves non-stationary and nonlinear dynamics. Rewards are formulated to maximize a given end objective while satisfying path constraints. Performance of the ADP-based dual controller is tested on a fed-batch bioreactor with two uncertain parameters.
Paper VI123-05.7
PDF · Video · Learning Approximate Semi-Explicit Hybrid MPC with an Application to Microgrids (I)
Masti, Daniele	IMT School for Advanced Studies
Pippia, Tomas	Delft University of Technology
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
De Schutter, Bart	Delft University of Technology
Keywords: Numerical methods for optimal control, Optimal control of hybride systems, Predictive control Abstract: We present a semi-explicit formulation of model predictive controllers for hybrid systems with feasibility guarantees. The key idea is to use a machine-learning approach to learn a compact predictor of the integer/binary components of optimal solutions of the multiparametric mixed-integer linear optimization problem associated with the controller, so that, on-line, only a linear programming problem must be solved. In this scheme, feasibility is ensured by a simple rule-based engine that corrects the binary configuration only when necessary. The performance of the approach is assessed on a well known benchmark for which explicit controllers based on domain-specific knowledge are already available. Simulation results show how our proposed method considerably lowers computation time without deteriorating closed-loop performance.
Paper VI123-05.8
PDF · Video · Reinforcement Learning Based on Real-Time Iteration NMPC (I)
Zanon, Mario	IMT Institute for Advanced Studies Lucca
Kungurtsev, Vyacheslav	Czech Technical University
Gros, Sebastien	NTNU
Keywords: Nonlinear predictive control, Real-time optimal control Abstract: Reinforcement Learning (RL) has proven a stunning ability to learn optimal policies from data without any prior knowledge on the process. The main drawback of RL is that it is typically very difficult to guarantee stability and safety. On the other hand, Nonlinear Model Predictive Control (NMPC) is an advanced model-based control technique which does guarantee safety and stability, but only yields optimality for the nominal model. Therefore, it has been recently proposed to use NMPC as a function approximator within RL. While the ability of this approach to yield good performance has been demonstrated, the main drawback hindering its applicability is related to the computational burden of NMPC, which has to be solved to full convergence. In practice, however, computationally efficient algorithms such as the Real-Time Iteration (RTI) scheme are deployed in order to return an approximate NMPC solution in very short time. In this paper we bridge this gap by extending the existing theoretical framework to also cover RL based on RTI NMPC. We demonstrate the effectiveness of this new RL approach with a nontrivial example modeling a challenging nonlinear system subject to stochastic perturbations with the objective of optimizing an economic cost.
Paper VI123-05.9
PDF · Video · Reinforcement Learning for Mixed-Integer Problems Based on MPC (I)
Gros, Sebastien	NTNU
Zanon, Mario	IMT Institute for Advanced Studies Lucca
Keywords: Predictive control, Adaptive control, Data-based control Abstract: Model Predictive Control has been recently proposed as policy approximation for Reinforcement Learning, offering a path towards safe and explainable Reinforcement Learning. This approach has been investigated for Q-learning and actor-critic methods, both in the context of nominal Economic MPC and Robust (N)MPC, showing very promising results. In that context, actor-critic methods seem to be the most reliable approach. Many applications include a mixture of continuous and integer inputs, for which the classical actor-critic methods need to be adapted. In this paper, we present a policy approximation based on mixed-integer MPC schemes, and propose a computationally inexpensive technique to generate exploration in the mixed-integer input space that ensures a satisfaction of the constraints. We then propose a simple compatible advantage function approximation for the proposed policy, that allows one to build the gradient of the mixed-integer MPC-based policy.
Paper VI123-05.10
PDF · Video · Non-Cooperative Distributed MPC with Iterative Learning (I)
Hu, Haimin	University of Pennsylvania
Gatsis, Konstantinos	University of Oxford
Morari, Manfred	ETH Zurich
Pappas, George J.	Univ of Pennsylvania
Keywords: Decentralized control, Data-based control, model predictive control for distributed parameter systems Abstract: This paper presents a novel framework of distributed learning model predictive control (DLMPC) for multi-agent systems performing iterative tasks. The framework adopts a non-cooperative strategy in that each agent aims at optimizing its own objective. Local state and input trajectories from previous iterations are collected and used to recursively construct a time-varying safe set and terminal cost function. In this way, each subsystem is able to iteratively improve its control performance and ensure feasibility and stability in every iterations. No communication among subsystems is required during online control. Simulation on a benchmark example shows the efficacy of the proposed method.
Paper VI123-05.11
PDF · Video · Learning Affine Predictors for MPC of Nonlinear Systems Via Artificial Neural Networks (I)
Masti, Daniele	IMT School for Advanced Studies
Smarra, Francesco	Università Degli Studi Dell'Aquila
D'Innocenzo, Alessandro	Università Degli Studi Di L'Aquila
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Data-based control, Nonlinear predictive control, Predictive control Abstract: Nonlinear model predictive control (MPC) problems can be well approximated by linear time-varying (LTV) MPC formulations in which, at each sampling step, a quadratic programming (QP) problem based on linear predictions is constructed and solved at runtime. To reduce the associated computation burden, in this paper we explore and compare two methodologies for learning the entire output prediction over the MPC horizon as a nonlinear function of the current state but affine with respect to the sequence of future control moves to be optimized. Such a learning process is based on input/output data collected from the process to be controlled. The approach is assessed in a simulation example and compared to other similar techniques proposed in the literature, showing that it provides accurate predictions of the future evolution of the process and good closed-loop performance of the resulting MPC controller. Guidelines for tuning the proposed method to achieve a desired memory occupancy / quality of fit tradeoff are also given.
Paper VI123-05.12
PDF · Video · Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control (I)
Zhu, Jia-Jie	Max Planck Institute for Intelligent Systems
Martius, Georg	Max Planck Institute for Intelligent Systems
Keywords: Parametric optimization, Optimal control of hybride systems Abstract: Today's fast linear algebra and numerical optimization tools have pushed the frontier of model predictive control (MPC) forward, to the efficient control of highly nonlinear and hybrid systems. The field of hybrid MPC has demonstrated that exact optimal control law can be computed, e.g., by mixed-integer programming (MIP) under piecewise-affine (PWA) system models. Despite the elegant theory, online solving hybrid MPC is still out of reach for many applications. We aim to speed up MIP by combining geometric insights from hybrid MPC, a simple-yet-effective learning algorithm, and MIP warm start techniques. Following a line of work in approximate explicit MPC, the proposed learning-control algorithm, LNMS, gains computational advantage over MIP at little cost and is straightforward for practitioners to implement.
Paper VI123-05.13
PDF · Video · Towards Safe Neural Network Supported Model Predictive Control (I)
Zieger, Tim	IAV, Otto-von-Guericke-Universität Magdeburg
Savchenko, Anton	Otto-von-Guericke-Universität Magdeburg
Oehlschlaegel, Thimo	IAV GmbH
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Predictive control, Control of constrained systems, Robust control Abstract: Model Predictive Control has proven to be a universal and flexible method to control complex nonlinear system with guaranteed constraint satisfaction. However, high dependency on model quality often renders it inappropriate for hard to model systems. On the other hand, machine learning methods show great performance when approximating functions based on data. This capability for learning with poor a priori knowledge, however, comes at the cost of low predictability and lack of safety guarantees. To overcome these drawbacks we illustrate how a neural network can be setup as a nonlinear feedforward control that augments the MPC control signal to approximate a desired control behaviour. For instance, it could aim to mimic the control behaviour of a human driver, while the underlying MPC exploits prior knowledge. Moreover, to preserve constraint satisfaction, we suggest to restrict the range of neural network outputs such that it intrinsically satisfies control input constraints. Subsequently, we represent the neural network control signal as a disturbance which enables the application of tube MPC to retain state constraints satisfaction at the cost of introducing some conservatism. We demonstrate these concepts via simulation, test and highlight both the advantages and the drawbacks of the proposed control structure.
Paper VI123-05.14
PDF · Video · Learning Markov Jump Affine Systems Via Regression Trees for MPC (I)
Smarra, Francesco	Università Degli Studi Dell'Aquila
D'Innocenzo, Alessandro	Università Degli Studi Di L'Aquila
Keywords: Data-based control, Predictive control, Numerical methods for optimal control Abstract: Model Predictive Control is a well consolidated technique to design optimal control strategies, leveraging the capability of a mathematical model to predict a system's behavior over a time horizon. However, building physics-based models for complex large-scale systems can be cost and time prohibitive. To overcome this problem we propose a methodology to exploit Regression Trees technique in order to build a Markov Jump System model of a large-scale system using historical data, and apply Model Predictive Control. A comparison with an optimal benchmark and related techniques is provided on an energy management system to validate the performance of the proposed methodology.
Paper VI123-05.15
PDF · Video · Distributed Model Predictive Safety Certification for Learning-Based Control (I)
Muntwiler, Simon	ETH Zürich
Wabersich, Kim Peter	ETH Zurich
Carron, Andrea	ETH Zurich
Zeilinger, Melanie N.	ETH Zurich
Keywords: Distributed robust controller synthesis, Control of constrained systems, Data-based control Abstract: While distributed algorithms provide advantages for the control of complex large-scale systems by requiring a lower local computational load and less local memory, it is a challenging task to design high-performance distributed control policies. Learning-based control algorithms offer promising opportunities to address this challenge, but generally cannot guarantee safety in terms of state and input constraint satisfaction. A recently proposed safety framework for centralized linear systems ensures safety by matching the learning-based input online with the initial input of a model predictive control law capable of driving the system to a terminal set known to be safe. We extend this idea to derive a distributed model predictive safety certification (DMPSC) scheme, which is able to ensure state and input constraint satisfaction when applying any learning-based control algorithm to an uncertain distributed linear system with dynamic couplings. The scheme is based on a distributed tube-based model predictive control (MPC) concept, where subsystems negotiate local tube sizes among neighbors in order to mitigate restrictiveness of the safety approach. In addition, we present a technique for generating a structured ellipsoidal robust positive invariant tube. In numerical simulations, we show that the safety framework ensures constraint satisfaction for an initially unsafe control policy and allows to improve overall control performance compared to robust distributed MPC.
Paper VI123-05.16
PDF · Video · Maximum Likelihood Methods for Inverse Learning of Optimal Controllers (I)
Menner, Marcel	ETH Zurich
Zeilinger, Melanie N.	ETH Zurich
Keywords: Data-based control, Learning for control, Constrained control Abstract: This paper presents a framework for inverse learning of objective functions for constrained optimal control problems, which is based on the Karush-Kuhn-Tucker (KKT) conditions. We discuss three variants corresponding to different model assumptions and computational complexities. The first method uses a convex relaxation of the KKT conditions and serves as the benchmark. The main contribution of this paper is the proposition of two learning methods that combine the KKT conditions with maximum likelihood estimation. The key benefit of this combination is the systematic treatment of constraints for learning from noisy data with a branch-and-bound algorithm using likelihood arguments. This paper discusses theoretic properties of the learning methods and presents simulation results that highlight the advantages of using the maximum likelihood formulation for learning objective functions.
Paper VI123-05.17
PDF · Video · Deterministic Global Nonlinear Model Predictive Control with Neural Networks Embedded (I)
Doncevic, Danimir T.	RWTH Aachen University
Schweidtmann, Artur M.	Aachener Verfahrenstechnik - Process Systems Engineering, RWTH A
Vaupel, Yannic	RWTH Aachen University
Schäfer, Pascal	Aachener Verfahrenstechnik - Process Systems Engineering, RWTH A
Caspari, Adrian	RWTH Aachen University
Mitsos, Alexander	RWTH Aachen University
Keywords: Data-based control, Model reduction, Nonlinear predictive control Abstract: Nonlinear model predictive control requires the solution of nonlinear programs with potentially multiple local solutions. Here, deterministic global optimization can guarantee to find a global optimum. However, its application is currently severely limited by computational cost and requires further developments in problem formulation, optimization solvers, and computing architectures. In this work, we propose a reduced space formulation for the global optimization of problems with recurrent neural networks (RNN) embedded, based on our recent work on feed-forward artificial neural networks embedded. The method reduces the dimensionality of the optimization problem significantly, lowering the computational cost. We implement the NMPC problem in our open-source solver MAiNGO and solve it using parallel computing on 40 cores. We demonstrate real-time capability for the illustrative van de Vusse CSTR case study. We further propose two alternatives to reduce computational time: i) reformulate the RNN model by exposing a selected state variable to the optimizer; ii) replace the RNN with a neural multi-model. In our numerical case studies each proposal results in a reduction of computational time by an order of magnitude.
Paper VI123-05.18
PDF · Video · Toward Safe Dose Delivery in Plasma Medicine Using Projected Neural Network-Based Fast Approximate NMPC (I)
Bonzanini, Angelo Domenico	UC Berkeley
Paulson, Joel	The Ohio State University
Graves, David B.	University of California at Berkeley
Mesbah, Ali	University of California, Berkeley
Keywords: Nonlinear predictive control, Robust control applications Abstract: Atmospheric pressure plasma jets (APPJs) are increasingly used for biomedical applications. Reproducible and effective operation of APPJs hinges on controlling the nonlinear effects of plasma on a target substrate in the face of intrinsic variabilities of the plasma as well as exogenous disturbances. This paper presents a low-memory fast approximate nonlinear model predictive control (NMPC) strategy for an APPJ with prototypical applications in plasma medicine. The NMPC objective is to regulate the delivery of the cumulative thermal effects of plasma to a substrate, while adhering to constraints pertaining to a patient's safety and comfort. Deep neural networks are used to approximate the implicit NMPC law with a cheap-to-evaluate explicit control law that has low memory requirements. Robust constraint satisfaction is guaranteed by projecting the output of the neural network onto a set that ensures the state stays within an appropriately defined invariant set. Closed-loop simulations and real-time control experiments indicate that the proposed approximate NMPC strategy is effective in handling nonlinear control costs at fast sampling times, while guaranteeing satisfaction of safety-critical system constraints. This work is a crucial step toward fast NMPC of safety-critical plasma applications using resource-limited embedded systems.
Paper VI123-05.19
PDF · Video · Identification of State-Space Linear Parameter-Varying Models Using Artificial Neural Networks (I)
Bao, Yajie	The University of Georgia
Mohammadpour Velni, Javad	The University of Georgia
Basina, Aditya	Michigan Tech University
Shahbakhti, Mahdi	University of Alberta
Keywords: LPV system identification, Predictive control, Linear parameter-varying systems Abstract: This paper presents an integrated structure of artificial neural networks, named state integrated matrix estimation (SIME), for linear parameter-varying (LPV) model identification. The proposed method simultaneously estimates states and explores structural dependency of matrix functions of a representative LPV model only using inputs/outputs data. The case with unknown (unmeasurable) states is circumvented by SIME using two estimators of the same state: one estimator represented by an ANN and the other obtained by LPV model equations. Minimizing the difference between these two estimators, as part of the cost function, is used to guarantee their consistency. The results from a complex nonlinear system, namely a reactivity controlled compression ignition (RCCI) engine, show high accuracy of the state-space LPV models obtained using the proposed SIME while requiring minimal hyperparameters tuning.
Paper VI123-05.20
PDF · Video · Online Learning Robust MPC: An Exploration-Exploitation Approach (I)
Manzano, Jose Maria	University of Seville
Calliess, Jan-Peter	University of Oxford
Muñoz de la Peña, David	Universidad De Sevilla
Limon, Daniel	Universidad De Sevilla
Keywords: Data-based control, Control of constrained systems, Tracking Abstract: This paper presents a predictive controller whose model is based on input-output data of the nonlinear system to be controlled. It uses a Lipschitz interpolation technique in which new data may be included in the database in real time, so the controller improves the system model online. An exploration and exploitation policy is proposed, allowing the controller to robustly and cautiously steer the system to the best reachable reference, even if the model lacks data in such region. The conditions needed to ensure recursive feasibility in the presence of output and input constraints and in spite of the uncertainties are given. The results are illustrated in a simulated case study.

VI123-06
On Nonlinear Infinite Dimensional Systems	Open Invited Session
Chair: Prieur, Christophe	CNRS
Co-Chair: Mironchenko, Andrii	University of Passau
Organizer: Marx, Swann	CNRS
Organizer: Wirth, Fabian	University of Passau
Organizer: Prieur, Christophe	CNRS
Paper VI123-06.1
PDF · Video · Sufficient Conditions for Pre-Compactness of State Trajectories (I)
Zwart, Hans	University of Twente
Keywords: stability of distributed parameter systems, control of hyperbolic systems and conservation laws, Lyapunov methods Abstract: In this paper we give suffcient conditions on a semi-linear differential equation ensuring the pre-compactness of its solution. The result is illustrated by two examples of vibrating strings in a network with a static damper.
Paper VI123-06.2
PDF · Video · A Spectral Small-Gain Condition for Input-To-State Stability of Infinite Networks (I)
Kawan, Christoph	Ludwig-Maximilians-Universität München
Mironchenko, Andrii	University of Passau
Swikir, Abdalla	Technical University of Munich
Noroozi, Navid	Otto Von Guericke University Magdeburg
Zamani, Majid	University of Colorado Boulder
Keywords: Input-to-State Stability, Control of interconnected systems, Lyapunov methods Abstract: This paper presents a tight small-gain theorem for networks composed of infinitely many finite-dimensional subsystems. Assuming that each subsystem is exponentially input-to-state stable, we show that if the gain operator, collecting all the information about the internal Lyapunov gains, has a spectral radius less than one, the overall infinite network is exponentially input-to-state stable. We illustrate the effectiveness of our result by applying it to traffic networks.
Paper VI123-06.3
PDF · Video · Shape-Based Nonlinear Model Reduction for 1D Conservation Laws (I)
Nikitin, Denis	Russian Academy of Sciences
Canudas de Wit, Carlos	CNRS-GIPSA-Lab
Frasca, Paolo	CNRS, GIPSA-Lab, Grenoble
Keywords: Model reduction, Infinite-dimensional systems Abstract: We present a novel method for model reduction of one-dimensional conservation law to the dynamics of the parameters describing the approximate shape of the solution. Depending on the parametrization, each parameter has a well-defined physical meaning. The obtained ODE system can be used for the estimation and control purposes. The model reduction is performed by minimizing the divergence of flows between the original and reduced systems, and we show that this is equivalent to the minimization of the Wasserstein distance derivative. The method is then tested on the heat equation and on the LWR (Lighthill-Whitham-Richards) model for vehicle traffic.
Paper VI123-06.4
PDF · Video · On Local Stability of Equilibrium Profiles of Nonisothermal Axial Dispersion Tubular Reactors (I)
Hastir, Anthony	University of Namur
Winkin, Joseph J.	University of Namur (UNamur)
Dochain, Denis	Univ. Catholique De Louvain
Keywords: stability of distributed parameter systems, Stability of nonlinear systems, Chemical engineering Abstract: Exponential (exp.) stability of equilibrium profiles for a nonisothermal axial dispersion tubular reactor is considered. This model is described by nonlinear partial differential equations (PDEs) whose state components are the temperature, the reactant and the product concentrations inside of the reactor. It is shown how to get appropriate local exponential stability of the equilibria for the nonlinear model, on the basis of stability properties of its linearized version and some relaxed Fréchet differentiability conditions of the nonlinear semigroup generated by the dynamics. In the case where the reactor can exhibit only one equilibrium profile, the latter is always locally exponentially stable for the nonlinear system. When three equilibria are highlighted, local bistability is established, i.e. the pattern (locally) "(exp.) stable -- unstable -- (exp.) stable" holds. The results are illustrated by some numerical simulations. As perspectives, the concept of state feedback is also used in order to show a manner to stabilize exponentially a nonlinear system on the basis of its capacity to stabilize exponentially a linearized version of the nonlinear dynamics and some Fréchet differentiability conditions of the corresponding closed-loop nonlinear semigroup.
Paper VI123-06.5
PDF · Video · Optimal Driving Strategies for Traffic Control with Autonomous Vehicles (I)
Liard, Thibault	University of Deusto
Stern, Raphael	University of Minnesota
Delle Monache, M. L.	Inria Grenoble - Rhône Alpes
Keywords: Singularities in optimization, Non-smooth and discontinuous optimal control problems, control of hyperbolic systems and conservation laws Abstract: This article considers the possibility of using a small number of autonomous vehicles (AV) for traffic control of the predominantly human-piloted traffic. Specifically, we consider the control of the AV to act as a moving bottleneck, which will be used to optimize traffic flow properties such as fuel consumption of the combined human-piloted and autonomous traffic flow.We use a coupled partial differential equation (PDE)-ordinary differential equation (ODE)framework to model the bulk traffic flow using a PDE, and the trajectory of an autonomous vehicle in the flow using an ODE, depending on the downstream traffic density. The autonomous vehicle acts on the traffic flow as a moving bottleneck via a moving flux constraint. Using this modeling framework, we consider an optimal control problem which consists in finding the optimal AV trajectory to minimize fuel consumption of the entire traffic flow. We prove existence of optimal AV trajectories and we present two different optimal driving strategies depending on the initial traffic conditions.
Paper VI123-06.6
PDF · Video · Optimal Control on the Velocity Term of the Bilinear Plate Equation (I)
Ait Aadi, Abderrahman	Moulay Ismail University
Zerrik, E. Hassan	MACS Team; Sciences Faculty, Moulay Ismail University
Keywords: control of heat and mass transfer systems, controllability and observability of distributed parameter systems Abstract: This paper investigates a regional optimal control problem of a plate equation described by a bilinear systems evolving in a spacial domain Omega. The control is distributed, bounded and acts on the velocity term of such equation. Then, we minimizes a functional cost constituted of the deviation between a desired state and the reached one only on a subregion omega of Omega and the energy term. The purpose of this study is to prove that a control solution of such problem exists, and characterised as a solution to an optimality system. Numerical approach is given and successfully illustrated by simulations.
Paper VI123-06.7
PDF · Video · Lyapunov Functions for Input-To-State Stability of Infinite-Dimensional Systems with Integrable Inputs (I)
Mironchenko, Andrii	University of Passau
Keywords: stability of distributed parameter systems, Input-to-State Stability, Stability of nonlinear systems Abstract: In this paper, we extend the ISS Lyapunov methodology to make it suitable for the analysis of ISS w.r.t. inputs from L_p-spaces. We show that the existence of a so-called L_p-ISS Lyapunov function implies L_p-ISS of a system. Also, we show that existence of a noncoercive L_p-ISS Lyapunov function implies L_p-ISS of a control system provided the flow map is continuous w.r.t. states and inputs and provided the finite-time reachability sets, corresponding to the input space L_p are bounded.
Paper VI123-06.8
PDF · Video · Design of Saturated Boundary Control for Hyperbolic Systems (I)
Shreim, Suha	Université Grenoble Alpes, Grenoble INP, Gipsa-Lab
Ferrante, Francesco	Université Grenoble Alpes
Prieur, Christophe	CNRS
Keywords: Stability of nonlinear systems, Lyapunov methods, control of hyperbolic systems and conservation laws Abstract: This paper deals with the stabilization of 1-D linear hyperbolic systems with saturated feedback boundary control. By following a Lyapunov approach, sufficient conditions for the global exponential stability in the L2 norm are given in the form of matrix inequalities. Numerical examples are presented to illustrate the theoretical results.

VI123-07
Theory and Applications of Extremum Seeking Control	Open Invited Session
Chair: Ebenbauer, Christian	University of Stuttgart
Co-Chair: Guay, Martin	Queen's Univ
Organizer: Grushkovskaya, Victoria	Alpen-Adria University of Klagenfurt
Organizer: Ebenbauer, Christian	University of Stuttgart
Organizer: Guay, Martin	Queen's Univ
Organizer: Zuyev, Alexander	Otto Von Guericke University Magdeburg
Paper VI123-07.1
PDF · Video · Acceleration-Actuated Source Seeking without Position and Velocity Sensing (I)
Suttner, Raik	University of Wuerzburg
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Adaptive control, Stability of nonlinear systems, Nonlinear observers and filter design Abstract: We study the problem of source seeking for an acceleration-controlled unicycle. The objective is to asymptotically stabilize the unicycle around states at which a smooth position-dependent signal (or cost) function attains a minimum value. An implementation of the proposed control strategy only requires measurements of the cost function value at the current position. We do not assume that the unicycle can measure its current positions or its current forward velocity. For this purpose, we extend a recently introduced approach to extremum seeking control, which is based on the approximation of so-called symmetric products of vector fields. An additional high-gain observer is used to estimate the derivative of the sensed cost signal. The estimates provided by the observer compensate for the missing velocity measurements and allow an reduction of the kinetic energy without velocity-dependent damping. Under suitable assumptions on the cost function, the control law leads to semi-global practical asymptotic stability.
Paper VI123-07.2
PDF · Video · Fixed-Time Newton-Like Extremum Seeking (I)
Poveda, Jorge I.	University of Colorado at Boulder
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Convex optimization, Adaptive control, Lyapunov methods Abstract: In this paper, we present a novel Newton-like extremum seeking controller for the solution of multivariable model-free optimization problems in static maps. Unlike existing asymptotic and fixed-time results in the literature, we present a scheme that achieves (practical) finite time convergence to a neighborhood of the optimal point, with a convergence time that is independent of the initial conditions and the Hessian of the cost function, and therefore can be arbitrarily assigned a priori by the designer with an appropriate choice of parameters in the algorithm. The extremum seeking dynamics exploit a class of fixed time convergence properties recently established in the literature for a family of Newton flows, as well as averaging results for perturbed dynamical systems that are not necessarily Lipschitz continuous. The proposed extremum seeking algorithm is model-free and does not require any explicit knowledge of the gradient and Hessian of the cost function. Instead, real-time optimization with fixed-time convergence is achieved by using real time measurements of the cost, which is perturbed by a suitable class of periodic excitation signals generated by a dynamic oscillator. Numerical examples illustrate the performance of the algorithm.
Paper VI123-07.3
PDF · Video · Fast Extremum Seeking Using Multisine Dither and Online Complex Curve Fitting (I)
van Keulen, Thijs Adriaan Cornelis	Technische Universiteit Eindhoven
van der Weijst, Robert	Eindhoven University of Technology
Oomen, Tom	Eindhoven University of Technology
Keywords: Extremum seeking and model free adaptive control Abstract: Fast online optimization of uncertain Wiener systems using extremum seeking control (ESC) is investigated. Derivative estimation in extremum seeking is herefore described as an online parametric system identification problem. Multisine dithering is applied with frequencies around the first resonance frequency of the system to remove the time scale separation between dither and plant dynamics which is commonly required in ESC. Recursive use of the Fourier transform, over a moving window of historic data, provides a frequency response function estimate of the system's local best linear approximation. Continuous online complex curve fitting is then applied to extrapolate to an estimate of the steady-state response which coincides with the local gradient of the steady-state objective function. An analysis of the closed-loop dynamics is provided. Transient improvements and robustness of the approach against plant variation are demonstrated with a simulation example.
Paper VI123-07.4
PDF · Video · An Extremum Seeking Control Based Approach for Alignment Problem of Mobile Optical Communication Systems (I)
Cai, Wenqi	King Abdullah University of Science and Technology (KAUST)
N. Alhashim, Abdullah	King Abdullah University of Science and Technology (KAUST)
N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Control under communication constraints (nonliearity), Tracking, Application of nonlinear analysis and design Abstract: Optical wireless communication (OWC) has proliferated a wide range of applications in manyfields due to its advantages of low-cost, high bandwidth, etc. However, the strict alignment requirements of widely used line-of-sight (LOS) deployments are challenging to be achieved, especially for those moving optical communication systems. In this paper, we propose an extremum seeking control based control strategy to solve the alignment problem for mobile optical communication systems. Our proposed approach consists of two steps: coarse alignment and fine alignment, both rely on the measurements from the vision sensor Pixy2. The coarse alignment uses a feedback proportional-derivative (PD) control and is responsible for tracking and following the receiver. The objective of the fine alignment is to get rid of the effects of any static or dynamic disturbances. The perturbation-based extremum seeking control (ESC) is adopted for a continuous search for the optimal position, where the received optical power is maximum in the presence of disturbance. The proposed approach is simple, effective, and easy to implement.
Paper VI123-07.5
PDF · Video · An Integral Nash Equilibrium Control Scheme for a Class of Multi-Agent Linear Systems (I)
KrilaŠević, Suad	TU Delft
Grammatico, Sergio	Delft Univ. of Tech
Keywords: Data-based control, Parametric optimization, Output feedback control Abstract: We propose an integral Nash equilibrium seeking control (I-NESC) law which steers the multi-agent system composed of a special class of linear agents to the neighborhood of the Nash equilibrium in noncooperative strongly monotone games. First, we prove that there exist parameters of the integral controller such that the system converges to the Nash equilibrium in the full-information case, in other words, without the parameter estimation scheme used in extremum seeking algorithms. Then we prove that there exist parameters of the I-NESC such that the system converges to the neighborhood of the Nash equilibrium in the limited information case where parameter estimation is used. We provide a simulation example that demonstrates that smaller perturbation frequencies and amplitudes are needed to attain similar convergence speed as the existing state-of-the-art algorithm.
Paper VI123-07.6
PDF · Video · Delayed Newton-Based Multivariable Extremum Seeking with Sequential Predictors (I)
Malisoff, Michael	Louisiana State Univ
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Delay systems, Asymptotic stabilization, Adaptive control Abstract: We provide a new method for Newton-based multivariable extremum seeking which allows different delays in each of the input channels. We allow arbitrarily long input delays. We use a perturbation based estimate and averaging. Our sequential predictor based delay compensation method eliminates the need for the distributed terms that were required in earlier delay compensation methods for extremum seeking. Unlike gradient-based approaches, our Newton-based method leads to an estimation error for the extremum that is independent of the inverse of the unknown Hessian. We illustrate our method in a source seeking example.
Paper VI123-07.7
PDF · Video · Extremum Seeking Control for Multi-Rotor Wind Turbine in the Full-Load Region (I)
Spagnolo, Fabio	Vestas Wind Systems A/S
Papageorgiou, Dimitrios	Technical University of Denmark
Galeazzi, Roberto	Technical University of Denmark
Sandberg Thomsen, Jesper	Vestas Wind Systems A/S
Hylling Sørensen, Kim	Vestas Wind Systems A/S
Keywords: Stability of nonlinear systems, Analytic design, Adaptive control Abstract: Multi-rotor wind turbines facilitate higher power production at a lower cost compared to their single-rotor counterparts. However, the larger induced loads due to yaw moments may lead to faster wear and tear on the tower structure and need be appropriately handled by means of pitch control. This paper investigates the feasibility of two different pitch control schemes based on extremum seeking principles for multi-rotor wind turbines in the full-load region. The proposed solutions are tested in simulation. Their performance is compared to that of a benchmark controller with respect to generator speed regulation, power optimisation and fatigue mitigation. The results show that the designed controllers match the performance of the conventional solution at the cost, however, of increased structural stress on the tower.
Paper VI123-07.8
PDF · Video · Extremum Seeking Approach for Nonholonomic Systems with Multiple Time Scale Dynamics (I)
Grushkovskaya, Victoria	Alpen-Adria University of Klagenfurt
Zuyev, Alexander	Otto Von Guericke University Magdeburg
Keywords: Stability of nonlinear systems, Lyapunov methods, Analytic design Abstract: In this paper, a class of nonlinear driftless control-affine systems satisfying the bracket generating condition is considered. A gradient-free optimization algorithm is developed for the minimization of a cost function along the trajectories of the controlled system. The algorithm comprises an approximation scheme with fast oscillating controls for the nonholonomic dynamics and a model-free extremum seeking component with respect to the output measurements. Exponential convergence of the trajectories to an arbitrary neighborhood of the optimal point is established under suitable assumptions on time scale parameters of the extended system. The proposed algorithm is tested numerically with the Brockett integrator for different choices of generating functions.
Paper VI123-07.9
PDF · Video · Finite-Time Extremum Seeking Control for a Class of Unknown Static Maps (I)
Guay, Martin	Queen's Univ
Keywords: Adaptive control, Convex optimization, Data-based control Abstract: This paper proposes an extremum-seeking control design that achieves finite-time stability of the optimum an unknown measured cost function. The finite-time extremum-seeking control technique is shown to achieve finite-time practical stability of the optimum of the unknown cost function. The main characteristic of the proposed extremum seeking control approach is that the target averaged system considered achieves finite-time stability of the unknown optimum. A simulation study is presented to demonstrate the effectiveness of the approach.
Paper VI123-07.10
PDF · Video · Inverse Optimality for Extremum Seeking Feedback under Delays (I)
Ferreira, Denis César	State University of Rio De Janeiro - UERJ
Oliveira, Tiago Roux	State University of Rio De Janeiro - UERJ
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Adaptive control, Delay systems, backstepping control of distributed parameter systems Abstract: We present a Gradient-based extremum seeking algorithm for maximizing unknown maps in the presence of constant delays. It is incorporated a filtered predictor feedback with a perturbation-based estimate for the Hessian of locally quadratic maps. Exponential stability and convergence to a small neighborhood of the unknown extremum point are achieved by using backstepping transformation and averaging theory in infinite dimensions. The low-pass filter (with a high enough pole) in the predictor feedback allows the technical application of the Hale and Lunel's averaging theorem for functional differential equations and also establishes an inverse optimal result for the closed-loop system. This inverse optimality property is for the first time demonstrated in extremum seeking designs and justifies the heuristic use of a low-pass filter between the demodulation and the integrator, which has historically been a part of the extremum seeking implementations free of delays.
Paper VI123-07.11
PDF · Video · Extremum Seeking for Nonlinear Uncertain Systems: A Small-Gain Synthesis (I)
Wang, Qiyue	Northeastern University
Qin, Zhengyan	Northeastern University
Liu, Tengfei	Northeastern University
Jiang, Zhong-Ping	Tandon School of Engineering, New York University
Keywords: Convex optimization, Input-to-State Stability, Stability of nonlinear systems Abstract: This paper studies the extremum seeking problem for static maps with the inputs of the maps generated by a nonlinear uncertain system. A new small-gain approach is developed which uses an extremum seeking strategy to generate a reference signal, and employs a control law for reference-tracking of the nonlinear uncertain systems. The notions of input-to-state stability (ISS) and input-to-output stability (IOS) are used to characterize the interconnection between the extremum seeking strategy and the reference-tracking controller, and the nonlinear small-gain theorem is employed to guarantee the stability of the closed-loop extremum seeking system. With the proposed approach, the extremum seeking problem for a complex nonlinear system is solvable as long as one can design a proper reference-tracking controller for the system. Examples are given to show the feasibility of the proposed approach, and a numerical simulation is employed to show the effectiveness of the proposed design.
Paper VI123-07.12
PDF · Video · A Newton Consensus Method for Distributed Optimization (I)
Guay, Martin	Queen's Univ
Keywords: Data-based control, Distributed nonlinear control, Adaptive control Abstract: This manuscript proposes a distributed Newton seeking for the solution of distributed optimization problems with locally measured but unknown cost functions. The approach implements a Newton step for both the primal and dual problems that can be implemented in a completely decentralized fashion. Unlike existing techniques, no exchange of derivative information between agents is required. In addition, no explicit inversion of the Hessian information is required to generate the required Newton step. The local gradients and Hessians are estimated using a perturbation based extremum seeking control technique. A simulation study demonstrates the effectiveness of the technique.
Paper VI123-07.13
PDF · Video · Extremum Seeking under Distributed Input Delay (I)
Tsubakino, Daisuke	Nagoya University
Oliveira, Tiago Roux	State University of Rio De Janeiro - UERJ
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Delay systems, Stability of nonlinear systems Abstract: In this paper, we propose an extremum seeking scheme for single-parameter static maps in the presence of distributed input delay. A probing signal is newly developed so that the delayed signal has a conventional form in standard extremum seeking problems. An update law for an estimate of the unknown argument of the extremum is designed based on the idea of the predictor feedback law. We prove the convergence of the estimation error to a neighborhood of the origin by means of the method of averaging. The effectiveness of the proposed scheme is confirmed by a numerical simulation.
Paper VI123-07.14
PDF · Video · A Distributed Algorithm for UAV-Based Communication Networks Using Constrained Extremum Seeking (I)
Liao, Chwen-Kai	University of Melbourne
Manzie, Chris	The University of Melbourne
Chapman, Airlie Jane	University of Melbourne
Keywords: Adaptive control, UAVs, Decentralized control Abstract: Unmanned autonomous vehicles offer a solution to maintaining adaptive multi-hop communication paths when fixed infrastructure is not available, as may be the case in disaster recovery or in contested environments. Some of the potential challenges these networks face are changing environmental conditions, changing numbers of available agents and the need to avoid certain domains. In this paper, a distributed implementation of a constrained extremum seeking approach is proposed to optimise the signal power along the communication chain by adapting vehicle locations within allowable regions. The approach is demonstrated via simulations that consider both homogeneous and heterogeneous signal transmission pathways.

VI123-08
Application of Nonlinear Analysis and Design	Regular Session
Chair: Kishida, Masako	National Institute of Informatics
Co-Chair: Araujo Pimentel, Guilherme	Pontifícia Universidade Católica Do Rio Grande Do Sul
Paper VI123-08.1
PDF · Video · A Notion of Equivalence for Linear Complementarity Problems Applications to the Design of Nonsmooth Bifurcations
Castaños, Fernando	CINVESTAV
Miranda-Villatoro, Félix Alfredo	University of Cambridge
Franci, Alessio	Department of Mathematics, UNAM
Keywords: Application of nonlinear analysis and design Abstract: Many systems of interest to control engineering can be modeled by linear complementarity problems. We introduce a new notion of equivalence between linear complementarity problems that sets the basis to translate the powerful tools of smooth bifurcation theory to this class of models. Leveraging this notion of equivalence, we introduce new tools to analyze, classify, and design non-smooth bifurcations in linear complementarity problems and their interconnection.
Paper VI123-08.2
PDF · Video · Normal Forms for Flat Two-Input Control Systems Linearizable Via a Two-Fold Prolongation
Nicolau, Florentina	Ensea Cergy
Respondek, Witold	INSA - Rouen
Keywords: Application of nonlinear analysis and design Abstract: We present normal forms for nonlinear two-input control systems that become static feedback linearizable after a two-fold prolongation of a suitably chosen control, which is one of the simplest dynamic feedback. They form a particular class of flat systems, namely those of differential weight n+4, where n is the number of states. We also show that the dynamic feedback creates singularities in the control space depending on the state and we discuss them.
Paper VI123-08.3
PDF · Video · On the Global Feedback Stabilization of Regenerative Optical Amplifiers
Deutschmann, Andreas	TU Wien
Kemmetmueller, Wolfgang	TU Wien, Automation and Control Institute
Kugi, Andreas	Vienna University of Technology
Keywords: Application of nonlinear analysis and design, Asymptotic stabilization, Control of bifurcation and chaos Abstract: The generation of high-energy laser pulses by so-called regenerative (optical) amplifiers is limited by the occurrence of period-doubling bifurcations induced by an inherently unstable pulse-to-pulse dynamics. Recently, the application of linear feedback methods to stabilize this pulse-to-pulse dynamics by modifying the supplied seed pulses was suggested as an alternative to the quite expensive current state of the art involving dedicated pre-amplifiers. To address some shortcomings inherent to the linear feedback, this paper investigates the design of nonlinear state feedback laws and in particular the possibility to stabilize the pulse-to-pulse dynamics globally subject to the given input constraints.
Paper VI123-08.4
PDF · Video · Open-Loop Interconnect Control Schedule Design for Spin Recovery Using Direct Numerical Continuation
G, Rohith	Research Scholar, Indian Institute of Technology Madras
Sinha, Nandan Kumar	IIT Madras
Keywords: Application of nonlinear analysis and design, Control of bifurcation and chaos, Aerospace Abstract: Recent interests in Loss-of-Control (LOC) related accidents of aircraft bring back focus on the need for construction of realistic simulations not only of impending accident scenarios but also of recovery of aircraft from fully developed accident scenarios. Developing control schedules for both the activities thereby becomes crucial. In this paper, a novel approach based on constrained numerical continuation procedure is presented to effectively compute open-loop control interconnect schedules for a six-degree-of-freedom aircraft model. For illustrative purposes, the approach based on a new formulation of constraint equations is used to design open-loop control interconnect schedule for recovery of an F-18 HARV model from auto-rotational spin condition.
Paper VI123-08.5
PDF · Video · MIMO Feedback Linearization of Redundant Robotic Systems Using Task-Priority Operational Space Control
Basso, Erlend A.	Norwegian Univ. of Science and Tech
Pettersen, Kristin Y.	Norwegian Univ. of Science and Tech
Keywords: Application of nonlinear analysis and design, Lagrangian and Hamiltonian systems, Stability of nonlinear systems Abstract: Redundant robotic systems are designed to accomplish multiple tasks simultaneously. Task-priority control schemes exploit system redundancy by arranging tasks in priority and ensuring strict prioritization between tasks at different priority levels. This paper investigates the relationship between task-priority operational space control and feedback linearization of multiple-input-multiple-output (MIMO) systems. We derive sufficient conditions for input-output feedback linearization and input-to-state feedback linearization of a redundant robotic system influenced by a task-priority operational space pre-feedback control law. Moreover, we analyze the effect of incompatible tasks and provide sufficient conditions for input-output and input-to-state feedback linearizability of the controllable dimensions of incompatible lower-priority tasks. These conditions can be employed when designing the operational space tasks in order to guarantee both task space and joint space stability.
Paper VI123-08.6
PDF · Video · A Convex Optimization Based Solution for the Robotic Manipulator Control Design Problem Subject to Input Saturation
Scheffer, Eduardo	Pontifícia Universidade Católica Do Rio Grande Do Sul
Castro, Rafael da Silveira	PUCRS
Salton, Aurelio Tergolina	Universidade Federal Do Rio Grande Do Sul (UFRGS)
Araujo Pimentel, Guilherme	Pontifícia Universidade Católica Do Rio Grande Do Sul
Keywords: Application of nonlinear analysis and design, Systems with saturation, Convex optimization Abstract: This paper proposes a state-feedback design procedure for robotic manipulator systems with saturating actuators, a solution which is based on convex optimization subject to constraints in the form of linear matrix inequalities. Our fundamental idea is to express the system dynamics in a novel differential-algebraic representation with state-derivative components. This approach allows us to provide a systematic control design framework with formal theoretical guarantees, such as the asymptotic stabilization of the manipulator attitude reference error within a prescribed exponential decay-rate. Our method is capable of dealing with the nonlinearities of a mechanical manipulator system, including the input saturation effect, without relying on any kind of linearization or approximation. A two-link planar robotic manipulator example is employed in order to illustrate the proposed approach.
Paper VI123-08.7
PDF · Video · Complex-Valued Sliding Mode Control of an Induction Motor
Doria-Cerezo, Arnau	Technical Univ. of Catalonia (UPC)
Olm, Josep M.	Universitat Politècnica De Catalunya
Repecho Del Corral, Víctor	Universitat Politècnica De Catalunya (UPC)
Biel, Domingo	Univ. Politecnica De Catalunya
Keywords: Sliding mode control, Power systems, Application of nonlinear analysis and design Abstract: Three-phase induction motors admit a complex-valued space state representation. In this paper, this complex description is used to design a torque controller and a rotor flux observer based on sliding modes. The advantage of using the complex representation is an order reduction of the system and a simplification of the analysis. The obtained results are illustrated by means of numerical simulations.
Paper VI123-08.8
PDF · Video · On the Linearization of Flat Two-Input Systems by Prolongations and Applications to Control Design
Gstöttner, Conrad	Johannes Kepler University Linz
Kolar, Bernd	Johannes Kepler University Linz
Schöberl, Markus	Johannes Kepler University of Linz
Keywords: Tracking Abstract: In this paper we consider (x,u)-flat nonlinear control systems with two inputs, and show that every such system can be rendered static feedback linearizable by prolongations of a suitably chosen (new) control. This result is not only of theoretical interest, but has also important implications on the design of flatness based tracking controls. We show that a tracking control based on quasi-static state feedback can always be designed in such a way that only measurements of a (classical) state of the system, and not measurements of a generalized Brunovsky state, as reported in the literature, are required.

VI123-09
Constrained Control	Regular Session
Chair: Olaru, Sorin	CentraleSupelec
Co-Chair: Koegel, Markus J.	Otto-von-Guericke-Universitaet Magdeburg
Paper VI123-09.1
PDF · Video · Navigation in Cluttered Environments with Feasibility Guarantees
Ioan, Daniel	L2S-Univ. Paris-Sud-CentraleSupelec-CNRS, Universite Paris Sacla
Prodan, Ionela	INP Grenoble
Olaru, Sorin	CentraleSupelec
Stoican, Florin	Politehnica University of Bucharest
Niculescu, Silviu-Iulian	Laboratory of Signals and Systems (L2S)
Keywords: Constrained control, Linear systems, Convex optimization Abstract: This paper addresses the navigation problem in a multi-obstacle environment and makes use of convex lifting in trajectory planning problems with anti-collision constraints. The design problem is commonly stated in the literature in terms of a constrained optimization problem over a non-convex domain. The convex lifting approach, advocated here, plays an instrumental role in the partitioning of the feasible space in accordance with the distribution of obstacles and in the subsequent generation of corridors in cluttered environments. We consider an adaptation of the generic MPC (Model Predictive Control) trajectory tracking problem, aiming to guarantee the feasibility and convergence. Simulation results and proof of concepts illustrations prove the effectiveness of the proposed approach.
Paper VI123-09.2
PDF · Video · Bounded Derivative Feedback Control with Application to Magnetic Levitation
Zaheer, Muhammad Hamad	University of New Hampshire
Arthur, Khalid	University of New Hampshire
Yoon, Se Young (Pablo)	University of New Hampshire
Keywords: Constrained control, Output feedback control (linear case), Control of bifurcation and chaos Abstract: In this paper, we study the stabilization of dynamic systems with uncertain equilibrium states and in the presence of bounded control. We propose state and output derivative feedback control schemes to stabilize the dynamic system, and to drive the system states to its true equilibrium state even when the location of such equilibrium is uncertain. Control bounds in the feedback control are also considered in this paper, and stability conditions are derived for the cases when the control energy is bounded, and when the maximum control is bounded. Stability conditions are derived in the form of matrix inequalities for both cases of control bounds, and numerical methods are discussed to synthesize feasible control solutions. The effectiveness of the proposed method is illustrated by an experimental implementation.
Paper VI123-09.3
PDF · Video · A New Reference Governor Strategy for Union of Linear Constraints
Romagnoli, Raffaele	Carnegie Mellon University
Couto, Luis D.	Université Libre De Bruxelles
Garone, Emanuele	Université Libre De Bruxelles
Keywords: Constrained control, Predictive control, Tracking Abstract: Classical scalar Reference Governor (RG) schemes require a convex admissible region. Recently, a novel scalar RG approach has been proposed for the case of nonconvex constraints that can be approximated as union of polyhedral sets. This new method, specifically developed for the charge control of lithium-ion batteries, shows good performance and the capability of handling these kind of constraints while keeping a very low computational footprint. However, this method can guarantee that the system will reach the desired set point only under very specific properties of the constraints. In this paper, we analyze these limitations and propose a solution that ensures convergence of the RG scheme under much milder conditions on the topology of the constraints.
Paper VI123-09.4
PDF · Video · Computing Invariant Sets of Discrete-Time Nonlinear Systems Via State Immersion
Wang, Zheming	Université Catholique De Louvain
Jungers, Raphaël M.	Université Catholique De Louvain
Ong, Chong-Jin	National Univ of Singapore
Keywords: Constrained control, Stability of nonlinear systems, Control of constrained systems Abstract: In this paper, we propose a method for computing invariant sets of discrete-time nonlinear systems by lifting the nonlinear dynamics into a higher dimensional linear model. In particular, we will focus on the maximal invariant set. Some special types of nonlinear systems can be considered as the projection of a higher dimensional linear system with a state immersion transformation. For such systems, the equivalence between invariant sets of the nonlinear system and its linear equivalent can be also established, which allows to characterize the maximal invariant set of the nonlinear system using a lifted linear model. For general nonlinear systems, we will use linear approximations because equivalent linear models cannot be achieved exactly. To handle mismatch errors, we tighten the constraint set of the lifted linear model, which will lead to an invariant inner approximation of the maximal invariant set.
Paper VI123-09.5
PDF · Video · Limit Behavior and the Role of Augmentation in Projected Saddle Flows for Convex Optimization
Hauswirth, Adrian	ETH Zurich
Ortmann, Lukas	ETH Zurich
Bolognani, Saverio	ETH Zurich
Dorfler, Florian	Swiss Federal Institute of Technology (ETH) Zurich
Keywords: Control of constrained systems Abstract: In this paper, we study the stability and convergence of continuous-time Lagrangian saddle flows to solutions of a convex constrained optimization problem. Convergence of these flows is well-known when the underlying saddle function is either strictly convex in the primal or strictly concave in the dual variables. In this paper, we show convergence under non-strict convexity when a simple, unilateral augmentation term is added. For this purpose, we establish a novel, non-trivial characterization of the limit set of saddle-flow trajectories that allows us to preclude limit cycles. With our presentation we try to unify several existing problem formulations as a projected dynamical system that allows projection of both the primal and dual variables, thus complementing results available in the recent literature.
Paper VI123-09.6
PDF · Video · Synthesis of an Adaptive State-Constrained Control for MIMO Euler-Lagrange Systems
Sachan, Kapil	Indian Institute of Science
Padhi, Radhakant	Indian Institute of Science
Keywords: Control of constrained systems, Adaptive control, Lyapunov methods Abstract: A state-constrained adaptive control synthesis is presented in this paper for multi-input multi-output Euler-Lagrange nonlinear systems associated with structured uncertainties. The controller is synthesized in two steps: (i) an approximated system is constructed to approximate model uncertainties (ii) a novel nonlinear error transformation based control law is designed to ensure the desired reference command tracking. A neural network is used in the approximated system to approximate the model uncertainties, and the weights of the neural network are updated using a stable weight update rule. The proposed controller ensures that the closed-loop states of the system will remain bounded by the user-defined constraints and the steady-state errors will converge asymptotically to a predefined domain. The proposed formulation also gives the flexibility to impose independent constraints on system states and leads to an easily on-board implementable closed-form control solution. The effectiveness of the control design is demonstrated by extensive computer simulations.
Paper VI123-09.7
PDF · Video · Antiwindup Design Approach to Constrained Primal-Dual Dynamics
Adegbege, Ambrose Adebayo	The College of New Jersey
Keywords: Control of constrained systems, Anti-windup, Constrained control Abstract: An antiwindup control framework is developed for primal-dual dynamics in convex optimization. The proposed architecture provides for straightforward implementation of the ensuing primal-dual dynamics and for establishing global asymptotic stability using the notion of shifted-passivity with Lyapunov function commonly encountered in antiwindup literature.
Paper VI123-09.8
PDF · Video · Constrained Trajectory Planning for Second-Order Chained Form Systems Using Time Polynomials
Golubev, Alexey	Bauman Moscow State Technical University
Keywords: Control of constrained systems, Constrained control, Analytic design Abstract: This paper deals with time polynomial based trajectory planning for differentially flat affine dynamical systems that can be written as a chain of second-order controlled subsystems. An analytical approach is proposed to account for state and input constraints by adjusting the standard third-order time polynomial based considerations. For a point-to-point motion planning problem the constraints are met by properly selecting the time of motion value or/and initial or final values of some of the state variables. As an illustrative example trajectory planning for a 3-DoF Delta pick and place robot is considered.
Paper VI123-09.9
PDF · Video · Efficient Feasible Set Characterization through Distance Field Map Algorithm and Its Use in Control
Obando, Andres Felipe	Universidad Ponificia Bolivariana
Muñoz, Diego A.	Universidad Pontificia Bolivariana
Keywords: Control of constrained systems, Process control, Application of nonlinear analysis and design Abstract: Feasibility on processes is a well used notion with several definitions in the literature according to the context. This is understood as the region of operative variables where phenomena of processes happen. In this work we propose a definition for feasibility set and explain an algorithm to characterize its shape and size in an efficient way. Additionally, we define a feasibility index to quantify the grade of belonging of a point inside the feasible set, instead of the yes/no usual belonging function. Finally, it is shown the use of previous concepts for control proposes. Through an optimization problem is found the set point that guarantees the feasibility, facing changes on disturbances. Results showed that the use of this proposal allows the optimization of productivity that still feasible despite the disturbances.
Paper VI123-09.10
PDF · Video · Control-Based Resource Management for Storage of Video Streams
Martins, Alexandre	Axis Communications
Lindberg, Mikael	Lund University
Maggio, Martina	Lund University
Arzen, Karl-Erik	Lund Inst. of Technology
Keywords: Constrained control, Anti-windup, Networked systems Abstract: Distributed surveillance systems typically consist of multiple cameras that need to store some fraction of their video streams at a central storage node. The disk space of this node constitutes a shared resource. In the paper the disk space allocation is formulated as a PI control problem and a new method for enforcing the global resource constraint inspired by anti-windup tracking is proposed. The approach is evaluated by simulations.
Paper VI123-09.11
PDF · Video · A High Dynamic Range Delta-Sigma Modulator Using Anti-Windup Compensated Integrators
Sadeghi Reineh, Maryam	University of California, Irvine
Fazli Yeknami, Ali	University of California, San Diego
Green, Michael	UCI
Jabbari, Faryar	Univ. of California at Irvine
Keywords: Systems with saturation, Anti-windup, Digital implementation Abstract: This paper presents a continuous-time (CT) Delta-Sigma modulator employing an anti-windup (AW) feedback control technique to mitigate integrator overload and maintain an acceptable performance simultaneously. The proposed technique accommodates a large dynamic range and can be applied to multi-loop modulators. According to simulations, using AW augmentations, for a 50% higher dynamic range (DR), integrators do not overload and the signal-to-distortion-ratio (SNDR) drops less than 1dB from the maximum SNDR of the modulator.
Paper VI123-09.12
PDF · Video · LQR Design under Stability Constraints
Scampicchio, Anna	University of Padova
Aravkin, Aleksandr	University of Washington
Pillonetto, Gianluigi	Univ of Padova
Keywords: Optimal control theory, Lyapunov methods, Linear systems Abstract: The solution of classic discrete-time, finite-horizon linear quadratic regulator (LQR) problem is well known in literature. By casting the solution to be a static state-feedback, we propose a new method that trades off low LQR objective value with closed-loop stability.
Paper VI123-09.13
PDF · Video · Guaranteed Memory Reduction in Synthesis of Correct-By-Design Invariance Controllers
Macoveiciuc, Elisei	University of the German Federal Armed Forces Munich
Reissig, Gunther	University of the Federal Armed Forces Munich
Keywords: Control problems under conflict and/or uncertainties, Discontinuous control, Control of constrained systems Abstract: Formal methods for analysis of dynamical systems through construction of finite symbolic abstractions have attracted significant interest as they allow solving complex control problems in a fully automated fashion. Nevertheless, their practical application is currently limited by the fact that they require enormous memory resources. We present a novel algorithm for solution of invariance problems within abstraction-based framework, which guarantees large storage reduction and fully applies to general non-linear plants. We also show that, in practice, the algorithm is faster compared to other methods.
Paper VI123-09.14
PDF · Video · On the Optimization of Actuator Saturation Limits for LTI Systems: An LMI-Based Invariant Ellipsoid Approach
Rotondo, Damiano	Universitetet I Stavanger
Rizzello, Gianluca	Saarland University
Keywords: Systems with saturation, Linear systems, Convex optimization Abstract: This paper considers the problem of optimal actuator dimensioning for LTI systems, in the sense of choosing appropriate saturation limits for a given set of admissible initial conditions and for a predefined integral state-feedback control law. By using an invariant ellipsoid argument, it is shown that this problem can be described as a linear matrix inequality (LMI)-based optimization that can be solved efficiently. Moreover, the paper shows that the optimal actuator dimensioning is connected to the choice of the initial conditions of the integral states of the controller, which can be included in the overall optimization to improve further the results. Two different methods are described and analyzed by means of simulation results.

VI123-10
Lagrangian and Hamiltonian Systems	Regular Session
Chair: Fujimoto, Kenji	Kyoto University
Co-Chair: Yamashita, Yuh	Hokkaido University
Paper VI123-10.1
PDF · Video · Overcoming the Dissipation Obstacle with Bicomplex Port-Hamiltonian Mechanics
Hutters, Coenraad	Delft University of Technology
Mendel, Max	TU Delft
Keywords: Lagrangian and Hamiltonian systems, Energy systems, Input-to-State Stability Abstract: The dissipation obstacle refers to the problem that there is no general solution to shape the energy of dissipative port-Hamiltonian (pH) systems with the method of Casimir functions. This paper argues that it is caused by lack of a strictly symplectic structure of a dissipative port-Hamiltonian system. We develop a method of bicomplex pH systems that is strictly symplectic and we show how it overcomes the obstacle and allows one to systematically use Casimir functions to shape the energy.
Paper VI123-10.2
PDF · Video · Explicit Port-Hamiltonian Formulation of Bond Graphs with Dependent Storages
Pfeifer, Martin	Karlsruhe Institute of Technology (KIT)
Caspart, Sven	Karlsruhe Institute of Technology (KIT)
Muller, Charles	Karlsruhe Institute of Technology (KIT)
Pfeiffer, Silja	Karlsruhe Institute of Technology (KIT)
Krebs, Stefan	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Lagrangian and Hamiltonian systems, Networked systems Abstract: Explicit port-Hamiltonian systems (PHSs) are the starting point for many powerful controller and observer design methods. It is well-known that explicit PHSs can be formulated on the basis of bond graphs. Indeed, the port-Hamiltonian formulation of bond graphs without dependent storages has been well investigated. However, little effort has been made towards bond graphs with dependent storages. This is a problem as dependent storages frequently occur in models from many engineering fields. In this paper, we address the explicit port-Hamiltonian formulation of bond graphs with dependent storages. Our idea is to express the port-Hamiltonian dynamics and output as functions of only the system inputs and independent storages. The main result is a rigorous and constructive method to formulate bond graphs containing dependent storages as explicit PHSs. An acadamic example illustrates and verifies our method.
Paper VI123-10.3
PDF · Video · Passivity-Based Nonlinear Active Suspension Control Utilizing Relative Information
Hao, Sheng	Hokkaido University
Yamashita, Yuh	Hokkaido University
Kobayashi, Koichi	Hokkaido University
Keywords: Lagrangian and Hamiltonian systems, Passivity-based control Abstract: In this paper, we present the design of active suspension system by using a kind of passivity-based control method, where the proposed suspension system provides the good ride comfort and the good road holding simultaneously and only uses relative displacement and velocity. We show that the proposed method can be extended to nonlinear case easily. The robustness of proposed method is also analyzed.
Paper VI123-10.4
PDF · Video · Explicit and Implicit IDA-PBC Design and Implementation for a Portal Crane
Vidal, Enrique J.	TU Ilmenau
Cieza A., Oscar B.	TU Ilmenau
Reger, Johann	TU Ilmenau
Keywords: Lagrangian and Hamiltonian systems, Passivity-based control, Lyapunov methods Abstract: The interconnection and damping assignment passivity-based control (IDA-PBC) is well-known for regulating the behavior of nonlinear systems. In underactuated mechanical systems (UMSs), its application requires the satisfaction of matching conditions, which in many cases demands to solve partial differential equations (PDEs). Only recently, the IDA-PBC method has been extended to UMSs in implicit representation, where the system dynamics are described by a set of differential-algebraic equations. In some system classes, this implicit model allows to circumvent the PDE obstacle and to construct an output-feedback law. This paper discusses the design and real-system implementation of the total energy shaping IDA-PBC with an optimal local performance for a portal crane system in implicit port-Hamiltonian representation. The implicit controller is compared with the simplified (explicit) IDA-PBC, introduced by Xue and Zhiyong (2017), which also shapes the total energy and avoids PDEs.
Paper VI123-10.5
PDF · Video · Virtual Holonomic Constraints Control for Port-Hamiltonian Systems: A Case Study of Fully Actuated Mechanical Systems
Okura, Yuki	Toyama Prefectural University
Fujimoto, Kenji	Kyoto University
Kojima, Chiaki	Toyama Prefectural University
Keywords: Lagrangian and Hamiltonian systems, Tracking Abstract: In this paper, virtual holonomic constraints control of port-Hamiltonian systems is proposed. As a case study, fully actuated mechanical systems formulated as port-Hamiltonian systems are considered in this paper. By introducing the coordinate transformation, a virtual holonomic constraint force is calculated as a nonlinear feedback input. When some assumptions hold, this feedback successfully converts the original mechanical system into the reduced order port-Hamiltonian system with desired holonmic constraints. A numerical example shows the effectiveness and the property of the proposed virtual holonominc control.

VI123-11
Model Reduction	Regular Session
Chair: Trenn, Stephan	University of Groningen
Co-Chair: Padoan, Alberto	University of Cambridge
Paper VI123-11.1
PDF · Video · Hybrid Loewner Data Driven Control
Vuillemin, Pierre	Onera - the French Aerospace Lab
Kergus, Pauline	LTH
Poussot-Vassal, Charles	Onera
Keywords: Model reduction, Digital implementation Abstract: This article describes how the Loewner framework can be exploited to create a discrete-time control-law from input-output frequency-data of a continuous-time plant so that their hybrid interconnection matches a given continuous-time reference model up to the Nyquist frequency. The resulting Hybrid Loewner Data Driven Control scheme is illustrated on two numerical examples.
Paper VI123-11.2
PDF · Video · Error Estimates for Model Order Reduction of Burgers' Equation
Abbasi, Mohammad Hossein	Eindhoven University of Technology
Iapichino, Laura	TU Eindhoven
Besselink, Bart	University of Groningen
Schilders, Wilhelmus	TU Eindhoven
van de Wouw, Nathan	Eindhoven Univ of Technology
Keywords: Model reduction, model reduction of distributed parameter systems, Parameter-varying systems Abstract: Burgers' equation is a nonlinear scalar partial differential equation, commonly used as a testbed for model order reduction techniques and error estimates. Model order reduction of the parameterized Burgers' equation is commonly done by using the reduced basis method. In this method, an error estimate plays a crucial rule in both accelerating the offline phase and quantifying the error induced after reduction in the online phase. In this study, we introduce two new estimates for this reduction error. The first error estimate is based on a Lur'e-type model formulation of the system obtained after the full-discretization of Burgers' equation. The second error estimate is built upon snapshots generated in the offline phase of the reduced basis method. The second error estimate is applicable to a wider range of systems compared to the first error estimate. Results reveal that when conditions for the error estimates are satisfied, the error estimates are accurate and work efficiently in terms of computational effort.
Paper VI123-11.3
PDF · Video · Model Reduction by Balanced Truncation of Dominant Lure Systems
Padoan, Alberto	University of Cambridge
Forni, Fulvio	University of Cambridge
Sepulchre, Rodolphe J.	University of Cambridge
Keywords: Model reduction, model reduction of distributed parameter systems, Robustness analysis Abstract: The paper presents a model reduction framework geared towards the analysis and design of systems that switch and oscillate. While such phenomena are ubiquitous in nature and engineering, model reduction methods are not well developed for non-equilibrium behaviors. The proposed framework addresses this need by exploiting recent advances on dominance theory. Classical balanced truncation for linear time-invariant systems is used to develop a dominance- preserving model reduction method for Lure systems, i.e.systems that can be decomposed as the feedback interconnection of a linear system and a static nonlinearity. The method is illustrated by approximating the oscillatory behavior of a discretized heat flow control system.
Paper VI123-11.4
PDF · Video · Loewner Functions for Linear Time-Varying Systems with Applications to Model Reduction
Simard, Joel David	Imperial College London
Astolfi, Alessandro	Imperial Col. London & Univ. of Rome Tor Vergata
Keywords: Model reduction, Time-varying systems Abstract: We introduce a method for model reduction of linear time-varying (LTV) systems by extending the Loewner framework developed for linear time-invariant (LTI) systems. This extension is accomplished by utilizing a state-space interpretation of the Loewner matrices previously developed by the authors. New time-varying Loewner functions are defined, and a Loewner equivalent model is produced using these functions.
Paper VI123-11.5
PDF · Video · A Time-Varying Gramian Based Model Reduction Approach for Linear Switched Systems
Hossain, Md Sumon	University of Groningen
Trenn, Stephan	University of Groningen
Keywords: Model reduction, Time-varying systems, Control of switched systems Abstract: We propose a model reduction approach for switched linear system based on a balanced truncation reduction method for linear time-varying systems. The key idea is to approximate the piecewise-constant coefficient matrices with continuous time-varying coefficients and then apply available balance truncation methods for (continuous) time-varying systems. The proposed method is illustrated with a low dimensional academic example.

VI123-12
Networked, Interconnected, and Distributed Nonlinear Systems	Regular Session
Chair: Jiang, Zhong-Ping	Tandon School of Engineering, New York University
Co-Chair: Schulze Darup, Moritz	Universität Paderborn
Paper VI123-12.1
PDF · Video · Decentralised Interpolating Control: A Periodic Invariance Approach
Scialanga, Sheila	University of Glasgow
Olaru, Sorin	CentraleSupelec
Ampountolas, Konstantinos	University of Thessaly
Keywords: Control of interconnected systems, Linear systems, Decentralized control Abstract: This paper presents a decentralised periodic interpolating control (dpIC) scheme for the constrained control of interconnected systems, which employs periodic invariance and vertex reachability of target sets. Periodic invariance allows the state of the system to leave a candidate set temporarily but return into the set in a finite number of steps. We consider a periodic invariant set with low-complexity (e.g. rectangle, hexagon for planar systems) to replace the expensive controllable invariant outer set. This set is defined within the controllable stabilising region of each subsystem and a reachability problem is solved off-line for each vertex of the outer set to provide an admissible control sequence that steers the system state back into the original target set after a finite number of steps. dpIC is effectuated between such periodic invariant sets for each subsystem and the local maximal admissible inner set by means of an inexpensive linear programming problem, which is solved on-line at the beginning of each periodic control sequence. dpIC is demonstrated on the problem of stabilising a platoon of vehicles.
Paper VI123-12.2
PDF · Video · Stability and Stabilizability of TS-Based Interconnected Non Linear Systems
Tiko, Souhail	Cadi Ayyad University
Mesquine, Fouad	Cadi Ayyad Univ
El Hajjaji, Ahmed	Univ. De Picardie Jules Verne
Keywords: Control of interconnected systems, Stability of nonlinear systems, Lyapunov methods Abstract: This paper aims to establish stability conditions for large scale non linear systems having unknown bounded interconnection terms. These conditions are then worked out to obtain design of stabilizing controllers for such systems. Takagi-Sugeno (TS) fuzzy modeling is used to handle the non linear interconnected systems. Further, the disadvantage of using the null product technique %given in the litterature when relying on the fuzzy Lyapunov function is explored. Unlike the continuous time TS fuzzy systems, the null product technique, when applied to continuous-time TS fuzzy large-scale systems (CFLSS) leads to more conservative results. Numerical examples in both cases of stability and design controller are presented to illustrate this disadvantage.
Paper VI123-12.3
PDF · Video · Robust Output Agreement of Multi-Agent Systems with Flexible Topologies
Wang, Zhanxiu	State Key Laboratory of Synthetical Automation for Process Indus
Liu, Tengfei	Northeastern University
Jiang, Zhong-Ping	Tandon School of Engineering, New York University
Keywords: Distributed nonlinear control, Control of interconnected systems, Input-to-State Stability Abstract: This paper studies the robust output agreement problem for second-order multi-agent systems with flexible topologies subject to measurement disturbances. A new distributed control law is proposed to guarantee the robust output agreement in the sense of input-to-state stability (ISS) as long as the union of the interconnection graphs satisfies a standard connectivity condition. It is proved that, robust output agreement can be achieved in the presence of any bounded measurement disturbances if the functions of the distributed control laws are radially unbounded, and a local result can still be guaranteed if the condition of radial unboundedness is not satisfied. Numerical simulations are employed to show the effectiveness of the main result.
Paper VI123-12.4
PDF · Video · Distributed Optimization of Nonlinear Uncertain Systems: An Adaptive Backstepping Design
Qin, Zhengyan	Northeastern University
Liu, Tengfei	Northeastern University
Jiang, Zhong-Ping	Tandon School of Engineering, New York University
Keywords: Distributed nonlinear control, Lyapunov methods Abstract: This paper proposes a Lyapunov-based adaptive backstepping approach to distributed optimization of nonlinear uncertain multi-agent systems. The model of each agent is in the strict-feedback form with parametric uncertainties. By only using local objective functions, this paper aims to solve the distributed optimization problem for the multi-agent system such that the outputs of the agents converge to the optimizer of the total objective function. Based on the idea of adaptive backstepping, the distributed optimization problem for the high-order multi-agent system is decomposed into solving the optimization or control problem for multiple first-order subsystems. The technical contributions lie in a Lyapunov-based design for distributed optimization, and a refined nonlinear damping design to deal with the newly appearing nonlinear uncertain terms caused by optimization. Based on the new designs, a Lyapunov function is constructed for the entire system, and the LaSalle-Yoshizawa Theorem is employed for convergence analysis. It is shown that the objective of distributed optimization is achievable if the local objective functions are convex with at least one of them being strongly convex. Computer-based numerical simulation is employed to show the effectiveness of the proposed design.
Paper VI123-12.5
PDF · Video · Mitigation of Quantization Effect in Observer-Based State-Feedback Control with Quantized Observation
Ohno, Shuichi	Hiroshima University
Atarashi, Kuga	Hiroshima University
Katayama, Tohru	Professor Emeritus Kyoto University
Keywords: Networked systems, Observers for linear systems Abstract: This paper studies observer-based state-feedback control of a linear system, where the observation signal is corrupted by the quantization error of an error feedback quantizer that consists of a uniform quantizer and a feedback filter. To mitigate the effect of the quantization error on the system output, we minimize the H2 norm of the transfer function from the round-off error of the uniform quantizer to the system output with respect to the observer gain and the feedback filter alternatively. The minimization with respect to the observer gain is formulated into an optimization under a linear matrix inequality and a bilinear matrix inequality, whose minimum is numerically found by an XY-centering algorithm. The minimization with respect to the feedback filter is a convex optimization whose solution can be numerically obtained. The two minimization problems are iteratively solved, until the H2 norm converges. A numerical example is provided to see the performance of our method.
Paper VI123-12.6
PDF · Video · Distance-Based Formation Maneuvering of Non-Holonomic Wheeled Mobile Robot Multi-Agent System
Hernández León, Pablo	CINVESTAV
Davila, Jorge	Instituto Politecnico Nacional
Salazar, Sergio	CINVESTAV
Ping, Xubin	Xidian University
Keywords: Networked systems, Sliding mode control, UAVs Abstract: In this paper, finite-time distance-based formation maneuvering control of a nonholonomic wheeled mobile robot multi-agent system in a leader-follower configuration is considered. The desired formation graph is assumed to be minimally and infinitesimally rigid, and only a subset of agents has access to the relative position and velocity of the leader. A distributed velocity estimator is employed by each agent to estimate the leader's velocity and therefore, the swarm velocity in finite-time. A finite-time formation maneuvering algorithm is presented and it is proved that drives the agents to the desired formation and tracks the leader's velocity in finite-time. Moreover, it is demonstrated that both the velocity estimator and the controller can be implemented in the agents' local coordinate frames. Simulations are provided to illustrate the effectiveness of the proposed algorithms.
Paper VI123-12.7
PDF · Video · Bearing Leader-Follower Formation Control under Persistence of Excitation
Tang, Zhiqi	Instituto Superior Técnico, Universidade De Lisboa
Cunha, Rita	Instituto Superior Técnico, Universidade De Lisboa
Hamel, Tarek	Université De Nice Sophia Antipolis
Silvestre, Carlos	University of Macau
Keywords: Nonlinear cooperative control, Distributed nonlinear control, Lyapunov methods Abstract: This paper addresses the problem of formation control with a leader-follower structure in three dimensional space by exploring persistence of excitation (PE) of the desired bearing reference, which is provided by a possibly moving or time-varying desired formation. Using only bearing measurements, control laws are proposed for a group of agents with single-integrator dynamics. By defining a desired formation such that the corresponding inter-vehicle bearing measurements are persistently exciting, relaxed conditions on the interaction topology (which do not require bearing rigidity nor constraint consistence) can be used to derive distributed control laws that guarantee exponential stabilization of the desired formation in terms of relative position. A key outcome of this approach is that even if there is only one connection originated from each follower, exponential stability of the formation can be achieved as long as the excitation conditions are met on the desired formation. The approach generalizes stability results provided in prior work for leader-first follower (LFF) structure, based on bearing rigidity and constraint consistence that required at least two connections for each follower except for the first one. Simulations results are provided to illustrate the performance of the proposed control method.
Paper VI123-12.8
PDF · Video · Non-Fragile Exponential Consensus of Nonlinear Multi-Agent Systems Via Sampled-Data Control
Ramasamy, Saravanakumar	Hiroshima University
Mukaidani, Hiroaki	Hiroshima University
Amini, Amir	Concordia University
Keywords: Stability of nonlinear systems, Robust control, Time-varying systems Abstract: In this article, non-fragile exponential consensus problem is investigated for nonlinear multi-agent systems (MASs) with nonlinear dynamics through the use of sampled-data controllers. The sampled-data system is translated to a continuous system with time-varying delay through input delay approach via control input. With the introduction of a sampled-data approach, the information is sent only to the network at each sampling instant and is inevitably subject to a transmission delay. By using the tools from algebraic graph theory and Lyapunov-Krasovskii functional (LKF) technique, it is proved that the concerned non-fragile consensus problem is solvable if the resultant consensus error system can be exponentially stabilized. Numerical example is given to illustrate the merits of the results obtained.
Paper VI123-12.9
PDF · Video · A Modified Hybrid Izhikevich Neuron: Modeling, Synchronization, and Experiments
Ortega, Guillermo	CICESE
Nuñez, Ricardo F.	CICESE
Pena Ramirez, Jonatan	Center for Scientific Research and Higher Education at Ensenada
Keywords: Hybrid and switched systems modeling, Experiment design Abstract: The original Izhikevich neuronal model is described by a nonlinear mathematical model with a static reset map. Due to the fact that the reset is applied instantaneously, it is not easy to implement this model with analog circuits. Consequently, this paper presents a modified Izhikevich neuronal model, in which the static and instantaneous reset is replaced by a dynamic reset, which is physically implementable. Furthermore, the resulting system is modeled as a hybrid system with two discrete modes. Additionally, the occurrence of synchronization in a pair of modified Izhikevich neurons is investigated and a comment on the local stability of the synchronous solution is given. Ultimately, the performance of the modified Izhikevich model is experimentally validated using electronic circuits.

VI123-13
Nonlinear Control for Aerospace Systems	Regular Session
Chair: Lefeber, Erjen	Eindhoven Univ of Technology
Co-Chair: Pereira, Fernando Lobo	Porto University
Paper VI123-13.1
PDF · Video · ESO-Based Saturated Deployment Control of Tethered Satellite System with Finite-Time Tracking Performance Guarantees
Wei, Caisheng	Central South University
Bian, Yanzhu	Central South University
Liao, Yuxin	Central South University
Luo, Shibin	Central South University
Yin, Zeyang	Northwestern Polytechnical University
Luo, Jianjun	School of Astronautics, Northwestern Polytechnical University
Keywords: Aerospace, Constrained control, Systems with saturation Abstract: This paper investigates a novel finite-time saturated deployment control approach for the tethered satellite system in the presence of uncertain dynamics and space perturbations, as well as state constraints. First, an integral Lyapunov function is constructed to remove the hard state constraints characterized by a finite-time convergent performance function. Then, a backstepping finite-time deployment controller is devised via using an extended state observer (ESO) to approach the unknown dynamics, perturbations and saturation deviation. Compared with the existing finite-time control methods, the prominent advantage of the proposed one is that the finite-time saturated deployment control is achieved without violating the state constraints and using fractional state feedback. Finally, an illustrative example is organized to validate the effectiveness of the proposed approach.
Paper VI123-13.2
PDF · Video · Rapid Fault Detection for Spacecraft in Infrared Reconstructed Images Using Image Mosaic Technique
Zhang, Kuo	University of Electronic Science and Technology of China
Yin, Chun	University of ElectronicScience and Technology of China, Chengdu6
Cheng, Yu-hua	University of Electronic Science and Technology of China
Huang, Xuegang	China Aerodynamics Research & Development Center
Dadras, Sara	Utah State University
Gou, Xuan	University of Electronic Science and Technology of China
Keywords: Aerospace, Fault-tolerant, Diagnosis Abstract: In order to satisfy the real-time and large scale requirement of spacecraft non-destructive testing using optical pulsed thermography, in this research, we propose a novel approach based on image mosaic technique which can create large scale or panoramic image mosaics from a set of ordered infrared reconstruction images with overlapping areas for defect detection. First, infrared reconstruction images are extracted from the original thermal video stream by the ICA method based on the idea of blind source signal processing. Then for this research's special mosaic object, a fast and accurate registration scheme is proposed. Abundant scale rotation invariant feature points are quickly obtained by using the hybrid feature detector and descriptor. Moreover, the feature matching process is realized by applying two-way FLANN and MSAC, parameters of the geometric transformation matrix are estimated by MSAC, and image mosaic is realized according to the geometric transformation model. The experimental results convinced the validity and efficiency of the proposed method.
Paper VI123-13.3
PDF · Video · Experimental Study for µm-Class Control of Relative Position and Attitude for Synthetic Aperture Telescope Using Formation Flying Micro-Satellites
Suzumoto, Ryo	The University of Tokyo
Ikari, Satoshi	The University of Tokyo
Miyamura, Norihide	Meisei University
Nakasuka, Shinichi	University of Tokyo
Keywords: Aerospace, Model validation, Disturbance rejection Abstract: Earth remote sensing from geostationary orbit (GEO) realizes high time resolution that is essential for disaster monitoring; however, the spatial resolution is commonly worse than observation from low Earth orbit (LEO). In order to achieve high-resolution and high-frequency GEO remote sensing, we have proposed a "Formation Flying Synthetic Aperture Telescope (FFSAT)" with multiple micro-satellites. The FFSAT can improve the spatial resolution by using the technique of a synthetic aperture, and therefore the relative positions and attitudes between the optical units of each satellite must be controlled with an accuracy better than 1/10 of the observation wavelength. In order to verify feasibility of such highly accurate control, µm-class control experiments were conducted by using COTS components, and numerical models of the components were constructed. Results of the experiments were integrated into a software simulator, and the µm-class formation flying control of the entire FFSAT system was numerically evaluated. In this simulation, highly accurate control was achieved with dual-stage actuators, which consist of piezo actuators and thrusters. The simulation results show that the formation can be controlled in µm-class accuracy under some assumptions.
Paper VI123-13.4
PDF · Video · Agile Spacecraft Attitude Control: An Incremental Nonlinear Dynamic Inversion Approach
Acquatella B., Paul	DLR, German Aerospace Center
Chu, Qiping	Delft University of Technology, Faculty of AerospaceEngineering
Keywords: Aerospace, Tracking, Application of nonlinear analysis and design Abstract: This paper presents an agile and robust spacecraft attitude tracking controller using the recently reformulated incremental nonlinear dynamic inversion (INDI). INDI is a combined model- and sensor-based control approach that only requires a control effectiveness model and measurements of the state and some of its derivatives, making a reduced dependency on exact system dynamics knowledge. The reformulated INDI allows a non-cascaded dynamic inversion control in terms of Modified Rodrigues Parameters (MRPs) where scheduling of the time-varying control effectiveness is done analytically. This way, the controller is only sensitive to parametric uncertainty of the augmented spacecraft inertia and its wheelset alignment. Moreover, we draw some parallels to time-delay control (TDC) -more familiar in the robotics community- which have been shown to be equivalent to the incremental formulation of proportional-integral-derivative (PID) control for second order nonlinear systems in controller canonical form. Simulation experiments for this particular problem demonstrate that INDI has similar nominal performance as TDC/PID control, but superior robust performance and stability.
Paper VI123-13.5
PDF · Video · Hybrid Control of Fixed-Wing UAVs for Large-Angle Attitude Maneuvers on the Two-Sphere
Reinhardt, Dirk Peter	Norwegian University of Science and Technology
Coates, Erlend M.	Norwegian University of Science and Technology
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Application of nonlinear analysis and design, UAVs, Discontinuous control Abstract: We propose the design of a hybrid controller for fixed-wing unmanned aerial vehicles which guarantees global exponential tracking of attitude references on the two-sphere. The chosen attitude representation is singularity-free and can be exploited to apply proportional feedback along the shortest path in the natural configuration space, giving it an advantage to conventional design methods based on Euler angle reprentations. The design includes the concept of synergistic potential functions to overcome the problem of a vanishing potential at the additional undesired equilibrium on the compact manifold. It employs proportional- derivative feedback with the relative velocity as an exogeneous input and allows for integration into conventional autopilot architectures. The controller is well-suited for the recovery from large attitude disturbances and the performance is demonstrated in a numerical example.
Paper VI123-13.6
PDF · Video · Grid and Polytopic LPV Modeling of Aeroelastic Aircraft for Co-Design
Mocsányi, Réka Dóra	Institute for Computer Science and Control
Takarics, Bela	Institute for Computer Science and Control
Vanek, Balint	MTA SZTAKI
Keywords: Parameter-varying systems, UAVs, Model reduction Abstract: Future aircraft tend to have increased flexibility that leads to increased aeroservoelastic (ASE) effects. Therefore, future aircraft control systems need active control to suppress ASE effects. Active flutter suppression can be effectively done in the linear parameter varying (LPV) framework. Control surface sizing for aircraft is traditionally done by iterations. In this approach engineering rules are used to determine the size of the control surfaces and the control laws are designed afterwards. Such method, besides being time consuming, might have further challenges in the future due to the coupling between the flexible and rigid body dynamics. Instead, "co-design" was recently proposed. In the co-design approach parametric aircraft models are developed based on which the control surface sizing and the control design are optimized in a single step. The purpose of this paper is to develop a control oriented, parametric control surface model of the mini MUTT aircraft that can be applied for co-design. The resulting control oriented LPV model needs to have sufficiently low dynamic order, which is achieved by the "bottom-up" modeling approach. A grid based LPV model is obtained from the nonlinear model by Jacobian linearization and the Tensor Product (TP) type polytopic model is obtained from the grid based LPV model via TP model transformation. The resulting low order parametric control surface LPV models are assessed with the nu-gap metric. These models can serve as a basis for simultaneous control surface sizing and baseline/flutter suppression control synthesis optimization.
Paper VI123-13.7
PDF · Video · Trajectory Tracking for a Multicopter under a Quaternion Representation
Nguyen, Huu Thien	University of Porto
Nguyen, Ngoc Thinh	University of Luebeck
Prodan, Ionela	INP Grenoble
Pereira, Fernando Lobo	Porto University
Keywords: Tracking, Output feedback control, UAVs Abstract: This paper proposes a two-layer hierarchical control scheme for trajectory tracking of a multicopter system using attitude quaternion. We first present the differential flatness properties of the system and then, exploit them to design the feedback linearization laws for the position controller at the high control level. Next, the computed-torque control method is employed for stabilizing the attitude quaternion. The whole control scheme is illustrated through simulations while the position controller is further tested under experiments over a nano-drone quadcopter platform.
Paper VI123-13.8
PDF · Video · A New Robust Command Shaping Method and Its Application in Quadrotor Slung System with Varying Parameters
Li, Chenxing	Technical University of Munich
Huo, Xin	Harbin Institute of Technology
Liu, Qingquan	Harbin Institute of Technology
Keywords: Tracking, UAVs, Control problems under conflict and/or uncertainties Abstract: Command shaping method is a mature feedforward control approach, and there exist many successful applications in the industrial fields. However, the traditional instruction shapers either are sensitive to the system parameters, or have some robustness but difficult to adjust the parameters, and meanwhile their conservations are increased unsurprisingly. To this end, a new robust command shaper is proposed in this paper, which is inspired by the two-mode ZV shaper and the EI shaper. The theoretical design procedure of the new shaper is presented. Besides, the robustness of the new shaper is analyzed and compared with other shapers based on the sensitivity curve. Finally, the shaper proposed in this paper is applied to the quadrotor slung system with varying parameters, and its effectiveness and superiority are proved by numerical simulations and comparative analyses.
Paper VI123-13.9
PDF · Video · Adaptive Tracking Control for Quadrotors without Linear Velocity Measurements
Hirata Acosta, Jonathan	CICESE
Pliego, Javier	Centro De Investigación Científica Y De Educación Superior De En
Cruz-Hernandez, Cesar	Scientific Research and Advanced Studies Center of Ensenada
Keywords: UAVs, Adaptive control, Observer design Abstract: The problem of trajectory tracking of a quadrotor without using linear velocity measurements and with model parameter uncertainties is addressed in this paper. A linear observer is proposed to overcome the problem of a lack of linear velocity measurements. The proposed adaptive control algorithm exploits the cascade structure of the translational and attitude dynamics of the quadrotor and guarantees asymptotic convergence of the tracking and observer errors. The attitude control is designed based on the unit quaternion; thus, the well-known singularities of the Euler angles are avoided. Simulation results are presented to show the performance of the proposed control scheme.
Paper VI123-13.10
PDF · Video · Reduced-Attitude Control of Fixed-Wing Unmanned Aerial Vehicles Using Geometric Methods on the Two-Sphere
Coates, Erlend M.	Norwegian University of Science and Technology
Reinhardt, Dirk Peter	Norwegian University of Science and Technology
Fossen, Thor I.	NTNU
Keywords: UAVs, Aerospace Abstract: As an alternative to reduced-attitude control of fixed-wing unmanned aerial vehicles using roll and pitch angles, we propose to use a global representation that evolves on the two-sphere. The representation of reduced attitude is invariant to rotations about the inertial gravity axis, which makes it well suited for banked turn maneuvers. With the relative airspeed viewed as an exogenous input, a nonlinear controller for almost semiglobal exponential tracking of reduced attitude is presented. For the regulation case, asymptotic convergence is almost global, and the relationship to a classical approach using Euler angles is established. In addition to being singularity-free, a benefit of the presented approach is that the proportional action is pointed along the shortest direction on the sphere. The performance of the controller is demonstrated in numerical simulations.
Paper VI123-13.11
PDF · Video · Fast Hildreth-Based Model Predictive Control of Roll Angle for a Fixed-Wing UAV
Lam, Victor Truong Thinh	Eindhoven University of Technology
Sattar, Abdul	RMIT University
Wang, Liuping	RMIT University
Lazar, Mircea	Eindhoven Univ. of Technology
Keywords: UAVs, Predictive control, Numerical methods for optimal control Abstract: In this paper we consider model predictive control (MPC) design for roll angle control for a fixed-wing unmanned aerial vehicle (UAV) with multiple segmented control surfaces. The challenge of roll angle control for a fixed-wing UAV consists of switching between inner and outer aileron pairs with hard constraints due to safety, energy saving and switching actuators. The novelty consists of formulating a hybrid control problem as a switched linear constrained MPC-QP problem and switched state observer design for fixed-wing UAV. A fast novel QP-solver based on the active-set QP-solver Hildreth is developed to meet the real-time implementation sampling time of Ts=10 ms. The designed MPC controllers are simulated using Matlab. Simulations and the CPU-time from the improved QP-solvers show MPC to be a very good solution for real-time roll angle control of fixed-wing UAVs.
Paper VI123-13.12
PDF · Video · Filtered Output Feedback Tracking Control of a Quadrotor UAV
Lefeber, Erjen	Eindhoven Univ of Technology
Greiff, Carl Marcus	Lund University
Robertsson, Anders	LTH, Lund University
Keywords: UAVs, Tracking, Output feedback control Abstract: We present a tracking controller for quadrotor UAVs which uses partial state information and filters measurement noise. We show uniform almost global and locally exponential asymptotic stability of the resulting closed-loop system, which implies robustness against bounded disturbances. We illustrate the performance of the controller by means of several numerical examples, including a complex looping maneuver.

VI123-15
Nonlinear Systems	Regular Session
Chair: Marconi, Lorenzo	Univ. Di Bologna
Co-Chair: Zaccarian, Luca	LAAS-CNRS and University of Trento
Paper VI123-15.1
PDF · Video · Input-Output Decoupling and Linearization of Nonlinear Multi-Input Multi-Output Time-Varying Delay Systems
Nicolau, Florentina	Ensea Cergy
Haidar, Ihab	ENSEA
Barbot, Jean Pierre	ENSEA
Aggoune, Woihida	ENSEA
Keywords: Delay systems Abstract: In this paper, we study the input-output decoupling and linearization of nonlinear multi-input multi-output time-varying delay systems. More precisely, we construct a feedback transformation for which the input-output map of the feedback modified system is linear. Contrary to the case of control systems without delay, when working with delay systems, two problems may arise when designing such a feedback: first, the control may not be bounded and, second, it may not be causal. In Nicolau et al. (2018), the authors gave an algorithm for the construction of a causal and bounded feedback that proposes a solution for the input-output decoupling and linearization problem for the particular case of two-input two-output systems. In the present paper, we generalize that algorithm to the multi-input multi-output case. The main idea of the algorithm is to introduce, at each step when the input-output decoupling is not possible, an artificial delay for the inputs that appear "too early" in the system.
Paper VI123-15.2
PDF · Video · Analysis and Modeling of State-Dependent Delay in Control Valves
Bram, Mads Valentin	Aalborg University Esbjerg
Calliess, Jan-Peter	University of Oxford
Roberts, Stephen	University of Oxford
Hansen, Dennis	Aalborg Universit Esbjerg
Yang, Zhenyu	Aalborg University
Keywords: Delay systems, Model validation, Process control Abstract: Pneumatic control valves are deployed in a wide variety of industrial applications and plants. The plethora of valve applications has a great span in required operational accuracy and time scales, from precise medical dosing valves to large valves used for level control in offshore separation tanks. It is common for these valves to have inherent position control deployed by the manufacturer, and as a result, these valve systems often receive a wanted opening degree, where the inherent position control drives the actual valve opening towards the wanted opening degree. From previous works utilizing pneumatic control valves for offshore produced water treatment, an inconsistent input-output delay was observed. This work presents experiments to detect and describe these delays, such that the model may be incorporated in the design of improved control solutions that account for these behaviors. A pin-cart model with state-dependent delay is proposed, validated using data from a continuously actuated valve, and compared to commonly used existing valve models. The proposed model exerts the state-dependent input-output delay successfully.
Paper VI123-15.3
PDF · Video · Predictor-Based Control for Nonlinear Mechanical Systems with Measurement Delay
Osuna-Ibarra, Linda Patricia	CINVESTAV-IPN GDL
Caballero-Barragán, Humberto	CINVESTAV-IPN GDL
Loukianov, Alexander G.	Cinvestav Ipn Gdl
Keywords: Delay systems, Tracking, Disturbance rejection Abstract: In this paper, a controller for nonlinear systems with delay in the measurement using a predictor-based strategy is proposed. The nonlinear systems considered in this work are the class of mechanical systems of triangular form and which mathematical model can be obtained by means of the Euler-Lagrange formulation. A predictor for the mechanical nonlinear system is applied in order to get a delay-free system. Then, a tracking PD controller is designed using the predictor to compensate the delay effect. In order to demonstrate the effectiveness of the control scheme proposed, two examples are presented, one to show the performance of the predictor and the other one to show the use of such predictor in order to control the system. Then, a tracking controller for time-varying references is designed for mechanical systems with measurement delay, and the performance is shown during simulation. Additionally, it is considered the case when external disturbances are present in the system and to deal with them a method of estimation of the disturbance is proposed. The results are shown and discussed and finally the conclusions for this work are given and ideas for future work are proposed.
Paper VI123-15.4
PDF · Video · A Study of the Influence of Stochastic Fractional-Order Delay Dynamics in a Networked Control System
Viola, Jairo	University of California Merced
Oziablo, Piotr	Bialystok University of Technology
Chen, YangQuan	University of California, Merced
Keywords: Networked systems, Systems with time-delays, Fractional systems Abstract: Stochastic communication delays are present in networked control systems and have a significant in uence over its closed-loop performance and stability. These delays are time-variant and have infinite variance, which indicates fractional-order behavior that can be modeled using alpha-stable distribution. This paper presents a quantitative analysis of the effects of fractional-order alpha-stable distribution random communication delays in a networked control system for a temperature control application. The networked closed-loop system assessment is performed using four different controllers. Two integer order PI controllers tuned using classic tuning methods, and two fractional-order PI controllers tuned using standard tuning rules for fractional-order system. One hundred simulation experiments are performed, modeling the random communication delays between the plant and controller using a alpha-Stable distribution with variable fractional-order. Obtained results show that fractional-order controllers can deal better with time-variant fractional-order random communication delays that follows an alpha-Stable distribution compared with the integer-order controllers.
Paper VI123-15.5
PDF · Video · Agile Latency Estimation for a Real-Time Service-Oriented Software Architecture
Kampmann, Alexandru	RWTH Aachen University
Mokhtarian, Armin	RWTH Aachen University
Rogalski, Jan	RWTH Aachen University
Kowalewski, Stefan	RWTH Aachen Univ
Alrifaee, Bassam	RWTH Aachen University
Keywords: Networked systems, Systems with time-delays, Supervision and testing Abstract: This paper presents our testbed and software pipeline for automatic latency estimation for a service-oriented software architecture (SOA). This type of architecture consists of modular services that are dynamically combined at runtime to form a functioning system. As different service combinations become possible at runtime, agile approaches for testing the resulting systems become necessary. Besides other factors, latencies are of particular interest for the implementation of control systems. Our agile approach automatically generates dummy services, including interfaces and tasks for internal processing, based on a service description in a human-readable format. Services are then automatically distributed to the computers of our testbed, which are connected through Ethernet. We empirically obtain latency estimates for processing and communication steps for a given composition of services. In this paper we describe our data format, abstractions about internal run-time behavior of services and the code generation pipeline. The evaluation presents latency estimates that we are able to obtain through our testbed that resembles the sense-plan-act paradigm.
Paper VI123-15.6
PDF · Video · Passivity-Based PI Control for AGV Wireless Power Transfer System
Liu, Jia	Zhejiang University
Liu, Zhitao	Zhejiang University
Su, Hongye	Zhejiang University
Keywords: Passivity-based control Abstract: Automatic guided vehicles (AGVs) recently have gained increasing attentions and applications, however, frequently stopping to recharge largely reduces service efficiency. Wireless power transfer (WPT) is considered as a practice energization way to solve this problem. In this paper, a passivity-based controller (PBC) and parameter designing method for compensation topology are proposed for AGVs WPT system. The PBC based on port-controlled Hamiltonian system (PCHS) is designed to achieve desired constant systematic working power by regulating the output voltage of DC/DC converter. The LCC-LCC resonant network is analyzed in the principle of the impedance matching method, and a proportional integral (PI) controller is implemented to realize zero steady-state error. Simulation are carried out in PLECS to verify analysis, and results show that proposed controller scheme and compensation designing method ensure the stability of the charging system against load variations, and the fast response performance of the control algorithm is also validated.
Paper VI123-15.7
PDF · Video · Stabilization of Passive Dynamical Systems with Actuator and Sensor Disturbances
Golubev, Alexey	Bauman Moscow State Technical University
Utkina, Nadezhda	Bauman Moscow State Technical University
Keywords: Passivity-based control, Input-to-State Stability, Robust control Abstract: We analyze stabilizability of passive dynamical systems subject to actuator and sensor disturbances. New sufficient conditions are given for the conventional static output feedback, which is used to stabilize passive systems, to guarantee the (integral) input-to-state stability property with respect to the disturbances. As an illustrative example application of the obtained results to robust state observer redesign is considered.
Paper VI123-15.8
PDF · Video · Nonlinear Swing down Control of the Acrobot
Xin, Xin	Okayama Prefectural University
Sakurai, Maki	Okayama Prefectural University
Izumi, Shinsaku	Okayama Prefectural University
Yamasaki, Taiga	Okayama Prefectural University
She, Jinhua	Tokyo Univ. of Tech
Liu, Yannian	Southeast University
Keywords: Passivity-based control, Stability of nonlinear systems, Asymptotic stabilization Abstract: In this paper, we concern swing down control of the Acrobot which is a 2-link planar robot with a single actuator driving the second joint, whose control objective is to stabilize the Acrobot to the downward equilibrium point with the two links in the downward position for all initial states of the Acrobot with the exception of a set of Lebesgue measure zero. To achieve this control objective, we design a nonlinear controller by using nonnegative linear feedback of the sine function of the angle of the second joint in addition to the negative linear feedback of its angular velocity. By analyzing globally the solution of the closed-loop system consisting of the Acrobot and the presented controller and focusing on the equilibrium points of the closed-loop system and their stability, we prove that the control objective is achieved provided that some conditions on two control gains are satisfied. We design the two control gains such that the real parts of the dominant poles of the linearized model of the closed-loop system around the downward equilibrium point are minimized. We provide simulation results for two Acrobots to show the effectiveness of the presented controller.
Paper VI123-15.9
PDF · Video · Uniform Global Asymptotic Synchronization of Kuramoto Oscillators Via Hybrid Coupling
Bertollo, Riccardo	Università Degli Studi Di Trento
Panteley, Elena V.	CNRS, ITMO
Postoyan, Romain	CRAN, CNRS, Université De Lorraine
Zaccarian, Luca	LAAS-CNRS and University of Trento
Keywords: Stability of hybrid systems, Networked systems, Lyapunov methods Abstract: Using a hybrid framework, we propose a generalized version of the well-known Kuramoto model for interconnected oscillators. The proposed model does not modify the classical model close to the synchronization set, but avoids the typical non-uniform convergence phenomenon. For the two-oscillators case, we prove the uniform global asymptotic stability of the consensus set by using a hybrid Lyapunov function whose generality promises possible extension of the result to higher order dynamics. We comparatively illustrate the achieved uniform convergence properties by simulating both the case with two and multiple oscillators, thus confirming the effectiveness of our approach.
Paper VI123-15.10
PDF · Video · A Hybrid Control Algorithm for Gradient-Free Optimization Using Conjugate Directions
Melis, Alessandro	University of Bologna
Sanfelice, Ricardo	University of California Santa Cruz
Marconi, Lorenzo	Univ. Di Bologna
Keywords: Stability of hybrid systems, Robustness analysis, Convex optimization Abstract: The problem of steering a particular class of n-dimensional continuous-time dynamical systems towards the minima of a function without gradient information is considered. We propose an hybrid controller, implementing a discrete-time Direct Search algorithm based on conjugate directions, able to solve the optimization problem for the resulting closed loop system in an almost global sense. Moreover, we propose a modified version by imposing a lower bound on the step size and able to achieve robust practical convergence to the optimum.
Paper VI123-15.11
PDF · Video · Control Design for Interval Type-2 Takagi-Sugeno Singular Systems with Time Delay
Makni, Salama	University of Gabes, Department of Electrical and Automatic Engi
Kchaou, Mourad	University of Hail Saudi Arabia
El Hajjaji, Ahmed	Univ. De Picardie Jules Verne
Chaabane, Mohamed	University of Sfax-Lab-STA
Keywords: Stability of nonlinear systems, Delay systems, Lyapunov methods Abstract: In this work, the admissibility analysis and the control problem are investigated for nonlinear singular systems represented by interval type-2 Takagi-Sugeno (T-S) fuzzy models with time delay. First, the interval type-2 fuzzy singular systems with time delay have been described. Second, the admissibility analysis of the autonomous singular systems is studied. Third, the control problem has been investigated. For this, an interval type-2 fuzzy control law is designed to guarantee the admissibility of the closed-loop system despite the presence of uncertainties and time delay. To demonstrate the existence of the proposed controller, by using generalised integral inequalities, sufficient delay-dependent conditions are given in terms of Linear Matrix Inequalities (LMIs). Finally, an application to inverted pendulum system presented by interval type-2 fuzzy models is afforded to show the effectiveness of the suggested method.
Paper VI123-15.12
PDF · Video · An Alternating Projection Algorithm for the "approximate" GCD Calculation
Limantseva, Olga	City, University of London
Halikias, George	City Univ
Karcanias, Nicos	City University London
Keywords: Application of nonlinear analysis and design, Polynomial methods, Structural properties Abstract: In the paper an approach is proposed for calculating the "best" approximate GCD of a set of coprime polynomials. The algorithm is motivated by the factorisation of the Sylvester resultant matrix of polynomial sets with nontrivial GCD. In the (generic) case of coprime polynomial sets considered here the aim is to minimise the norm of the residual error matrix of the inexact factorisation in order to compute the "optimal" approximate GCD. A least-squares alternating projection algorithm is proposed as an alternative to the solution of the corresponding optimisation problem via nonlinear programming techniques. The special structure of the problem in this case, however, means that the algorithm can be reduced to a sequence of standard subspace projections and hence no need arises to compute gradient vectors, Hessian matrices or optimal step-lengths. An estimate of the asymptotic convergence rate of the algorithm is finally established via the inclination of two subspaces.
Paper VI123-15.13
PDF · Video · Local Controllability of Magnetized Purcell's Swimmers
Moreau, Clément	Inria Sophia Antipolis
Keywords: Motion Control Systems, Identification and control methods, Micro and Nano Mechatronic Systems Abstract: We focus on the control theory aspects of the dynamics of magnetized micro-swimmer robots made of two or three rigid links. Under generic assumptions on the parameters, we show that the control system which models the swimmers' dynamics is locally controllable in small time around its equilibrium position (the straight line), but with bounded controls that do not go to zero as the target state gets closer to the initial state. Numerical simulations illustrate the results, which are relevant for useful applications in the micro-swimming field.
Paper VI123-15.14
PDF · Video · Rapidly Oscillating Systems on the Plane: Weak Resonances and Asymptotic Control
Belikov, Sergey	SPM Labs
Belikov, Ruslan	NASA
Keywords: Non-smooth and discontinuous optimal control problems, Control of bifurcation and chaos, Optimal control theory Abstract: Rapidly Oscillating Systems (ROS) is a class of perturbed dynamical systems with a small parameter that contains oscillating part with the period proportional to the parameter. These include a lot of classical perturbed systems that found wide applications in celestial mechanics, electronics, mechatronics, nanotechnology, etc. However, many important systems of the class cannot be treated classically. In recent years these non-classical ROS found important applications in control of bipedal walk, rapidly varying media, frequency demodulation, Atomic Force Microscopy, etc. A characteristic specific of the non-classical ROS is that oscillations depend not only on time, but also on phase variables. This allows to manipulate the oscillation functions and to use them for asymptotic control. The purpose of this paper is to illustrate non-classical ROS methods and their properties on simple, but representative, 2D examples without technical details of real applications. In some cases these also provide a new technique to the classical systems.

VI123-16
Stabilization of Nonlinear Systems	Regular Session
Chair: Polyakov, Andrey	INRIA Lille Nord-Europe
Co-Chair: Zerrik, E. Hassan	MACS Team; Sciences Faculty, Moulay Ismail University
Paper VI123-16.1
PDF · Video · Reduction-Based Stabilization of Nonlinear Discrete-Time Systems through Delayed State Measurements
Mattioni, Mattia	Università Degli Studi Di Roma La Sapienza
Moreschini, Alessio	Sapienza University of Rome
Monaco, Salvatore	Sapienza Università Di Roma
Normand-Cyrot, Marie-Dorothée	CNRS-Univ. Paris-Sud-Supélec
Keywords: Asymptotic stabilization, Delay systems, Lyapunov methods Abstract: In this paper, the problem of stabilizing nonlinear discrete-time systems affected by delayed state measures is addressed under average passivity-based control. The contribution stands in the introduction of a new delay-free dynamics which is used for the design of the stabilizing feedback. Simulations over an academic example illustrate the performances in a comparative sense.
Paper VI123-16.2
PDF · Video · Stabilization of Equilibrium for Underactuated Mechanical Systems without Potential Energy
He, Xiaodong	Peking University
Geng, Zhiyong	Peking University
Keywords: Asymptotic stabilization, Lagrangian and Hamiltonian systems, Control of constrained systems Abstract: This paper investigates the equilibrium stabilization problem for a class of underactuated mechanical systems which do not possess potential energy. The dynamics of the system is established under the framework of Rimannian geometry, and differential geometric methods are employed in the design of stabilization controller. The main novelty of this paper is that we stabilize the equilibrium by constructing an artificial potential for the closed-loop system, which is related to the designed configuration feedback. Once the artificial potential satisfy certain requirements with respect to the equilibrium, the stability of the system can be guaranteed. Furthermore, by incorporating dissipative feedback into the control strategy, we successfully obtain the exponential stability of the equilibrium.
Paper VI123-16.3
PDF · Video · On Estimation and Feedback Control of Spin-1/2 Systems with Unknown Initial States
Liang, Weichao	L2S, CentraleSupélec
Amini, Nina Hadis	L2S, CentraleSupelec, CNRS
Mason, Paolo	L2S CentraleSupélec, CNRS
Keywords: Asymptotic stabilization, Lyapunov methods, Stability of nonlinear systems Abstract: In this paper, we consider stochastic master equations describing the evolutions of quantum systems interacting with electromagnetic fields undergoing continuous-time measurements. In particular, we study feedback control of quantum spin-1/2 systems in the case of unawareness of initial states and in presence of measurement imperfections. We prove that the fidelity between the true quantum filter and its estimation (with arbitrary initial state) converges to one under appropriate assumption on the feedback controller. This shows the asymptotic convergence of such filters. In the more general case of spin-J systems, we discuss heuristically the asymptotic behavior of the true quantum filter and the associated estimation, and the possibility of exponentially stabilizing such systems towards an eigenvector of the measurement operator by an appropriate feedback.
Paper VI123-16.4
PDF · Video · On the Stability and Stabilization of Nonlinear Non-Stationary Discrete Systems
Andreev, Aleksandr	Ulyanovsk State University
Peregudova, Olga	Ulyanovsk State University
Sutyrkina, Katherine	Ulyanovsk State University
Keywords: Asymptotic stabilization, Lyapunov methods, Stability of nonlinear systems Abstract: The study of many biological, economic and other processes leads to its modeling based on discrete equations. Currently, the need to develop a mathematical apparatus for the qualitative analysis of discrete equations is caused by the creation of digital control systems, processors and microprocessors as well as discrete methods of signal transmission in automatic control systems and other theoretical and technical problems. One of the important areas of the qualitative analysis of discrete equations is the stability problem. The main method for studying the stability of nonlinear differential, discrete, and other types of equations is the direct Lyapunov method. The aim of this paper is to develop the direct Lyapunov method in the study of the limiting behavior and asymptotic stability of nonlinear nonstationary discrete equations using the comparison principle. New theorems are proved that are applied in the stability problem of the well-known epidemiological model as well as in solving the stabilization problem of a nonlinear discrete controlled system. An example is shown illustrating a qualitative difference in the conditions of stabilization of non-stationary and stationary discrete systems.
Paper VI123-16.5
PDF · Video · Data-Driven Robust Stabilization with Robust DOA Enlargement for Nonlinear Systems
Lu, Chaolun	Zhejiang University of Technology
Li, Yongqiang	Zhejiang University of Technology
Hou, Zhongsheng	Beijing Jiaotong Univ
Feng, Yuanjing	Zhejiang University of Technology
Feng, Yu	Zhejiang University of Technology
Chi, Ronghu	Qingdao University of Science and Technology
Bu, Xuhui	Henan Polytechnic University
Keywords: Asymptotic stabilization, Robust control, Data-based control Abstract: This paper present a method based on simulation data to optimize Lyapunov functions to stabilize nonlinear systems such that an estimation of the domain of attraction (DOA) is maximized. For non-affine nonlinear system, our previous work proposes an approach to estimate robust closed-loop DOA for uncertain nonlinear systems by sampling the state- and input-space. However, the main drawback is that the Lyapunov function is given and does not consider the problem of finding a good Lyapunov function to enlarge the estimate of the robust closed-loop DOA. The motivation of this paper is to enlarge the estimate of the closed-loop DOA in order to reduce conservatism of the DOA estimate. To achieve this goal, a solvable optimization problem is formulated to use sum-of-squares techniques to evaluate the cost for a given Lyapunov function and then optimizing over Lyapunov functions via existing meta-heuristic optimization methods. The effectiveness of proposed method is verified by numerical results.
Paper VI123-16.6
PDF · Video · On Finite-Time Stability of Sub-Homogeneous Differential Inclusions
Braidiz, Youness	Ecole Centrale De Lille
Efimov, Denis	Inria
Polyakov, Andrey	INRIA Lille Nord-Europe
Perruquetti, Wilfrid	Ecole Centrale De Lille
Keywords: Asymptotic stabilization, Stability of nonlinear systems, Lyapunov methods Abstract: Sub-homogeneity property is introduced and is related to differential inclusion (DI). A non linear ordinary differential equation or ODE (which may not admit a homogeneous approximations) can be transformed into a sub-homogeneous DI (which is a homogeneous extension of the original ODE). Using this homogeneous extension, one can directly recover finite-time stability property for some particular class of nonlinear systems. In the last section, such sub-homogeneity property is used to design a nonlinear finite-time observer.
Paper VI123-16.7
PDF · Video · An Output Stabilization of Second Order Semilinear Systems
Ezzaki, Lahcen	Higher School of Education and Training, Ibn Zohr University, Ag
Zerrik, E. Hassan	MACS Team; Sciences Faculty, Moulay Ismail University
Keywords: Asymptotic stabilization, Stability of nonlinear systems, stability of distributed parameter systems Abstract: This paper considers regional stabilization for a class of second order semilinear systems on a subregion of the system evolution domain. Then under sufficient conditions we give controls that ensure regional exponential and strong stabilization.

VI123-17
Nonlinear Observers and Applications	Regular Session
Chair: Kravaris, Costas	Texas A&M University
Co-Chair: Zaccarian, Luca	LAAS-CNRS and University of Trento
Paper VI123-17.1
PDF · Video · PEMFC State and Parameter Estimation through a High-Gain Based Adaptive Observer
Cecilia, Andreu	Institut De Robòtica I Informàtica Industrial, CSIC-UPC
Serra, Maria	Universitat Politècnica De Catalunya
Costa-Castelló, Ramon	Universitat Politècnica De Catalunya (UPC)
Keywords: Energy systems, Nonlinear observers and filter design, Observer design Abstract: This work presents the design of an adaptive observer to estimate the cathode catalytic layer's water content of a polymer electrolyte membrane fuel cell and some of the parameters related to its water dynamics. However, in general, existing adaptive observer algorithms require a certain relative degree condition which is not satisfied in the concerned fuel cell system. This conflict is solved by modifying the adaptive observer strategy with an auxiliary signal that does satisfy the relative degree condition. This signal is estimated through a high-gain observer. The viability of the presented observer is validated through numerical simulations.
Paper VI123-17.2
PDF · Video · Sampled-Data Observers for Delay Systems
Ahmed-Ali, Tarek	Université De Caen Normandie
Karafyllis, Iasson	National Technical University of Athens
Giri, Fouad	University of Caen Normandie
Keywords: Nonlinear observers and filter design, Delay systems Abstract: This paper studies the problem of designing sampled-data observers and observer-based, sampled-data, output feedback stabilizers for systems with both discrete and distributed, state and output time-delays. The obtained results can be applied to time delay systems of strict-feedback structure. The proposed design approach consists in exploiting an existing observer, which features robust exponential convergence of the error when continuous-time output measurements are available. The observer is then modified, mainly by adding an inter-sample output predictor, to compensate for the effect of data-sampling. Using Lyapunov stability tools and small-gain analysis, we show that robust exponential stability of the error is preserved, provided the sampling period is not too large.
Paper VI123-17.3
PDF · Video · Capacity Estimation of Lithium-Ion Battery Based on Electrochemical Model with Electrolyte Dynamics
Chen, Guangwei	Zhejiang Universuty
Liu, Zhitao	Zhejiang University
Su, Hongye	Zhejiang University
Keywords: Nonlinear observers and filter design, Energy systems, backstepping control of distributed parameter systems Abstract: The remaining capacity of a battery is a crucial indicator, which has significant impact on State of Charge (SoC) estimation and the safe operations of electric vehicles. In this paper, an electrochemical model considering the electrolyte dynamics is proposed to estimate the real capacity of a lithium-ion battery. The electrochemical model with electrolyte dynamics governed by several partial differential equations has the potential to accurately describe varieties of phenomenons inside the battery. Furthermore, a Pade’ one-order approximation is adopted to obtain the transfer function between the boundary lithium-ion concentration and input current, then a boundary state estimator is proposed to estimate the the boundary lithium- ion concentration. After that, the least square method is used to obtain the adaptive update law for maximum concentration estimation in anode. Finally, the correctness of the aforementioned estimation methods is verified through simulation.
Paper VI123-17.4
PDF · Video · Lyapunov-Based Observer Design for Steam Boilers
Hölzl, Stefan Lambert	Graz University of Technology
Seeber, Richard	Graz University of Technology
Tranninger, Markus	Graz University of Technology
Bauer, Robert	Kristl, Seibt & Co Ges.m.b.H
Horn, Martin	Graz University of Technology
Keywords: Nonlinear observers and filter design, Lyapunov methods, Application of nonlinear analysis and design Abstract: Steam boilers are widely used in industrial applications ranging from air conditioning to power plants. Advanced control schemes for such boilers require the knowledge of internal state variables, which are not always measurable. This paper proposes a new observer for steam boilers whose construction builds on a special state variable choice and a Lyapunov-based design of the observer gains. Tuning insight is gained from an oscillator-like structure of the (linearised) observer error dynamics. Comparisons to an extended Kalman filter in simulations and on experimental data from a small-scale automotive application demonstrate the performance of the proposed approach.
Paper VI123-17.5
PDF · Video · Reduced-Order Nonlinear Observer Design for Two-Time-Scale Systems
Duan, Zhaoyang	Texas A&M University
Kravaris, Costas	Texas A&M University
Keywords: Nonlinear observers and filter design, Model reduction, Observer design Abstract: A two-time-scale system involves both fast and slow dynamics. This paper studies the design of nonlinear observers for general nonlinear two-time-scale systems and presents a reduced-order observer design approach. The reduced-order observer is derived based on a lower-dimensional model to reconstruct the slow states, along with the algebraic slow-motion invariant manifold function to reconstruct the fast states. Through an error analysis, it is shown that even though the observer is designed based on the reduced model by neglecting the fast dynamics, it is capable of providing accurate estimation of the states of the original detailed system. It will render a vanishing estimation error, with exponential convergence rate governed by the subsystem of fast dynamics and the chosen observer design parameters. In the last part of the paper, the proposed reduced-order observer is designed for an anaerobic digestion process as an illustrative example to evaluate its performance and convergence properties.
Paper VI123-17.6
PDF · Video · Design of Reduced-Order Observers and Output Feedback Controllers for Sampled-Data Strict-Feedback Systems with Time-Varying Sampling Intervals
Katayama, Hitoshi	Shizuoka Univ
Keywords: Nonlinear observers and filter design, Networked systems, Output feedback control Abstract: We consider the design of reduced-order observers and output feedback stabilizing controllers for sampled-data strict-feedback systems with time-varying sampling intervals. We introduce a nominal sampling interval to construct the Euler model and we use it to design reduced-order observers, state feedback controllers, and observer-based output feedback controllers. Then we give the sufficient conditions that the designed observers and controllers achieve the desired control performance for the exact model of sampled-data systems. We also give numerical examples to illustrate the proposed design of reduced-order observers and controllers.
Paper VI123-17.7
PDF · Video · Immersion Based Observer for the Switched Reluctance Motor
De La Guerra, Alejandra	Metropolitan Autonomous University
Gutierrez-Giles, Alejandro	Cinvestav
Besancon, Gildas	Ense3, Grenoble INP
Keywords: Nonlinear observers and filter design, Observer design, Control of switched systems Abstract: This article presents a high-gain Kalman-like observer for the switched reluctance motor that can reconstruct the angular position and velocity from the measured variables, i. e., stator currents and voltages. This is possible after the results obtained from an observability analysis, which in turn permits the application of an immersion to transform the motor model into a suitable form for the observer implementation. Numerical simulations are incorporated to explain and validate the observer design. The procedure includes an active phase detection stage and a current-based speed controller that defines the commutation required for this kind of motors. The proposed observer is capable of reconstructing the mechanical variables (rotor position and speed) by employing only electrical ones (currents and voltages).
Paper VI123-17.8
PDF · Video · MHE Based State and Parameter Estimation for Systems Subjected to Non-Gaussian Disturbances
Varshney, Devyani	Indian Institute of Technology, Bombay
Patwardhan, Sachin C.	Indian Institute of Technology Bombay
Bhushan, Mani	Indian Institute of Technology Bombay
Biegler, Lorenz T.	Carnegie Mellon Univ
Keywords: Nonlinear observers and filter design, Parameter-varying systems Abstract: Moving horizon estimation (MHE) is a popular state estimation technique, particularly due to its similarity with model predictive control. The probabilistic formulation of the conventional MHE is developed under the simplifying assumption that state disturbances and measurement noise densities are Gaussian. However, many systems of interest are subjected to uncertainties that have non-Gaussian densities. In current work, we formally extend an existing probabilistic Bayesian formulation of MHE [Varshney et al., 2019] to simultaneous state and parameter estimation for systems subjected to non-Gaussian uncertainties in the state dynamics and measurement model. The efficacy of the proposed MHE has been demonstrated by conducting stochastic simulation studies on a system subjected to non-Gaussian densities. Analysis of simulation results reveals that the estimation performance of the proposed MHE formulation is superior to estimation performances of the conventional Bayesian estimators that can handle non-Gaussian densities and employ the random walk model for parameter variations.
Paper VI123-17.9
PDF · Video · Observers of the Vlasov-Poisson System
Cisse, Amadou	University of Lorraine, the Research Center for Automatic Contro
Boutayeb, Mohamed	Université De Lorraine
Keywords: Nonlinear observers and filter design, Stability of nonlinear systems, Linear parameter-varying systems Abstract: This work focuses on observer's for one-dimensional (1D) Vlasov-Poisson (VP) system. Thanks to the Discontinuous Galerkin method (DGM) to put the system into a suitable and explicit state space representation form. Then we construct a state observer of finite dimension that assures asymptotic convergence under weak conditions. Indeed, we introduce a useful Linear Parameter Varying System formulation to compute the observer gain matrix from a Linear Matrix Inequality. Moreover, since matrices obtained by the DGM are tridiagonal, we show that only a reduced order observer is necessary to estimate the whole state of the system. In the noise context, extension to H_infinity state estimation is also established.
Paper VI123-17.10
PDF · Video · Efficient Temperature Profile Estimation for Silicon Wafers Based on Subspace Observers
Tranninger, Markus	Graz University of Technology
Seeber, Richard	Graz University of Technology
Steinberger, Martin	Graz University of Technology
Horn, Martin	Graz University of Technology
Keywords: Nonlinear observers and filter design, Time-varying systems, Application of nonlinear analysis and design Abstract: This work proposes a computationally effcient observation algorithm for the surface temperature profile of heated silicon wafers. The observer exploits the fact that only a few modes of the original large-order model are unstable or slowly converging. In this case, it suffices to modify only these modes by the observer's output feedback gain. Compared to classical observation techniques, the proposed method allows to compute the feedback gain for a state space of lower dimension, which reduces computational complexity. A comparison of the approach with the extended Kalman-Bucy Filter using experimental data shows its appealing performance.
Paper VI123-17.11
PDF · Video · Leader-Tracking in a Shape-Preserving Formation with Bearing-Only Measurements
Yang, Ziwen	Shanghai Jiao Tong University
Zhu, Shanying	Shanghai Jiao Tong University
Chen, Cailian	Shanghai Jiao Tong University
Feng, Gang	City Univ. of Hong Kong
Keywords: Nonlinear observers and filter design, Time-varying systems, Tracking Abstract: This paper studies the problem of shape-preserving formation control for multi-agent systems where only bearing measurements are available. Most existing methods to solve the problems assume that accurate global or local position measurements of agents are available, or use estimators to get these information without analysis of estimators' effects on the closed loop system stability. In this work, we propose a framework integrating an estimator to get relative positions using bearing-only measurements and an estimator-based controller to achieve tracking a pair of leaders in a formation with a preserved shape. The estimator is designed by exploiting orthogonality to cope with the high non-linearity of bearing measurements, based on which the controller is designed with the estimated relative positions. With rigorous theoretical analysis of the closed-loop system, we characterize the leaders which can be tracked by followers in a shape-preserving formation using bearing-only measurements, and the asymptotic stability of the closed-loop system can be guaranteed. Simulations testify the effectiveness of the proposed framework.
Paper VI123-17.12
PDF · Video · Time-Energy Efficient Finite Time Attitude Tracking Control of Spacecraft Using Disturbance Observer
Amrr, Syed Muhammad	Indian Institute of Technology Delhi
Banerjee, Arunava	Indian Institute of Technology Delhi
Nabi, Mashuq-un	Indian Institute of Technology, New Delhi
Keywords: Robust control, Aerospace, Sliding mode control Abstract: In this paper, the attitude controller of spacecraft tracks the time-energy near-optimal angular velocity generated by the Legendre Pseudospectral method (LPSM). The near-optimal reference trajectory is obtained offline by applying the LPSM on the nominal spacecraft dynamics, which is without noises and disturbances. The proposed tracking control scheme works online, and along with the tracking of the near-optimal path, it also rejects the external disturbances and noises. The composite control law is developed by combining the sliding mode control (SMC) and the output of a finite-time disturbance observer. The SMC ensures the finite tie results whereas the disturbance observer helps in avoiding the chattering in control. The stability analysis of relative dynamics under the proposed scheme guarantees the convergence of sliding surface and relative states in finite-time. The simulation analysis further illustrates the effective performance of the proposed strategy.
Paper VI123-17.13
PDF · Video · Robust Sliding Window Observer-Based Controller Design for Lipschitz Discrete-Time Systems
Gasmi, Noussaiba	University of Lorraine
Boutayeb, M.	University of Lorraine
Thabet, Assem	Ecole Nationale Des Ingénieurs De Gabés
Aoun, Mohamed	Bordeaux 1
Bel Haj Frej, Ghazi	University of Bordeaux, FRANCE
Keywords: Robust control, Stability of nonlinear systems, Nonlinear observers and filter design Abstract: The aim of this paper is to develop a new observer-based stabilization strategy for a class of Lipschitz uncertain systems. This new strategy improves the performances of existing methods and ensures better convergence conditions. The observer and the controller are enriched with sliding windows of measurements and estimated states, respectively. This technique allows to increase the number of decision variables and thus get less restrictive and more general LMI conditions. The established sufficient stability conditions are in the form of Bilinear Matrix Inequality (BMI). The obtained constraint is transformed, through a useful approach, to a more suitable one easily tractable by standard software algorithms. Numerical example is given to illustrate the performances of the proposed approach.
Paper VI123-17.14
PDF · Video · Localization from Inertial Data and Sporadic Position Measurements
Sferlazza, Antonino	University of Palermo
Zaccarian, Luca	LAAS-CNRS and University of Trento
Garraffa, Giovanni	University of Palermo
D'Ippolito, Filippo	Universita' Di Palermo
Keywords: Stability of hybrid systems, Input-to-State Stability, Observer design Abstract: A novel estimation strategy for inertial navigation in indoor/outdoor environment is proposed with a specific attention to the sporadic nature of the non-periodic measurements. After introducing the inertial navigation model, we introduce an observer providing an asymptotic estimate of the plant state. We use a hybrid dynamical system representation for our results, in order to provide an effective, and elegant theoretical framework. The estimation error dynamics with the proposed observer shows a peculiar cascaded interconnection of three subsystems (allowing for intuitive gain tuning), with perturbations occurring either on the jump or on the flow dynamics (depending on the specific subsystem under consideration). For this structure, we show global exponential stability of the error dynamics. Experimental results carried out by means of a hardware-in-the-loop method confirm the effectiveness of the proposed solution.

VI123-18
Nonlinear Output Feedback	Regular Session
Chair: Röbenack, Klaus	TU Dresden
Co-Chair: Marconi, Lorenzo	Univ. Di Bologna
Paper VI123-18.1
PDF · Video · On Output-Based Accelerated Stabilization of a Chain of Integrators: Implicit Lyapunov-Krasovskii Functional Approach
Nekhoroshikh, Artem	ITMO University
Efimov, Denis	Inria
Polyakov, Andrey	INRIA Lille Nord-Europe
Perruquetti, Wilfrid	Ecole Centrale De Lille
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Fridman, Emilia	Tel-Aviv Univ
Keywords: Output feedback control, Delay systems, Lyapunov methods Abstract: The problem of output accelerated stabilization of a chain of integrators is considered. Proposed control law nonlinearly depends on the output and its delayed values, and it does not use an observer to estimate the unmeasured components of the state. It is proven that such a nonlinear delayed control law ensures practical output stabilization with rates of convergence faster than exponential. The effective way of computation of feedback gains is given. It is shown that closed-loop system stability does not depend on the value of artificial delay, but the maximum value of delay determines the width of stability zone. The efficiency of the proposed control is demonstrated in simulations.
Paper VI123-18.2
PDF · Video · A Computationally Efficient Approach for Robust Gain-Scheduled Output-Feedback LQR Design for Large-Scale Systems
Ilka, Adrian	Chalmers University of Technology
Murgovski, Nikolce	Chalmers University of Technology
Keywords: Output feedback control, Linear parameter-varying systems, Optimal control theory Abstract: This paper proposes a novel and simple control design procedure for sub-optimal robust gain-scheduled (GS) output-feedback linear quadratic regulator (LQR) design for large-scale uncertain linear parameter-varying (LPV) systems. First, we introduce a simple and practical technique to convexify the controller design problem in the scheduled parameters. Then, we propose an iterative Newton-based approach for gain-scheduled output-feedback LQR design with necessary and sufficient stability conditions. Next, we propose a simple modification to the proposed algorithm to design robust GS controllers. Finally, the proposed algorithm is applied for air management and fueling strategy of diesel engines, where the designed robust GS proportional-integral-derivative (PID) controller is validated on a benchmark model using real-world road profile data.
Paper VI123-18.3
PDF · Video · On a Generalized Flat Input Definition and Physical Realizability
Fritzsche, Klemens	TU Dresden
Röbenack, Klaus	TU Dresden
Keywords: Output feedback control, Tracking, Analytic design Abstract: We generalize the definition of flat inputs to implicit nonlinear differential equations of higher order. By allowing injections of input components and its time derivatives up to some finite order in both the dynamics and the output equations we show that physical realizability of generalized flat inputs can be achieved in cases that were shown to possess no physically realizable flat input. In addition, it can be shown that there always exists a physically realizable (generalized) flat input with an order less than the system order in the linear case.
Paper VI123-18.4
PDF · Video · Robust Regulator Design of General Linear Systems with Sampled Measurements
Wang, Lei	The University of Sydney
Marconi, Lorenzo	Univ. Di Bologna
Kellett, Christopher M.	The Australian National University
Keywords: Output regulation, Linear multivariable systems, Robustness analysis Abstract: This paper studies the robust output regulation problem of general linear continuous-time systems with periodically sampled measurements, consisting of both the regulation errors and the extra measurements. With some standard conditions, we propose a novel robust implementable regulator design paradigm, that is comprised of a generalized zero-order hold device, a discrete-time compensator, a discrete-time washout filter and a discrete-time stabilizer.
Paper VI123-18.5
PDF · Video · Hybrid Output Regulation of DC-DC Converter for Dynamic Wireless Charging System
Zhang, Mengting	Zhejiang University
Marconi, Lorenzo	Univ. Di Bologna
Liu, Zhitao	Zhejiang University
Su, Hongye	Zhejiang University
Keywords: Output regulation, Stability of hybrid systems Abstract: This paper illustrates a control strategy for voltage regulation problem of DC-DC converter in dynamic wireless charging applications. The control goal is to compensate for the disturbances on the input voltage of the DC-DC converter that changes periodically due to the motion of the electric vehicle assumed to have a constant speed. The paper aims at comparing two different control solutions based on continuous and hybrid internal model-based regulators. According to the relative distance of the transmitter coils the fluctuation of the input voltage is approximated as a continuous-time or a spline-based periodic signal and internal model- based solutions, which are continuous time or hybrid according to the fluctuation modelling, are proposed to compensate for such a disturbance. The control performance of the proposed control schemes are tested through simulation by showing how, as long as the relative distance between the coils increases, the more involved hybrid solutions improve the performances when compared with the more simple continuous-time ones.
Paper VI123-18.6
PDF · Video · Modified Backstepping Algorithm with Disturbances Compensation for Nonlinear MIMO Systems
Konovalov, Dmitry	ITMO University
Vrazhevsky, Sergey	ITMO University
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Kremlev, Artem	ITMO University
Keywords: Robust control, Output feedback control, Disturbance rejection Abstract: The paper deals with a novel modified backstepping algorithm to ensure the stability of the nonlinear multiple-input multiple-output plant under unknown bounded parametric uncertainties, Lipschitz nonlinear disturbances, and cross-couplings. The modification is based on the auxiliary loop method that permits to estimate undesired dynamics as disturbances and suppress them. High robustness of the closed-loop system without using high-gain components is achieved. The ractical contribution of the results is demonstrated using laboratory platform ''Twin Rotor MIMO System''.

VI123-19
Nonlinear Predictive Control	Regular Session
Chair: Lucia, Sergio	TU Berlin
Co-Chair: Limon, Daniel	Universidad De Sevilla
Paper VI123-19.1
PDF · Video · Fast Cooperative Distributed Model Predictive Control Based on Parametric Sensitivity
Yu, Tianyu	Zhejiang University
Xu, Zuhua	Zhejiang University
Zhao, Jun	Zhejiang University
Chen, Xi	Zhejiang University
Biegler, Lorenz T.	Carnegie Mellon Univ
Keywords: Distributed nonlinear control, Nonlinear predictive control, Nonlinear cooperative control Abstract: This paper deals with computational delay in distributed nonlinear model predictive control. A fast, cooperative distributed model predictive control algorithm is proposed based on parametric sensitivity. The implementation strategy is divided into two different stages. In the background stage, the future state is estimated one step forward with the current state and input. The local MPC controllers perform distributed optimization based on the predicted state and iterate to obtain the nominal optimal solutions. In the online stage, all the controllers correct their nominal optimal inputs through parametric sensitivity. Specifically, each controller formulates its local sensitivity equation based on the state estimation error. In order to solve these linear equations in a distributed way, Jacobi iterative method is applied. The overall algorithm can provide fast control action. A case study is provided to show the promising performance of the proposed method.
Paper VI123-19.2
PDF · Video · A Terminal State Contractive Nonlinear MPC with Output Zones and Input Targets
Sencio, Rafael	University of São Paulo
Souza, Guilherme Augusto Silva de	University of São Paulo
Santoro, Bruno	Universidade Federal De São Paulo
Odloak, Darci	University of São Paulo
Keywords: Nonlinear predictive control, Constrained control, Tracking Abstract: Terminal equality and inequality constraints along with terminal costs are known to be ingredients that grant stability in many Nonlinear Model Predictive Control (NMPC) approaches. Despite the availability of different methods for computing a suitable terminal set and cost, they usually rely on the linearization of the system and the design of terminal stabilizing control laws. Thus, approaches based on contracting constraints represent an alternative to circumvent the calculation of terminal sets and penalties. The present work proposes an NMPC based on a terminal state contracting constraint. This approach also avoids the need of large prediction horizon, helping to alleviate the computational burden usually associated with NMPC. Another contribution of this proposal is a formulation in terms of output zone control and input targets, designed for the common situation in the process industry where the number of degrees of freedom is not enough to independently track the setpoint of all controlled variables. A simulated case study is presented with the application of the proposed controller to the well-known quadruple-tank process.
Paper VI123-19.3
PDF · Video · Design and Simulation of a Machine-Learning and Model Predictive Control Approach to Autonomous Race Driving for the F1/10 Platform
Tatulea-Codrean, Alexandru	TU Dortmund University
Mariani, Tommaso	Technische Universität Dortmund
Engell, Sebastian	TU Dortmund
Keywords: Nonlinear predictive control, Data-based control Abstract: This paper addresses the challenges of developing an embedded non-linear model predictive control (NMPC) solution for the optimal driving of miniature scale autonomous vehicles (AVs). The NMPC approach lends itself perfectly to driving applications, provided that a system for localization and tracking of the vehicle is available. An important challenge in the implementation results from the need to accurately steer the vehicle at high speeds, which requires fast actuation. In this paper we present a solution to this problem, which employs an artificial neural network (ANN) controller trained with rigorous NMPC input-output data. We discuss the development process, from modelling until the realization of the ANN controller within the operating system of the AV. The procedure is demonstrated within the virtual environment of the popular F1/10 race car, an AV platform widely used in AI and autonomous driving challenges. The results contain both NMPC and ANN-based simulations for different race tracks and for different driving strategies. The main focus of this work lies in the formulation of the optimal driving control problem and the training method of the ANN. Our approach uses a standardization of the driving problem, which enables us to abstractize optimal driving and to simplify it for the learning process.We show how driving patterns can be learned accurately on a reduced set of training data and that they can subsequently be extended to new and more challenging driving situations.
Paper VI123-19.4
PDF · Video · Distributed Min-Max MPC for Dynamically Coupled Nonlinear Systems: A Self-Triggered Approach
Wei, Henglai	University of Victoria
Zhang, Kunwu	University of Victoria
Shi, Yang	University of Victoria
Keywords: Nonlinear predictive control, Distributed nonlinear control, Predictive control Abstract: This paper considers the formation stabilization problem of dynamically coupled nonlinear systems with parametric uncertainties and additive disturbances. We develop a distributed min-max model predictive control (MPC) framework, in which each subsystem adopts the local optimal control action by solving the constrained optimization problem. As a main contribution of this paper, a self-triggered strategy is presented within the proposed framework for resource-constrained coupled systems. By implementing the distributed self-triggered scheduler, the communication burden is significantly alleviated while ensuring comparable control performance. In addition, for each subsystem the latest information is transmitted to its neighbors asynchronously at the local triggering time instants. Moreover, the resulting distributed self-triggered min-max MPC framework ensures the constraints satisfaction and the closed-loop stability. Finally, the numerical experiments are performed to verify the theoretical results.
Paper VI123-19.5
PDF · Video · Optimal Energy Management for Hybrid Electric Aircraft
Doff-Sotta, Martin	University of Oxford
Cannon, Mark	University of Oxford
Bacic, Marko	Rolls Royce
Keywords: Nonlinear predictive control, Industrial applications of optimal control, Aerospace Abstract: A convex formulation is proposed for optimal energy management in aircraft with hybrid propulsion systems consisting of gas turbine and electric motor components. By combining a point-mass aircraft dynamical model with models of electrical and mechanical powertrain losses, the fuel consumed over a planned future flight path is minimised subject to constraints on the battery, electric motor and gas turbine. The resulting optimisation problem is used to define a predictive energy management control law that takes into account the variation in aircraft mass during flight. A simulation study based on a representative 100-seat aircraft with a prototype parallel hybrid electric propulsion system is used to investigate the properties of the controller. We show that an optimisation-based control strategy can provide significant fuel savings over heuristic energy management strategies in this context.
Paper VI123-19.6
PDF · Video · Quasi Time-Optimal Nonlinear Model Predictive Control with Soft Constraints
Ismail, Jawad	University of Kaiserslautern
Liu, Steven	University of Kaiserslautern
Keywords: Nonlinear predictive control, Industrial applications of optimal control, motion planning for distributed parameter systems Abstract: In many mechatronic applications, controller input costs are negligible and time optimality is of great importance. As a result, the obtained control input has mostly a bang-bang nature, which excite undesired mechanical vibrations, especially in systems with flexible structures. This paper tackles the time-optimal control problem and proposes a novel approach, which explicitly addresses the vibrational behavior in the context of the receding horizon technique. Such technique is a key feature, especially for systems with a time-varying vibrational behavior. In the context of model predictive control (MPC), vibrational behavior is predicted and coped in a soft-constrained formulation, which penalize any violation of undesired vibrations. This formulation enlarges the feasibility on a wide operating range in comparison with a hard-constrained formulation. The closed-loop performance of this approach is demonstrated on a numerical example of stacker crane with high degree of flexibility.
Paper VI123-19.7
PDF · Video · An Approach to State Signal Shaping by Limit Cycle Model Predictive Control
Cateriano Yáñez, Carlos	Fraunhofer Institute for Silicon Technology
Lichtenberg, Gerwald	Hamburg University of Applied Sciences
Pangalos, Georg	Fraunhofer Institute for Silicon Technology ISIT
Sanchis, Javier	Polytechnical Univ of Valencia
Keywords: Nonlinear predictive control, Optimal control theory, Power systems Abstract: A novel nonlinear model predictive control approach for state signal shaping is proposed. The control strategy introduces a residual shape cost kernel based on the dynamics of circular limit cycles from a supercritical Neimark-Sacker bifurcation normal form. This allows the controller to impose a fundamental harmonic state signal shape with a specific frequency and amplitude. An application example for harmonic compensation in distribution grids integrated with renewable energies is presented. The controller is tasked with the calculation of the reference current for an active power filter used for load compensation. The results achieved are successful, reducing the harmonic distortion to satisfactory levels while ensuring the correct frequency and amplitude.
Paper VI123-19.8
PDF · Video · Data-Driven Quasi-LPV Model Predictive Control Using Koopman Operator Techniques
Gonzalez, Pablo	Hamburg University of Technology
Datar, Adwait	Institute of Control Systems, Hamburg University of Technology
Göttsch, Patrick	Hamburg University of Technology
Werner, Herbert	Hamburg Univ of Technology
Keywords: Nonlinear predictive control, Parameter-varying systems, Data-based control Abstract: A fast data-driven extension of the velocity-based quasi-linear parameter-varying model predictive control (qLMPC) approach is proposed for scenarios where first principles models are not available or are computationally too expensive. We use tools from the recently proposed Koopman operator framework to identify a quasi-linear parameter-varying model (in input/output and state-space form) by choosing the observables from physical insight. An online update strategy to adapt to changes in the plant dynamics is also proposed. The approach is validated experimentally on a strongly nonlinear 3-degree-of-freedom Control Moment Gyroscope, showing remarkable tracking performance.
Paper VI123-19.9
PDF · Video · A Multi-Stage Economic NMPC for the Tennessee Eastman Challenge Process
Tatulea-Codrean, Alexandru	TU Dortmund University
Fischer, Jonas	Technische Universität Dortmund
Engell, Sebastian	TU Dortmund
Keywords: Nonlinear predictive control, Predictive control, Chemical engineering Abstract: This paper addresses the design and implementation of a robust nonlinear model predictive control (NMPC) scheme for a benchmark plant-wide control problem. The focus of our research is on the performance of direct optimizing control for a complex large-scale process which is subject to plant-model mismatch and external disturbances. As a benchmark case for control and monitoring applications, the Tennessee Eastman Challenge (TEC) process has been widely employed in many publications. We present a first NMPC implementation for this where only economics criteria are used for the control of the process. The results obtained demonstrate the viability of plant-wide economics optimizing NMPC. We also address the issue of robustness against model uncertainties and employ multi-stage NMPC to tackle these. Different possible multi-stage NMPC implementations are discussed and the trade-offs between economic performance and robustness are highlighted.
Paper VI123-19.10
PDF · Video · Nonlinear Model Predictive Control Based on Existing Mechanistic Models of Polymerisation Reactors
Pfeiffer, Bernd-Markus	Siemens AG
Oppelt, Mathias	Siemens AG
Leingang, Chris	Siemens AG
Pantelides, Costas	Imperial College London
Pereira, Frances	Process Systems Enterprise
Keywords: Nonlinear predictive control, Process control, Industrial applications of optimal control Abstract: Model Predictive Control (MPC) is established as the most powerful and most successful method for multivariable control in the process industries. Most industrial applications of MPC rely on linear dynamic process models that are identified from active experiments on the plant. If a rigorous mechanistic model of the respective process unit already exists, it would be attractive to use this model directly inside an MPC algorithm. The PSE software "gPROMS Nonlinear Model Predictive Controller" (gNLMPC) provides precisely this functionality, and this paper describes its application to a polymerization reactor. Properties, features and advantages of linear and nonlinear MPC are compared systematically.
Paper VI123-19.11
PDF · Video · A Model-Based Online Reference Prediction Strategy for Model Predictive Motion Cueing Algorithms
Biemelt, Patrick	University of Paderborn
Link, Christopher	University of Paderborn
Gausemeier, Sandra	Heinz Nixdorf Institute, University of Paderborn
Traechtler, Ansgar	University of Paderborn
Keywords: Nonlinear predictive control, Real-time optimal control, Control of constrained systems Abstract: Interactive driving simulation has become a key technology to support the development and optimization process of modern vehicle components and driver assistance systems both in academic research and in the automotive industry. However, the validity of the results obtained within the virtual environment depends essentially on the adequate reproduction of the simulated vehicle movements and the corresponding immersion of the driver. For that reason, specific motion platform control strategies, so-called Motion Cueing Algorithms (MCA), are used to replicate the simulated accelerations and angular velocities within the physical limitations of the driving simulator best possible. In this paper, we present a novel model-based approach to predict oncoming vehicle motion at runtime. For that purpose, a virtual driver model as well as a simplified vehicle dynamics model are introduced to estimate the future driver inputs and the resulting vehicle trajectories according to the current driving situation. This additional system knowledge enables control algorithms designed on the idea of Model Predictive Control (MPC) to exploit their potential more efficiently. The performance of the proposed prediction strategy is evaluated on the basis of measurement data from a real test run in comparison to an ideal prediction and a constant reference, using a hybrid kinematics motion system as an application example.
Paper VI123-19.12
PDF · Video · Complexity Minimisation of Suboptimal MPC without Terminal Constraints
Pavlov, Andrei	The University of Melbourne
Muller, Matthias A.	Leibniz University Hannover
Manzie, Chris	The University of Melbourne
Shames, Iman	University of Melbourne
Keywords: Nonlinear predictive control, Real-time optimal control, Predictive control Abstract: This paper generalises stability analysis of Nonlinear Model Predictive Control without terminal constraints to incorporate possible suboptimality of MPC solutions and develops a framework for minimisation of computational efforts associated with obtaining such a solution. The framework is applied to primal-dual interior-point solvers by choosing the length of the prediction horizon together with a degree of suboptimality of the solution in a way that reduces algorithmic complexity while satisfying certain stability and performance guarantees. The framework ensures an optimal choice for the prediction horizon in order to minimise computational complexity if applied to linear or convex quadratic MPC problems, and acts as a good indicator to this end in the more general case of nonlinear systems. This is illustrated in a numerical case study, where we apply the proposed framework to a nonholonomic robot.
Paper VI123-19.13
PDF · Video · A Robust Method for Dual Faceted Linearization
Igarashi, Yusuke	Tokyo Institute of Technology
Yamakita, Masaki	Tokyo Inst. of Tech
Ng, Jerry	Massachusetts Institute of Technology
Asada, H. Harry	Massachusetts Inst. of Tech
Keywords: Nonlinear predictive control, Robust control applications, Numerical methods for optimal control Abstract: The dynamics of nonlinear systems become linear systems when lifted to higher or infinite dimensional spaces. We call such linear system representations and approximations, 'lifting linear' representations. The lifting linear representations are linear system representations that are closer to the original systems than Taylor series approximations. Once we have such a linear system representation, we can apply linear control theory to the nonlinear systems. In Model Predictive Control (MPC), the computation time is reduced because the nonlinear optimization problem becomes a convex quadratic optimization problem. In this paper, we propose a method to make Dual Faceted Linearization (DFL) robust for uncertainties of the plants. It will be shown that the proposed method can yield a lifting linearization leading to better control results for MPC by numerical examples.
Paper VI123-19.14
PDF · Video · Multicopter Attitude Control through NMPC Design with Guaranteed Stability
Nguyen, Ngoc Thinh	University of Luebeck
Prodan, Ionela	INP Grenoble
Lefevre, Laurent	Univ. Grenoble Alpes
Keywords: Nonlinear predictive control, Stability of nonlinear systems, UAVs Abstract: This paper presents an original NMPC (Nonlinear Model Predictive Control) design with guaranteed stability for the attitude set-point angle tracking of multicopters. The design is an extension of our previous work on stabilizing the NMPC scheme for ``computed-torque like'' systems by using terminal invariant set constructed under the CTC (Computed-Torque Control) controller. The novelty resides in the complexity reduction for the design process which is done by reducing the dependence of the required elements (e.g., the terminal region's radius, the Lipschitz constant) on the desired angle set-points which change fast and are not known in advance. The contributions are validated in simulation over a quadcopter model.
Paper VI123-19.15
PDF · Video · Model Predictive Coverage Control
Carron, Andrea	ETH Zurich
Zeilinger, Melanie N.	ETH Zurich
Keywords: Nonlinear predictive control, Tracking, Constrained control Abstract: Cooperative robotic problems often require coordination in space in order to complete a given task, important examples include search and rescue, operations in hazardous environments, and autonomous taxi deployment. Events can be quickly detected by partitioning the working environment and assigning one robot to each partition. However, a crucial factor that limits the effectiveness and usage of coverage algorithms is related to the ability of taking decisions in the presence of constraints. In this paper, we propose a coverage control algorithm that is capable of handling nonlinear dynamics, and state and input constraints. The proposed algorithm is based on a nonlinear tracking model predictive controller and is proven to converge to a centroidal Voronoi configuration. We also introduce a procedure to design the terminal ingredients of the model predictive controller. The effectiveness of the algorithm is then highlighted with a numerical simulation.
Paper VI123-19.16
PDF · Video · Hierarchical Attack Identification for Distributed Robust Nonlinear Control
Braun, Sarah	Siemens AG
Albrecht, Sebastian	Siemens AG
Lucia, Sergio	TU Berlin
Keywords: Control problems under conflict and/or uncertainties, Nonlinear predictive control, Distributed nonlinear control Abstract: Developing tools for attack identification in large-scale networked control systems is a research area of increasing significance for the secure and reliable operation of autonomous control systems. Due to scalability limits and privacy issues of individual subsystems, attack identification methods should not rely on global model knowledge. We address systems of interconnected nonlinear subsystems with coupled dynamics or constraints in a distributed control setup. The local controllers share information about the coupling variables of the subsystems and are designed to be robust towards attacks and uncertain influences through neighboring subsystems. We present a scalable hierarchical attack identification method which monitors the evolution of the coupling variables after an attack occurred in some unknown subsystem. Based on the mutual exchange of local sensitivity information among the subsystems, the propagation of the attack through the network is approximated. The propagation equations are used to formulate a quadratic program whose solution determines the attack signal that explains the observed network evolution best. The developed approach is applied to the IEEE 30 bus system to illustrate attack identification in power systems with faulty buses.

VI123-20
Nonlinear Switched Systems	Regular Session
Chair: Tochilin, Pavel	Moscow State (Lomonosov) University
Co-Chair: Lacerda, Márcio J.	Federal University of São João Del-Rei
Paper VI123-20.1
PDF · Video · Limit Cycle Global Asymptotic Stability of Continuous-Time Switched Affine Systems
Egidio, Lucas	School of Mechanical Engineering, UNICAMP
Deaecto, Grace S.	FEM/UNICAMP
Geromel, Jose C.	UNICAMP
Keywords: Asymptotic stabilization, Control of switched systems, Convex optimization Abstract: This paper treats global asymptotic stability of a limit cycle, determined by the designer, for continuous-time switched affine systems, taking into account sampled and non-sampled switching rules. More specifically, our goal is to design a state-dependent switching function assuring global asymptotic stability of a limit cycle, which is determined from criteria of interest related to the system steady-state response. The conditions, expressed in terms of differential linear matrix inequalities, are based on a time-varying quadratic Lyapunov function and take into account a guaranteed cost, which assures a suitable performance level for the system transient response. These conditions can be converted into two linear matrix inequalities, making the problem simple-to-solve. An academic example is used for validation and comparison.
Paper VI123-20.2
PDF · Video · Piecewise Affine Feedback Control for Approximate Solution of the Target Control Problem
Tochilin, Pavel	Moscow State (Lomonosov) University
Keywords: Control of switched systems, Discontinuous control Abstract: This paper presents an approach for approximate solution of the target control problem for a class of nonlinear systems on a finite time interval. The main idea is to use a comparison principle from dynamic programming theory together with a special class of piecewise affine value functions for the piecewise linearized form of the original system of ODEs. Two cases are considered: with continuous value function and with discontinuous one. The resulting feedback control functions are also piecewise affine, continuous or discontinuous respectively. For both cases the theorems on sufficient conditions for solving the feedback control problem are formulated and proved. The appropriate computational procedures complement theoretical results.
Paper VI123-20.3
PDF · Video · Stabilization of Switched Affine Systems Via Multiple Shifted Lyapunov Functions
Serieye, Mathias	LAAS-CNRS
Albea-Sanchez, Carolina	LAAS-CNRS, University of Toulouse, UPS
Seuret, Alexandre	Cnrs / Laas
Jungers, Marc	CNRS - Université De Lorraine
Keywords: Control of switched systems, Lyapunov methods, Stability of nonlinear systems Abstract: This paper deals with the stabilization of switched affine systems. The particularities of this class of nonlinear systems are first related to the fact that the control action is performed through the selection of the switching mode to be activated and, second, to the problem of providing an accurate characterization of the set where the solutions to the system converge to. In this paper, we propose a new method based on a control Lyapunov function, that provides a more accurate invariant set for the closed-loop systems, which is composed by the union of potentially several disjoint subsets. The main contribution is presented as a non convex optimization problem, which refers to a Lyapunov-Metzler condition. Nevertheless a gridding technique applied on some parameters allows obtaining a reasonable solution through an LMI optimization. The method is then illustrated on two numerical examples that demonstrate the potential of the method.
Paper VI123-20.4
PDF · Video · Sampled-Data Set Stabilization of Switched Boolean Control Networks
Yerudkar, Amol	University of Sannio, Italy
Del Vecchio, Carmen	Università Del Sannio
Glielmo, Luigi	University of Sannio
Keywords: Control of switched systems, Networked systems, Systems biology Abstract: In this paper, the set stabilization of switched Boolean control networks (SBCNs) under sampled-data feedback control is addressed. Here, the control input is switching signal-dependent, and SBCNs can switch only at the sampling instants. First, the sampled point control invariant subset (SPCIS) of SBCNs is defined, and an algorithm is provided to obtain the largest SPCIS under arbitrary switching signal. Based on the largest SPCIS, some necessary and sufficient conditions are presented for the set stabilization of SBCNs by switching signal-dependent sampled-data (SSDSD) state feedback control. Furthermore, a constructive procedure is given to design all possible SSDSD state feedback controllers. Finally, some examples are presented to illustrate the effectiveness of the obtained results.
Paper VI123-20.5
PDF · Video · Stability Analysis of Discrete-Time LPV Switched Systems
Lacerda, Márcio J.	Federal University of São João Del-Rei
Agulhari, Cristiano M.	Federal University of Technology - Paraná
Keywords: Stability of hybrid systems, Parameter-varying systems, Lyapunov methods Abstract: This paper addresses the stability problem for discrete-time switched systems under autonomous switching. Each mode of the switched system is modeled as a Linear Parameter Varying (LPV) system, the time-varying parameters can vary arbitrarily fast and are represented in a polytopic form. The Lyapunov theory is employed to get new conditions in the form of parameter-dependent LMIs. The constructed Lyapunov function takes advantage of using an augmented state vector with shifted states in its construction. In this sense, the Lyapunov function employed in this paper can be viewed as a discrete-time LPV switched Lyapunov function. Numerical experiments illustrate the efficacy of the technique in providing stability certificates.

VI123-21
Nonlinear Tracking	Regular Session
Chair: Invernizzi, Davide	Politecnico Di Milano
Co-Chair: Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Paper VI123-21.1
PDF · Video · Application of a Nonovershooting Tracking Control Method for the Double Buck Converter
Schmid, Robert	The University of Melbourne
Srour, Tony	University of Melbourne
Reger, Johann	TU Ilmenau
Keywords: Output regulation, Tracking, Application of nonlinear analysis and design Abstract: The problem of avoiding overshoot in tracking control problems has an extensive history, but only a few works have offered methods that are applicable to a nonlinear plant. The recent paper (Schmid, 2019) adapted some methods from the linear control systems literature to offer state feedback laws to deliver a nonovershooting response in all outputs of a multi-input multi-output feedback linearisable plant. A double-buck converter consists of cascaded buck converters connected to a single voltage supply. Taking the system outputs as the voltages across the two load resistors, we use dynamic averaging to obtain a nonlinear state model for the converter. We introduce suitable coordinates to show it has a well-defined vector relative degree and show the system is feedback linearisable. The methods of (Schmid, 2019) are then employed to obtain a state feedback law that ensures both outputs track arbitrary time-varying reference trajectories without overshoot.
Paper VI123-21.2
PDF · Video · Integral Control of Stable Nonlinear Systems Based on Singular Perturbations
Lorenzetti, Pietro	Tel Aviv University
Weiss, George	Tel Aviv University
Natarajan, Vivek	Indian Institute of Technology Bombay
Keywords: Tracking, Anti-windup, Lyapunov methods Abstract: One of the main issues related to integral control is windup, which occurs when, possibly due to a fault, the input signal u of the plant reaches a value outside the allowed input range U. This paper presents an integral controller with anti-windup, called saturating integrator, for a single-input single-output nonlinear plant having a curve of locally exponentially stable equilibrium points that correspond to constant inputs in U. A closed-loop system is formed by connecting the saturating integrator in feedback with the plant. The control objective is to make the output signal y of the plant track a constant reference r, while not allowing its input signal u to leave U. Using singular perturbation methods, we prove that, under reasonable assumptions, the equilibrium point of the closed-loop system is exponentially stable, with a "large" region of attraction. Moreover, when the state of the closed-loop system converges to this equilibrium point, then the tracking error tends to zero. A step-by-step procedure is presented to perform the closed-loop stability analysis, by finding separately a Lyapunov function for the reduced (slow) model and a Lyapunov function for the boundary-layer (fast) system. Afterwards, a Lyapunov function for the closed-loop system is built as a convex combination of the two previous ones, and an upper bound on the controller gain is found such that closed-loop stability is guaranteed. Finally, we show that if certain stronger conditions hold, then the domain of attraction of the stable equilibrium point of the closed-loop system can be made large by choosing a small controller gain.
Paper VI123-21.3
PDF · Video · Command-Filtering-Based Adaptive Finite-Time Tracking Control for Ball and Plate System
Wang, Aoxiang	University of Science and Technology Liaoning
Li, Xiaohua	University of Science and Technology Liaoning
He, Shuai	University of Science and Technology Liaoning
Cao, Xiaojie	University of Science and Technology Liaoning
Jing, Yuanwei	Northeastern University
Chen, Ming	University of Science and Technology Liaoning
Keywords: Tracking, Constrained control, Lyapunov methods Abstract: The finite-time tracking control problem is studied for non-strict feedback ball and plate systems considered friction, coupling term and external disturbance comprehensively. An adaptive finite-time tracking control strategy based on command filtering is proposed, and the adaptive neural finite-time tracking controller is given for the ball and plate system with unknown input saturation. The designed controller can guarantee that the tracking error of the system can converge to a small neighborhood of the origin within finite time, and all signals in the closed loop system are bounded in the finite time. Finally, a simulation for the designed controller is given, and the simulation results verify the effectiveness and superiority of the proposed control scheme.
Paper VI123-21.4
PDF · Video · Hierarchical Dynamic Control for Robust Attitude Tracking
Invernizzi, Davide	Politecnico Di Milano
Lovera, Marco	Politecnico Di Milano
Zaccarian, Luca	LAAS-CNRS and University of Trento
Keywords: Tracking, Disturbance rejection, Robust control Abstract: In this paper robust attitude tracking for fully actuated rigid bodies is addressed. By exploiting the cascade structure of the underlying mathematical model, a hierarchical framework including a large number of dynamic feedback controllers is proposed. The closed loop results in error dynamics comprising an inner loop associated with the angular velocity error, and an outer loop associated with the attitude error. We then establish sufficient conditions for solving the attitude tracking problem from an (almost) global perspective by leveraging recent results on stabilization of nonlinear cascades and invariance principles for differential inclusions. The modular nature of the proposed approach allows one to conclude stronger stability properties than those available for existing dynamic control laws, such as PID loops, often employed in applications.
Paper VI123-21.5
PDF · Video · Control Lyapunov Function Design for Trajectory Tracking Problems of Wheeled Mobile Robot
Kubo, Ryoya	Tokyo University of Science
Fujii, Yasuhiro	Tokyo University of Science
Nakamura, Hisakazu	Tokyo University of Science
Keywords: Tracking, Lyapunov methods, Asymptotic stabilization Abstract: Trajectory tracking is an important control problem that has been studied by many researchers. However, no studies have discussed the trajectory tracking problem for a wheeled mobile robot via the minimum projection method. This paper proposes a Tracking Control Lyapunov Function (TCLF) design that uses dynamic extension and the minimum projection method. The proposed method converges the two-wheeled mobile robot to a time-varying target state. Moreover, the effectiveness of the proposed method is validated through a computer simulation.
Paper VI123-21.6
PDF · Video · Simple Control Scheme for Robust Tracking and Model Following of Uncertain Systems with Unknown Dead-Zone Inputs and Nonlinear Perturbations
Wu, Hansheng	Prefectural University of Hiroshima
Ge, Rongxiang	Prefectural University of Hiroshima
Keywords: Tracking, Model following control, Constrained control Abstract: The robust tracking and model following problem is investigated for a class of uncertain systems with completely unknown dead-zone inputs and any nonlinear perturbations. It is supposed that the uncertain nonlinearities are any continuous and bounded nonlinear functions which are unknown. Based on Wu inequality, a new design method is developed so that (i) the resulting robust tracking control schemes are direct, instead of the complicated ones consisting of two parts, to overcome the constraint of control input; (ii) it is unnecessary to understand any information on the nonlinear upper bound functions of uncertain nonlinearities, which results in the structural simplicity of robust tracking control schemes. In addition, it is also proved that the tracking error between the output of an actual nonlinear system with input constraints and the dynamical signals of the given reference model is uniformly exponentially bounded.
Paper VI123-21.7
PDF · Video · Multidimensional Path Tracking with Global Least Squares Solution
Handler, Johannes	Montanuniversität Leoben
Harker, Matthew	University of Leoben
Rath, Gerhard	University of Leoben
Keywords: Tracking, Numerical methods for optimal control, Optimal control theory Abstract: In this paper, a new method for model based optimal tracking control is presented. The special composition of the cost functional leads to design parameters for constraining the solution so as to ensure that machine limitations are not violated. By minimizing the cost functional with the calculus of variations, or more precisely the Euler-Lagrange equations, the state space representation of the system dynamics is transformed into an augmented state space representation describing the optimal tracking dynamics. The optimal control input is numerically calculated by solving the set of differential equations, given by the augmented state space system, globally with a specialized least-squares solver. The general control approach is demonstrated on an underactuated crane-like system with fixed load hoisting length operating in the horizontal plane. In this case the introduced design parameters determine the trade-off between the cost of tracking accuracy and the cost of using large values of crane speed and acceleration. The potential of the proposed control scheme is proven by both simulation and experimental tests. The multibody simulation is carried out with the software Simscape Multibody. For the experimental verification an industrial robot is used whose end effector only moves in a horizontal plane to imitate the trolley of an overhead crane.
Paper VI123-21.8
PDF · Video · Trajectory Tracking in Rectangular Billiards by Unfolding the Billiard Table
Menini, Laura	University of Rome Tor Vergata
Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Tornambe, Antonio	Univ. Di Roma Tor Vergata
Keywords: Tracking, Output feedback control, Control of constrained systems Abstract: In this paper, a position feedback controller is proposed to solve the tracking problem in rectangular billiards. Such a controller is obtained by transforming the billiard table into a surface on which the ball moves without experiencing any impact, i.e., by reflecting the billiard table rather than the ball trajectory, and designing a position feedback controller based on such an unfolded billiard table. Furthermore, it is shown how such an infinite billiard table can be mapped to the surface of a torus, thus leading to bounded trajectories of the ball.

VI123-22
Sliding Mode Control	Regular Session
Chair: Bandyopadhyay, Bijnan	IIT Bombay
Co-Chair: Koch, Charles Robert	University of Alberta
Paper VI123-22.1
PDF · Video · Output Constrained Sliding Mode Control: A Variable Gain Approach
Spiller, Mark	University of Duisburg-Essen
Söffker, Dirk	Univ of Duisburg-Essen
Keywords: Constrained control, Sliding mode control Abstract: In this paper output constrained sliding mode control of nonlinear relative degree two systems is considered. The constraints are formulated with respect to the first derivative of the control variable. The system may be effected by matched disturbances. Only the uncertainty bounds are required to be known. A multi-controller approach with variable gains is proposed. The controller guarantees that the constraints can at most be violated for a finite-time, which can be shortened by tuning the controller parameters. Despite the action of the multiple controllers the tracking error of the approach is guaranteed to be bounded.
Paper VI123-22.2
PDF · Video · Event-Triggered Discrete-Time Sliding Mode Control for High-Order Systems Via Reduced-Order Model Approach
Kumari, Kiran	Indian Institute of Technology Bombay
Bandyopadhyay, Bijnan	IIT Bombay
Reger, Johann	TU Ilmenau
Behera, Abhisek K.	Technion - Israel Institute of Technology
Keywords: Model reduction, Sliding mode control, Networked systems Abstract: We propose the design of event-triggered (ET) discrete-time sliding mode (DTSM) control for a high-order discrete-time system via a reduced-order model-based approach. This design includes a triggering mechanism using a reduced-order state vector and a controller based on the modified Bartoszewicz' reaching law for a reduced-order model of the system, to stabilize the uncertain high-order system. The main advantages of using a reduced-order vector in the event condition are the low-order synthesis of the controller and the sampling pattern, which may be sparser than the full vector-based design. This motivation arises from the fact that relaxing a few components of the state vector in the triggering mechanism may decrease its rate of violation. An added advantage of the proposal is that the transmission of the reduced-order vector, particularly in a network-based implementation, can outperform the full-order based design due to the severe challenges that exist in the data network. The robust performance for the closed-loop system is achieved using the DTSM control. We show that our proposal guarantees the stability of the full-order plant with the reduced-order triggering mechanism. The control execution is Zeno-free because of the inherent discrete nature of the control. The efficiency of the proposed method is shown using the simulation results of a numerical example.
Paper VI123-22.3
PDF · Video · Integration of PD-Type Iterative Learning Control with Adaptive Sliding Mode Control
Norouzi Yengeje, Armin	University of Alberta
Koch, Charles Robert	University of Alberta
Keywords: Sliding mode control, Adaptive control, Tracking Abstract: Proportional-Derivative type Iterative Learning Controller (PD-ILC) is combined with an Adaptive Sliding Mode Controller (ASMC) using a plug-in structure to a rotary pendulum. The ASMC adaptation law is used to update a switching gain of sliding surface in Sliding Mode Control (SMC) controller. The proposed hybrid controller stability and convergence are mathematically shown and then experimentally demonstrated using two-degree-of-freedom (2-DOF) Quanser QUBE Servo 2 Rotary Pendulum. Results illustrate that adaptation law helps the controllers to achieve higher accuracy tracking performance compared to the classic SMC controller. Based on the experimental results, the hybrid control of PD-ILC and ASMC has faster and more accurate tracking results than ILC controller indicating the combined controller has better performance than the individual controllers.
Paper VI123-22.4
PDF · Video · Multivariable Adaptive Dual Layer Super-Twisting Algorithm
Azevedo Filho, Jair Luiz	Federal University of Rio De Janeiro
Nunes, Eduardo Vieira Leao	COPPE - Federal Univ. of Rio De Janeiro
Keywords: Sliding mode control, Disturbance rejection, Lyapunov methods Abstract: In this paper, a novel Multivariable Adaptive Super-Twisting Algorithm is proposed. The adaptation scheme is based on a dual-layer structure and does not require the knowledge of upper bounds for the matched disturbances. By exploiting information extracted from the equivalent control, it is possible to adapt both gains to enforce a second-order sliding mode while avoiding a conservative overestimation of the disturbance, which is important to mitigate the undesirable effects of chattering.
Paper VI123-22.5
PDF · Video · Second-Order SMC with Disturbance Compensation for Robust Tracking Control in PMSM Applications
Aschemann, Harald	University of Rostock
Haus, Benedikt	Leuphana University of Lüneburg
Mercorelli, Paolo	Leuphana University of Lueneburg
Keywords: Sliding mode control, Disturbance rejection, Power systems Abstract: In this contribution, a cascaded control strategy is presented for a permanent magnet synchronous motor (PMSM) that compensates for model nonlinearities and enables an accurate as well as robust trajectory tracking. The proposed strategy comprises the combination of an inversion-based current control, one of two alternative second-order sliding mode control approaches (SMC) and an extended Kalman filter (EKF). The reference values for the inversion-based current controllers are calculated by a Maximum Torque Per Ampere (MTPA) strategy in an outer control loop. As second-order SMC approaches are investigated: one design based on an integrator extension of the control input, whereas the other is given by a hybrid twisting control. Both alternatives mitigate undesired chattering while the EKF yields smooth estimates for both the state variables and a lumped disturbance torque from noisy measurements. Moreover, the robustness of the overall control structure is increased, chattering effects are reduced and unknown disturbances as well as parameter uncertainty are addressed by combining second-order sliding mode control with estimator-based disturbance compensation. The potential of the proposed nonlinear control strategy is pointed out by successful simulation studies.
Paper VI123-22.6
PDF · Video · Double-Hidden-Layer Recurrent Neural Network Fractional-Order Sliding Mode Control for Shunt Active Power Filter
Fei, Juntao	Hohai University
Wang, Huan	Hohai University
Hua, Mingang	Hohai University
Keywords: Sliding mode control, Fractional systems, Adaptive control Abstract: In this paper, a fractional-order sliding mode control scheme based on a double-hidden-layer recurrent neural network is proposed for a single-phase shunt active power filter. Considering the shortcomings of traditional neural networks that the approximation accuracy is not high and weight and center vector of neural networks are unchangeable, a new double-hidden-layer recurrent neural network structure which contains two hidden layers to make the network have more powerful fitting ability, is designed to approximate the unknown nonlinearities. An original output feedback neural network with two hidden layers is designed to estimate the uncertainties regardless of unknown system characteristics and external disturbances. A fractional-order term is added to the sliding mode controller to have more adjustable space and better optimization space. Experimental results verified the validity of the designed controller and proved that it can complete the current compensation well with acceptable current tracking error, demonstrating the outstanding compensation performance and strong robustness
Paper VI123-22.7
PDF · Video · Model Following Quasi-Sliding Mode Control Strategy
Adamiak, Katarzyna Karolina	Lodz University of Technology
Bartoszewicz, Andrzej	Technical Univ. of Lodz
Keywords: Sliding mode control, Model following control, Robust control Abstract: Our study introduces a new model reference based approach to the design of sliding mode controller for discrete-time dynamical systems subject to external disturbances. We propose to begin the control design with generation of the reference trajectory for the system using its mathematical model and a hyperbolic tangent based sliding mode reaching law. Next, for the real disturbed plant, we propose a reaching function, which follows the reference trajectory in each step. Further, we prove that this approach ensures existence of quasi-sliding motion according to the definition of Gao et al. Moreover, the proposed controller offers a significant reduction of the width of the achieved quasi-sliding mode band in comparison to other sliding mode methodologies, which results in an improvement of the system’s robustness. The properties of our control scheme are finally illustrated with a simulation example.
Paper VI123-22.8
PDF · Video · Chattering Mitigated Sliding Mode Control of Uncertain Nonlinear Systems
Spiller, Mark	University of Duisburg-Essen
Söffker, Dirk	Univ of Duisburg-Essen
Keywords: Sliding mode control, Predictive control, Data-based control Abstract: In this paper chattering mitigated sliding mode control of uncertain nonlinear systems is considered. Concrete knowledge about the system parameters or uncertainty bounds is assumed to be unavailable. A combined sliding mode and data-driven model-free predictive control strategy is proposed. Calculation of the predictive control input is based on a linearized system description. The parameters of the linearized model are estimated online using a Kalman filter and input-output data. The sliding mode controller guarantees boundedness of the tracking error. The switching gain adapts online which avoids the uncertainty bounds of the system to be known. Overestimation of the bounds is avoided by the use of the predictive controller, leading to mitigation of the chattering effect. The effectiveness of the proposed strategy is confirmed by a simulation example.
Paper VI123-22.9
PDF · Video · A Modified SDRE-Based Sub-Optimal Hypersurface Design in SMC
özcan, Sinan	Turkish Aerospace
Çopur, Engin Hasan	Necmettin Erbakan University
Arıcan, Ahmet Çağrı	Gazi University
Salamci, Metin U.	Gazi Univ
Keywords: Sliding mode control, Robust control, Robust control applications Abstract: Sliding Mode Control (SMC) plays a prominent role in dealing with matched uncertainties. In classical SMC design, the sliding surface (SS) is crucial to the guarantee for the stability and desired performance, especially if the system is nonlinear. A possible way to fulfill these desired performances for nonlinear systems is to use State Dependent Riccati Equation (SDRE) method, enabling SS to be designed even optimally. However, SDRE may suffer an inherent stability problem as well as a computational burden. To overcome these issues, in a recent study, a new SDRE method has been proposed. Therefore, this study takes advantages of the advanced SDRE method in designing a sub-optimal SS and also provides some comparative results with the conventional one to establish the feasibility of the proposed SDRE-based SMC control architecture experimentally. Experiments are conducted by using a 3-DOF helicopter platform and the results reveal that the proposed SDRE-based SMC is able to produce smoother SS than the conventional counterpart.
Paper VI123-22.10
PDF · Video · Model-Free Sliding-Mode Controller for Soft Landing of Reluctance Actuators
Moya-Lasheras, Eduardo	Universidad De Zaragoza
Ramirez-Laboreo, Edgar	Universidad De Zaragoza
Sagues, Carlos	Universidad De Zaragoza
Keywords: Sliding mode control, Tracking, Stability of hybrid systems Abstract: Some electromagnetic actuators suffer from high velocity impacts during non-controlled switching operations, which cause contact bouncing, mechanical wear, and acoustic noise. Soft-landing control strategies aim at minimizing the impact velocities of these devices to improve their performance. This paper presents a sliding-mode controller for soft landing of single-coil reluctance actuators. It is a switching model-free controller, which results in a very simple implementation. A generalized dynamical hybrid model of an actuator is utilized for deriving the robustness condition, based on the Lyapunov theory. Then, the condition is evaluated for a dynamical model, based on a commercial device, and several reference trajectories. Finally, the controller performance is validated through simulations. The effect of the sampling rate on the resulting impact velocities is also analyzed.

VI123-23
Stability of Nonlinear Systems	Regular Session
Chair: Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Co-Chair: Ito, Hiroshi	Kyushu Institute of Technology
Paper VI123-23.1
PDF · Video · Global Control for a Class of Feedforward Nonlinear Systems with Uncertain Measurement Functions
Zha, Wenting	China University of Mining and Technology (Beijing)
Zhai, Junyong	Southeast University
Liang, Yingyu	China University of Mining and Technology (Beijing)
Keywords: Asymptotic stabilization, Robust control, Lyapunov methods Abstract: Based on the nested-saturation technique, this paper investigates the global stabilization problem for a class of upper-triangular nonlinear systems with uncertain measurement functions. By imposing certain assumptions on the uncertain powers, a state-feedback controller, only involving the known parameters, is designed to locally stabilize the nonlinear system. Then, a saturated controller is constructed by combining the nested function and the local stabilizer. With appropriate saturation level, it can be proved that the saturated controller is able to make the closed-loop system globally asymptotically stable. Finally, a simulation example is presented to demonstrate the effectiveness and robustness of the proposed control scheme.
Paper VI123-23.2
PDF · Video · Observer-Based Robust H_infty Control for Uncertain Discrete-Time T-S Fuzzy Systems
Bentaleb, Ahmed	University Cadi Ayyad
Benzaouia, Abdellah	Faculty of Science Semlalia
El Hajjaji, Ahmed	Univ. De Picardie Jules Verne
Karama, Asma	Cadi Ayyad University
Keywords: Lyapunov methods, Asymptotic stabilization, Robust control (linear case) Abstract: This paper investigates robust observer based H_infty control problem for uncertain discrete-time Takagi-Sugeno fuzzy systems. By using fuzzy Lyapunov functions and some special derivations, Sufficient relaxed conditions for synthesis of a fuzzy observer and a fuzzy controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). The proposed approach provides more relaxed conditions comparing with the existing techniques in literature, also ensures better H_infty control performance. Simulation example is presented to show the effectiveness of the proposed design method.
Paper VI123-23.3
PDF · Video · Phase Margins in a Class of Nonlinear Systems: Lyapunov, Circle Criterion and Describing Function Approaches
Das, Siddharth Sankar	The University of Alabama in Huntsville
Shtessel, Yuri B.	Univ. of Alabama at Huntsville
Plestan, Franck	Ecole Centrale De Nantes-LS2N
Keywords: Lyapunov methods, Convex optimization, Stability of nonlinear systems Abstract: In this work, Phase Margins are studied for a class of Nonlinear Systems specifically the Lur’e type. New definitions are proposed for Practical Phase Margins in such systems and the corresponding computational algorithms are developed via Describing Function, Circle Criterion and Lyapunov methods. The efficacy of the proposed approaches are illustrated on a tutorial example.
Paper VI123-23.4
PDF · Video · Computation of Lyapunov Functions under State Constraints Using Semidefinite Programming Hierarchies
Souaiby, Marianne	Laas -- Cnrs
Tanwani, Aneel	LAAS -- CNRS, Université De Toulouse
Henrion, Didier	LAAS-CNRS, Univ. Toulouse
Keywords: Lyapunov methods, Convex optimization, Stability of nonlinear systems Abstract: In this article, we provide an algorithm for computing a Lyapunov function for a class of systems where the state trajectories are constrained to evolve within a closed convex set. The dynamical systems that we consider comprise a differential equation which ensures continuous evolution within the domain, and a normal cone inclusion which ensures that the state trajectory remains within a prespecified set at all times. Finding a Lyapunov function for such a system boils down to finding a function which satisfies certain inequalities on the admissible set of state constraints. It is well-known that this problem, despite being convex, is computationally difficult. For conic constraints, we provide a discretization algorithm based on simplical partitioning of a simplex, so that the search of desired function is a addressed by constructing a hierarchy (associated with the diameter of the cells in the partition) of linear programs. The second algorithms that we propose is tailored for semi-algebraic sets, where a hierarchy of semidefinite programs is constructed to compute Lyapunov functions as a sum-of-squares polynomial.
Paper VI123-23.5
PDF · Video · Smaller and Negative Exponents in Lyapunov Functions for Interconnected iISS Systems
Ito, Hiroshi	Kyushu Institute of Technology
Keywords: Lyapunov methods, Input-to-State Stability, Systems with saturation Abstract: For integral input-to-state stable (iISS) systems, stability of their interconnections can be established through a small-gain condition. Unlike input-to-state stable (ISS) systems, iISS systems admit gain functions only in limited ranges. Thus, composing a Lyapunov function which is valid globally is instrumental for addressing iISS. A Lyapunov function which is popular in the iISS framework proves the stability of interconnected systems whenever the small-gain condition is satisfied. However, it is hardly practical since its nonlinearities are often artificial and involve astonishingly large exponents. This paper drastically reduces the exponents analytically and numerically. This paper also extends the exponents to negative numbers, and demonstrates that two-sided exponents allow one to avoid unnecessary complicated Lyapunov functions.
Paper VI123-23.6
PDF · Video · A Speed Regulator for a Torque-Driven Inertia Wheel Pendulum
Sandoval, Jesus	Instituto Tecnologico De La Paz
Kelly, Rafael	CICESE
Santibanez, Victor	Instituto Tecnologico De La Laguna
Moreno-Valenzuela, Javier	CITEDI-IPN
Keywords: Lyapunov methods, Lagrangian and Hamiltonian systems, Stability of nonlinear systems Abstract: In this paper, we present a speed regulator for a torque-driven inertia wheel pendulum. The proposed controller allows bringing the nonactuated pendulum towards its upright position, while the wheel moves asymptotically at desired constant speed, recovering the popular position regulation control objective for both pendulum and wheel when the desired wheel speed is zero. Also, a rigorous stability analysis based on the Lyapunov theory and the Barbashin-Krasovskii theorem is presented. Simulation results upon a torque-driven inertia wheel pendulum model illustrate the performance of the proposed controller.
Paper VI123-23.7
PDF · Video · State-Feedback Control for Continuous-Time LPV Systems with Polynomial Vector Fields
Ferreira, Gabriel	Federal University of São João Del-Rei
Leite, Valter J. S.	CEFET/MG - Campus Divinopolis
Lacerda, Márcio J.	Federal University of São João Del-Rei
Keywords: Lyapunov methods, Parameter-varying systems, Asymptotic stabilization Abstract: This paper is concerned with the design of state-feedback controllers for Linear Parameter Varying (LPV) polynomial continuous-time systems. The vector field presents polynomial dependence on the states. Two synthesis conditions are proposed, the first one considers arbitrary rates of variation in the time-varying parameters, while the second one provides LPV controllers that are constructed based on a smoothed approximation of the time-varying parameter. The sum of squares matrix decomposition is employed to solve the proposed conditions. The L2 gain is also considered to give a robustness measure of the proposed controllers. The results are illustrated with examples from the literature.
Paper VI123-23.8
PDF · Video · On Existence of Oscillations in Persidskii Systems
Wang, Jian	Hangzhou Dianzi University
Mendoza Avila, Jesus	National Autonomous University of Mexico
Efimov, Denis	Inria
Aleksandrov, Alexander	Applied Mathematics and ControlProcesses, St.PetersburgStateUnive
Fridman, Leonid M.	National Autonomous University of Mexico
Keywords: Lyapunov methods, Stability of nonlinear systems, Input-to-State Stability Abstract: The conditions of existence of oscillations in the sense of Yakubovich are considered for a class of generalized nonlinear Persidskii systems. To this end, the conditions of local instability at the origin and global boundedness of solutions are presented in the form of linear matrix inequalities. The proposed theory is applied for robustness analysis of nonlinear feedback controls in linear systems with respect to unmodeled dynamics.
Paper VI123-23.9
PDF · Video · Robust Stabilization of Control Affine Systems with Homogeneous Functions
Zimenko, Konstantin	ITMO University
Polyakov, Andrey	INRIA Lille Nord-Europe
Efimov, Denis	Inria
Keywords: Robust control, Stability of nonlinear systems, Lyapunov methods Abstract: The stabilization problem of the affine control system dot x=f_0(x)+sum_{i=1}^m u_if_i(x) with homogeneous functions f_0, f_i is studied. This class of systems is of interest due to the robust properties of homogeneity and the fact that many affine systems can be approximated by or transformed to the class under consideration. An advantage of the introduced design method is that the tuning rules are presented in the form of linear matrix inequalities. Performance of the approach is illustrated by a numerical example.
Paper VI123-23.10
PDF · Video · Divergence Conditions for Stability Study of Autonomous Nonlinear Systems
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Gushchin, Pavel	Gubkin Russian State University of Oil and Gas (National Researc
Nekhoroshikh, Artem	ITMO University
Keywords: Stability of nonlinear systems Abstract: A novel method for stability study of autonomous dynamical systems using the flow and divergence of the vector field is proposed. Necessary and sufficient stability conditions are proposed. A relation between the method of Lyapunov functions and the proposed method is established. The examples illustrate the application of the proposed method and the existing ones.
Paper VI123-23.11
PDF · Video · Adaptive Control Allocation: A Human-In-The-Loop Stability Analysis
Tohidi, Seyed Shahabaldin	Bilkent University
Yildiz, Yildiray	Bilkent University
Keywords: Stability of nonlinear systems, Adaptive control, Sliding mode control Abstract: This paper demonstrates the stability limits of a human-in-the-loop closed loop control system, where the plant to be controlled has redundant actuators with uncertain dynamics. Two different human operator models are considered: For tasks that require very accurate control commands, pilots are shown to produce control commands resembling the output of a pure gain controller. Therefore, we first analyze the stability of the uncertain nonlinear closed loop system with a pure gain pilot model. Another commonly employed model, to represent the inability of the human operator to respond to high frequency inputs, is the lag filter. In our second analysis, we show the stability properties of the human-in-the-loop control system where a lag filter operator model is utilized. A flight control task, where the pilot controls the pitch angle via a pitch rate stick input, and the controller receives separate roll and yaw rate references, is simulated to demonstrate the accuracy of the stability analysis.
Paper VI123-23.12
PDF · Video · Robust Regions of Attraction for State-Constrained Perturbed Discrete-Time Polynomial Systems
Xue, Bai	Institute of Software, Chinese Academy of Science
Zhan, Naijun	Institute of Software, Chinese Academy of Science
Li, Yangjia	Institute of Software, CAS
Keywords: Stability of nonlinear systems, Convex optimization, Sum-of-squares Abstract: In this paper we propose a convex programming based method for computing robust regions of attraction for state-constrained perturbed discrete-time polynomial systems. The robust region of attraction of interest is a set of states such that every possible trajectory initialized in it will approach an equilibrium state while never violating the specified state constraint, regardless of the actual perturbation. Based on a Bellman equation which characterizes the interior of the maximal robust region of attraction as the strict one sub-level set of its unique bounded and continuous solution, we construct a semi-definite program for computing robust regions of attraction. Under appropriate assumptions, the existence of solutions to the constructed semi-definite program is guaranteed and there exists a sequence of solutions such that their strict one sub-level sets inner-approximate and converge to the interior of the maximal robust region of attraction in measure. Finally, we demonstrate the method by two examples.
Paper VI123-23.13
PDF · Video · Newton's Method: Sufficient Conditions for Practical and Input-To-State Stability
Colabufo, Giuseppe Giorgio	Ecole Polytechnique
Dower, Peter M.	University of Melbourne
Shames, Iman	University of Melbourne
Keywords: Stability of nonlinear systems, Input-to-State Stability Abstract: Newton’s method is a classical iterative algorithm for the numerical computation of isolated roots of algebraic equations and stationary points of functions. While its application is ubiquitous in a plethora of fields, questions concerning its robust stability to uncertainties in problem data and numerical accuracy often arise in practice. This paper seeks to provide sufficient conditions for practical stability, input-to-state-stability (ISS), integral ISS (iISS) and incremental ISS (deltaISS) of Newton’s method in the presence of such uncertainties, and provide illustrative examples of their application.
Paper VI123-23.14
PDF · Video · Lyapunov Based Hierarchical Trajectory Control of an Autonomous Ground Vehicle Subjected to Slip
Patil, Omkar Sudhir	University of Florida
Bhasin, Shubhendu	Indian Institute of Technology Delhi
Keywords: Stability of nonlinear systems, Lyapunov methods Abstract: The dynamics of wheel slip plays an important role in generation of traction forces, responsible for driving a ground vehicle. It is important to take these dynamics into account while designing control laws, in order to ensure stability of the autonomous vehicle. In this paper, the longitudinal and lateral slip dynamics are modeled and incorporated in the vehicle model. The key contribution of this paper is the design of a nonlinear hierarchical controller to address the trajectory tracking problem in presence of combined longitudinal and lateral slip dynamics. A Lyapunov based analysis is used to guarantee stability of the closed-loop system. Simulation results are provided to demonstrate the efficacy of the proposed controller.
Paper VI123-23.15
PDF · Video · Almost Global Attitude Stabilisation of a 3-D Pendulum by Means of Two Control Torques
Mason, Paolo	L2S CentraleSupélec, CNRS
Greco, Luca	CentraleSupélec
Keywords: Stability of nonlinear systems, Lyapunov methods, Asymptotic stabilization Abstract: We investigate the problem of stabilising the attitude of a 3-D axially symmetric pendulum. The system is assumed to be actuated by two torques acting on a plane orthogonal to the symmetry axis. We develop a smooth control law to stabilise the pendulum to the upright position with a given orientation starting from almost all initial conditions. Our approach consists in two steps: first, stabilising the kinematic subsystem by using the angular velocity as a virtual input; second, exploiting the actual inputs to force the angular velocity to follow the reference designed in the previous step.
Paper VI123-23.16
PDF · Video · Stability Conditions of TS Fuzzy Systems with Switched Polynomial Lyapunov Functions
Elias, Leandro José	Instituto Federal De Educação, Ciência E Tecnologia De São Paulo
Faria, Flávio A.	UNESP - Univ Estadual Paulista
Araujo, Rayza	Depto Engenharia Elétrica E Computação, Universidade De São Paulo
Oliveira, Vilma A.	Universidade De Sao Paulo
Keywords: Stability of nonlinear systems, Lyapunov methods, Asymptotic stabilization Abstract: Exploring properties of membership functions, sufficient conditions based on linear matrix inequalities (LMIs) for a existence of a switched polynomial Lyapunov function are proposed. To obtain the LMIs, the time derivative of membership functions are described as a finite polytopic representation, leading to less conservative conditions than other published results. A numerical example illustrates the efficiency of the stabilizing conditions.
Paper VI123-23.17
PDF · Video · On Fixed-Time Stability of a Class of Nonlinear Systems
Braidiz, Youness	Ecole Centrale De Lille
Polyakov, Andrey	INRIA Lille Nord-Europe
Efimov, Denis	Inria
Perruquetti, Wilfrid	Ecole Centrale De Lille
Keywords: Stability of nonlinear systems, Lyapunov methods, Asymptotic stabilization Abstract: Fixed-time stability of some class of non-linear systems is investigated using the introduced notions of sub- and sup-homogeneity. These concepts allow the systems (even if they do not admit homogeneous approximations) to be analyzed using the homogeneity of their extensions. Then, finite-time and fixed-time stability properties can be recovered. The proposed stability conditions are not based on Lyapunov arguments. In the last section, an example illustrates the obtained results.
Paper VI123-23.18
PDF · Video · On Lyapunov-Lur'e Functional Based Stability Criterion for Discrete-Time Lur'e Systems
Zhang, Jingfan	The University of Manchester
Carrasco, Joaquin	University of Manchester
Heath, William	University of Manchester
Keywords: Stability of nonlinear systems, Lyapunov methods, Input-to-State Stability Abstract: In this manuscript, we consider the stability problem of Lur'e systems with slope-restricted nonlinearities. We focus on a specific parametrisation of the Lyapunov-Lur'e functional in the literature, and extend it to a higher order. Meanwhile, we show this Lyapunov-Lur'e functional based stability criterion is equivalent to the search for noncausal FIR multipliers with a restricted form for the SISO case. Finally, we discuss the restrictions of this Lyapunov-Lur'e functional approach with some numerical examples.
Paper VI123-23.19
PDF · Video · Nonsmooth Stabilization and Its Computational Aspects
Osinenko, Pavel	Skoltech Institute of Science and Technology
Schmidt, Patrick	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Stability of nonlinear systems, Lyapunov methods, Non-smooth and discontinuous optimal control problems Abstract: This work has the goal of briefly surveying some key stabilization techniques for general nonlinear systems, for which, as it is well known, a smooth control Lyapunov function may fail to exist. A general overview of the situation with smooth and nonsmooth stabilization is provided, followed by a concise summary of basic tools and techniques, including general stabilization, sliding-mode control and nonsmooth backstepping. Their presentation is accompanied with examples. The survey is concluded with some remarks on computational aspects related to determination of sampling times and control actions.
Paper VI123-23.20
PDF · Video · Harmonic Balance Analysis of Pull-In Range and Oscillatory Behavior of Third-Order Type 2 Analog PLLs
Kuznetsov, Nikolay	Saint-Petersburg State Univ
Lobachev, Mikhail	Saint Petersburg State University
Yuldashev, Marat	Saint Petersburg State University
Yuldashev, Renat	St. Petersburg State University
Kolumban, Geza	Budapest University of Technology and Economics
Keywords: Stability of nonlinear systems, Nonlinear observers and filter design, Lyapunov methods Abstract: The most important design parameters of each phase-locked loop (PLL) are the local and global stability properties, and the pull-in range. To extend the pull-in range, engineers often use type 2 PLLs. However, the engineering design relies on approximations which prevent a full exploitation of the benefits of type 2 PLLs. Using an exact mathematical model and relying on a rigorous mathematical thinking this problem is revisited here and the stability and pull-in properties of the third-order type 2 analog PLLs are determined. Both the local and global stability conditions are derived. As a new idea, the harmonic balance method is used to derive the global stability conditions. That approach offers an extra advantage, the birth of unwanted oscillations can be also predicted. As a verification it is shown that the sufficient conditions of global stability derived by the harmonic balance method proposed here and the well-known direct Lyapunov approach coincide with each other, moreover, the harmonic balance predicts the birth of oscillations in the gap between the local and global stability conditions. Finally, an example when the conditions for local and global stability coincide, is considered.
Paper VI123-23.21
PDF · Video · Control of Dynamical Systems with Given Restrictions on Output Signal with Application to Linear Systems
Furtat, Igor	Institute of Problems of Mechanical Engineering Russian Academy
Gushchin, Pavel	Gubkin Russian State University of Oil and Gas (National Researc
Keywords: Stability of nonlinear systems, Output regulation Abstract: We propose a novel method for control of dynamical systems that ensures the belonging of an output signal to the given set at any time. The method is based on a special change of coordinates such that the initial problem with given restrictions on an output variable can be performed as the problem of the input-to-state stability analysis of a new extended system without restrictions. This method is used for control of linear plants.
Paper VI123-23.22
PDF · Video · A Characterization of Robust Regions of Attraction for Discrete-Time Systems Based on Bellman Equations
Xue, Bai	Institute of Software
Zhan, Naijun	Institute of Software, Chinese Academy of Science
Li, Yangjia	Institute of Software, CAS
Keywords: Stability of nonlinear systems, Robust control, Control of constrained systems Abstract: In this paper we present a Bellman equation for computing robust regions of attraction for state-constrained perturbed discrete-time systems. The robust region of attraction of interest is a set of states such that every trajectory initialized in it will approach an equilibrium while never violating a specified state constraint, regardless of the actual perturbation. In this approach, the interior of the maximal robust region of attraction is characterized as the strict one sub-level set of the unique bounded and continuous solution to a Bellman equation.
Paper VI123-23.23
PDF · Video · Leonov's Nonlocal Reduction Technique for Nonlinear Integro-Differential Equations
Smirnova, Vera	St.Petersburg State University of Architecture and Civil Enginee
Proskurnikov, Anton V.	Politecnico Di Torino
Keywords: Stability of nonlinear systems, stability of distributed parameter systems Abstract: Starting from pioneering works by Lur'e, Popov and Zames, global stability theory for nonlinear control systems has been primarily focused on systems with only one equilibrium. Global stability criteria for other kinds of attractors (such as e.g. infinite sets of equilibria) are not well studied and typically require special tools, primarily based on the Lyapunov method. Analysis of stability becomes especially complicated for infinite-dimensional dynamical systems with multiple equilibria, e.g. systems described by delay or more general convolutionary equations. In this paper, we propose novel stability criteria for infinite-dimensional systems with periodic nonlinearities, which have infinite sets of equilibria and describe dynamics of phase-locked loops and other synchronization circuits. Our method combines Leonov's nonlocal reduction technique with the idea of Popov's "integral indices" and allows to obtain new frequency-domain conditions, ensuring the convergence of every solution to one of the equilibria points.
Paper VI123-23.24
PDF · Video · Analysis of Integral Input-To-State Stable Time-Delay Systems in Cascade
Göksu, Gökhan	CentraleSupélec,
Chaillet, Antoine	CentraleSupelec - IUF
Keywords: Delay systems, Input-to-State Stability, Lyapunov methods Abstract: We consider the cascade interconnection of two nonlinear time-delay systems, each of which being integral input-to-state stable (iISS). We provide an explicit growth rate condition on the dissipation rate of the driving system and the input rate of the driven system under which the overall cascade is globally asymptotically stable in the absence of inputs (0-GAS), and its solutions are bounded in response to any input with a suitable bounded-energy assumption.
Paper VI123-23.25
PDF · Video · Event Triggering Control for Dynamical Systems with Designable Inter-Event Times
Chu, Xing	Yunnan University
Huang, Na	Hangzhou Dianzi University
Sun, Zhiyong	Eindhoven University of Technology (TU/e)
Keywords: Input-to-State Stability, Linear systems, Robustness analysis Abstract: This paper presents a class of event-triggering rules for dynamical control systems with guaranteed positive minimum inter-event time (IET). We first propose an event-based function design with guaranteed control performance using a clock-like variable for general nonlinear systems, and later specialize them to general linear systems. Compared to the existing static and dynamic triggering mechanisms, the proposed triggering rules feature a robust global event-separation property, and can be easily implemented on practical digital platforms to meet various hardware limitations. Finally, several numerical simulations are given to illustrate the theoretical results.
Paper VI123-23.26
PDF · Video · Analysis of Singular Perturbations for a Class of Interconnected Homogeneous Systems: Input-To-State Stability Approach
Mendoza Avila, Jesus	National Autonomous University of Mexico
Efimov, Denis	Inria
Moreno, Jaime A.	Universidad Nacional Autonoma De Mexico-UNAM
Fridman, Leonid M.	National Autonomous University of Mexico
Keywords: Stability of nonlinear systems, Input-to-State Stability, Lyapunov methods Abstract: In this work an interconnection of two singularly perturbed homogeneous systems of different degrees is considered. Under relaxed restrictions on the smoothness of the right-hand sides of the system, and some standard assumptions, the conditions of local or practical asymptotic stability of the interconnection are established by means of ISS properties and the Small-Gain Theorem. Moreover, the domains of stability and attractions are estimated. Finally, the results are illustrated through an example with a homogeneous system of negative degree.
Paper VI123-23.27
PDF · Video · On the Converse Passivity Theorems for LTI Systems
Kao, Chung-Yao	National Sun Yat-Sen University
Khong, Sei Zhen	-
van der Schaft, Arjan J.	Univ. of Groningen
Keywords: Passivity-based control, Robust control (linear case), Robustness analysis Abstract: Converse passivity theorems are established forfinite-dimensional (FD) linear time-invariant (LTI) systems. Consider an FD LTI system G1 interconnected in positive feedback with another FD LTI system G2. It is demonstrated that when the closed-loop system is (robustly) stable (in the sense offinite L2 gain) for arbitrary strictly passive G2, then -G1 must necessarily be passive. It is also demonstrated that when the closed-loop system is uniformly stable across the set of arbitrary passive G2, then -G1 must necessarily be strictly passive. The proofs are constructive; i.e., we show how to find a de-stabilizing FD LTI G2 when G1 violates the necessity condition of stability.

VI123-24
Switching - Stability and Control	Regular Session
Chair: Ferrari, Riccardo M.G.	Delft University of Technology
Co-Chair: Maestre, Jose M.	University of Seville
Paper VI123-24.1
PDF · Video · Metzler Matrix-Based Switching Control Scheme for Linear Systems with Prescribed Performance Guarantees
Guo, Zongyi	Northwestern Polytechnical University
Henry, David	Université De Bordeaux
Guo, Jianguo	Northwestern Polytechnical Univerisity
Wang, Zheng	Northwestern Polytechnical University , Xi’an, China
Cieslak, Jérôme	University of Bordeaux
Chang, Jing	Xidian University
Keywords: Controller constraints and structure, Switching stability and control, Discontinuous control Abstract: This paper investigates the issue of control design for linear systems with prescribed performance. The novelty of the proposed solution relies on a switching control scheme that uses the interval theory. Different from the existing prescribed performance control approaches, the error transformation and the logarithmic/tangent function are no longer required in the presented control. Alternatively, a switching scheme inspired by the interval observer technique is introduced to ensure the errors not violating performance bound functions. The proposed control establishes an unified prescribed performance control framework which covers the bounded stability, asymptotic stability and finite-time stability only via selecting the corresponding performance bound functions. Numerical examples are simulated to demonstrate the effectiveness of the proposed approach.
Paper VI123-24.2
PDF · Video · Impulsive Observer Design for Switched Linear Systems with Time Varying Sampling and (a)synchronous Switching Rules
Etienne, Lucien	IMT Lille-Douai
Motchon, Koffi M. Djidula	Université De Reims Champagne Ardenne, CReSTIC EA 3804
Duviella, Eric	IMT Lille Douai
Guelton, Kevin	Université De Reims Champagne-Ardenne
Keywords: Observer design, Stability of hybrid systems, Output feedback control Abstract: Observer synthesis for switched linear systems with time-varying sampled-data measurements is addressed in this paper. Between sampling times, the behaviour of the observer under consideration has the particularity to be that of the estimated active mode while, at the sampling times a correction (or an update) is made using the estimated active mode and the sampled output signal. Two cases are discussed: i) the situation where no delay occurs in the estimation of the active mode and, ii) the more practical case where the estimated switching signal that defines the proposed observer is a delayed replica of the plant's switching signal. In these two situations, appropriate time-varying piecewise quadratic Lyapunov functions are used to establish convergence conditions of the proposed observer in the linear matrix inequalities (LMIs) framework.
Paper VI123-24.3
PDF · Video · Path Following with Stable and Unstable Modes Subject to Time-Varying Dwell-Time Conditions
Le, Duc	University of Florida
Chen, Hsi-Yuan	University of Florida
Teel, Andrew R.	Univ. of California at Santa Barbara
Dixon, Warren E.	Univ of Florida
Keywords: Switching stability and control, Control of switched systems, Stability of nonlinear systems Abstract: Systems are often tasked with operating in modes where state feedback is available intermittently. The analysis of such systems involves analyzing the behavior of individual subsystems and the time that each subsystem is active, i.e., dwell-time conditions. Often, these dwell-time conditions are conservative, potentially limiting the performance of the overall system. In an effort to reduce conservativeness of the dwell-time condition, an adaptive data-driven extremum seeking (ESC) method is used to develop a time-varying dwell-time condition. Specifically, the ESC drives the evolution of the dwell-time condition to a less conservative dwell-time condition while simultaneously ensuring stability of the overall system. Simulations demonstrate a nearly threefold increase in a maximum dwell-time that results in significant changes to the behavior of an agent tasked with following a path outside a feedback region.
Paper VI123-24.4
PDF · Video · A Geometric Stabilization of Planar Switched Systems
Chenavier, Cyrille	Inria Lille - Nord Europe
Ushirobira, Rosane	Inria
Valmorbida, Giorgio	L2S, CentraleSupelec
Keywords: Switching stability and control, Linear systems, Asymptotic stabilization Abstract: In this paper, we investigate a particular class of switching functions between two linear systems in the plan. The considered functions are defined in terms of geometric constructions. More precisely, we introduce two criteria for proving uniform stability of such functions, both criteria are based on the construction of a Lyapunov function. The first criterion is constructed in terms of an algebraic reformulation of the problem and linear matrix inequalities. The second one is purely geometric. Finally, we illustrate the second method with a numerical example.
Paper VI123-24.5
PDF · Video · Initial State Design for Suppressing Undesirable Effects of Controller Switches
Suyama, Koichi	Tokyo Univ. of Marine Science and Technology
Sebe, Noboru	Kyushu Inst. of Tech
Keywords: Switching stability and control, Linear systems, Time-invariant systems Abstract: We propose a new initial state design procedure for a newly-activated controller at a controller switch. By minimizing the value of the state-dependent switching L2 gain presented in this paper, we can obtain the optimal initial state for suppressing the difference between the actuality that a controller switch occurs and the virtual situation where it does not occur.
Paper VI123-24.6
PDF · Video · Control Design and Lyapunov Functions Via Bernstein Approximations: Exact Results
Hamadneh, Tareq	Aalborg University
Athanasopoulos, Nikolaos	Queen's University Belfast
Wisniewski, Rafal	Aalborg University
Keywords: Switching stability and control, Optimal control theory Abstract: We study the control problem for polynomial continuous-time dynamical systems. We consider polynomial Lyapunov functions and controllers, both parameterised in Bernstein form. Specifically, we present necessary and sufficient conditions for existence of polynomial controllers and Lyapunov functions of some maximum degree, providing at the same time explicit upper bounds on the degree of the involved Bernstein polynomials. The formulated conditions are a set of algebraic inequalities, in the space of Bernstein coefficients.
Paper VI123-24.7
PDF · Video · Interval Full-Order Switched Positive Observers for Uncertain Switched Positive Linear Systems
Otsuka, Naohisa	Tokyo Denki Univ
Kakehi, Daiki	Tokyo Denki University
Keywords: Switching stability and control, Positive systems, Observer design Abstract: In this paper, we study observation problems for uncertain switched positive linear systems. Firstly, interval full-order switched positive observers for both continuous-time and discrete-time uncertain switched positive linear systems are studied. Further, it is shown that the obtained results are reduced to the results of non-switched positive linear systems. Finally, two illustrative numerical examples of interval full-order observes for both continuous-time and discrete-time uncertain switched positive linear systems are investigated.
Paper VI123-24.8
PDF · Video · Switched Control of a Three-Phase AC-DC Power Converter
Egidio, Lucas	School of Mechanical Engineering, UNICAMP
Deaecto, Grace S.	FEM/UNICAMP
Barros, Tarcio Andre S.	FEM/Unicamp
Keywords: Switching stability and control, Power systems, Tracking Abstract: In this paper, a new switched control strategy for three-phase AC-DC power converters, also known as controlled rectifiers, is proposed. More specifically, a switching function is determined to command the converter switches at each instant of time assuring global asymptotic tracking of a desired reference trajectory, which is related to a constant output voltage and sinusoidal phase currents. This is generally a desired situation for AC-DC power converters as it can ensure unitary power factor and rectified steady-state DC voltage simultaneously. The proposed switching function must also assure a guaranteed performance cost. The design conditions are based on a Lyapunov function, which is dependent on the electrical angle, and are expressed in terms of linear matrix inequalities (LMIs). Simulation results put in evidence the effectiveness of the proposed methodology and motivate future related works.
Paper VI123-24.9
PDF · Video · A Topology-Switching Coalitional Control and Observation Scheme with Stability Guarantees
Chanfreut, Paula	University of Seville
Keijzer, Twan	Delft Center for Systems and Control, Delft University of Techno
Ferrari, Riccardo M.G.	Delft University of Technology
Maestre, Jose M.	University of Seville
Keywords: Switching stability and control, Time-invariant systems, Controller constraints and structure Abstract: In this paper a coalitional control and observation scheme is presented in which the coalitions are changed online by enabling and disabling communication links. Transitions between coalitions are made to best balance overall system performance and communication costs. Linear Matrix Inequalities are used to design the controller and observer, guaranteeing stability of the switching system. Simulation results for vehicle platoon control are presented to illustrate the proposed method.

VI124
Design Methods - Optimal Control
VI124-01 Numerical Methods for Predictive Control   Open Invited Session, 15 papers
VI124-02 Applications of Optimal and Predictive Control   Regular Session, 15 papers
VI124-03 Differential or Dynamic Games   Regular Session, 6 papers
VI124-04 Numerical Methods for Optimal Control   Regular Session, 7 papers
VI124-05 Optimal and Predictive Control of Hybrid Systems   Regular Session, 8 papers
VI124-06 Optimal Control Theory   Regular Session, 14 papers
VI124-07 Predictive Control   Regular Session, 13 papers
VI124-08 Real-Time and Efficient Predictive Control   Regular Session, 11 papers
VI124-09 Robust and Learning Predictive Control   Regular Session, 14 papers
VI124-10 Robust and Stochastic Optimal Control   Regular Session, 8 papers

VI124-01
Numerical Methods for Predictive Control	Open Invited Session
Chair: Kerrigan, Eric C.	Imperial College London
Co-Chair: McInerney, Ian	Imperial College London
Organizer: McInerney, Ian	Imperial College London
Organizer: Faqir, Omar	Imperial College London
Organizer: Nie, Yuanbo	Imperial College London
Organizer: Kerrigan, Eric C.	Imperial College London
Paper VI124-01.1
PDF · Video · Efficient Solution Method Based on Inverse Dynamics of Optimal Control Problems for Fixed-Based Rigid-Body Systems (I)
Katayama, Sotaro	Kyoto University
Ohtsuka, Toshiyuki	Kyoto University
Keywords: Numerical methods for optimal control, Nonlinear predictive control Abstract: We propose an efficient solution method of finite horizon optimal control problems (FHOCPs) for fixed-based rigid-body systems based on inverse dynamics. Our method can reduce the computational cost compared with the conventional FHOCP based on forward dynamics. We reformulate the FHOCP for the rigid-body systems by utilizing the generalized acceleration as the decision variables and inverse dynamics as the equality constraint. We derive the necessary conditions of the optimal control, namely, the optimality conditions, and formulate a two-point boundary-value problem that can be solved efficiently by using the recursive Newton Euler algorithm (RNEA) and the partial derivatives of RNEA. The results of the several numerical experiments on nonlinear model predictive control using the proposed formulation demonstrate the effectiveness of our approach.
Paper VI124-01.2
PDF · Video · A New Heuristic Approach for Low-Thrust Spacecraft Trajectory Optimization (I)
Coppens, Peter	KU Leuven
Hermans, Ben	KU Leuven
Vandersteen, Jeroen	European Space Agency
Pipeleers, Goele	Katholieke Universiteit Leuven
Patrinos, Panagiotis	KU Leuven
Keywords: Aerospace, Numerical methods for optimal control, Real-time optimal control Abstract: Electrical propulsion is gaining popularity in the satellite industry. Their high efficiency however comes at the cost of decreased thrust and longer transfer times. As such the interest in solving the large optimization problems associated with these long transfers has re-surged. This paper presents a heuristic approach to solving such low-thrust satellite trajectory optimization problems, based on control law blending and averaging. We derive the nonlinear program resulting from this approach and introduce PANOC, a recent optimization algorithm well suited for optimal control problems. The resulting controller is considerably faster than more classical, non-heuristic approaches, without a significant loss in optimality.
Paper VI124-01.3
PDF · Video · The L_1 Exact Penalty-Barrier Phase for Degenerate Nonlinear Programming Problems in Ipopt (I)
Thierry, David	Carnegie Mellon University
Biegler, Lorenz T.	Carnegie Mellon Univ
Keywords: Large scale optimization problems, Singularities in optimization, Numerical methods for optimal control Abstract: Failure to satisfy Constraint Qualifications (CQs) leads to serious convergence difficulties for state-of-the-art Nonlinear Programming (NLP) solvers. Since this failure is often overlooked by practitioners, a strategy to enhance the robustness properties for problems without CQs is vital. Inspired by penalty merit functions and barrier-like strategies, we propose and implement a combination of both in Ipopt. This strategy has the advantage of consistently satisfying the Linear Independence Constraint Qualification (LICQ) for an augmented problem, readily enabling regular step computations within the interior-point framework. Additionally, an update rule inspired by the work of Byrd et al. (2012) is implemented, which provides a dynamic increase of the penalty parameter as stationary points are approached. Extensive test results show favorable performance and robustness increases for our L1−penalty strategies, when compared to the regular version of Ipopt. Moreover, a dynamic optimization problem with nonsmooth dynamics formulated as a Mathematical Program with Complementarity Constraints (MPCC) was solved in a single optimization stage without additional reformulation. Thus, this L1−strategy has proved useful for a broad class of degenerate NLPs.
Paper VI124-01.4
PDF · Video · Pycombina: An Open-Source Tool for Solving Combinatorial Approximation Problems Arising in Mixed-Integer Optimal Control (I)
Bürger, Adrian	Karlsruhe University of Applied Sciences
Zeile, Clemens	Otto von Guericke University Magdeburg
Hahn, Mirko	Otto von Guericke University Magdeburg
Altmann-Dieses, Angelika	Karlsruhe University of Applied Sciences
Sager, Sebastian	Otto von Guericke University Magdeburg
Diehl, Moritz	University of Freiburg
Keywords: Nonlinear predictive control, Control of switched systems, Numerical methods for optimal control Abstract: Application of Model Predictive Control (MPC) for nonlinear switched systems often leads via discretization to Mixed-Integer Non-Linear Programs (MINLPs), which in a real-time setting can be solved approximately using a dedicated decomposition approach. One stage within this approach is the solution of a so-called Combinatorial Integral Approximation (CIA) problem, which is a Mixed-Integer Linear Program (MILP) that can be solved either approximately or to global optimality. The applicability of these decomposition methods depends strongly on efficient implementations, while many practical applications also require the consideration of a variety of additional and complex combinatorial constraints. In this work, we provide a comprehensive introduction to the open-source software tool pycombina, which enables users to automatically formulate CIA problems and provides methods for fast and efficient solution of these problems. In a case study, the usage of the tool is exemplified for input data from a real-life MPC application.
Paper VI124-01.5
PDF · Video · Exact Complexity Certification of an Early-Terminating Standard Primal Active-Set Method for Quadratic Programming (I)
Arnström, Daniel	Linköping University
Axehill, Daniel	Linköping University
Keywords: Real-time optimal control, Convex optimization, Predictive control Abstract: In this paper we present a method to exactly certify the iteration complexity of a primal active-set algorithm for quadratic programs which is terminated early, given a specific multi-parametric quadratic program. The primal active-set algorithm's real-time applicability is, hence, improved by early termination, increasing its computational efficiency, and by the proposed certification method, providing guarantees on worst-case behaviour. The certification method is illustrated on a multi-parametric quadratic program originating from model predictive control of an inverted pendulum, for which the relationship between allowed suboptimality and iterations needed by the primal active-set algorithm is presented.
Paper VI124-01.6
PDF · Video · Mesh Refinement for Event-Triggered Nonlinear Model Predictive Control (I)
Faqir, Omar	Imperial College London
Kerrigan, Eric C.	Imperial College London
Keywords: Nonlinear predictive control, Numerical methods for optimal control, Optimal control theory Abstract: We consider the effect of using approximate system predictions in event-triggered control schemes. Such approximations often result from numerical transcription methods for solving continuous-time optimal control problems. Mesh refinement schemes guarantee upper bounds on the error in the differential equations used to model system dynamics. In particular, we show that with the accuracy guarantees of a mesh refinement scheme, then event-triggering schemes based on bounding the difference between predicted and measured state can be used with a guaranteed strictly positive inter-update time. We determine a lower bound for this time and show that additional knowledge of the employed transcription method and evaluation of the approximation errors may be used to obtain better online estimates of inter-update times. This is the first work to consider using the solution accuracy of an optimal control problem as a metric for triggering new control updates.
Paper VI124-01.7
PDF · Video · Active-Set Based Inexact Interior Point QP Solver for Model Predictive Control (I)
Frey, Jonathan	University of Freiburg
Di Cairano, Stefano	Mitsubishi Electric Research Laboratory
Quirynen, Rien	Mitsubishi Electric Research Laboratories (MERL)
Keywords: Numerical methods for optimal control, Real-time optimal control, Convex optimization Abstract: Interior point methods are applicable to a large class of problems and can be very reliable for convex optimization, even without a good initial guess for the optimal solution. Active-set methods, on the other hand, are often restricted to linear or quadratic programming but they have a lower computational cost per iteration and superior warm starting properties. The present paper proposes an approach for improving the numerical conditioning and warm starting properties of interior point methods, based on an active-set identification strategy and inexact Newton-type optimization techniques. In addition, we show how this reduces the average computational cost of the linear algebra operations in each interior point iteration. We developed an efficient C code implementation of the active-set based interior point method (ASIPM) and show that it can be competitive with state of the art solvers for a standard case study of model predictive control stabilizing an inverted pendulum on a cart.
Paper VI124-01.8
PDF · Video · Inexact Adjoint-Based SQP Algorithm for Real-Time Stochastic Nonlinear MPC (I)
Feng, Xuhui	ShanghaiTech University
Di Cairano, Stefano	Mitsubishi Electric Research Laboratory
Quirynen, Rien	Mitsubishi Electric Research Laboratories (MERL)
Keywords: Numerical methods for optimal control, Stochastic optimal control problems, Nonlinear predictive control Abstract: This paper presents a real-time algorithm for stochastic nonlinear model predictive control (NMPC). The optimal control problem (OCP) involves a linearization based covariance matrix propagation to formulate the probabilistic chance constraints. Our proposed solution approach uses a tailored Jacobian approximation in combination with an adjoint-based sequential quadratic programming (SQP) method. The resulting algorithm allows the numerical elimination of the covariance matrices from the SQP subproblem, while ensuring Newton-type local convergence properties and preserving the block-sparse problem structure. It allows a considerable reduction of the computational complexity and preserves the positive definiteness of the covariance matrices at each iteration, unlike an exact Jacobian-based implementation. The real-time feasibility and closed-loop control performance of the proposed algorithm are illustrated on a case study of an autonomous driving application subject to external disturbances.
Paper VI124-01.9
PDF · Video · Linear Quadratic Control Computation for Systems with a Directed Tree Structure (I)
Zafar, Armaghan	University of Melbourne
Farokhi, Farhad	The University of Melbourne
Cantoni, Michael	University of Melbourne
Keywords: Numerical methods for optimal control, Predictive control, Large scale optimization problems Abstract: A computational method is proposed for solving a structured quadratic optimal control problem subject to linear discrete-time dynamics arising from a directed tree structured interconnection of heterogeneous sub-systems. The problem is first formulated as a quadratic program with structure along three dimensions of the decision space. A nested algorithm based on block Jacobi iterations is proposed for the linear system of equations obtained from the corresponding first-order optimality conditions. It is shown that the per iteration computational burden scales favorably with increasing problem size in each dimension. The computations at each iteration are amenable to distributed implementation on a network of parallel processors mirroring the tree graph structure of the problem. Numerical experiments based on a model data for an automated irrigation network are used to demonstrate aspects of the approach, including the impact of early termination of the inner iterations in agreement with corresponding analysis.
Paper VI124-01.10
PDF · Video · Fast Gradient Method for Model Predictive Control with Input Rate and Amplitude Constraints (I)
Kempf, Idris	University of Oxford
Goulart, Paul J.	University of Oxford
Duncan, Stephen	Univ of Oxford
Keywords: Predictive control, Convex optimization, Constrained control Abstract: This paper is concerned with the computing efficiency of model predictive control (MPC) problems for dynamical systems with both rate and amplitude constraints on the inputs. Instead of augmenting the decision variables of the underlying finite-horizon optimal control problem to accommodate the input rate constraints, we propose to solve this problem using the fast gradient method, where the projection step is solved using Dykstra’s algorithm. We show that, relative to the Alternating Direction of Method Multipliers (ADMM), this approach greatly reduces the computation time while halving the memory usage. Our algorithm is implemented in C and its performance demonstrated using several examples.
Paper VI124-01.11
PDF · Video · OpEn: Code Generation for Embedded Nonconvex Optimization (I)
Sopasakis, Pantelis	Queen’s University Belfast
Fresk, Emil	Luleå University of Technology
Patrinos, Panagiotis	KU Leuven
Keywords: Numerical methods for optimal control, Real-time optimal control, Nonlinear predictive control Abstract: We present Optimization Engine (OpEn): an open-source code generation tool for real-time embedded nonconvex optimization, which implements a novel numerical method. OpEn combines the proximal averaged Newton-type method for optimal control (PANOC) with the penalty and augmented Lagrangian methods to compute approximate stationary points of nonconvex problems. The proposed method involves very simple algebraic operations such as vector products, has a low memory footprint and exhibits very good convergence properties that allow the solution of nonconvex problems on embedded devices. OpEn's core solver is written is Rust - a modern, high-performance, memory-safe and thread-safe systems programming language - while users can call it from Python, MATLAB, C, C++, ROS or over a TCP socket.
Paper VI124-01.12
PDF · Video · Closed-Form Preconditioner Design for Linear Predictive Control (I)
McInerney, Ian	Imperial College London
Kerrigan, Eric C.	Imperial College London
Constantinides, George A.	Imperial College London
Keywords: Numerical methods for optimal control, Predictive control, Analytic design Abstract: Model Predictive Control (MPC) with linear models and constraints is extensively being utilized in many applications, many of which have low power requirements and limited computational resources. In these resource-constrained environments, many designers choose to utilize simple iterative first-order optimization solvers, such as the Fast Gradient Method. Unfortunately, the convergence rate of these solvers is affected by the conditioning of the problem data, with ill-conditioned problems requiring a large number of iterations to solve. In order to reduce the number of solver iterations required, we present a simple closed-form method for computing an optimal preconditioning matrix for the Hessian of the condensed primal problem. To accomplish this, we also derive spectral bounds for the Hessian in terms of the transfer function of the predicted system. This preconditioner is based on the Toeplitz structure of the Hessian and has equivalent performance to a state-of-the-art optimal preconditioner, without having to solve a semidefinite program during the design phase.
Paper VI124-01.13
PDF · Video · CIAO*: MPC-Based Safe Motion Planning in Predictable Dynamic Environments (I)
Schoels, Tobias	University of Freiburg
Rutquist, Per	Tomlab Optimization
Palmieri, Luigi	Robert Bosch GmbH
Zanelli, Andrea	University of Freiburg
Arras, Kai Oliver	Robert Bosch GmbH
Diehl, Moritz	University of Freiburg
Keywords: Predictive control, Convex optimization, Real-time optimal control Abstract: Robots have been operating in dynamic environments and shared workspaces for decades. Most optimization based motion planning methods, however, do not consider the movement of other agents, e.g. humans or other robots, and therefore do not guarantee collision avoidance in such scenarios. This paper builds upon the Convex Inner ApprOximation (CIAO) method and proposes a motion planning algorithm that guarantees collision avoidance in predictable dynamic environments. Furthermore, it generalizes CIAO’s free region concept to arbitrary norms and proposes a cost function to approximate time optimal motion planning. The proposed method, CIAO*, finds kinodynamically feasible and collision free trajectories for constrained single body robots using model predictive control (MPC). It optimizes the motion of one agent and accounts for the predicted movement of surrounding agents and obstacles. The experimental evaluation shows that CIAO* reaches close to time optimal behavior.
Paper VI124-01.14
PDF · Video · HPIPM: A High-Performance Quadratic Programming Framework for Model Predictive Control (I)
Frison, Gianluca	University of Freiburg
Diehl, Moritz	University of Freiburg
Keywords: Numerical methods for optimal control, Real-time optimal control, Predictive control Abstract: This paper introduces HPIPM, a high-performance framework for quadratic programming (QP), designed to provide building blocks to efficiently and reliably solve model predictive control problems. HPIPM currently supports three QP types, and provides interior point method (IPM) solvers as well (partial) condensing routines. In particular, the IPM for optimal control QPs is intended to supersede the HPMPC solver, and it largely improves robustness while keeping the focus on speed. Numerical experiments show that HPIPM reliably solves challenging QPs, and that it outperforms other state-of-the-art solvers in speed.
Paper VI124-01.15
PDF · Video · Stability Analysis of Real-Time Methods for Equality Constrained NMPC (I)
Zanelli, Andrea	University of Freiburg
Tran Dinh, Quoc	University of North Carolina at Chapel Hill
Diehl, Moritz	University of Freiburg
Keywords: Nonlinear predictive control, Stability of nonlinear systems, Numerical methods for optimal control Abstract: In this paper, a proof of asymptotic stability for the combined system-optimizer dynamics associated with a class of real-time methods for equality constrained nonlinear model predictive control is presented. General Q-linearly convergent online optimization methods are considered and asymptotic stability results are derived for the case where a single iteration of the optimizer is carried out per sampling time. In particular, it is shown that, if the underlying sampling time is sufficiently short, asymptotic stability can be guaranteed. The results constitute an extension to existing attractivity results for the well-known real-time iteration strategy.

VI124-02
Applications of Optimal and Predictive Control	Regular Session
Chair: Stoustrup, Jakob	Aalborg University
Co-Chair: Yu, Shuyou	Jilin University
Paper VI124-02.1
PDF · Video · Optimal Control for Water Distribution Networks with Unknown Dynamics
Val, Jorge	Aalborg University
Wisniewski, Rafal	Aalborg University
Kallesøe, Carsten Skovmose	Grundfos
Keywords: Industrial applications of optimal control, Adaptive control, Optimal control theory Abstract: Optimal control for Water Distribution Networks (WDN) is subject to complex system models. Typically, detailed models are not available or the implementation is too expensive for small utilities. Reinforcement Learning (RL) methods are well known techniques for model-free control. This paper proposes a model-free controller for WDN based on RL methods and presents experimental evidence of the practicality of the design.
Paper VI124-02.2
PDF · Video · Stabilising the Light Spectrum of LED Solar Simulators Using LQG Control
Hofbauer, Julian	Leipzig University of Applied Sciences (HTWK Leipzig)
Rudolph, Mathias	Leipzig University of Applied Sciences (HTWK Leipzig)
Streif, Stefan	Technische Universität Chemnitz
Keywords: Industrial applications of optimal control, Model validation, Observer design Abstract: For analysis of photovoltaic cells artificial light sources, so called solar simulators can be used. The light spectrum and light intensity of the considered LED solar simulators is time varying due to current induced heating of the semiconductor. The change influences the measurement accuracy for the characterisation of solar cells. With the current as a control variable, the light intensity can be stabilised. The drift in the light colour can only be compensated with spectrally adjacent LEDs. Based on known physical and phenomenological correlations concerning the behaviour of LEDs, model equations for the solar simulator were developed and simplified. The corresponding parameters were determined by experiments on a solar simulator. A LQG controller was designed for the stabilisation of the time-varying spectrum. The controller is tested in simulations for different light spectra. The improvements over the uncontrolled case are demonstrated.
Paper VI124-02.3
PDF · Video · Discrete-Time State-Dependent Proportional-Integral Control for Torque Tracking of Hydrostatic Transmissions
Dang, Ngoc Danh	University of Rostock, Chair of Mechatronics
Aschemann, Harald	University of Rostock
Keywords: Industrial applications of optimal control, Parameter-varying systems, Disturbance rejection Abstract: This paper presents both design and implementation of a discrete-time proportional-integral (PI) tracking control for the desired output torque of a nonlinear hydrostatic transmission system affected by disturbances and uncertainties. The control is conceived in a decentralized form, in which the bent-axis angle and the torque of the hydraulic motor are controlled separately. The motor bent-axis angle is adjusted by a pure feedforward control law, whereas the torque of the hydraulic motor is controlled using a PI state feedback from a online-solution of the state-dependent Riccati equation. State variables and external disturbances are reconstructed by a discrete-time nonlinear observer. The stability of the closed-loop system as well as the observer are investigated by linear matrix inequalities. The achieved tracking performance indicates the robustness of the overall control structure in the presence of system disturbances and uncertainties. The proposed control is evaluated by means of simulations and experiments using the dedicated test rig at the Chair of Mechatronics, University of Rostock.
Paper VI124-02.4
PDF · Video · Low-Complexity Hierarchical Control for Distributed Shopping Center HVAC
Petersen, Joakim Børlum	Aalborg University
Bendtsen, Jan Dimon	Aalborg Univ
Alleyne, Andrew G.	Univ. of Illinois at Urbana-Champaign
Stoustrup, Jakob	Aalborg University
Keywords: Industrial applications of optimal control, Predictive control, Energy systems Abstract: In this paper we present a low-complexity hierarchical control approach to fan-coil-based HVAC systems, applicable to shopping centers as exemplified through a case study of a Danish shopping center. Although Model Predictive Control remains the optimal approach performance-wise, we show that we can recover 66% of the performance with the proposed approach, when considering no model-mismatch for the Model Predictive Controller. The recovered performance comes with the added benefits of increased reusablity and operator transparency, given no dependence on an accurate dynamical model and lower complexity.
Paper VI124-02.5
PDF · Video · Online Offset Optimization for Urban Traffic Network with Distributed Model Predictive Control
Xu, Yunwen	Shanghai Jiao Tong University
Wu, Na	Shanghai Jiao Tong University
Li, Dewei	Shanghai Jiao Tong University
Xi, Yugeng	Shanghai Jiao Tong University
Keywords: Predictive control, Adaptive control Abstract: This paper proposes a distributed control framework to optimize the offset for a path in a traffic network with arbitrary topology. Each intersection along the target path applies the model predictive control to optimize their own phase sequence and green splits with the objective of minimizing the sum of queue lengths. The first intersection on this path is regarded as the main intersection and responsible for optimizing the start green time and duration of the first phase on this path with a weighted objective according to the real-time traffic information, while the other intersections take the constraints of offset imposed by intersections ahead into consideration. The signal cycles of these intersections are fixed but allowed to be different. For computation efficiency, the nonlinear optimization problem is approximately reformulated as a mixed-integer linear programming problem. Numerical experiments on a calibrated network of Caohejing District in Shanghai indicate that our proposed method can effectively decrease delay time and waiting time, especially at medium and high traffic loads.
Paper VI124-02.6
PDF · Video · Nash Optimality Based Distributed Model Predictive Control for Vehicle Platoon
Yu, Shuyou	Jilin University
Li, Yongfu	Chongqing University of Posts and Telecommunications
Ebenbauer, Christian	University of Stuttgart
Chen, Hong	Jilin Univ, Campus NanLing
Chen, Hao	Jilin University
Feng, Yangyang	Jilin University
Zhang, Yajing	Jilin University
Keywords: Predictive control, Decentralized control, Linear systems Abstract: In this paper, a distributed model predictive control algorithm (DMPC) based on Nash optimality is proposed for automated vehicle platoon control. The optimization decision of vehicle platoon is decomposed into the decentralized optimization of single vehicles, in which the Nash optimality algorithm is adopted to solve the decentralized optimization problem. Thus, each vehicle can reach the local optimal target and the whole team can reach its Nash equilibrium. The methodology employs neighborhood information of the entire platoon through on-board sensors and V2V communication to achieve coordination of the entire platoon. The ability of the methods in terms of robustness to disturbances and cyber-physical interaction is demonstrated with simulation case studies.
Paper VI124-02.7
PDF · Video · Formulation of Fatigue Dynamics As Hybrid Dynamical System for Model Predictive Control
Loew, Stefan	TU Munich, Siemens AG
Obradovic, Dragan	Siemens
Keywords: Predictive control, Optimal control of hybride systems, Industrial applications of optimal control Abstract: The standard fatigue estimation procedure is formulated as a Hybrid Dynamical System, which subsequently is utilized to calculate an economic terminal cost in MPC. This formulation is enabled by the development of a novel algorithm for continuous stress cycle identification. A second hybrid dynamical system is designed to provide fatigue cost gradients. The formulation turns out to be a powerful generalization of previous fatigue cost formulations, and additionally introduces consideration of past stress into the cost function. Presented closed-loop simulations using a wind turbine model provide insight into the subsystems of the hybrid dynamical system, and show the benefit of memorizing the past.
Paper VI124-02.8
PDF · Video · Design of a Robust LQG Compensator for an Electric Power Steering
Irmer, Marcus	Cologne University of Applied Sciences
Henrichfreise, Hermann	Cologne University of Applied Sciences
Keywords: Optimal control theory, Robustness analysis, Robust controller synthesis Abstract: The control of the driver's hand torque of an electric power steering system has been state of the art for years. However, due to nonlinear spring characteristics, gear ratios, and degrees of freedom which are unconsidered in the design model for the controller or observer design, the challenge still lies in the robust implementation of this control approach. In this paper, the results of a systematic model and system analysis are used to develop an approach that solves the current stability and robustness problems existing in the serial development of steering systems while maintaining the same control quality. For this, a modified optimal control design is applied which uses an augmented design model.
Paper VI124-02.9
PDF · Video · Model Predictive Control with Time Varying Parameters for Plasma Shape and Current in a Tokamak
Mitrishkin, Yuri	M.V. Lomonosov Moscow State University
Kartcev, Nikolai	V.A. Trapeznikov Institute of Control Sciences of the Russian Ac
Korenev, Pavel	V.A. Trapeznikov Institute of Control Sciences
Patrov, Mikhail	Ioffe Physical Technical Institute of the Russian Academy of Sci
Keywords: Modeling and simulation of power systems, Control system design Abstract: Synthesis and modeling of the original time-varying magnetic control system for plasma shape and current on the base of the Model Predictive Control principle in a tokamak is considered. The study was done for the Globus-M2 tokamak (Ioffe Institute, St. Petersburg, RF). The system presented has a hierarchical structure with time-varying Model Predictive Controller at the top level and robust time-invariant controllers at the low level. The approach of adaptation of the plasma magnetic axis position to the shape parameters is used to resolve the contradiction between plasma position and shape. Numerical modeling of the control system synthesized has shown the efficiency of the proposed approach and a possibility to apply it in physical experiments.
Paper VI124-02.10
PDF · Video · Mixed-Integer Model Predictive Control for Large-Area MR-HIFU Hyperthermia in Cancer Therapy
Deenen, Daniel Andreas	Eindhoven University of Technology
Maljaars, Bert	Eindhoven University of Technology
Sebeke, Lukas	University Clinic of Cologne
de Jager, Bram	Technische Universiteit Eindhoven
Heijman, Edwin	Philips Research Europe, Department Minimally Invasive Healthcar
Grüll, Holger	University Hospital of Cologne
Heemels, Maurice	Eindhoven University of Technology
Keywords: Model predictive control of hybrid systems, Hybrid and switched systems modeling Abstract: In hyperthermia treatments, cancer tissue is heated to enhance the desired effects of radio- and chemotherapies. A powerful technology for noninvasive feedback-controlled hyperthermia is magnetic-resonance-guided high-intensity focused ultrasound (MR-HIFU), which enables fast and millimeter-accurate heating inside the body. Electronic beam steering allows for volumetric heating, but due to its limited steering range can only be used to treat small tumors. For the treatment of larger tumors, the transducer itself must be mechanically relocated as well. Due to system limitations, however, the admissible transducer positions must be restricted to a finite set that is chosen a priori. Moreover, non-negligible time is needed for transducer relocation, during which no heating is possible. In this paper, we present a mixed-integer model predictive controller that simultaneously optimizes over the power deposition by electronic beam steering – a continuous subproblem – as well as the mechanical transducer motions – a discrete subproblem. By incorporating model knowledge of the tissue’s thermal response and of the transducer carrier motion system into the predictive algorithm, the controller optimizes treatment temperature while respecting temperature and actuation constraints. The performance of the proposed feedback control setup is demonstrated by means of simulation.
Paper VI124-02.11
PDF · Video · Model Predictive Control of an Anaesthia Workstation Ventilation Unit
Männel, Georg	Universität Zu Lübeck
Siebert, Marlin	Universität Zu Lübeck
Kleinewalter, Dennis	Universität Zu Lübeck
Brendle, Christian	RWTH Aachen University
Rostalski, Philipp	Universität Zu Lübeck
Keywords: Predictive control, Control of constrained systems, Constrained control Abstract: Modern intensive care therapy as well as general anesthesia would not be possible, without respiratory support. Yet, unphysiological pressure levels and gas concentrations pose a serious risk to severely harm the patient. Advanced control schemes could improve the patient's safety and ensure the therapeutic success. Model predictive control (MPC) for instance allows to incorporate information about the patient at runtime through an internal model of the system, e.g. by using the lung compliance or airway resistance as model parameters. Furthermore, it can guarantee the satisfaction of constraints, which is useful, when considering physiological safety bounds. In this article we propose a two layered model-based control architecture for pressure controlled ventilation. The purpose of the lower layer is to approximately linearize the actuator dynamics, while the second layer implements a MPC controlling the pressure at the upper airways of the patient. The control architecture is implemented in an experimental setup, incorporating the ventilation unit of an anesthesia workstation. Initial results are presented, with the focus on the general feasibility of the chosen approach.
Paper VI124-02.12
PDF · Video · Optimal Control of Joint Multi-Virus Infection and Information Spreading
Taynitskiy, Vladislav	Saint Petersburg State University
Gubar, Elena	St. Petersburg State University
Fedyanin, Denis	ICS RAS
Petrov, Ilya	V. A. Trapeznikov Institute of Control Sciences of RAS Moscow, R
Zhu, Quanyan	New York University
Keywords: Optimal control theory, Complex systems, Stability of nonlinear systems Abstract: Nowadays, epidemic models provide an appropriate tool to describe the propagation of biological viruses in human or animal populations, rumors and misinformation in social networks, and malware in both computer and ad hoc networks. It is common that there are multiple types of malware infecting a network of computing devices, and different messages can spread over the social network. Information spreading and virus propagation are interdependent processes. To capture their independencies, we integrate two epidemic models into one holistic framework, known as the modified Susceptible-Warned-Infected-Recovered-Susceptible (SWIRS) model. The first epidemic model describes the information spreading regarding the risk of malware attacks and possible preventive procedures. The second one describes the propagation of multiple viruses over the network of devices. To minimize the impact of the virus spreading and improve the protection of the networks, we consider an optimal control problem with two types of control strategies: information spreading among healthy nodes and the treatment of infected nodes. We obtain the structure of optimal control strategies and study the condition of epidemic outbreaks. The main results are extended to the case of the network of two connected clusters. Numerical examples are used to corroborate the theoretical findings.
Paper VI124-02.13
PDF · Video · Energy-Efficiency-Oriented Gradient-Based Economic Predictive Control of Multiple-Chiller Cooling Systems
Nadales, J.M	Universidad De Sevilla
Ordonez, Joaquin G.	University of Seville
Coronel, Juan F.	University of Seville
Limon, Daniel	Universidad De Sevilla
Keywords: Linear multivariable systems, Process control, Energy systems Abstract: The growing use of air conditioning systems has become one of the main drivers of energy consumption in buildings. Many efforts are being made to develop new designs and control strategies to improve energy efficiency and minimise electricity consumption. In this work, a model for a case study of multiple-chiller-based cooling system is presented, based on surrogate models derived from information provided by manufacturers, and the study of the economic performance index. Then, an economic predictive control strategy will aim to operate the system optimizing the efficiency of the plant. Instead of the classical two-layer economic predictive control structure, where the reference to be tracked by the controller is given by a real-time optimizer, here we consider a single-layer control strategy where the gradients with respect to the manipulated inputs of the economic performance index are included in the cost function of the model predictive controller. The resulting optimization problem to be solved on line is a QP, which considerably eases the optimization problem, while also avoiding discrepancies between layers that could lead to loss of feasibility.
Paper VI124-02.14
PDF · Video · On Offset-Free Continuous Model Predictive Current Control of Permanent Magnet Synchronous Motors
Hammoud, Issa	Technical University of Munich
Xu, Ke	University Paderborn
Hentzelt, Sebastian	IAV GmbH
Oehlschlaegel, Thimo	IAV GmbH
Kennel, Ralph	Technical University of Munich
Keywords: Application of power electronics, Control system design Abstract: In this work, an offset-free continuous control set model predictive current control (CCS-MPCC) strategy for synchronous machines based on a slack formulation of the Primal-Dual Interior-Point method is proposed. A horizon of two steps is achieved within 100 microsecond sampling period. To account for robustness against model mismatch and uncertainty, an incremental formulation of the MPC problem is used to ensure zero steady-state tracking error. The proposed controller is compared with the state of the art Field Oriented Control with PI controllers (FOC-PI), with the Deadbeat Model Predictive Current Control (DB-MPCC), and with the latter controller combined with discrete integrators in the feedback loop (DB-MPCC-I). Experimental results on a 0.5 kW PMSM prove that the proposed CCS-MPCC has outperformed the state of the art control techniques typically used to control electrical machines.
Paper VI124-02.15
PDF · Video · Optimal Control and Inverse Optimal Control with Continuous Updating for Human Behavior Modeling
Petrosian, Ovanes	Saint-Petersburg State University
Inga, Jairo	Karlsruhe Institute of Technology (KIT)
Kuchkarov, Ildus	Saint-Petersburg State University
Flad, Michael	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Optimal control of hybride systems, Real-time optimal control, Regulation (linear case) Abstract: The theory of optimal control has received considerable attention to model motion behaviour or decision making of humans. Most approaches are based on a fixed (or infinite) time horizon which implies that all information is available at the beginning of the time interval. Nevertheless, it is reasonable to believe that the human uses information defined by a continuously moving information horizon at each time instant and adapts accordingly. Therefore, in this paper, we propose an optimal feedback control approach based on the paradigm of continuous updating. The model parameters which define individual human behaviour consist of the cost function parameters and the length of the information horizon, which can be identified via a corresponding inverse optimal control approach. We show the applicability of the approach with simulations of a potential application example of human behaviour identification from the point of view of a driving assistance system.

VI124-03
Differential or Dynamic Games	Regular Session
Chair: Mårtensson, Jonas	KTH Royal Institute of Technology
Co-Chair: Cappello, Domenico	Imperial College London
Paper VI124-03.1
PDF · Video · Strategic Bidding of Private Information for Dynamic LQ Networks under Moral Hazard
Wasa, Yasuaki	Waseda University
Uchida, Kenko	Waseda Univ
Keywords: Differential or dynamic games, Control problems under conflict and/or uncertainties, Large scale optimization problems Abstract: This paper investigates the whole system behavior caused by the influence of the agents' strategic behavior while utilizing their individual control and private information for a dynamic linear-quadratic (LQ) network in the presence of a principal-agent relationship. The principal aims at integrating agents' behavior into the socially optimal one based on private information bid by the agents. To avoid a moral hazard on agents' controls, the principal must give a reward to the agents. The reward induces the agents to choose their controls achieving the social objective under the true private information case, but the reward cannot prevent the strategic bidding of the agents' private information. Under this situation, the case is considered that all the agents minimize their net cost composed of their own private cost and the reward from the principal, which is called the strategic bidding problem under moral hazard. Then, the strategic bidding problem is formulated and the optimal design of the problem is analytically derived. Their effectiveness and limitations are also discussed through a simulation.
Paper VI124-03.2
PDF · Video · Approximate Nash Equilibrium Solutions of Linear Quadratic Differential Games
Cappello, Domenico	Imperial College London
Mylvaganam, Thulasi	Imperial College London
Keywords: Differential or dynamic games, Linear systems, Optimal control theory Abstract: It is well known that finding Nash equilibrium solutions of nonzero-sum differential games is a challenging task. Focusing on a class of linear quadratic differential games, we consider three notions of approximate feedback Nash equilibrium solutions and provide a characterisation of these in terms of matrix inequalities which constitute quadratic feasibility problems. These feasibility problems are then recast first as bilinear feasibility problems and finally as rank constrained optimisation problems, i.e. a class of static problems frequently encountered in control theory.
Paper VI124-03.3
PDF · Video · Robust Multi-Agent Differential Games for General Linear Systems with Model Uncertainties
Liu, Fei	Beihang University
Dong, Xiwang	Beihang University
Li, Qingdong	Beihang University
Ren, Zhang	Beihang University
Keywords: Differential or dynamic games, Linear systems, Robustness analysis Abstract: The problem of infinite-horizon multi-agent differential games is investigated, where the process can be modeled by a set of uncertain linear dynamics. The players are divided into two teams, one of which consists of a fixed number of follower agents while the other has one leader agent. The two teams constitute the adversaries. The multi-agent differential games can be transformed into a two-player game. The dynamics of the agents are subjected to norm-bound model uncertainties. Based on quadratic stabilization techniques, a set of saddle point strategies of the game is designed to stabilize the closed-loop multi-agent system, where the weighting matrices of the cost function are properly selected. For any given cost function, by modifying the solution of the linear quadratic differential game of the nominal model, the sufficient conditions are presented such that the stabilization of the system is guaranteed and the uncertainties are compensated. It is proved that the modified solution achieves optimality. A numerical example is given to verify the effectiveness of the theoretical results.
Paper VI124-03.4
PDF · Video · Distributing Potential Games on Graphs Part I. Game Formulation
El-Hawwary, Mohamed I.	KTH Royal Institute of Technology
Mårtensson, Jonas	KTH Royal Institute of Technology
Keywords: Differential or dynamic games, Networked systems Abstract: The paper presents the problem of distributing potential games over communication graphs. Suppose a potential game can be designed for a group of agents (players) where each has access to all others’ actions (strategies). The paper shows how to design a corresponding potential game for these agents if the full information assumption is replaced with communication over a network depicted by undirected graphs with certain properties. A state-based formulation for potential games is utilized. This provides degrees of freedom to handle the previous information limitation. Notions of Nash’s equilibria for the developed game (called here distributed potential game) are presented, and relations between these equilibria and those of the full information game are studied. In part II of the paper learning Nash equilibria for the newly developed game is studied. The development focuses on providing a way to utilize available algorithms of the full information game. The motivation for the results comes from a platoon matching problem for heavy duty vehicles. Utilizing the newly developed distributed game, recent results based on potential games can be extended, providing a basis for an on-the-go strategy where platoon matching on road networks can be solved locally.
Paper VI124-03.5
PDF · Video · Distributing Potential Games on Graphs Part II. Learning with Application to Platoon Matching
El-Hawwary, Mohamed I.	KTH Royal Institute of Technology
Mårtensson, Jonas	KTH Royal Institute of Technology
Keywords: Differential or dynamic games, Networked systems Abstract: In part I of the paper the problem of distributing potential games over undirected graphs was formulated. A restricted information potential game was designed using state-based formulation. Here, learning Nash equilibria for this game is studied. An algorithm is developed with mainly two phases, an estimation phase and a learning phase. The setting allows for available learning methods of the full information game to be directly incorporated in the learning phase. The result matches the outcome (i.e. converges to the same equilibria) of the full information game. In addition, the design takes into account considerations of convergence time, and synchrony of actions update. The developed distributed game and learning algorithm are used to solve a platoon matching problem for heavy duty vehicles. This serves two objectives. First, it provides a motivation for the presented gaming results. Second, the problem addressed can facilitate platoon matching where it provides a basis for an on-the-go strategy.
Paper VI124-03.6
PDF · Video · Robust Incentive Stackelberg Strategy for Markov Jump Delay Stochastic Systems Via Static Output Feedback
Mukaidani, Hiroaki	Hiroshima University
Ramasamy, Saravanakumar	Hiroshima University
Xu, Hua	Univ. of Tsukuba
Zhuang, Weihua	University of Waterloo
Keywords: Differential or dynamic games, Stochastic optimal control problems, Systems with time-delays Abstract: A static output feedback (SOF) incentive Stackelberg game (ISG) for a continuous-time Markov jump delay stochastic system (MJDSS) is discussed. The existence conditions on the SOF incentive Stackelberg strategy set are established in terms of the solvability of a set of higher-order cross-coupled stochastic algebraic Lyapunov-type equations (CCSALTEs). A classical Lagrange-multiplier technique is used to derive the CCSALTEs, thereby avoiding having to solve the bilinear matrix inequalities (BMIs), a well-known NP-hard problem in designing the SOF strategy. A heuristic algorithm is proposed to solve CCSALTEs such that robust convergence is attained by applying the Krasnoselskii-Mann (KM) iterative algorithm. A simple numerical example demonstrates the efficiency of the SOF incentive Stackelberg strategy.

VI124-04
Numerical Methods for Optimal Control	Regular Session
Chair: Stursberg, Olaf	University of Kassel
Co-Chair: Fujimoto, Kenji	Kyoto University
Paper VI124-04.1
PDF · Video · Approximate Dynamic Programming with Gaussian Processes for Optimal Control of Continuous-Time Nonlinear Systems
Beppu, Hirofumi	Kyoto University
Maruta, Ichiro	Kyoto University
Fujimoto, Kenji	Kyoto University
Keywords: Numerical methods for optimal control Abstract: In this paper, a new algorithm for realization of approximate dynamic programming (ADP) with Gaussian processes (GPs) for continuous-time (CT) nonlinear input-affine systems is proposed to infinite horizon optimal control problems. The convergence for the ADP algorithm is proven based on the assumption of an exact approximation, where both the cost function and the control input converge to their optimal values, that is, the solution to the Hamilton-Jacobi-Bellman (HJB) equation. The approximation errors, however, are unavoidable in almost every case of applications. In order to tackle the problem, the proposed algorithm is derived with the proof of convergence, where the cost function and the control input, which are both approximated, converge to those of the ADP as the number of data for GPs approaches infinity. A numerical simulation demonstrates the effectiveness of the proposed algorithm.
Paper VI124-04.2
PDF · Video · Efficient Solution of Distributed MILP in Control of Networked Systems
Liu, Zonglin	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Numerical methods for optimal control, Optimal control of hybride systems, Networked systems Abstract: This paper considers the distributed solution of Mixed-Integer Linear Programming (MILP) problems, a class of problems which is of interest, e.g., in optimization-based control of networked systems involving hybrid dynamics. For a larger number of subsystems, the high combinatorial complexity arising from the integer variables usually prohibits the use of centralized solution schemes, and thus requires distributed computational approaches. The proposed approach is inspired by results based on the Shapley-Folkman-Starr theorem, but it relaxes some conservative assumptions in order to enhance the computational efficiency. Numerical experiments for different MILP problems confirm the advantage of the proposed method with respect to computation times.
Paper VI124-04.3
PDF · Video · Numerical Methods for Construction of Value Functions in Optimal Control Problems with Infinite Horizon
Bagno, Alexander	Krasovskii Institute of Mathematics and Mechanics of Ural Branch
Tarasyev, Alexander M.	Krasovskii Institute of Mathematics and Mechanics of Ural Branch
Keywords: Numerical methods for optimal control, Optimal control theory, Differential or dynamic games Abstract: The article is devoted to the analysis of optimal control problems with infinite time horizon. These problems arise in economic growth models and in stabilization problems for dynamic systems. The problem peculiarity is a quality functional with an unbounded integrand which is discounted by an exponential index. The problem is reduced to an equivalent optimal control problem with the stationary value function. It is shown that the value function is the generalized minimax solution of the corresponding Hamilton–Jacobi equation. The boundary condition for the stationary value function is replaced by the property of the Holder continuity and the sublinear growth condition. A backward procedure on infinite time horizon is proposed for construction of the value function. This procedure approximates the value function as the generalized minimax solution of the stationary Hamilton–Jacobi equation. Its convergence is based on the contraction mapping method defined on the family of uniformly bounded and H¨older continuous functions. After the special change of variables the procedure is realized in numerical finite difference schemes on strongly invariant compact sets for optimal control problems and differential games.
Paper VI124-04.4
PDF · Video · Frequency-Domain Methods and Polynomial Optimization for Optimal Periodic Control of Linear Plants
Epperlein, Jonathan	IBM Research Europe
Bamieh, Bassam	Univ. of California at Santa Barbara
Keywords: Numerical methods for optimal control, Polynomial methods, Time-invariant systems Abstract: We consider the problem of periodic trajectory design for single-output systems which may be subject to periodic external disturbances. We show how trajectories optimizing a possibly nonquadratic and nonconvex polynomial performance objective can be found by using the frequency-domain description of the plant by converting the problem to a polynomial optimization problem (POP) in the Fourier coefficients of the external input signals. The method is suited for distributed-parameter systems, since the system transfer functions are not required to be rational; the computational complexity of the method depends on the order of the polynomial nonlinearities in the performance objective as well as the number of required harmonics, but is independent of the underlying system dimension.
Paper VI124-04.5
PDF · Video · Robust Time-Varying Continuous-Time Optimization with Pre-Defined Finite-Time Stability
Romero, Orlando	Rensselaer Polytechnic Institute
Benosman, Mouhacine	Mitsubishi Electric Research Laboratories (MERL)
Keywords: Numerical methods for optimal control, Real-time optimal control, Singularities in optimization Abstract: In this paper we propose a new family of continuous-time optimization algorithms based on discontinuous second order gradient optimization flows, with finite-time convergence guarantees to local optima, for locally strongly convex time-varying cost functions. To analyze our flows, we first extend a well-know Lyapunov inequality condition for finite-time stability, to the case of time-varying differential inclusions. We then prove the convergence of these second-order flows in finite-time. We show the performance of these flows on a time-varying quadratic cost and on the nonlinear time-varying Rosenbrock function.
Paper VI124-04.6
PDF · Video · A Sequential Algorithm for Sampled Mixed-Integer Optimization Problems
Chamanbaz, Mohammadreza	Singapore University of Technology and Design
Bouffanais, Roland	Singapore University of Technology and Design
Keywords: Large scale optimization problems, Convex optimization, Complex systems Abstract: In this paper, we propose a computationally efficient algorithm for solving mixed-integer sampled optimization problems involving a large number of constraints. The proposed algorithm has a sequential nature. Specifically, at each iteration of the algorithm, the feasibility of a candidate solution is verified for all the constraints involved in the sampled optimization problem and violating constraints are identified. As a second step, an optimization problem is formed whose constraint set involves the current basis---the minimal set of constraints defining the current candidate solution---and a limited number of the observed violating constraints. We prove that the algorithm converges to the optimal solution in finite time. Additionally, we establish the effectiveness of the proposed algorithm using mixed-integer linear, and quadratically constrained quadratic programming problems.
Paper VI124-04.7
PDF · Video · A Novel High Speed Multi-Objective Evolutionary Optimisation Algorithm
De Buck, Viviane	KU Leuven
Hashem, Ihab	KU Leuven
Van Impe, Jan F. M.	KU Leuven
Keywords: Evolutionary algorithms for optimal control Abstract: Multi-objective optimisation problems (MOOPs) consider multiple objectives simultaneously. Solving these problems does not render one unique solution but instead a set of equally optimal solutions, i.e., the Pareto front. The goal of solving a MOOP is to accurately and efficiently approximate the Pareto front. The use of evolutionary optimisation algorithms is widespread in this discipline. During each iteration, parent solutions are combined and mutated to create new offspring solutions. Both populations are subsequently combined and sorted. Only the N fittest solutions of the combined set are selected as the parent solutions for the subsequent iteration. The fitness of a solution is defined by its convergence to the Pareto front and its contribution to the overall solution diversity. Widely used evolutionary algorithms, like NSGA-II (Deb et al., 2002), use non-dominated sorting to assess the convergence of solutions and the concept of crowding distance to ensure a high solution diversity. Both concepts, however, require that all N solutions of the population are compared with all other (N-1) solutions for both aspects, and this for all M objectives. This results in a computational complexity of O(M N^2). In this contribution, a novel evolutionary algorithm is presented, boasting a significantly lower computational complexity of O(N log(N)). This is achieved by subdividing the feasible space into angular sections. Solutions are scored based on their distance from the current Utopia point and the overall crowdedness of their respective section. Sorting the population based on the attributed scores allows the selection of the N fittest solutions, without having to mutually compare them.

VI124-05
Optimal and Predictive Control of Hybrid Systems	Regular Session
Chair: Stursberg, Olaf	University of Kassel
Co-Chair: Negenborn, Rudy	Delft University of Technology
Paper VI124-05.1
PDF · Video · A Bi-Level Approach to MPC for Switching Nonlinear Systems
Ebrahim, Taher Sabry Elsayed Gomaa	Techniche Universität Dortmund
Engell, Sebastian	TU Dortmund
Keywords: Model predictive control of hybrid systems Abstract: In this paper, a nonlinear model predictive control scheme for switching dynamical systems is presented. The controller comprises of two layers of optimization. The upper layer is based on the embedding transformation technique, hence it does not require prior knowledge of the switching sequence. In particular, it provides the optimal relaxed switching sequence together with the optimal regulating inputs and the corresponding trajectories of the states. Within the lower layer, the integrality constraints are restored and a switching solution is recomputed to minimize the error with respect to the trajectories given from the upper-level optimization. The scheme is presented and the bounds of the integer approximation errors are evaluated together with brief recursive feasibility analysis. Simulation results of a tracking and an economics optimizing nonlinear MPC for a supermarket refrigerator system show the applicability and efficiency of the proposed approach.
Paper VI124-05.2
PDF · Video · Model Predictive Control with Memory-Based Discrete Search for Switched Linear Systems
Larsen, Rie B.	Delft University of Technology
Atasoy, Bilge	Delft University of Technology
Negenborn, Rudy	Delft University of Technology
Keywords: Stability and stabilization of hybrid systems, Model predictive control of hybrid systems Abstract: Controlling systems with both continuous and discrete actuators using model predictive control is often impractical, since mixed-integer optimization problems are too complex to solve sufficiently fast. This paper proposes a parallelizable method to control both the continuous input and the discrete switching signal for linear switched systems. The method uses ideas from Bayesian optimization to limit the computation to a predefined number of convex optimization problems. The recursive feasibility and stability of the method is guaranteed for initially feasible solutions. Results from simulated experiments show promising performances and computation times.
Paper VI124-05.3
PDF · Video · Mixed-Integer Model Predictive Control of Hybrid Impulsive Linear Systems
Bajcinca, Naim	University of Kaiserslautern
Pedrosa, Matheus	University of Kaiserslautern
Yfantis, Vassilios	Technische Universität Kaiserslautern
Keywords: Model predictive control of hybrid systems, Hybrid and switched systems modeling, Optimal control of hybrid systems Abstract: We devise a model predictive control algorithm for impulsive linear systems with autonomous flow dynamics and controlled jumps. Thereby the moments of jumps are not fixed, but rather considered as decision variables. To this end, the complete system dynamics is formulated as a mixed-logical dynamical system after an appropriate discretization step. The resulting optimization problem contains both discrete and continuous decision variables, giving rise to a mixed-integer programming problem. The objective of the optimization is to steer the states into a target set. The stability is addressed through an appropriate cost function together with invariance conditions, as well as by introducing terminal constraints which are only enforced within a certain distance to the target set, thus, providing a trade-off between guaranteed convergence to the target set and computational complexity.
Paper VI124-05.4
PDF · Video · Hierarchical MPC of Hybrid Power Systems Based on Fuzzy Discrete Abstraction
Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Xia, Jiajun	East China University of Science and Technology
Keywords: Intelligent control of power systems, Constraint and security monitoring and control, Modeling and simulation of power systems Abstract: A hierarchical control approach is proposed for hybrid systems with discrete-valued input based on fuzzy discrete abstraction and model predictive control (MPC) scheme. The system is firstly abstracted to a discrete event system (DES). Then a higher-level supervisor is designed to provide the control input alphabet for each discrete state, while a fuzzy model predictive controller is developed for the original system in the lower level. Simulation results of emergency frequency control of electric power systems are provided to show the superior frequency recovery characteristic of the proposed hierarchical control scheme in comparison with two existing control methods.
Paper VI124-05.5
PDF · Video · On the LQ Based Stabilization for a Class of Switched Dynamic Systems
Ortiz Castillo, Marco Antonio	Centro De Investigación Y De Estudios Avanzados Del IPN (CINVEST
Bonilla, Moises E.	CINVESTAV-IPN
Loiseau, Jean Jacques	Lab. Sciences Du Numérique De Nantes - LS2N CNRS
Malabre, Michel	Ls2n, Umr Cnrs 6004
Azhmyakov, Vadim	Universidad EAFIT
Keywords: Optimal control of hybride systems, Stability of hybrid systems, Descriptor systems Abstract: This paper deals with the stabilization of a class of time-dependent linear autonomous systems with a switched structure. For this aim, the switched dynamic system is modeled by means of an implicit representation combined with a Linear-Quadratic (LQ) type control design. The proposed control design stabilizes the resulting system for all of the possible realizations of its locations. In order to solve the Algebraic Riccati Equation (ARE) associated with the LQ control strategy one only needs the knowledge of the algebraic structure related to the switched system. We finally prove that the proposed optimal LQ type state feedback stabilizes the closed-loop switched system no matter which location is active. The proposed theoretical approaches are illustrated by a numerical example.
Paper VI124-05.6
PDF · Video · Generalized H_2 Control with Transients for Linear Hybrid Systems
Biryukov, Ruslan	Architecture and Civil Engineering State University
Keywords: Optimal control of hybride systems, Linear systems Abstract: This paper considers linear time-varying hybrid systems and introduces a notion of the finite-horizon generalized H_2 norm with transients. It is defined as the worst-case peak value of the output in response to uncertain initial states and external disturbances. Such a measure represents the induced operator norm from L_2 to L_infty because the peak value of the vector signal is considered as its generalized L_infty norm. This approach allows to characterize the generalized H_2 norm in terms of both the difference Lyapunov equation and difference linear matrix inequalities (DLMIs). By using the derived characterization the optimal control and Pareto optimal controls are synthesized minimizing the finite-horizon generalized H_2 norm with transients. Finally, an example is given to illustrate the proposed technique.
Paper VI124-05.7
PDF · Video · On Optimal Control of Flat Hybrid Automata
Zahn, Frederik	Karlsruher Institut Für Technologie
Kleinert, Tobias	BASF SE
Hagenmeyer, Veit	Karlsruhe Institute of Technology
Keywords: Optimal control of hybrid systems, Hybrid and switched systems modeling Abstract: Recently, Flat Hybrid Automata (FHA) were introduced as a new model class of hybrid systems. In order to answer the evident question of an optimal operation of the new class of FHA, a well-posed optimization problem definition for FHA is presented. This problem formulation also includes costs on discrete--state transitions and switching actions. We present a solution for a reduced problem: FHA with autonomous switching. For these, a new algorithm is introduced which solves the optimal control problem. The application of this optimization algorithm is shown with an electrical network example.
Paper VI124-05.8
PDF · Video · Robust Point-To-Set Control of Hybrid Systems with Uncertainties Using Constraint Tightening
Liu, Zonglin	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Optimal control of hybride systems, Disturbance rejection, Robust control Abstract: This paper proposes a solution to the problem of computing optimal point-to-set control strategies for hybrid systems with mixed inputs and uncertainties in the continuous-valued dynamics as well as the reset functions. The solution is based on the idea to account for the uncertainties by tightening the guard and invariant sets, and thus construct a substitute hybrid automaton with deterministic transition dynamics. It can be ensured that a solution for this new model also solves the problem for the original system, i.e. the latter is robustly transferred between initial point and target set.

VI124-06
Optimal Control Theory	Regular Session
Chair: Pereira, Fernando Lobo	Porto University
Co-Chair: Yamashita, Yuh	Hokkaido University
Paper VI124-06.1
PDF · Video · Approximate Time-Optimal Control Considering System Bandwidth and Saturation
Yang, Yunjie	Tsinghua University
He, Yang	Tsinghua University
Zhu, Jihong	Tsinghua University
Keywords: Control problems under conflict and/or uncertainties, Optimal control theory, Systems with saturation Abstract: Future aircraft requires its servo actuator systems possess high dynamic and high precision capability. Due to direct optimal control methods are difficult to balance system dynamics and precision, a multi-mode proximate time-optimal control (PTO) law is proposed in this paper. First, the characteristic model, which expresses the input-output feature of the actuator as a first order link series an integrator, is established. Then, with the phase plane as the analysis tool, the switching zone and linear zone of the PTO control law are constructed. When the system state is outside of both zones, the bang-bang optimal scheme is adopted to achieve rapidity. And when the system state enters the switching zone, the bang-bang suboptimal scheme is developed to avoid oscillations or even limit cycles. Proportional-derivative (PD) scheme is applied in the linear zone to obtain a determinately local asymptotic stability around the origin. Numerical simulations are carried out to corroborate the advantages of the PTO control law.
Paper VI124-06.2
PDF · Video · Optimal Regulators for Nonlinear Systems with Incompatible State and Input Cost Functions
Yamashita, Yuh	Hokkaido University
Sakai, Yuta	Hokkaido University
Kobayashi, Koichi	Hokkaido University
Keywords: Optimal control theory, Asymptotic stabilization Abstract: When a desired state is different from the state at which input cost becomes zero, a naive application of the optimal control methodology may lead an ill-posed problem. In this study, we propose a new method where the input cost is slightly changed so that the optimal control problem is well defined. The method can realize an energy-efficient control, which considers the actual energy consumption. We also confirm the effectiveness of the proposed method via a case study of an example.
Paper VI124-06.3
PDF · Video · Gradient-Bounded Dynamic Programming with Submodular and Concave Extensible Value Functions
Lebedev, Denis	University of Oxford
Goulart, Paul J.	University of Oxford
Margellos, Kostas	University of Oxford
Keywords: Dynamic Resource Allocation, Data-Driven Decision Making, Control in economics Abstract: We consider dynamic programming problems with finite, discrete-time horizons and prohibitively high-dimensional, discrete state-spaces for direct computation of the value function from the Bellman equation. For the case that the value function of the dynamic program is concave extensible and submodular in its state-space, we present a new algorithm that computes deterministic upper and stochastic lower bounds of the value function similar to dual dynamic programming. We then show that the proposed algorithm terminates after a finite number of iterations. Finally, we demonstrate the efficacy of our approach on a high-dimensional numerical example from delivery slot pricing in attended home delivery.
Paper VI124-06.4
PDF · Video · Necessary Conditions of Optimality for a Time-Optimal Bi-Level Sweeping Control Problem
Khalil, Nathalie	Faculty of Engineering, University of Porto
Pereira, Fernando Lobo	Porto University
Keywords: Optimal control theory, Control of constrained systems Abstract: This article concerns a simple instance of an optimal control problem paradigm combining bi-level optimization with sweeping processes, initially investigated in a previous work of the authors. This class of problems arises for instance in the structured crowd motion control problems in a confined space. We propose a specific class of time-optimal bi-level problem with sweeping process dynamics represented in terms of a truncated normal cone at the lower level. We establish the necessary optimality conditions of the Maximum Principle of Pontryagin type in the Gamkrelidze's form. Two techniques are at the core of the analysis: a) the smooth approximation of the low level sweeping control system, thereby avoiding the absence of Lipschitzianity resulting from the sweeping process and, b) the flattening of the bi-level structure to a single level problem by using a exact penalization technique involving the value function of the low level problem to incorporate its inherent constraint in the bi-level structure. Necessary optimality conditions are applied to the resulting approximate flattened problem, and the main result of this article is obtained by passing to the limit.
Paper VI124-06.5
PDF · Video · On the Problems of Optimal and Minmax Type Control under Vector Criteria
Komarov, Yury	Lomonosov MSU
Kurzhanski, Alexander B.	Moscow State University and Univ. of California, Berkeley
Keywords: Optimal control theory, Control problems under conflict and/or uncertainties Abstract: The topic of this paper is to solve two types of problems in controlled system dynamics formulated in terms of vector-valued criteria whose application depends on the type of ordering for the scalar participants of each such criterion. The first problem is that of optimal control under vector criterion with ordering of the Pareto type. The problem is to indicate the dynamics of the Pareto front. The second is that of finding vector-valued controls of the minmax type. Here the internal problem of dynamic maximization is due to a vector criterion with given type of ordering while the external problem is that of vector-valued dynamic minimization under another type of ordering. A similar situation arises for controls of the maxmin type. The paper indicates a variety of solution formulas that describe vector-valued dynamic interrelations for the problems of minmax and maxmin. The solutions are reached by using the Hamiltonian formalism. The suggested vector type of control problem settings are motivated by structure of system dynamics for physical motions, economics, finance, environmental models and related issues. Examples of applications are indicated.
Paper VI124-06.6
PDF · Video · Lossless Convexification of Optimal Control Problems with Semi-Continuous Inputs
Malyuta, Danylo	University of Washington
Acikmese, Behcet	University of Washington
Keywords: Optimal control theory, Convex optimization, Optimal control of hybride systems Abstract: This paper presents a novel one-shot convex optimization method for finding globally optimal solutions of a class of mixed-integer non-convex optimal control problems. We consider problems with non-convex constraints that restrict the input norms to be either zero or lower- and upper-bounded. The non-convex problem is relaxed to a convex one whose optimal solution is proved to be optimal almost everywhere for the original problem, a procedure known as lossless convexification. The solution relies on second-order cone programming and demonstrates that a meaningful class of optimal control problems with binary variables can be solved reliably and in polynomial time. A rocket landing example with a coupled thrust-gimbal constraint corroborates the effectiveness of the approach.
Paper VI124-06.7
PDF · Video · A Geometric Characterization of the Slow Space of the Hamiltonian System Arising from the Singular LQR Problem
Qais, Imrul	Indian Institute of Technology Bombay
Pal, Debasattam	Indian Institute of Technology Bombay
Bhawal, Chayan	Indian Institute of Technology Guwahati
Keywords: Optimal control theory, Descriptor systems, Linear multivariable systems Abstract: In this paper we first characterize the slow space of a given state-space system. We provide this characterization in terms of an eigenspace of the corresponding Rosenbrock matrix pair. We also characterize the "good" slow space in terms of a stable eigenspace of the Rosenbrock matrix pair. Moreover, we show how the dimensions of these subspaces can be calculated from the determinant of the Rosenbrock matrix pencil. Then, we apply these results to the Hamiltonian system arising from the singular linear quadratic regulator (LQR) problem and explore a few interesting properties of the good slow space of this Hamiltonian system. Finally, we provide a feedback law to achieve the smooth optimal solutions.
Paper VI124-06.8
PDF · Video · On Linear Quadratic Regulation of Linear Port-Hamiltonian Systems
Caballeria, Javier	Universidad Técnica Federico Santa María
Vargas, Francisco J.	Universidad Técnica Federico Santa María
Ramirez, Hector	Universidad Federico Santa Maria
Wu, Yongxin	ENSMM / Université Bourgogne Franche-Comté
Le Gorrec, Yann	FEMTO-ST, ENSMM
Keywords: Optimal control theory, Passivity-based control, Time-invariant systems Abstract: The linear quadratic regulator is a widely used and studied optimal control technique for the control of linear dynamical systems. It consists in minimizing a quadratic cost functional of the states and the control inputs by the means of solving a linear Riccati equation. The effectiveness of the linear quadratic regulator relies on the cost function parameters hence, an appropriate selection of these parameters is of mayor importance in the control design. Port-Hamiltonian system modelling arise from balance equations, interconnection laws and the conservation of energy. These systems encode the physical properties in their structure matrices, energy function and definition of input and output ports. This paper establishes a relation between two classical passivity based control tools for port-Hamiltonian systems, namely control by interconnection and damping injection, with the linear quadratic regulator. These relations allow then to select the weights of the quadratic cost functional on the base of physical considerations. A simple RLC circuit has been used to illustrate the approach.
Paper VI124-06.9
PDF · Video · Bounds on Time-Optimal Concatenations of Arcs for Two-Input Driftless 3D Systems
Sigalotti, Mario	Inria
Keywords: Optimal control theory, Singularities in optimization Abstract: We study a driftless system on a three-dimensional manifold driven by two scalar controls. We assume that each scalar control has an independent bound on its modulus and we prove that, locally around every point where the controlled vector fields satisfy some suitable nondegeneracy Lie bracket condition, every time-optimal trajectory has at most five bang or singular arcs. The result is obtained using first- and second-order necessary conditions for optimality.
Paper VI124-06.10
PDF · Video · Investigation of Conditions for Non-Degeneracy and Normality in Control Problems with Equality and Inequality State Constraints
Arutyunov, Aram V.	Peoples Friendship Univ.of Russia
Karamzin, Dmitry	Federal Research Center "Computer Science and Control" of the Ru
Pereira, Fernando Lobo	Porto University
Keywords: Optimal control theory, Singularities in optimization, Constrained control Abstract: This work aims to investigate conditions for normality and non-degeneracy of the maximum principle for general state-constrained optimal control problems in which the state constraints are given by equalities and inequalities. Non-degeneracy is proved under a regularity condition formulated in terms of the limiting normal cone to the feasible control set. The same regularity condition implies normality of the maximum principle if one of the end-points is free.
Paper VI124-06.11
PDF · Video · On the Structure of the Solution of Continuous-Time Algebraic Riccati Equations with Closed-Loop Eigenvalues on the Imaginary Axis
Ntogramatzidis, Lorenzo	Curtin University
Arumugam, Vishnuram	Curtin University
Ferrante, Augusto	University of Padova
Keywords: Optimal control theory, Time-invariant systems Abstract: This paper proposes a decomposition of the continuous-time algebraic Riccati equation aimed at eliminating the problem of the presence of closed-loop eigenvalues on the imaginary axis. In particular, we show that it is possible to parameterize the the entire set of solutions of the given Riccati equation in terms of the solutions of a reduced-order Riccati equation, which is associated to a Hamiltonian matrix with no eigenvalues on the imaginary axis, and some free parameters arising from the presence of imaginary eigenvalues of the Hamiltonian matrix.
Paper VI124-06.12
PDF · Video · On Optimal Control of Discounted Cost Infinite-Horizon Markov Decision Processes under Local State Information Structures
Peng, Guanze	New York University
Veeraruna, Kavitha	IIT Bombay
Zhu, Quanyan	New York University
Keywords: Stochastic hybrid systems Abstract: This paper investigates a class of optimal control problems associated with Markov processes with local state information. The decision-maker has only a local access to a subset of a state vector information as often encountered in decentralized control problems in multi-agent systems. Under this information structure, part of the state vector cannot be observed. We leverage ab initio principles and find a new form of Bellman equations to characterize the optimal policies of the control problem under local information structures. The dynamic programming solutions feature a mixture of dynamics associated unobservable state components and the local state-feedback policy based on the observable local information. We further characterize the optimal local-state feedback policy using linear programming methods. To reduce the computational complexity of the optimal policy, we propose an approximate algorithm based on virtual beliefs to find a sub-optimal policy. We show the performance bounds on the sub-optimal solution and corroborate the results with numerical case studies.
Paper VI124-06.13
PDF · Video · Tangency Property and Prior-Saturation Points in Planar Minimal Time Problems
Bayen, Terence	University of Montpellier 2
Cots, Olivier	Toulouse Univ., INP-ENSEEIHT-IRIT
Keywords: Optimal control of hybrid systems Abstract: In this paper, we address properties of the minimal time synthesis for control-affine-systems in the plane involving a saturation point for the singular control. First, we provide sufficient conditions on the data ensuring occurence of a prior-saturation point. Then, we show that the bridge, i.e., the optimal bang arc issued from the singular locus at this point) is tangent to the switching curve at the prior-saturation point. We illustrate these results on a fed-batch model in bioprocesses.
Paper VI124-06.14
PDF · Video · Optimal Control of Trajectories Ensemble for a Class of Discrete Dynamic Systems
Golovkina, Anna	Saint Petersburg State University
Ovsyannikov, Dmitri	Saint Petersburg State University
Keywords: Optimal control of hybrid systems, Discrete event modeling and simulation Abstract: The control problems concerning the manipulation of system trajectories ensembles have received increased attention in recent years. This paper considers a class of nonlinear discrete-time systems with additive control and develops a systematic method to design optimal controls that steer an ensemble from an initial state to a terminal one minimizing the cost functional that estimates ensemble dynamics in average. Necessary optimality condition as well as functional variation are constructed. These allow building different iterative or gradient-based methods to minimize the desired control cost criterion. The motivation for this study originates from the optimization problem of advanced fuel cycle in accelerator driven system. The grand challenge here remains to address the coupled problem over the multiple cycles in the planning horizon taking into account manufacturing and nuclear data uncertainties. A brief description of physical problem and corresponding mathematical model for optimization of advanced fuel cycle in terms of the proposed approach are presented.

VI124-07
Predictive Control	Regular Session
Chair: Stoica Maniu, Cristina	CentraleSupélec/Laboratoire De Signaux Et Systèmes
Co-Chair: Chen, Hong	Tongji University
Paper VI124-07.1
PDF · Video · Distributed Model Predictive Control with Asymmetric Adaptive Terminal Sets for the Regulation of Large-Scale Systems
Aboudonia, Ahmed	ETH Zurich
Eichler, Annika	DESY
Lygeros, John	ETH Zurich
Keywords: Predictive control Abstract: In this paper, a novel distributed model predictive control (MPC) scheme with asymmetric adaptive terminal sets is developed for the regulation of large-scale systems with a distributed structure. Similar to typical MPC schemes, a structured Lyapunov matrix and a distributed terminal controller, respecting the distributed structure of the system, are computed offline. However, in this scheme, a distributed positively invariant terminal set is computed online and updated at each time instant taking into consideration the current state of the system. In particular, we consider ellipsoidal terminal sets as they are easy to compute for large-scale systems. The size and center of these terminal sets, together with the predicted state and input trajectories, are considered as decision variables in the online phase. The efficacy of the proposed scheme is illustrated in simulation by comparing it to a recent distributed MPC scheme with adaptive terminal sets.
Paper VI124-07.2
PDF · Video · Periodic Set Invariance As a Tool for Constrained Reference Tracking
Soyer, Martin	CentraleSupélec, Renault
Olaru, Sorin	CentraleSupelec
Ampountolas, Konstantinos	University of Thessaly
Scialanga, Sheila	University of Glasgow
Fang, Zhou	Renault
Keywords: Predictive control, Constrained control, Tracking Abstract: This paper explores the concept of periodic invariance and its use for trajectory tracking problems subject to state and input constraints, offering important computational advantages. In principle, traditional techniques based on receding horizon optimization are computationally expensive due to long prediction and optimization horizons, and number of control and state constraints in a constrained control problem. Their complexity is further affected by additional constraints needed to ensure recursive feasibility via a controllable invariant set. Practically, such invariant sets are difficult to obtain off-line and use them on-line. To overcome this problem, this paper suggests to employ periodic invariant sets as a simple set-theoretic tool for constrained reference tracking problems.
Paper VI124-07.3
PDF · Video · Anomaly-Handling in Lyapunov-Based Economic Model Predictive Control Via Empirical Models
Durand, Helen	Wayne State University
Keywords: Process control, Nonlinear predictive control, Chemical engineering Abstract: A question that faces data-driven autonomous systems is verification that they will perform in a safe manner despite changes in the environment on which they act over time or incomplete knowledge of the system model. This work analyzes closed-loop stability of nonlinear systems under Lyapunov-based economic model predictive control (LEMPC) with data-driven models in the case where it is desirable to have the ability to detect when the data-driven model is or becomes insufficiently accurate for maintaining the closed-loop state in an expected region of state-space. Implications of the results for false sensor measurement cyberattacks seeking to impact the fidelity of models derived from model identification are discussed and illustrated through a chemical process example.
Paper VI124-07.4
PDF · Video · Dynamic Programming for Explicit Linear MPC with Point-Symmetric Constraints
Mitze, Ruth	Ruhr-Universität Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Predictive control, Control of constrained systems, Parametric optimization Abstract: The solution to a constrained linear-quadratic optimal control problem can be expressed as a set of active sets. We recently proposed an algorithm that constructs this set by iteratively increasing the horizon. In the present paper, we improve this algorithm for problems with point-symmetric constraints. This is done by showing that such problems can be reformulated as symmetric quadratic programs and by exploiting properties of symmetric quadratic programs in the algorithm. A considerable reduction of the computational effort can be achieved, which will be demonstrated with an example.
Paper VI124-07.5
PDF · Video · Data-Driven Tracking MPC for Changing Setpoints
Berberich, Julian	University of Stuttgart
Köhler, Johannes	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Allgower, Frank	University of Stuttgart
Keywords: Predictive control, Data-based control, Tracking Abstract: We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system parametrization to predict future trajectories based on behavioral systems theory. The control objective is tracking of a given input-output setpoint. We prove that this setpoint is exponentially stable for the closed loop of the proposed MPC, if it is reachable by the system dynamics and constraints. For an unreachable setpoint, our scheme guarantees closed-loop exponential stability of the optimal reachable equilibrium. Moreover, in case the system dynamics are known, the presented results extend the existing results for model-based setpoint tracking to the case where the stage cost is only positive semidefinite in the state. The effectiveness of the proposed approach is illustrated by means of a practical example.
Paper VI124-07.6
PDF · Video · Computing Impulsive Equilibrium Sets with Respect to Target Zone for Linear Impulsive Systems
Louembet, Christophe	Universite De Toulouse
Gonzalez, Alejandro, Hernan	Institute of Technological Development for the ChemicalIndustry
Sanchez, Ignacio Julián	Conicet - Unl
Keywords: Predictive control, Discontinuous control, Linear systems Abstract: Linear impulsive control systems are convenient to formulate a venue of real-life problems, from diseases treatment to aerospace guidance. To take into account that the origin is the only formal equilibrium of such systems while usual control objective consist in stabilizing a desired target region that exclude it, a different concept of equilibrium -- which includes periodic/orbital trajectories -- has been defined. This work presents a new characterization of the equilibrium sets respecting this target region for linear impulsive systems. Based on the Lucasz-Markov theorem a tractable and non conservative description is obtained. Furthermore, to assess this description, the constrained equilibrium set is explicitly used in the formulation of a model-based controller.
Paper VI124-07.7
PDF · Video · Constrained Linear State Signal Shaping Model Predictive Control for Harmonic Compensation in Power Systems
Weihe, Kathrin	HAW Hamburg
Cateriano Yáñez, Carlos	Fraunhofer Institute for Silicon Technology
Pangalos, Georg	Fraunhofer Institute for Silicon Technology ISIT
Lichtenberg, Gerwald	Hamburg University of Applied Sciences
Keywords: Predictive control, Industrial applications of optimal control, Power systems Abstract: For signal shaping problems, in contrast to reference following problems, a possibility is to make use of the signals shape, described by a difference equation. In order to do this, a shape class is defined, giving a measure on how close to a specific shape a signal is. The shape class defines the weighting matrices of the standard quadratic cost function of a model predictive controller. The optimization problem is solved with constraints using a standard quadratic program solver. An application example shows the applicability for active power filters.
Paper VI124-07.8
PDF · Video · Stability and Performance in Transient Average Constrained Economic MPC without Terminal Constraints
Rosenfelder, Mario	University of Stuttgart
Köhler, Johannes	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Predictive control, Nonlinear predictive control, Constrained control Abstract: In this paper, we investigate system theoretic properties of transient average constrained economic model predictive control (MPC) without terminal constraints. We show that the optimal open-loop solution passes by the optimal steady-state for consecutive time instants. Using this turnpike property and suitable controllability conditions, we provide closed-loop performance bounds. Furthermore, stability is proved by combining the rotated value function with an input-to-state (ISS) Lyapunov function of an extended state related to the transient average constraints. The results are illustrated with a numerical example.
Paper VI124-07.9
PDF · Video · A Hierarchical MPC Scheme for Ensembles of Hammerstein Systems
Petzke, Felix	Technische Universität Chemnitz
Farina, Marcello	Politecnico Di Milano
Streif, Stefan	Technische Universität Chemnitz
Keywords: Large scale optimization problems, Nonlinear predictive control, Model reduction Abstract: Hierarchical control approaches have been one of the elective methods for the optimal control of large-scale systems in the last decades. In (Petzke et al., 2018) we presented a multirate hierarchical MPC scheme for linear systems, with remarkable flexibility and scalability properties. In this paper we extend the former approach to ensembles of Hammerstein systems and we complement the method by proposing a suitable high-level optimizer. The theoretical properties are discussed in the light of the theoretical properties of the former method. Lastly, an example case study is presented to show the effectiveness of the proposed method.
Paper VI124-07.10
PDF · Video · A Modifier-Adaptation Approach to the One-Layer Economic MPC
Vergara-Dietrich, Jose Dolores	Universidade Tecnológica Federal Do Paraná
Mirasierra, Victor	Universidad De Sevilla
Ferramosca, Antonio	CONICET
Normey-Rico, Julio Elias	Universidade Federal De Santa Catarina
Limon, Daniel	Universidad De Sevilla
Keywords: Model predictive control of hybrid systems, Nonlinear adaptive control Abstract: In this paper, we address the problem of modeling error in economically optimal control. A single layer controller is proposed that integrates the economical part of the Real Time Optimization (RTO), the dynamic part of the Model Predictive Control (MPC) and the Modifier Adaptation strategy (MA), resulting in a controller with the following characteristics: a) recursive feasibility guarantee of the controller ; b) asymptotic closed-loop stability for any change in the economic cost function; c) convergence guarantee to the economic optimum of the real plant (offset-free) for any change in the cost function of the controller; and d) simple implementation of the controller. We show the behaviour of the proposal by means of a motivating example that highlights the performance of the proposed algorithm
Paper VI124-07.11
PDF · Video · Actuation Attacks on Constrained Linear Systems: A Set-Theoretic Analysis
Trodden, Paul	University of Sheffield
Maestre, Jose M.	University of Seville
Ishii, Hideaki	Tokyo Institute of Technology
Keywords: Control problems under conflict and/or uncertainties, Constrained control, Robustness analysis Abstract: This paper considers a constrained discrete-time linear system subject to actuation attacks. The attacks are modelled as false data injections to the system, such that the total input (control input plus injection) satisfies hard input constraints. We establish a sufficient condition under which it is not possible to maintain the states of the system within a compact state constraint set for all possible realizations of the actuation attack. The developed condition is a simple function of the spectral radius of the system, the relative sizes of the input and state constraint sets, and the proportion of the input constraint set allowed to the attacker.
Paper VI124-07.12
PDF · Video · Chance-Constrained MPC for Voronoi-Based Multi-Agent System Deployment
Chevet, Thomas	Laboratoire Des Signaux Et Systèmes, Université Paris-Saclay, CN
Stoica Maniu, Cristina	CentraleSupélec/Laboratoire De Signaux Et Systèmes
Vlad, Cristina	Laboratoire Des Signaux Et Systèmes, CentraleSupélec
Zhang, Youmin	Concordia University
Camacho, Eduardo F.	University of Seville
Keywords: Linear systems, Time-invariant systems, Predictive control Abstract: This paper proposes a new chance-constrained model predictive control (CCMPC) algorithm with state estimation applied to the two-dimensional deployment of a multi-vehicle system where each agent is subject to process noise and measurement noise. The bounded convex area of deployment is partitioned into time-varying Voronoi cells defined by the position of each agent. Due to the presence of noise in the system model, stochastic constraints appear in the model predictive control problem. The proposed decentralized robust CCMPC algorithm drives the multi-agent system into a static Chebyshev configuration where each agent lies on the Chebyshev center of its Voronoi cell. Simulation results show the effectiveness of the proposed control strategy on a fleet of quadrotors subject to wind perturbations and measurement noise.
Paper VI124-07.13
PDF · Video · Path Tracking and Coordination Control of Multi-Agent Systems: A Robust Tube-Based MPC Scheme
D'Alfonso, Luigi	University of Calabria, UNICAL
Fedele, Giuseppe	Università Della Calabria
Franze, Giuseppe	Universita' Della Calabria
Keywords: Distributed robust controller synthesis, Predictive control, Control of constrained systems Abstract: This paper addresses the reference tracking problem subject to formation constraints for a group of unmanned vehicles. A scheme based on receding horizon control ideas has been developed, whose the main feature consists in avoiding the need to explicitly impose non-convex constraints in the underlying optimization problem. The latter has been achieved by exploiting the properties provided by a novel description of the kinematic evolution when the agents are organized as a swarm. Numerical simulations on a team of five agents described by double integrator models are presented to show the effectiveness of the proposed control architecture.

VI124-08
Real-Time and Efficient Predictive Control	Regular Session
Chair: Alamo, Teodoro	Universidad De Sevilla
Co-Chair: Ohtsuka, Toshiyuki	Kyoto University
Paper VI124-08.1
PDF · Video · Linear Direct Transcription for Nonlinear Constrained Optimal Control Problems
Wang, Zhong	Northwestern Ploytechnical University
Li, Yan	Northwestern Polytechnical University
Keywords: Numerical methods for optimal control, Real-time optimal control, Optimal control theory Abstract: Nonlinear optimal control problems are frequently transformed into nonlinear programming problems for which the solving process is generally time-consuming. In this paper, a linear direct transcription method is proposed for nonlinear optimal control problems. Taking advantage of the state-dependent coefficient parameterization method and the spectral discretization method, the nonlinear optimal control problem is successively linearized and turned into a sequence of efficiently solvable mixed linear complementarity problems. The proposed direct transcription method is linear in two ways: the nonlinear system is linearized using state-dependent coefficient parameterization; the resulting quadratic programming problem is converted into a mixed linear complementarity problem. Simulations are implemented, and numerical results verify the effectiveness and efficiency of the proposed method.
Paper VI124-08.2
PDF · Video · PLC Implementation of a Real-Time Embedded MPC Algorithm Based on Linear Input/output Models
Krupa, Pablo	University of Seville
Saraf, Nilay	ODYS S.r.l., IMT School for Advanced Studies Lucca
Limon, Daniel	Universidad De Sevilla
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Predictive control, Digital implementation, Disturbance rejection (linear case) Abstract: How to efficiently implement Model Predictive Control (MPC) in embedded systems is a topic that is attracting a lot of research recently, due to its impact in practical applications. Implementing MPC in industrial Programmable Logic Controllers (PLCs) is of particular interest due to their widespread prevalence in the industry in comparison with other embedded systems, such as FPGAs or microcontrollers. In this paper, we present a PLC implementation of real-time embedded MPC for multivariable systems described by linear time-invariant input/output models subject to upper and lower bounds on input and output variables. The MPC algorithm uses a recently developed primal active-set method for bounded-variable least-squares problems. We highlight and address some crucial challenges that arise in implementing the MPC algorithm in a PLC. Possible extensions of the proposed methods are presented along with hardware-in-the-loop simulation results of controlling a nonlinear multivariable system using a real industrial PLC.
Paper VI124-08.3
PDF · Video · Cloud-Based Model Predictive Control with Variable Horizon
Skarin, Per	Lund University
Eker, Johan	Ericsson Research / Lund University
Arzen, Karl-Erik	Lund Inst. of Technology
Keywords: Predictive Control, Industrial applications of optimal control, Real-time optimal control Abstract: A novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the proposed method can be generalized to implement robust and scalable controllers that benefit from cloud technology. We show results from two horizon selection strategies, service degradation and connectivity issues.
Paper VI124-08.4
PDF · Video · Accelerated Model Predictive Control Using Restricted Quadratic Programming
Maitland, Anson	University of Waterloo
McPhee, John	Professor, University of Waterloo
Keywords: Predictive control, Numerical methods for optimal control, Real-time optimal control Abstract: We present a method to reduce the computational burden of solving a sequence of convex quadratic programs (QPs). By determining offline what search space is most important, we can restrict our online problem to that subspace, reducing the dimension and computational cost of the QP solver. The process we present is very simple requiring surprisingly little data. Further, we present a modified sequential QP algorithm that leverages the restricted QP approach to solve nonlinear programming problems found in model predictive control. Lastly, we apply these to a benchmark MPC problem and demonstrate their effectiveness using a variety of established QP solvers. We demonstrate that QP problems can be solved faster with minimal MPC performance degradation and highlight future directions for this work.
Paper VI124-08.5
PDF · Video · Efficient Solution of Equality Constrained Quadratic Programming Arising in Model Predictive Control
Costantini, Giuliano	Technische Universität Kaiserslautern
Görges, Daniel	University of Kaiserslautern
Keywords: Predictive control, Numerical methods for optimal control, Real-time optimal control Abstract: Fast Model Predictive Control (Fast MPC) is a set of techniques which aim at reducing the complexity of solving receding horizon control optimization problems. One method consists in exploiting the structure induced by the system dynamics. This drastically reduces the complexity of the problem from cubic to linear dependence on the horizon length. Such approach is possible for the multi-stage MPC formulation which is characterized by having an almost separable structure, i.e. coupling occurs only between consecutive stages. This paper proposes a novel technique that efficiently solves general linear-quadratic optimal control problems and hence does not require a multi-stage formulation. The method also provides other advantages including: higher solution accuracy, warm starting, and approximate solutions by early termination. This is achieved by embedding the Riccati recursion in a Projected Conjugate Gradient (PCG) method.
Paper VI124-08.6
PDF · Video · Explicit Spline-Based Continuous-Time MPC: A Study on Design and Performance
Rohal-Ilkiv, Boris	Slovak University of Technology
Gulan, Martin	Slovak University of Technology
Minarčík, Peter	Slovak University of Technology in Bratislava
Keywords: Predictive control, Parametric optimization, Optimal control theory Abstract: This paper presents a continuous-time model predictive control scheme based on Bspline functions used for signals and model approximation. The proposed controller offers two interesting advantages. First, it formulates the control signal as a continuous polynomial spline function, the nature of which is determined by its control polygon that is subject of optimization. Second, all continuous constraints assumed over prediction horizon are consistently transformed into constraints imposed on a finite number of elements of this control polygon. Using parametric quadratic programming we further show how to obtain an explicit representation of the proposed controller, which is known for its efficient online implementation. The featured simulation study demonstrates that by a suitable choice of number and position of knots of the spline function over the prediction horizon it is possible to substantially reduce the number of critical regions of the explicit controller while preserving control performance, and to mitigate the direct correlation between number of regions and chosen length of prediction horizon.
Paper VI124-08.7
PDF · Video · FPGA Implementation Framework for Low Latency Nonlinear Model Predictive Control
Patne, Vaishali	Pune University
Ingole, Deepak	University of Lyon, IFSTTAR, ENTPE
Sonawane, Dayaram	College of Engineering Pune
Keywords: Real-time optimal control, Nonlinear predictive control, Constrained control Abstract: Embedded implementation of real-time Nonlinear Model Predictive Control (NMPC) is extremely challenging and complex. This paper presents a framework for implementation of NMPC on Field Programmable Gate Array (FPGA). We show the step-by-step procedure of FPGA implementation framework design of NMPC for a case study of 2D-crane system. In the implementation, we used GRAMPC software to construct NMPC and subsequently generate an FPGA specific low-level C/C++ code of the optimization solver. Generated C/C++ code is optimized for memory, speed, and resource utilization by the customized approach of applying pipelining and directives using Xilinx Vivado HLS toolchain. The NMPC is implemented on a Xilinx's ZYNQ-7000 SoC ZC706 FPGA board. The detailed analysis of the controller computational complexity in terms of memory, resource utilization, clock, and power consumption is presented. The performance of implemented NMPC is verified through Hardware-in-the-Loop (HIL) co-simulation using system generator tool. The presented results show the feasibility of FPGA-based GRAMPC framework for ultra-fast applications of NMPC.
Paper VI124-08.8
PDF · Video · Cascaded Nonlinear MPC for Realtime Quadrotor Position Tracking
Schlagenhauf, Jonas	University of Freiburg
Hofmeier, Peter	University of Freiburg
Bronnenmeyer, Thilo	Kiteswarms GmbH
Paelinck, Reinhart	Kiteswarms GmbH
Diehl, Moritz	University of Freiburg
Keywords: Real-time optimal control, Nonlinear predictive control, Decentralized control Abstract: In this paper we present a cascaded control approach using nonlinear model-predictive controllers for both stages. Using a quadrotor platform as an exemplary target plant with fast nonlinear dynamics, a real-time capable design is proposed that does not require the plant dynamics to exhibit clearly separable time constants as in classical cascaded control. In contrast to similar work we employ NMPC for the inner control loop instead of classical control approaches such as PID control, allowing to keep predictive properties as well as explicit constraint handling. We demonstrate via Monte-Carlo simulations that our design is able to achieve a significantly better position tracking performance of the quadrotor while being equally computationally expensive compared to monolithic position tracking NMPC.
Paper VI124-08.9
PDF · Video · Automatic Code Generation Tool for Nonlinear Model Predictive Control with Jupyter
Katayama, Sotaro	Kyoto University
Ohtsuka, Toshiyuki	Kyoto University
Keywords: Real-time optimal control, Nonlinear predictive control, Numerical methods for optimal control Abstract: We present an automatic code generation tool, AutoGenU for Jupyter, for nonlinear model predictive control (NMPC) with a user-friendly and interactive interface utilizing JupyterLab and Jupyter Notebook. We utilize a symbolic computation package SymPy for automatic C++ code generation. We also developed numerical solvers of NMPC using the continuation/GMRES (C/GMRES) method and multiple-shooting-based C/GMRES method in C++. AutoGenU for Jupyter provides the simulation environment of NMPC with these solvers and visualization of the simulation results. We give an example of code generation and numerical simulation of a swing-up control of a cart pole using AutoGenU for Jupyter
Paper VI124-08.10
PDF · Video · Contraction Properties of the Advanced Step Real-Time Iteration for NMPC
Nurkanović, Armin	Siemens AG
Zanelli, Andrea	University of Freiburg
Albrecht, Sebastian	Siemens AG
Frison, Gianluca	University of Freiburg
Diehl, Moritz	University of Freiburg
Keywords: Real-time optimal control, Numerical methods for optimal control, Nonlinear predictive control Abstract: In this paper we study the contraction properties of the recently introduced Advanced Step Real-Time Iteration (AS-RTI) under active-set changes. Compared to the well-known Real-Time Iteration, in order to improve optimality, in the AS-RTI some extra calculations on a problem with a predicted state are carried out. This enables us to trade off controller performance for computational load in a simple manner. Under standard assumptions, we prove the contraction of the iterates and boundedness of the numerical error. To achieve these goals we use generalized equations, Robinson's strong regularity and recently presented results for abstract real-time algorithms. Finally, we present a numerical benchmark, where the performance of dierent variants of the AS-RTI is demonstrated on an industrial case study.
Paper VI124-08.11
PDF · Video · A Fast Iterative Approach for Optimal Control of Nonlinear Systems
Liu, Jiaqi	Jilin University
Dong, Shiying	Jilin University
Hong, Jinlong	Jilin University
Gao, Bingzhao	Jilin University
Chen, Hong	Jilin Univ, Campus NanLing
Keywords: Real-time optimal control, Numerical methods for optimal control, Output regulation Abstract: To improve computational efficiency, a fast iterative solution method is proposed to solve optimization problems of nonlinear systems in this paper. The main idea is to extract the main linear part from the nonlinear system, and then regard the remaining nonlinear part as disturbance, so that the converted system can be solved by combining the optimal solution of the linear system with the fast iterative solution proposed. After the fast iterative solution method is introduced, its effectiveness is validated through a numerical example and an application which is engine energy-saving control while taking vehicle speed tracking into consideration. All of the simulation results show that the proposed iterative algorithm has the advantages of fast convergence speed and high accuracy.

VI124-09
Robust and Learning Predictive Control	Regular Session
Chair: Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Co-Chair: Bitmead, Robert	University of California San Diego
Paper VI124-09.1
PDF · Video · Fusing Multiple Time Varying Tubes for Robust MPC
Koegel, Markus J.	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Constrained control, Nonlinear predictive control, Control of constrained systems Abstract: We consider robust tube based model predictive control of discrete time, constrained, linear systems subject to additive disturbances. Standard tube based approaches utilize as an auxiliary control law a single, fixed feedback/gain to counteract the effect of the future disturbances in the predictions. The fictive - never applied - control law allows to bound the error between the real state and the nominal predictions by so called tubes. The tube control law strongly influences the shape and size of the tube. Consequently, the choice of the gain has a major impact on the domain of attraction and the control performance of the overall controller. The objective of this work is to overcome these limitations by combining multiple tubes online, each determined by a different controller gain. This reduces the conservatism and improves the closed loop performance. The computational demand for the resulting control law increases only marginally, compared to the standard case.We establish constraint satisfaction, robust recursive feasibility and robust stability. Moreover extension to the case of varying disturbance bounds are discussed. The proposed approach and its benefits are illustrated using simulations.
Paper VI124-09.2
PDF · Video · Computation of Invariant Tubes for Robust Output Feedback Model Predictive Control
Hu, Cheng	Imperial College London
Liu, Chengyuan	University of Nottingham
Jaimoukha, Imad M.	Imperial College London
Keywords: Output feedback control (linear case), Observers for linear systems, Robust linear matrix inequalities Abstract: This paper presents an algorithm to calculate tightened invariant tubes for output feedback model predictive controllers (MPC). We consider discrete-time linear time-invariant (DLTI) systems with bounded state and input constraints and subject to bounded disturbances. In contrast to existing approaches which either use pre-defined control and observer gains or compute the control and observer gains that optimize the volume of the invariant sets for the estimation and control errors separately, we consider the problem of optimizing the volume of these sets simultaneously. The nonlinearities associated with computing the control and observer gains are circumvented by the application of Farkas' Theorem and an extended Elimination Lemma, to convert the nonconvex optimization problem into a convex semidefinite program. An update algorithm is then used to reduce the volume of the invariant tube through a finite number of iterations. Numerical examples are provided to illustrate the effectiveness of the proposed algorithm.
Paper VI124-09.3
PDF · Video · Model Predictive Control with Forward-Looking Persistent Excitation
Brüggemann, Sven	University of California San Diego
Bitmead, Robert	University of California San Diego
Keywords: Predictive control, Adaptive control, Robust estimation Abstract: This work deals with the dual-control problem of simultaneous regulation and model parameter estimation in model predictive control. We propose an adaptive model predictive control which guarantees a persistently exciting closed loop sequence by only looking forward in time into the prediction horizon. Earlier works needed to look backwards and preserve prior regressor data. With the new approach, under the assumption of a known periodic persistently exciting reference trajectory around the equilibrium, we demonstrate exponential convergence of nonlinear systems under the influence of the adaptive model predictive control combined with a recursive least squares identifier with forgetting factor despite bounded noise. The results are, at this stage, local in state and parameter estimate space.
Paper VI124-09.4
PDF · Video · Formulation of Min-Max Model Predictive Control As a Box-Constrained Robust Least Squares Estimation Problem
Orsini, Valentina	Università Politecnica Delle Marche
Jetto, L.	Univ. Di Ancona
Keywords: Predictive control, Constrained control, Robust estimation Abstract: The purpose of this paper is to propose a new approach to the Min-Max Model Predictive Control (MMMPC) of Linear Time-Invariant Discrete-time Polytopic (LTIDP) systems. The purpose is to simplify the treatment of complex issues like stability and feasibility analysis of robust MPC as well as to reduce the complexity of the relative optimization procedure. The new approach is based on a two Degrees Of Freedom (2DOF) control scheme where the output r(k) of the feedforward Input Estimator (IE) is used as input forcing a stable closed-loop system Σf. Σf is the feedback connection of an LTIDP plant Σp with an LTI dynamic controller Σg. The task of Σg is to guarantee the quadratic stability of Σf, as well as the fulfillment of hard constraints on some physical variables of Σf for any input r(k) satisfying an "a priori" determined admissibility condition. The input r(k) is computed by the feedforward IE through the on-line minimization of a worst case finite-horizon quadratic cost functional and is applied to Σf according to the usual receding horizon strategy. Rather than resorting to an "ad hoc" software, the numerical complexity issue is here addressed reducing the number of both decision variables and constraints involved in the on-line constrained optimization procedure. This is obtained modeling r(k) as a B-spline function, which is known to be a universal approximator which also admits a parsimonious parametric representation. This allows us to reformulate the minimization of the worst case cost functional as a box-constrained Robust Least Squares (RLS) estimation problem which can be efficiently solved using Second Order Cone Programming (SOCP).
Paper VI124-09.5
PDF · Video · Learning Robustness with Bounded Failure: An Iterative MPC Approach
Bujarbaruah, Monimoy	UC Berkeley
Shetty, Akhil	University of California, Berkeley
Poolla, Kameshwar	University of California at Berkeley
Borrelli, Francesco	University of California
Keywords: Predictive control, Control of constrained systems, Linear systems Abstract: We propose an approach to design a Model Predictive Controller (MPC) for constrained Linear Time Invariant systems performing an iterative task. The system is subject to an additive disturbance, and the goal is to learn to satisfy state and input constraints robustly. Using disturbance measurements after each iteration, we construct Confidence Support sets, which contain the true support of the disturbance distribution with a given probability. As more data is collected, the Confidence Supports converge to the true support of the disturbance. This enables design of an MPC controller that avoids conservative estimate of the disturbance support, while simultaneously bounding the probability of constraint violation. The efficacy of the proposed approach is then demonstrated with a detailed numerical example.
Paper VI124-09.6
PDF · Video · Tube-Based Anticipative Robust MPC for Systems with Multiplicative Uncertainty
Peschke, Tobias	Technische Universität Kaiserslautern
Görges, Daniel	University of Kaiserslautern
Keywords: Predictive control, Linear parameter-varying systems, Time-varying systems Abstract: Many control problems contain time-varying or parameter-varying dynamics. With model predictive control (MPC), it is possible to include known plant variations into the controller for improving control performance. Unfortunately, perfect knowledge of the plant is rarely available and the accurateness of models may change over time and operating points. Robust control approaches consider worst-case realizations with a static model which ensures constraint satisfaction and stability but may yield conservative performance. The control algorithm presented in this paper uses anticipative information about future uncertainties and varying models to improve control performance while ensuring stability and feasibility. Possible system trajectories are bounded by polytopic tubes and recursive feasibility is achieved by the use of a terminal set. The controller properties are evaluated in a numerical example and compared to a similar control algorithm.
Paper VI124-09.7
PDF · Video · Robust Economic Model Predictive Control without Terminal Conditions
Schwenkel, Lukas	University of Stuttgart
Köhler, Johannes	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Allgower, Frank	University of Stuttgart
Keywords: Predictive control, Nonlinear predictive control, Constrained control Abstract: In this paper, a tube-based economic Model Predictive Control (MPC) scheme for systems subject to bounded disturbances is investigated that uses neither terminal costs nor terminal constraints. We provide robust guarantees on the closed-loop performance under suitable dissipativity and controllability conditions. Furthermore, we prove practical convergence to an optimal robust control invariant set, as well as its practical stability under slightly stronger assumptions. Hence, this work extends the results from nominal economic MPC without terminal conditions to systems with bounded disturbances by using similar turnpike arguments and a properly modified stage cost. The results are discussed in a numerical example.
Paper VI124-09.8
PDF · Video · Output Feedback Stochastic MPC with Packet Losses
Yan, Shuhao	University of Oxford
Cannon, Mark	University of Oxford
Goulart, Paul J.	University of Oxford
Keywords: Predictive control, Output feedback control, Convex optimization Abstract: The paper considers constrained linear systems with stochastic additive disturbances and noisy measurements transmitted over a lossy communication channel. We propose a model predictive control (MPC) law that minimises a discounted cost subject to a discounted expectation constraint. Sensor data is assumed to be lost with known probability, and data losses are accounted for by expressing the predicted control policy as an affine function of future observations, which results in a convex optimal control problem. An online constraint-tightening technique ensures recursive feasibility of the online optimization and satisfaction of the expectation constraint without bounds on the distributions of the noise and disturbance inputs. The cost evaluated along trajectories of the closed loop system is shown to be bounded by the optimal predicted cost. A numerical example is given to illustrate these results.
Paper VI124-09.9
PDF · Video · Robust Analysis and Sensitivity Design of Model Predictive Control
Barzgaran, Bijan	University of Washington
Mesbahi, Mehran	Univ of Washington
Keywords: Predictive control, Robust control (linear case), Robust controller synthesis Abstract: Model Predictive Control (MPC) algorithms have an inherently time domain based design. Design parameters are directly connected to the discrete time domain (sample time, prediction horizon), or impact the discrete time state-space model (weight matrices). We provide an analysis and design method for MPC systems in the frequency domain, including the determination of robustness margins. Pre-designed MPC applications are analyzed for their multi-dimensional gain and phase margin. An adjustment design method to improve unsatisfactory results is given. This approach is shown in a simulation example.
Paper VI124-09.10
PDF · Video · Repetitive Set-Based Learning Robust Predictive Control for Lur'e Systems
Nguyen, Hoang Hai	Otto-von-Guericke-Universität Magdeburg
Morabito, Bruno	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Predictive control, Robust control, Data-based control Abstract: Robust control of uncertain nonlinear systems subjects to constrants often leads to conservatism. Such behaviors can be possibly improved by updating the model of the uncertainty with the data collected during the operation time or bounding the parameters. This paper proposes an approach to robustly control the discrete-time Lur'e system subject to states and input constraints, where the unknown memoryless nonlinearity is sector-bounded and its Lipschitz constant is assumed to be given. In the first phase of operation, when no data has been collected, a robust MPC controller obtained from solving linear matrix inequalities is used. This formulation is also used to computed the safe region, in which the system can operate safely. After sufficient data has been collected, an upper and lower bound of of the nonlinearity can be constructed by using the Lipschitz constant. A controller based on tube-based MPC is used, which results in less conservatism and provides more flexibility. Data of the nonlinearity can be further updated to reduce uncertainty, and hence, decrease the size of the tube. Under additional conditions, the controller can safely explore the region outside the safe regions to collect more data of the unknown nonlinearity to improve performance and region of attraction.
Paper VI124-09.11
PDF · Video · Combined Robust and Stochastic Model Predictive Control for Models of Different Granularity
Brüdigam, Tim	Technical University of Munich
Teutsch, Johannes	Technical University of Munich
Wollherr, Dirk	Technical University of Munich
Leibold, Marion	Technical University of Munich
Keywords: Predictive control, Stochastic optimal control problems Abstract: Long prediction horizons in Model Predictive Control (MPC) often prove to be efficient, however, this comes with increased computational cost. Recently, a Robust Model Predictive Control (RMPC) method has been proposed which exploits models of different granularity. The prediction over the control horizon is split into short-term predictions with a detailed model using MPC and long-term predictions with a coarse model using RMPC. In many applications robustness is required for the short-term future, but in the long-term future, subject to major uncertainty and potential modeling difficulties, robust planning can lead to highly conservative solutions. We therefore propose combining RMPC on a detailed model for short-term predictions and Stochastic MPC (SMPC), with chance constraints, on a simplified model for long-term predictions. This yields decreased computational effort due to a simple model for long-term predictions, and less conservative solutions, as robustness is only required for short-term predictions. The effectiveness of the method is shown in a mobile robot collision avoidance simulation.
Paper VI124-09.12
PDF · Video · A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control under General Bounded Disturbances
Schlüter, Henning	University Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Predictive control, Stochastic optimal control problems, Control problems under conflict and/or uncertainties Abstract: This paper presents a nonlinear model predictive control strategy for stochastic systems with state- and input-dependent, finite-support disturbances subject to individual chance constraints. Our approach uses an online computed stochastic tube to ensure stability, constraint satisfaction, and recursive feasibility in the presence of stochastic uncertainties. The shape of the tube and the constraint backoff is based on an offline computed incremental Lyapunov function.
Paper VI124-09.13
PDF · Video · Stochastic MPC with Distributionally Robust Chance Constraints
Mark, Christoph	University of Kaiserslautern
Liu, Steven	University of Kaiserslautern
Keywords: Predictive control, Stochastic optimal control problems, Probabilistic robustness Abstract: In this paper we discuss distributional robustness in the context of stochastic model predictive control (SMPC) for linear time-invariant systems. We derive a simple approximation of the MPC problem under an additive zero-mean i.i.d. noise with quadratic cost. Due to the lack of distributional information, chance constraints are enforced as distributionally robust (DR) chance constraints, which we opt to unify with the concept of probabilistic reachable sets (PRS). For Wasserstein ambiguity sets, we propose a simple convex optimization problem to compute the DR-PRS based on finitely many disturbance samples. The paper closes with a numerical example of a double integrator system, highlighting the reliability of the DR-PRS w.r.t. the Wasserstein set and performance of the resulting SMPC.
Paper VI124-09.14
PDF · Video · A Sampling-And-Discarding Approach to Stochastic Model Predictive Control for Renewable Energy Systems
Csáji, Balázs Csanád	SZTAKI
Kis, Krisztián Balázs	Institute for Computer Science and Control, Budapest, H-1111, Ke
Kovács, András	MTA SZTAKI
Keywords: Probabilistic robustness, Randomized algorithms, Energy systems Abstract: The paper applies the scenario approach to stochastic model predictive control for renewable energy systems. First, the controllable and the (quasi-periodic) uncontrollable parts are decomposed. The latter is modeled by a Box-Jenkins system with appropriately chosen inputs. For the controllable part, a linear state space model is used with an affine state-feedback controller. Several numerical experiments are presented on a public lighting microgrid, e.g., about forecasting the energy balance, the effects of various controller parametrizations, reoptimization frequencies, and discarding unfavorable scenarios. The results indicate that even a low order, time-independent controller with a slow reoptimization frequency can be efficient.

VI124-10
Robust and Stochastic Optimal Control	Regular Session
Chair: Kashima, Kenji	Kyoto University
Co-Chair: Gershon, Eli	Tel Aviv Univ
Paper VI124-10.1
PDF · Video · An Auto-Tuning LQR Based on Correlation Analysis
Huang, Xujiang	TU-Ilmenau
Li, Pu	Technische Universität Ilmenau
Keywords: Control problems under conflict and/or uncertainties, Time-invariant systems, Linear systems Abstract: In this paper, we present an auto-tuning method for Linear Quadratic Regulator (LQR) based on correlation analysis. Unlike previous studies which focused on LQR tuning strategies exclusively by evaluating the control performance, we propose to explore the explicit relationship between the model and weighting parameters in LQR. The objective of this paper is twofold: (1) we introduce an approach to the identification and quantification of the correlation between a model parameter and a weighting parameter in LQR; (2) an auto-tuning method is worked out which is explicitly related to the variation of the model parameter. As a result, an optimal value of the weighting parameter can be effectively determined and, in the meantime, the parameter variation estimated. Through the numerical example, we demonstrate the effectiveness of the proposed auto-tuning method in restoring the control performance under unknown parameter variations.
Paper VI124-10.2
PDF · Video · Robust Stackelberg Games Via Static Output Feedback Strategy for Uncertain Stochastic Systems with State Delay
Mukaidani, Hiroaki	Hiroshima University
Ramasamy, Saravanakumar	Hiroshima University
Xu, Hua	Univ. of Tsukuba
Zhuang, Weihua	University of Waterloo
Keywords: Differential or dynamic games, Stochastic optimal control problems, Systems with time-delays Abstract: In this paper, a robust Stackelberg game for a class of uncertain stochastic systems with state delay is investigated. After introducing some definitions and preliminaries, we derive the conditions for the existence of the robust static output feedback (SOF) Stackelberg strategy set such that the upper bounds of leader's cost function and the weighted cost function of the followers are minimized respectively. In order to obtain the robust SOF Stackelberg strategy set, a heuristic algorithm is proposed based on the stochastic Lyapunov type matrix equations (SLMEs) and the linear matrix inequalities (LMIs). In particular, it is shown that robust convergence is guaranteed by applying the Krasnoselskii-Mann (KM) iterative algorithm. An academic numerical example is presented to demonstrate the effectiveness of the proposed method.
Paper VI124-10.3
PDF · Video · Lyapunov-Krasovskii Prescribed Derivative and the Bellman Functional for Time-Delay Systems
Ortega-Martínez, Jorge-Manuel	CINVESTAV-IPN
Santos, Omar	Universidad Autónoma Del Estado De Hidalgo
Mondie, Sabine	CINVESTAV-IPN
Keywords: Optimal control theory, Systems with time-delays, Linear systems Abstract: The Dynamic Programming approach for optimal control problem establishes that the necessary condition for optimality is that the minimum cost function (the Bellman functional) must satisfy the Hamilton-Jacobi-Bellman equation. A sufficient condition is that if there exists a functional that satisfies the Hamilton-Jacobi-Bellman equation, then it is the minimum cost function. For linear time-delay systems, Krasovskii proposed the Bellman functional, and an optimal structure for the controller was reported. The Dynamic Programming combined with prescribed derivative functionals leads to an iterative procedure which allows finding suboptimal controls law at each step. There is numerical evidence that shows that these functionals are equivalent. However, their algebraic structure is different. The Bellman functional has only three terms and the iterative functional is composed by thirteen summands. The algebraic relation between both functionals is not easy to see. The present contribution gives a proof of this connection by using Fubini’s Theorem.
Paper VI124-10.4
PDF · Video · Canonical Dynamic Programming Equations Subject to Ambiguity
Tzortzis, Ioannis	University of Cyprus
Charalambous, Charalambos D.	Univ of Cyprus
Keywords: Stochastic optimal control problems Abstract: This paper studies the infinite horizon average cost Markov control model subject to ambiguity on the controlled process conditional distribution. The stochastic control problem is formulated as a minimax optimization in which, (i) the existence of optimal policies is established through a pair of canonical dynamic programming equations derived for Borel state and action spaces, and (ii) the controlled process maximizing conditional distribution is characterized through a water-filling solution derived for finite state and action spaces. To obtain average cost optimal policies numerically a policy iteration algorithm is also developed. Finally, as an application of the proposed canonical dynamic programming equations, an example is provided.
Paper VI124-10.5
PDF · Video · Balanced Stochastic Optimal Control of Uncertain Linear Systems with Constraints
Hahn, Jannik	Universität Kassel
Stursberg, Olaf	University of Kassel
Keywords: Stochastic optimal control problems, Disturbance rejection (linear case), Robust control (linear case) Abstract: This paper addresses fnite-time horizon optimal control for discrete-time dynamics with additional stochastic isturbances. In contrast to most existing approaches to this problem, we also minimize the uncertainty of future states arising from stochastic disturbances and from an uncertain initial state. Thus, the optimal control strategy balances the minimization f the expected distances to a reference signal, and the inimization of the uncertainty respectively. As opposed to prior work, the optimization is formulated subject to possible disturbance feedback policies. This enables to solve one semi-definite program over H steps, instead of solving H problems over one step, and the resulting reduced complexity allows one to use the scheme in online and predictive control. The proposed method is applicable to time-varying state constraints (in the sense of chance constraints) as well as time-invariant input constraints.
Paper VI124-10.6
PDF · Video · Continuity of the Value Function for Stochastic Sparse Optimal Control
Ito, Kaito	Kyoto University
Ikeda, Takuya	Kyoto University
Kashima, Kenji	Kyoto University
Keywords: Stochastic optimal control problems, Optimal control theory, Non-smooth and discontinuous optimal control problems Abstract: In this paper, we investigate the continuity of the value function for a stochastic sparse optimal control. The most common method to solve stochastic optimal control problems is the dynamic programming. Specifically, if the value function is smooth, it satisfies the associated Hamilton-Jacobi-Bellman (HJB) equation. However, in general, the value function for our problem is not differentiable because of the nonsmoothness of the L0 cost functional. Instead, we can expect that the value function is a viscosity solution to the HJB equation. This paper shows the continuity of our value function as a first step for showing that the value function is a viscosity solution.
Paper VI124-10.7
PDF · Video · Application of Sub-Predictors Control for Linear Delayed Stochastic Systems
Gershon, Eli	Tel Aviv Univ
Shaked, Uri	Tel-Aviv Univ
Keywords: Stochastic optimal control problems, Systems with time-delays, Robust control (linear case) Abstract: The problem of robust predictor-based Hoo state-feedback control for uncertain continuous-time stochastic state-multiplicative retarded systems is extended to include a set of sub-predictors, thus considerably improving the control performance. The multiplicative noise appears in the system dynamic matrix, while the delay resided in the input to the system. In this problem, a cost function is defined which is the expected value of the standard Hoo performance index with respect to the uncertain parameters. In the robust case, the solution is obtained via a simple set of linear matrix inequalities. We bring a detailed numerical example that demonstrates the superiority of designing state-feedback control via a set of Luenberger-type sub predictors compared to a single predictor design.
Paper VI124-10.8
PDF · Video · Data-Driven Optimal Control of Linear Time-Invariant Systems
Kastsiukevich, Dzmitry	Belarusian State University
Dmitruk, Natalia	Belarusian State University
Keywords: Control problems under conflict and/or uncertainties, Data-based control, Predictive control Abstract: We consider an optimal control problem for discrete-time linear time-invariant systems subject to unknown state-space model, constrained inputs and noisy output measurements. Since traditional model-based optimal control problem formulations and methods are not applicable to the problem under consideration, we propose a data-driven robust formulation based on the explicit model description derived from a single measured trajectory of the system. Then we propose an open-loop optimal feedback control scheme and show that its efficient implementation requires solution of a number of optimal estimation problems and a deterministic optimal control problem, all in data-driven formulations. The main contributions of this paper are the separation of the estimation and control processes in the data-driven context and the resulting robust feedback control scheme.

VI125
Design Methods - Robust Control
VI125-01 Uncertainty Quantification in Control and Optimization – Tools, Methods and Applications   Open Invited Session, 17 papers
VI125-02 Linear Parameter-Varying Systems   Regular Session, 9 papers
VI125-03 Robust and Convex Optimization   Regular Session, 7 papers
VI125-04 Robust Control and Estimation   Regular Session, 5 papers
VI125-05 Robust Control Applications   Regular Session, 6 papers

VI125-01
Uncertainty Quantification in Control and Optimization – Tools, Methods and Applications	Open Invited Session
Chair: Faulwasser, Timm	TU Dortmund University
Co-Chair: Streif, Stefan	Technische Universität Chemnitz
Organizer: Faulwasser, Timm	TU Dortmund University
Organizer: Streif, Stefan	Technische Universität Chemnitz
Organizer: Schenkendorf, Rene'	TU Braunschweig
Organizer: Gerster, Stephan	RWTH Aachen University
Paper VI125-01.1
PDF · Video · Conformally Mapped Polynomial Chaos Expansions for Uncertain Dynamical Systems (I)
Georg, Niklas	Technische Universität Braunschweig
Römer, Ulrich	Technische Universität Braunschweig
Keywords: Linear systems, Uncertainty descriptions, Time-invariant systems Abstract: Polynomial Chaos expansions are among the most popular tools for uncertainty quantification. In this work, we address surrogate modeling for random dynamical systems in the frequency domain, where the randomness accounts for uncertainties in system input parameters. It has been pointed out several times that Polynomial Chaos methods may converge slowly if such systems operate close to resonances or if the input randomness is large. As a remedy, we propose to use conformal mappings to enhance the accuracy of Polynomial Chaos expansions in a certain frequency range. These transformations may enlarge the region of analyticity of the underlying function to be approximated and hence, improve the cost accuracy ratio. We will explain the underlying mechanism and derive transformed Polynomial Chaos expansions which still feature the desired orthogonality properties. The algorithmic development will be complemented by several numerical examples which demonstrate the effectiveness of the proposed approach.
Paper VI125-01.2
PDF · Video · Data-Driven Stochastic Distribution Network Reconfiguration (I)
Huang, Wanjun	The University of Hong Kong
Zheng, Weiye	The University of Hong Kong
Hill, David J.	The University of Hong Kong
Keywords: Stochastic optimal control problems, Uncertainty descriptions, Data-based control Abstract: Distribution network reconfiguration (DNR) is indispensable for the operation of active distribution networks. To address the uncertainties of renewables and variables loads, a data-driven stochastic DNR model is proposed for day-ahead DNR of three-phase unbalanced distribution networks. The switching cost and expected costs resulted from power losses and load balance are minimized. Based on the analysis of historical data, the probability distribution of DG output and load demand is derived using a data-driven method. To improve computation efficiency, a mixed-integer linear programming problem is formulated using linearization techniques. Numerical tests are carried out in an IEEE unbalanced benchmark. The comparison with the conventional deterministic method verifies the effectiveness of the proposed method.
Paper VI125-01.3
PDF · Video · Feedback Control Design Maximizing the Region of Attraction of Stochastic Systems Using Polynomial Chaos Expansion (I)
Ahbe, Eva	ETH Zurich
Listov, Petr	EPFL, Lausanne
Iannelli, Andrea	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Control problems under conflict and/or uncertainties, Stability of nonlinear systems, Constrained control Abstract: A feedback control design is proposed for stochastic systems with finite second moment which aims at maximising the region of attraction of the equilibrium point. Polynomial Chaos (PC) expansions are employed to represent the stochastic closed loop system by a higher dimensional set of deterministic equations. By using the PC expanded system representation, the available information on the uncertainty affecting the system explicitly enters the control design problem. Further, this allows Lyapunov methods for deterministic systems to be used to formulate the stability criteria certifying the region of attraction. These criteria are parametrized by the feedback gain and formulated in a polynomial optimization program which is solved using sum-of-squares methods. This approach offers flexibility in the choice of the stochastic feedback law and accounts for input constraints. The application is demonstrated by two numerical examples.
Paper VI125-01.4
PDF · Video · Sensitivity-Assisted Robust Nonlinear Model Predictive Control with Scenario Generation (I)
Yu, Zhou (Joyce)	Carnegie Mellon University
Biegler, Lorenz T.	Carnegie Mellon Univ
Keywords: Control problems under conflict and/or uncertainties, Nonlinear predictive control, Numerical methods for optimal control Abstract: We propose a sensitivity-assisted multistage Nonlinear Model Predictive Control strategy, called samNMPC, to address multistage stochastic programs for robust NMPC. Our approach divides the scenario sets in the stochastic programming formulation into critical and noncritical sets. Critical scenarios are selected by scenario generation based on worst- case constraint determination, while stage costs for noncritical scenarios are determined by sensitivity-based approximations. The resulting multi-stage NMPC problem leads to a first order accurate control profile that satisfies all constraints under uncertainty. Moreover, computational costs of this formulation scale independently of the number of disturbance variables, and only linearly with the robust horizon and number of constraints. Our proposed approach is illustrated on a CSTR (continuous stirred tank reactor) case study with two uncertain parameters. Compared to competing approaches, samNMPC delivers robust performance of multi-stage NMPC with significantly less computational cost.
Paper VI125-01.5
PDF · Video · PolyChaos.jl - a Julia Package for Polynomial Chaos in Systems and Control (I)
Muehlpfordt, Tillmann	Karlsruhe Institute of Technology
Zahn, Frederik	Karlsruher Institut Für Technologie
Hagenmeyer, Veit	Karlsruhe Institute of Technology
Faulwasser, Timm	TU Dortmund
Keywords: Probabilistic robustness, Uncertainty descriptions, Numerical methods for optimal control Abstract: Polynomial Chaos Expansion (PCE) is an increasingly popular technique for uncertainty propagation and quantification in systems and control. Based on the theory of Hilbert spaces and orthogonal polynomials, PCE allows for a unifying mathematical framework to study systems under arbitrary uncertainties ofnite variance; we introduce this problem as a so-called mapping under uncertainty. For practical PCE-based applications we require orthogonal polynomials relative to given probability densities, and their quadrature rules. With PolyChaos.jl we provide a Julia software package that delivers the desired functionality: given a probability density function, PolyChaos.jl offers several numerical routines to construct the respective orthogonal polynomials, and the quadrature rules together with tensorized scalar products. PolyChaos.jl is thefirst PCE-related software written in Julia, a scientific programming language that combines the readability of scripted languages with the speed of compiled languages. We provide illustrating numerical examples that show both PCE and PolyChaos.jl in action.
Paper VI125-01.6
PDF · Video · An Efficient Model-Error Model Update Strategy for Multi-Stage NMPC with Model-Error Model (I)
Thangavel, Sakthi	TU Dortmund
Engell, Sebastian	TU Dortmund
Keywords: Predictive control, Control problems under conflict and/or uncertainties Abstract: Multi-stage NMPC with model-error model (MS-MEM) handles structural plant-model mismatch present in the nominal model of the plant in a non-conservative fashion. A model-error model (MEM) that consists of a stable linear time-invariant dynamics and a static time-variant nonlinear mapping is built using the past data such that it captures the unmodeled dynamics of the plant. The scenario tree is built for the nominal and for the extreme realizations of the plant obtained using the nominal model and the model-error model, and a multi-stage decision problem is formulated. In this paper, we propose an efficient strategy to update the model-error model present in the MS-MEM approach if new measurements invalidate the model-error model. The advantages of the proposed scheme over the previous approach where only the gain of the linear model is updated are demonstrated for a continuous stirred tank reactor (CSTR) benchmark example.
Paper VI125-01.7
PDF · Video · Stabilization of Stochastic Fluctuations in Hyperbolic Systems (I)
Gerster, Stephan	RWTH Aachen University
Keywords: control of hyperbolic systems and conservation laws, stability of distributed parameter systems Abstract: We consider steady states of physical systems that are described by hyperbolic balance laws. We derive control policies that damp small perturbations over time. Uncertainties in model parameters are taken into account. Theoretical results are illustrated by stabilizing a viscoplastic material.
Paper VI125-01.8
PDF · Video · Nested Sampling Approach to Set-Membership Estimation (I)
Paulen, Radoslav	Slovak University of Technology in Bratislava
Gomoescu, Lucian	Imperial College London
Chachuat, Benoit	Imperial College London
Keywords: Robust estimation, Uncertainty descriptions, Model validation Abstract: This paper is concerned with set-membership estimation in nonlinear dynamic systems. The problem entails characterizing the set of all possible parameter values such that given predicted outputs match their corresponding measurements within prescribed error bounds. Most existing methods to tackle this problem rely on outer-approximation techniques, which perform poorly when the parameter host set is large due to the curse of dimensionality. An adaptation of nested sampling—a Monte Carlo technique introduced to compute Bayesian evidence—is presented herein. The nested sampling algorithm leverages efficient strategies from Bayesian statistics for generating an inner-approximation of the desired parameter set. Several case studies are presented to demonstrate the approach.
Paper VI125-01.9
PDF · Video · Data-Driven Solution of Stochastic Differential Equations Using Maximum Entropy Basis Functions (I)
Deshpande, Vedang M.	Texas A&M University
Bhattacharya, Raktim	Texas A&M
Keywords: Uncertainty descriptions Abstract: In this paper we present a data-driven approach for uncertainty propagation. In particular, we consider stochastic differential equations with parametric uncertainty. Solution of the differential equation is approximated using maximum entropy (maxent) basis functions similar to polynomial chaos expansions. Maxent basis functions are derived from available data by maximization of information-theoretic entropy, therefore, there is no need to specify basis functions beforehand. We compare the proposed maxent based approach with existing methods.
Paper VI125-01.10
PDF · Video · A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming (I)
Zhu, Jia-Jie	Max Planck Institute for Intelligent Systems
Muandet, Krikamol	Max Planck Institute for Intelligent Systems
Diehl, Moritz	University of Freiburg
Schölkopf, Bernhard	Max-Planck-Inistitue for Biological Cybernetics
Keywords: Uncertainty descriptions, Randomized algorithms Abstract: This work presents the concept of kernel mean embedding and kernel probabilistic programming in the context of stochastic systems. We propose formulations to represent, compare, and propagate uncertainties for fairly general stochastic dynamics in a distribution-free manner. The new tools enjoy sound theory rooted in functional analysis and wide applicability as demonstrated in distinct numerical examples. The implication of this new concept is a new mode of thinking about the statistical nature of uncertainty in dynamical systems.
Paper VI125-01.11
PDF · Video · Global Sensitivity Methods for Design of Experiments in Lithium-Ion Battery Context (I)
Pozzi, Andrea	Università Degli Studi Di Pavia
Xie, Xiangzhong	TU Braunschweig
Raimondo, Davide Martino	Università Degli Studi Di Pavia
Schenkendorf, Rene'	TU Braunschweig
Keywords: Robust estimation, Uncertainty descriptions, Energy systems Abstract: Battery management systems may rely on mathematical models to provide higher performance than standard charging protocols. Electrochemical models allow us to capture the phenomena occurring inside a lithium-ion cell and therefore, could be the best model choice. However, to be of practical value, they require reliable model parameters. Uncertainty quantification and optimal experimental design concepts are essential tools for identifying systems and estimating parameters precisely. Approximation errors in uncertainty quantification result in sub-optimal experimental designs and consequently, less-informative data, and higher parameter unreliability. In this work, we propose a highly efficient design of experiment method based on global parameter sensitivities. This novel concept is applied to the single-particle model with electrolyte and thermal dynamics (SPMeT), a well-known electrochemical model for lithium-ion cells. The proposed method avoids the simplifying assumption of output- parameter linearization used in conventional Fisher information matrix-based experimental design strategies. Thus, the optimized current input profile results in experimental data of higher information content and in turn, in more precise parameter estimates.
Paper VI125-01.12
PDF · Video · PoCET: A Polynomial Chaos Expansion Toolbox for Matlab (I)
Petzke, Felix	Technische Universität Chemnitz
Mesbah, Ali	University of California, Berkeley
Streif, Stefan	Technische Universität Chemnitz
Keywords: Uncertainty descriptions, Stochastic optimal control problems, Control in system biology Abstract: We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and nonlinear dynamic systems with time-invariant stochastic parameters or initial conditions, as well as several tools for simulating such systems. It offers a built-in handling of Gaussian, uniform, and beta probability density functions, projection and collocation-based calculation of PCE coefficients, and the calculation of stochastic moments from a PCE. Efficient algorithms for the calculation of the involved integrals have been designed in order to increase its applicability. PoCET comes with a variety of introductory and instructive examples. Throughout the paper we show how to perform a polynomial chaos expansion on a simple ordinary differential equation using PoCET, as well as how it can be used to solve the more complex task of optimal experimental design.
Paper VI125-01.13
PDF · Video · Fast Stochastic Model Predictive Control of Unstable Dynamical Systems (I)
von Andrian, Matthias	Massachusetts Institute of Technology
Braatz, Richard D.	Massachusetts Institute of Technology
Keywords: Predictive control, Probabilistic robustness, Control problems under conflict and/or uncertainties Abstract: Fast stochastic model predictive control (FSMPC) is a multivariable control algorithm that explicitly takes constraints and probabilistic parametric uncertainties into account while having low online computational cost for dynamical systems of high state dimension. This article extends FSMPC to be applicable to model uncertainty descriptions that include unstable dynamical systems. The proposed control structure, which embeds output feedback into past FSMPC formulations, is illustrated in a numerical example. Two different options for designing the embedded output feedback are compared and discussed.
Paper VI125-01.14
PDF · Video · Fast Probabilistic Uncertainty Quantification and Sensitivity Analysis of a Mars Life Support System Model (I)
Makrygiorgos, Georgios	University of California, Berkeley
Sen Gupta, Soumyajit	University of Florida
Menezes, Amor	Univ. of Florida
Mesbah, Ali	University of California, Berkeley
Keywords: Uncertainty descriptions Abstract: Mars life support system models consist of numerous mission-critical, interrelated, and scenario-specific parameters. The large size and involved nature of these models make them computationally expensive, with parameters that are subject to several sources of uncertainty. Accurately characterizing these uncertainties and their impact on overall model predictions is crucial for decision-support and mission optimization. This paper focuses on uncertainty quantification of a model of a space crop cultivation system, which is one of several systems that are required on a long-duration manned Mars mission. The model performs constrained optimization of the equivalent system mass (ESM) metric, which augments shipped mass costs with those of pressurized volume, demanded power, thermal control, and needed crew time. This paper uses surrogate modeling for fast quantification of the effect of probabilistic uncertainty in mission-critical parameters of semi-empirical equations that describe crop growth and equipment operation. This work shows sparse polynomial chaos-Kriging (PCK) yields a computationally cheap-to-evaluate surrogate for the minimum ESM that accounts for probabilistic uncertainty in 86 model parameters. This surrogate model accelerates a global sensitivity analysis that elucidates which crop growth and equipment operation parameters are critical to mission outcome variability. The PCK surrogate model realizes a 100-fold computational speed gain in the estimation of the probability distribution of the minimum ESM.
Paper VI125-01.15
PDF · Video · Polynomial Chaos-Based Flight Control Optimization with Guaranteed Probabilistic Performance
Shi, Dalong	Technical University of Munich
Fang, Xiang	Technical University of Munich
Holzapfel, Florian	Technische Universität München
Keywords: Parametric optimization, Control problems under conflict and/or uncertainties, Probabilistic robustness Abstract: A probabilistic performance-oriented controller design approach based on polynomial chaos expansion and optimization is proposed for flight dynamic systems. Unlike robust control techniques where uncertainties are conservatively handled, the proposed method aims at propagating uncertainties effectively and optimizing control parameters to satisfy the probabilistic requirements directly. To achieve this, the sensitivities of violation probabilities are evaluated by the expansion coefficients and the fourth moment method for reliability analysis, after which an optimization that minimizes failure probability under chance constraints is conducted. Afterward, a time-dependent polynomial chaos expansion is performed to validate the results. With this approach, the failure probability is reduced while guaranteeing the closed-loop performance, thus increasing the safety margin. Simulations are carried out on a longitudinal model subject to uncertain parameters to demonstrate the effectiveness of this approach.
Paper VI125-01.16
PDF · Video · Control and Filtering Problems for Linear Time-Varying Systems Based on Ellipsoidal Reachable Sets
Balandin, Dmitry V.	Nizhny Novgorod State University
Biryukov, Ruslan	Architecture and Civil Engineering State University
Kogan, Mark M.	Architecture and Civil Engineering Univ
Keywords: Control problems under conflict and/or uncertainties, Time-varying systems, Observers for linear systems Abstract: The paper is devoted to reachable sets of linear time-varying continuous systems under uncertain initial states and disturbances with a bounded uncertainty measure. The uncertainty measure is the sum of a quadratic form of the initial state and the integral over the finite-time interval from a quadratic form of the disturbance. It is shown that the reachable set of the system under this assumption is an evolving ellipsoid with a matrix being a solution to the linear matrix differential equation. This result is used to synthesize the optimal observer providing the minimal ellipsoidal set as the estimate of the system state, as well as optimal controllers steering the system state into a final target ellipsoidal set or keeping the entire system trajectory in a prescribed ellipsoidal tube under all admissible initial states and disturbances. The relationship between the optimal ellipsoidal observer and the Kalman filter are established. Numerical modeling with the Mathieu equation for parametric vibrations of a linear oscillator illustrates the results.
Paper VI125-01.17
PDF · Video · Low-Complexity Stabilizing PWA Controllers for Linear Systems with Parametric Uncertainties
Lu, Liang	Zhejiang University
Kvasnica, Michal	Slovak University of Technology in Bratislava
Keywords: Parametric optimization, Lyapunov methods, Robust controller synthesis Abstract: Explicit MPC often results in a large number of irregular partitions in the feasible region as the dimension of the system increases and the storage requirement for the control and region parameters often limit its applications. In this paper, we consider a class of discrete-time linear systems with polytopic parametric uncertainties and provide a robust control Lyapunov based synthesis method to obtain robust low-complexity PWA controllers on regular partitionings. By implementing a refinement procedure, we can fit the PWA feedback control law in each regular partitioning based on feasibility of linear programming problems, which preserves stability, constraint satisfaction, and certain performance requirement. Numerical examples will demonstrate the eectiveness of the approach.

VI125-02
Linear Parameter-Varying Systems	Regular Session
Chair: Scherer, Carsten W.	Department of Mathematics, University of Stuttgart
Co-Chair: Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Paper VI125-02.1
PDF · Video · Lifting to Passivity for H2-Gain-Scheduling Synthesis with Full Block Scalings
Rösinger, Christian A.	University of Stuttgart
Scherer, Carsten W.	Department of Mathematics, University of Stuttgart
Keywords: Linear parameter-varying systems, Controller constraints and structure, Convex optimization Abstract: We focus on the H2-gain-scheduling synthesis problem for time-varying parametric scheduling blocks with scalings. Recently, we have presented a solution of this problem for D- and positive real scalings by guaranteeing finiteness of the H2-norm for the closed-loop system with suitable linear fractional plant and controller representations. In order to reduce conservatism, we extend these methods to full block scalings by designing a triangular scheduling function and by introducing a new lifting technique for gain-scheduled synthesis that enables convexification.
Paper VI125-02.2
PDF · Video · Output-Feedback Synthesis for a Class of Aperiodic Impulsive Systems
Holicki, Tobias	University of Stuttgart
Scherer, Carsten W.	Department of Mathematics, University of Stuttgart
Keywords: Linear parameter-varying systems, Convex optimization, Robust linear matrix inequalities Abstract: We derive novel criteria for designing stabilizing dynamic output-feedback controllers for a class of aperiodic impulsive systems subject to a range dwell-time condition. Our synthesis conditions are formulated as clock-dependent linear matrix inequalities (LMIs) which can be solved numerically, e.g., by using matrix sum-of-squares relaxation methods. We show that our results allow us to design dynamic output-feedback controllers for aperiodic sample-data systems and illustrate the proposed approach by means of a numerical example.
Paper VI125-02.3
PDF · Video · Flocking of Linear Parameter Varying Agents: Source Seeking Application with Underwater Vehicles
Attallah, Aly	Hamburg University of Technology
Datar, Adwait	Institute of Control Systems, Hamburg University of Technology
Werner, Herbert	Hamburg Univ of Technology
Keywords: Linear parameter-varying systems, Distributed nonlinear control, Tracking Abstract: A distributed flocking control scheme is proposed for a network of Autonomous Underwater Vehicles (AUVs) which are modeled as Linear Parameter Varying (LPV) systems. This scheme is applied here to the solution of a source seeking problem, i.e. the vehicles (agents) measure the local values of a scalar field and are required to flock to its maximum (source). It is assumed that agents have the gradient and Hessian information of the scalar field at their current position. The control architecture of each agent is divided into two modules: a flocking filter which receives data from neighbours and generates a reference signal based on a flocking control law, and a feedback loop for tracking this reference. By this approach, a separation in design is achieved by designing a local LPV tracking controller for each agent and a network flocking filter which can be analyzed to guarantee stability in the sense of Lyapunov, i.e. the boundedness of agents' trajectories. Simulation results illustrate the practicality and benefits of the proposed flocking architecture scheme by applying it to a network of realistic autonomous underwater vehicles.
Paper VI125-02.4
PDF · Video · LPV Framework for Non-Linear Dynamic Control of Soft Robots Using Finite Element Model
Thieffry, Maxime	Sorbonne University
Kruszewski, Alexandre	Ecole Centrale De Lille
Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Duriez, Christian	INRIA
Keywords: Linear parameter-varying systems, Model reduction Abstract: This work presents a methodology to control soft robots using a reduced order nonlinear finite element model. The Linear Parameter-Varying (LPV) framework is used both to model the robot along a prescribed trajectory and to design its control law. Model reduction algorithms along with radial basis functions network are used to identify the nonlinear behavior of the robot. Finally, the method is validated through simulation experiments.
Paper VI125-02.5
PDF · Video · Modified Preactuation Tracking Control for LPV Systems with Application to Boost Converters
Miyoshi, Shota	The University of Tokyo
Ohnishi, Wataru	The University of Tokyo
Koseki, Takafumi	The University of Tokyo
Sato, Motoki	Toyo Denki Seizo K.K
Keywords: Linear parameter-varying systems, Parameter-varying systems, Power systems Abstract: Boost converters are usually employed as constant or discrete variable voltage sources. They are expected as a continuously variable voltage source for electric drives (based on pulse-amplitude modulation control), or for reduction of the size of energy buffer components for mass motor drives. When changing the output voltage of boost converters according to the duty ratio, the nonlinear and nonminimum phase characteristics of boost converters cause undershoots. This study was devoted to extending the technique known as preactuated multirate feedforward (PMF), which can effectively compensate for the effects caused by nonminimum phase characteristics in boost converters. PMF was originally considered for linear time-invariant systems. In this study, the technique was extended to linear parameter-varying systems by the interpolation method. Simulation and experimental results verified the effectiveness of the proposed approach.
Paper VI125-02.6
PDF · Video · Observer-Based LPV Control with Anti-Windup Compensation: A Flight Control Example
Theis, Julian	Hamburg University of Technology
Sedlmair, Nicolas	Hamburg University of Technology
Thielecke, Frank	Hamburg University of Technology
Pfifer, Harald	University of Nottingham
Keywords: Linear parameter-varying systems, Robust controller synthesis, Anti-windup Abstract: A low-complexity anti-windup compensation scheme for linear parameter-varying (LPV) controllers is proposed in this paper. Anti-windup compensation usually increases complexity of LPV controllers significantly. A synthesis algorithm is used in this paper that, unlike conventional algorithms, splits the problem into an observer synthesis and a subsequent state feedback synthesis. The resulting controller structure is exploited for a novel differential implementation that allows straightforward incorporation of conventional anti-windup logics. The method is used to design a pitch-axis flight control law for an unmanned aerobatic aircraft, where anti-windup compensation is an important practical requirement. Applicability is demonstrated in nonlinear simulation using a flight-test-validated high-fidelity model.
Paper VI125-02.7
PDF · Video · Parameter-Dependent H-Infinity Control for MEMS Gyroscopes: Synthesis and Analysis
Saggin, Fabricio	Ecole Centrale De Lyon
Ayala-Cuevas, Jorge	Ecole Centrale De Lyon
Korniienko, Anton	Ecole Centrale De Lyon, Laboratoire Ampère
Scorletti, Gerard	Ecole Centrale De Lyon
Keywords: Linear parameter-varying systems, Robustness analysis, Digital implementation Abstract: The accuracy of micro-electro-mechanical systems (MEMS) gyroscopes is sensitive to variations of the drive mode resonance frequency. To tackle this problem, we propose a parameter-dependent H-infinity control with a simple parameterization that guarantees, with reduced conservatism, a specified level of performance of the drive mode. We consider the design of continuous- and discrete-time controllers. In the discrete-time case, nonrational dependence on the parameter of interest appears. Then, we propose a method based on the Taylor approximation and the mu-analysis to validate the performance of drive mode. Numerical examples confirm the effectiveness of our approach.
Paper VI125-02.8
PDF · Video · Shifting H Infinity Linear Parameter Varying State-Feedback Controllers Subject to Time-Varying Input Saturations
Ruiz, Adrián	Universitat Politècnica De Catalunya (UPC)
Rotondo, Damiano	Universitetet I Stavanger
Morcego, Bernardo	Universitat Politecnica De Catalunya
Keywords: Linear parameter-varying systems, Systems with saturation, Disturbance rejection (linear case) Abstract: This paper establishes a methodology based on linear matrix inequalities (LMIs) to design a shifting H infinity linear parameter varying (LPV) state-feedback controller for systems affected by time-varying input saturations. By means of the shifting paradigm, the instantaneous saturation values are linked to a scheduling parameter vector. Then, the disturbance rejection is dealt with the quadratic boundedness concept and the shifting H infinity methodology. The design conditions are obtained within the LPV framework using ellipsoidal invariant sets, thus obtaining an LMI-based feasibility problem that can be solved via available solvers. Finally, the main characteristics of the proposed approach are validated by means of an illustrative example.
Paper VI125-02.9
PDF · Video · Robust Cascade LMI Design of MIMO Control System for Plasma Position, Current, and Shape Model with Time-Varying Parameters in a Tokamak
Konkov, Artem	Lomonosov Moscow State University
Mitrishkin, Yuri	M.V. Lomonosov Moscow State University
Korenev, Pavel	V.A. Trapeznikov Institute of Control Sciences
Patrov, Mikhail	Ioffe Physical Technical Institute of the Russian Academy of Sci
Keywords: Robust linear matrix inequalities, Linear parameter-varying systems, Linear multivariable systems Abstract: A new robust hierarchical plasma magnetic control system with time-varying parameters and cascade circuits for the Globus-M2 tokamak (Ioffe Institute) has been synthesized by means of the linear matrix inequalities (LMI) method. Each control cascade has a separate objective: placing poles of the closed-loop system in the D-region to guarantee robust performance, restriction of the H_inf-norm of the transfer function between external disturbances and the plant outputs of the closed-loop system, tracking PF-currents, CS-current, plasma current, plasma position, gaps between the plasma separatrix and the first wall. Control cascades were synthesized for an array of plant linear models corresponding to reconstructed plasma equilibria at different time points of the tokamak discharges. The LMIs allow the synthesis of one LTI controller, providing the required performance and system stability margin for each model from a given array. Tracking cascades use new MIMO PID controllers adjusted by means of the LMIs.

VI125-03
Robust and Convex Optimization	Regular Session
Chair: Cannon, Mark	University of Oxford
Co-Chair: Zeng, Xianlin	Beijing Institute of Technology
Paper VI125-03.1
PDF · Video · Global Exponential Stability of the Douglas-Rachford Splitting Dynamics
Hassan-Moghaddam, Sepideh	University of Southern California
Jovanovic, Mihailo	University of Southern California
Keywords: Convex optimization, Application of nonlinear analysis and design, Stability of nonlinear systems Abstract: Many modern optimization problems admit a composite form in which the objective function is given by the sum of a smooth term and a nonsmooth regularizer. Such problems can be solved via proximal methods and their variants, including the Douglas-Rachford (DR) splitting algorithm. In this paper, we view the DR splitting flow as a dynamical system and leverage techniques from control theory to study its global stability properties. In particular, for problems with strongly convex objective functions, we utilize the theory of integral quadratic constraints to prove global exponential stability of the ordinary differential equation that governs the evolution of the DR splitting flow. In our analysis, we use the fact that this algorithm can be interpreted as a variable-metric gradient method on the DR envelope and exploit structural properties of nonlinear terms that arise from composition of reflected proximal operators.
Paper VI125-03.2
PDF · Video · A Clique Graph Based Merging Strategy for Decomposable SDPs
Garstka, Michael	University of Oxford
Cannon, Mark	University of Oxford
Goulart, Paul J.	University of Oxford
Keywords: Convex optimization, Large scale optimization problems Abstract: Chordal decomposition techniques are used to reduce large structured positive semidefinite matrix constraints in semidefinite programs (SDPs). The resulting equivalent problem contains multiple smaller constraints on the nonzero blocks (or cliques) of the original problem matrices. This usually leads to a significant reduction in the overall solve time. A further reduction is possible by remerging cliques with significant overlap. The degree of overlap for which this is effective is dependent on the particular solution algorithm and hardware to be employed. We propose a novel clique merging approach that utilizes the clique graph to identify suitable merge candidates for any SDP solver algorithm. We show its performance in combination with a first-order method by comparing it with two existing approaches on selected problems from a benchmark library. Our approach is implemented in the latest version of the conic ADMM-solver COSMO.
Paper VI125-03.3
PDF · Video · Accelerated First-Order Continuous-Time Algorithm for Solving Convex-Concave Bilinear Saddle Point Problem
Zeng, Xianlin	Beijing Institute of Technology
Dou, Lihua	Beijing Institute of Technology
Chen, Jie	Beijing Institue of Technology
Keywords: Convex optimization, Lyapunov methods, Application of nonlinear analysis and design Abstract: First-order methods have simple structures and are of great importance to big data problems because first-order methods are easy to implement in a distributed or parallel way. However, in the worst cases, first-order methods often converge at a rate O(1/t), which is slow. This paper considers a class of convex-concave bilinear saddle point problems and proposes an accelerated first-order continuous-time algorithm. We design the accelerated algorithm by using both increasing and decreasing damping coefficients in the saddle point dynamics. If parameters of the proposed algorithm are proper, the algorithm owns O(1/t^2) convergence without any strict or strong convexity requirement. Finally, we apply the algorithm to numerical examples to show the superior performance of the proposed algorithm over existing ones.
Paper VI125-03.4
PDF · Video · Privacy against State Estimation: An Optimization Framework Based on the Data Processing Inequality
Murguia, Carlos	Eindhoven University of Technology
Shames, Iman	University of Melbourne
Farokhi, Farhad	The University of Melbourne
Nesic, Dragan	Univ of Melbourne
Keywords: Convex optimization, Randomized algorithms, Probabilistic robustness Abstract: Information about the system state is obtained through noisy sensor measurements. This data is coded and transmitted to a trusted user through an unsecured communication network. We aim at keeping the system state private; however, because the network is not secure, opponents might access sensor data, which can be used to estimate the state. To prevent this, before transmission, we randomize coded sensor data by passing it through a probabilistic mapping, and send the corrupted data to the trusted user. Making use of the data processing inequality, we cast the synthesis of the probabilistic mapping as a convex program where we minimize the mutual information (our privacy metric) between two estimators, one constructed using the randomized sensor data and the other using the actual undistorted sensor measurements, for a desired level of distortion -- how different coded sensor measurements and distorted data are allowed to be.
Paper VI125-03.5
PDF · Video · Decomposed Structured Subsets for Semidefinite Optimization
Miller, Jared	Northeastern University
Zheng, Yang	Harvard University
Sznaier, Mario	Northeastern University
Papachristodoulou, Antonis	Univ of Oxford
Keywords: Convex optimization, Relaxations, Sum-of-squares Abstract: Semidefinite programs (SDPs) are important computational tools in controls, optimization, and operations research. Standard interior-point methods scale poorly for solving large-scale SDPs. With certain compromise of solution quality, one method for scalability is to use the notion of structured subsets (e.g. diagonally-dominant (DD) and scaled-diagonally dominant (SDD) matrices), to derive inner/outer approximations for SDPs. For sparse SDPs, chordal decomposition techniques have been widely used to derive equivalent SDP reformations with smaller PSD constraints. In this paper, we investigate a notion of decomposed structured subsets by combining chordal decomposition with DD/SDD approximations. This notion takes advantage of any underlying sparsity via chordal decomposition, while embracing the scalability of DD/SDD approximations. We discuss the applications of decomposed structured subsets to semidefinite optimization. Basis pursuit for refining DD/SDD approximations are also incorporated into the decomposed structured subset framework, and numerical performance is improved as compared to standard DD/SDD approximations. These results are demonstrated on H-infinity norm estimation problems for networked systems.
Paper VI125-03.6
PDF · Video · Sum-Of-Squares Based Computation of a Lyapunov Function for Proving Stability of a Satellite with Electromagnetic Actuation
Misra, Rahul	Aalborg University
Wisniewski, Rafal	Aalborg University
Karabacak, Ozkan	Aalborg University
Keywords: Sum-of-squares, Control of constrained systems, Lyapunov methods Abstract: This work focuses on the computation of a candidate Lyapunov function for a Low Earth Orbit satellite which is actuated using only magnetorquers. A satellite having only electromagnetic actuation is not controllable when the magnetic moment produced by the magnetorquers is parallel to the geomagnetic field. Further, the dynamics of the system are periodic due to the periodic nature of the geomagnetic field. Previously, a locally stable Proportional-Derivative control has been designed for such a satellite. In this work, we have found a polynomial candidate Lyapunov function for the resultant closed loop system using Sum-of-Squares (SoS) polynomials and Putinar's Positivstellensatz. Unlike previous applications of SoS techniques on rigid bodies, the kinematics have been defined using unit quaternions. The unit quaternions have a well-known advantage of being a singularity free representation of attitude kinematics with only a single constraint. The unit quaternion constraint has been ensured using semialgebraic sets. Furthermore, special emphasis has been placed on the verification of the candidate Lyapunov function and we have simulated the closed loop system with the candidate Lyapunov function.
Paper VI125-03.7
PDF · Video · A Multi-Commodity Flow Problem for Fair Resource Allocation in Multi-Path Video Delivery Networks
De Cicco, Luca	Politecnico Di Bari
Manfredi, Gioacchino	Politecnico Di Bari
Palmisano, Vittorio	Politecnico Di Bari
Mascolo, Saverio	Politecnico Di Bari
Keywords: Convex optimization Abstract: Video streaming services employ the Internet to distribute content to an ever-increasing number of concurrent viewers. Leading video platforms employ a delivery architecture employed which requires players to run a control algorithm dynamically choosing the video bitrate to match the time-varying network bandwidth and avoid playback interruptions due to buffer underruns. Such an algorithm is generally designed to (selfishly) improve the quality individually perceived by users. This control architecture leads, in the optimal case, to maximize the average quality perceived collectively by all users and not to a distribution of resources that is fair in terms of user perceived quality. We argue that video service providers should manage their delivery network to address fairness issues to gracefully degrade the perceived quality equally for all users when resources become scarce. Even though the general problem of providing a fair level of perceived quality does not scale with the cumbersome number of concurrent users, this paper shows that the Multi-Commodity Flow Problem (MCFP) optimization framework is a proper and efficient tool to address this open issue. First, we show how to cast the resource allocation problem to an MCFP and then we propose a strategy to make the resulting problem tractable for video distribution platforms serving massive audiences. The performance of the proposed optimal fair resource allocation strategy is assessed using realistic simulations involving thousands of concurrent video sessions on a real network topology by varying both the total load on the network and key system parameters.

VI125-04
Robust Control and Estimation	Regular Session
Chair: Scherer, Carsten W.	Department of Mathematics, University of Stuttgart
Co-Chair: Zanon, Mario	IMT Institute for Advanced Studies Lucca
Paper VI125-04.1
PDF · Video · Robust Control Design for Linear Systems Via Multiplicative Noise
Gravell, Benjamin	University of Texas at Dallas
Mohajerin Esfahani, Peyman	TU Delft
Summers, Tyler	University of Texas at Dallas
Keywords: Robust controller synthesis, Robust control (linear case), Uncertainty descriptions Abstract: Robust stability and stochastic stability have separately seen intense study in control theory for many decades. In this work we establish relations between these properties for discrete-time systems and employ them for robust control design. Specifically, we examine a multiplicative noise framework which models the inherent uncertainty and variation in the system dynamics which arise in model-based learning control methods such as adaptive control and reinforcement learning. We provide results which guarantee robustness margins in terms of perturbations on the nominal dynamics as well as algorithms which generate maximally robust controllers.
Paper VI125-04.2
PDF · Video · Controller Synthesis to Achieve Robust Stability against Bicoprime Factor Uncertainty: An LMI Approach
Tsiakkas, Mihalis	University of Cyprus
Lanzon, Alexander	University of Manchester
Keywords: Robust controller synthesis, Robust linear matrix inequalities, Uncertainty descriptions Abstract: In this paper, a Linear Matrix Inequality approach is presented for synthesizing controllers that robustly stabilize a plant against Bicoprime Factor uncertainty. Following the development of the general case, non-normalized results, the usefulness of normalized Bicoprime Factorizations is studied in this context and shown to be beneficial in deducing the existence of a robustly stabilizing controller for given robust stability margin. Finally, a numerical example is provided to demonstrate the practical applicability of the developed methodology.
Paper VI125-04.3
PDF · Video · Sequential Processing and Performance Optimization in Nonlinear State Estimation
Battilotti, Stefano	Univ. La Sapienza
Keywords: Robust estimation, Observer design, Nonlinear observers and filter design Abstract: We propose a framework for designing observers for noisy nonlinear systems with global convergence properties and performing robustness and noise sensitivity. Our state observer is the result of the combination of a state norm estimator with a bank of Kalman-type filters, parametrized by the state norm estimator. The state estimate is sequentially processed through the bank of lters. In general, existing nonlinear state observers are responsible for estimation errors which are sensitive to model uncertainties and measurement noise, depending on the initial state conditions. Each Kalman-type filter of the bank contributes to improve the estimation error performances to a certain degree in terms of sensitivity with respect to noise and initial state conditions. A sequential processing algorithm for performance optimization is given and simulations show the effectiveness of these sequential filters.
Paper VI125-04.4
PDF · Video · Dimensionality Reduction of Sliced-Normal Distributions
Crespo, Luis G	NASA Langley
Colbert, Brendon	Arizona State University
Kenny, Sean	NASA Langley
Giesy, Daniel	NASA Langley
Keywords: Uncertainty descriptions, Data-based control, Sum-of-squares Abstract: Sliced-Normal (SN) distributions enable the characterization of complex multivariate data as both a vector of possibly dependent random variables and as a semi-algebraic, tightly enclosing set. SNs inject the physical space into a higher dimensional (so-called) feature space using a polynomial mapping. Optimization-based strategies for estimating SNs from data in both physical and feature space were recently developed. The formulations in physical space yield non-convex optimization programs whose solutions exhibit the best performance, whereas the formulations in feature space yield either an analytical solution or a convex program thereby facilitating their application to higher dimensional datasets. In both cases, however, the exponential dependency of the number of optimization variables on the dimension of feature space limits their applicability to moderately sized problems. In this paper we propose two strategies to mend for this deficiency. The first technique identifies groups of highly interdependent parameters in a distribution-free framework. This classification enables estimating a SN for any of such groups independently of the other groups thereby reducing the computational complexity of the estimation process. The second technique reduces the dimension of feature space by only retaining the monomials of the polynomial mapping that significantly increase the likelihood of the data while leveraging SNs estimated in lower dimensions.
Paper VI125-04.5
PDF · Video · Dynamic Output Disturbance Models for Robust Constraint Satisfaction
Mulagaleti, Sampath Kumar	IMT School of Advanced Studies Lucca
Zanon, Mario	IMT Institute for Advanced Studies Lucca
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Uncertainty descriptions, Predictive control, Constrained control Abstract: Robust control methods such as tube-based robust model predictive control (MPC) schemes, developed to provide robust constraint satisfaction guarantees, require an uncertain model of the controlled plant. In this paper, we present a method to identify such models, along with a robust MPC scheme with reduced conservativeness tailored to employ them. We consider input-output models in which uncertainty is modeled as an additive disturbance on the output. Reduction of conservativeness is achieved by identifying the dynamics generating the disturbance. Standard linear system identification methods are used in the model development procedure, with residuals from the identification process extracted to characterize uncertainty in a set-membership setting. The effectiveness of a using dynamic output disturbance models is demonstrated through simulations.

VI125-05
Robust Control Applications	Regular Session
Chair: Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Co-Chair: Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Paper VI125-05.1
PDF · Video · Robust Decentralized Switching Control of UAVs Using UWB-Based Localization and Cooperation
Jansch-Porto, Joao Paulo	Univ. of Illinois at Urbana-Champaign
Dullerud, Geir E.	Univ. of Illinois at Urbana-Champaign
Keywords: Robust control applications, Decentralized control, Control of switched systems Abstract: In this paper, we implement a switched decentralized controller, along with a proposed communication protocol, to control a nested multi-agent system without the need for a centralized processing node. More specifically, we apply a recently developed method for switched systems synthesis, which gives exact conditions for existence of a block-lower triangular path-dependent controller with l_2-induced norm performance. The synthesis conditions are given in the form of a semidefinite program (SDP), which is computed offline for a predefined switching sequence. Each robot is equipped with a ultra-wideband (UWB) unit, which allows it to both estimate its position and communicate with other robots.
Paper VI125-05.2
PDF · Video · Robust Control of a Lightweight Structure for Digital Fabrication
Stürz, Yvonne Rebecca	University of California Berkeley
Iannelli, Andrea	ETH Zurich
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Keywords: Robust control applications, Robust control (linear case), Robust controller synthesis Abstract: For a material efficient construction process of lightweight concrete shells, tensioned cable nets can be used as a supporting formwork. In order to guarantee the mechanical stability of the shells, tight tolerances in their form need to be met. To this end, methods have recently been proposed to readjust the form of the cable net on the construction site. This paper proposes a novel view on the cable net model as a dynamical system and derives robust control approaches based on H-infinity and mu synthesis. Both approaches can account for input uncertainties and external disturbances. The mu controller additionally is robust against the uncertain model parameters, which makes their precise identification unnecessary. The mu synthesis also provides a priori bounds on the allowable fabrication tolerances of the cable net in order to guarantee robust performance of the closed-loop system. The resulting LTI controllers can be applied to the system without expert knowledge about the system model or the underlying optimization. The effectiveness of the controllers is demonstrated in numerical experiments.
Paper VI125-05.3
PDF · Video · A Stochastic Optimization Approach to the Aggregation of Electric Vehicles for the Provision of Ancillary Services
Rossini, Matteo	Università Degli Studi Di Milano
Sandroni, Carlo	RSE SpA
Vignali, Riccardo	RSE SpA
Keywords: Robust control applications, Stochastic optimal control problems, Convex optimization Abstract: We address the problem of the optimal management of an aggregate of electric vehicles (EVs) for the provision of ancillary services to the grid, by means of a bidirectional vehicle-to-grid (V2G) infrastructure. We consider the case of a charging point operator that acts as an aggregator and has to optimally choose the charge/discharge power profile of each vehicle so as to maximize its profits, while satisfying technical constraints and final user constraints (the latter expressed as a minimum desired charge for motion). In this setting the aggregator can operate on both an energy market and an ancillary services market: in the latter, the deployed power depends on a signal received by the aggregator after the market closing time; this signal can be discrete or continuous. We formulate the problem via stochastic programming, under the assumptions of optimal bidding strategy and known vehicle arrivals and departures. We obtain, via mixed-integer linear programming, an exact robust counterpart of the constraints and an expected value cost function, which is exact if the signal is discrete. If the signal is continuous, the cost function varies depending on the probability distribution of the signal and could require an approximation to obtain a computationally tractable formulation. We then show that, in the case of uniform probability, an efficient formulation can be obtained by introducing a negligible approximation of the cost function; a numerical example shows the validity of the approach.
Paper VI125-05.4
PDF · Video · Joint Controller and Detector Design against Data Injection Attacks on Actuators
C. Anand, Sribalaji	Uppsala University
Teixeira, André M.H.	Uppsala University
Keywords: Robust controller synthesis, Observer design, Fault-tolerant Abstract: This paper addresses the issue of data injection attacks on actuators in control systems. Considering attacks that aim at maximizing impact while remaining undetected, the paper revisits the recently proposed output-to-output gain, which is compared to classical sensitivity metrics such as H_infty and H_-. In its original formulation, the output-to-output gain is unbounded for strictly proper systems. This limitation is further investigated and addressed by modifying the performance output of the system and ensuring that the system from attack signal to performance output is also strictly proper. With this system description, and by using the theory of dissipative systems, a Bi-linear Matrix Inequality (BMI) is formulated for system design. Using this BMI, a design algorithm is proposed based on the heuristic of alternating minimization. Through numerical simulations of the proposed algorithm, it is found that the output-to-output gain presents advantages over the other metrics: the effect of the attack is reduced in the performance output and increased in the detection output in a relatively large spectrum of frequencies.
Paper VI125-05.5
PDF · Video · Zonotopic Set-Membership Estimation for Switched Systems Based on W_i-Radius Minimization: Vehicle Application
Ifqir, Sara	IBISC Laboratory, Evry Val d'Essonne University
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Ichalal, Dalil	IBISC-Lab, Evry Val d'Essonne University
Ait Oufroukh, Naima	IBISC
Mammar, Said	University Evry Val D'Essonne
Keywords: Robust estimation, Uncertainty descriptions, Robust linear matrix inequalities Abstract: This work is devoted to the problem of guaranteed set-membership state estimation based on zonotopes for discrete-time switched systems with bounded uncertainties and unknown inputs. The additive uncertainties in this contribution are treated using the so called W_i-Radius. The size of the zonotope which contains the real system state is decreased at each sample time. The complete solution procedure is formulated as a LMI-constrained optimization problem. The proposed design is applied to the robust state estimation of vehicle lateral dynamics state. Simulation results based on real data demonstrate the performance of the proposed method.
Paper VI125-05.6
PDF · Video · Finite Time Horizon Analysis of Launch Vehicles under Mass and Thrust Uncertainty
Biertümpfel, Felix	University of Nottingham
Bennani, Samir	European Space Agency
Pfifer, Harald	University of Nottingham
Keywords: Robustness analysis, Time-varying systems, Aerospace Abstract: This paper presents a new approach to include thrust and mass uncertainties in the worst case loads analysis of launch vehicles during the atmospheric ascend. The analysis is based on recent results on the worst case gain computation of uncertain, finite time horizon linear time varying (LTV) systems. Representing the uncertainties as integral quadratic constraints, the worst case gain condition can be formulated as a parameterized Riccati differential equation (RDE). While this framework allows including certain parametric uncertainties, e.g., aerodynamic uncertainties, it is not straightforward to include thrust uncertainty in the launcher analysis. The reason being that there is an inherent coupling between the thrust and the mass of the launcher, such that any uncertainty in the thrust also effects the mass of the launcher. Further, both thrust and mass have a direct effect on the launch trajectory, whereas the LTV model is obtained via linearization along the nominal trajectory. Hence, it is no longer valid, for large perturbations of the launch trajectory. The former issue is resolved in the paper by including a mass state in the launcher model and treating the thrust uncertainty as an external disturbance. For the latter problem it is proposed to cover a set of launch trajectories with a dynamic uncertainty. Using the robust LTV framework, a worst case aerodynamic loads analysis under thrust uncertainty and wind disturbances is performed in this paper. The results are compared to a Monte Carlo simulation on a high fidelity nonlinear launcher model.

VI126
Design Methods - Distributed Parameter Systems
VI126-01 Control of Flexible Structures and Fluid-Structure Interactions   Invited Session, 6 papers
VI126-02 Estimation and Control of PDE Systems   Invited Session, 10 papers
VI126-03 Hamiltonian Methods for the Control of Multidomain Distributed Parameter Systems   Invited Session, 6 papers
VI126-04 Observers and Output Feedbacks for Systems Containing PDEs   Invited Session, 9 papers
VI126-05 Distributed Parameter System   Regular Session, 19 papers
VI126-06 Distributed Parameter Systems Applications   Regular Session, 9 papers

VI126-01
Control of Flexible Structures and Fluid-Structure Interactions	Invited Session
Chair: Le Gorrec, Yann	FEMTO-ST, ENSMM
Co-Chair: Zwart, Hans	University of Twente
Organizer: Le Gorrec, Yann	FEMTO-ST, ENSMM
Organizer: Zwart, Hans	University of Twente
Organizer: Weiss, George	Tel Aviv University
Organizer: Zhao, Xiaowei	University of Warwick
Paper VI126-01.1
PDF · Video · Non-Linear Damping for Scattering-Passive Systems in the Maxwell Class (I)
Singh, Shantanu	Tel Aviv University
Weiss, George	Tel Aviv University
Tucsnak, Marius	University of Bordeaux
Keywords: Infinite-dimensional systems, well-posed distributed parameter systems, semigroup and operator theory Abstract: We start from a special class of scattering passive linear infinite-dimensional systems introduced in Staffans and Weiss (SIAM J. Control and Opt., 2012). This class is called the Maxwell class of systems, because it includes the scattering formulation of Maxwell's equations, as well as various wave and beam equations. We generalize this class by allowing a nonlinear damping term. While the system may have unbounded linear damping (for instance, boundary damping), the nonlinear damping term N is "bounded" in the sense that it defined on the whole state space (but no actual continuity assumption is made on N. We show that this new class of nonlinear infinite dimensional systems is well-posed and scattering passive. Our approach uses the theory of maximal monotone operators and the Crandall-Pazy theorem about nonlinear contraction semigroups, which we apply to a Lax-Phillips type nonlinear semigroup that represents the whole system, with input and output signals.
Paper VI126-01.2
PDF · Video · Data-Driven Structural Control of Monopile Wind Turbine Towers Based on Machine Learning (I)
Zhang, Jincheng	University of Warwick
Zhao, Xiaowei	University of Warwick
Wei, Xing	University of Warwick
Keywords: Data-based control, control of fluid flows and fluids-structures interactions, Energy systems Abstract: This paper studies the data-driven structural control of monopile wind turbine towers based on machine learning approach, by using an active tuned mass damper (TMD) located in the nacelle. The adaptive dynamic programming (ADP) approach is employed to obtain the optimal controller which is derived on the modern large-scale machine learning platform Tensorflow. The proposed network structure includes three simple three-layer neural networks (NNs), i.e. a plant network, a critic network, and an action network. The plant network is used to capture the fully nonlinear dynamics of the structural system while the action network is used to approximate the optimal controller. Their training requires the gradient information flowing through the whole network. The automatic differentiation is used in this paper for all the gradient derivations, which greatly improves the employed ADP algorithm's ability in solving complex practical problems. The simulation results of structural control of monopile turbine towers show that on average the active TMD achieves 15% performance improvement on tower fatigue load reduction over a passive TMD, with small active power consumption (less than 0.24% of the turbine's nominal power production). Besides, the controller design considers the trade-off between control performance and power consumption.
Paper VI126-01.3
PDF · Video · Modal-Based Model Predictive Control of Multibody Very Flexible Structures (I)
Artola, Marc	Imperial College London
Wynn, Andrew	Imperial College London
Palacios, Rafael	Imperial College Lonodn
Keywords: Nonlinear predictive control, Model reduction, Control of interconnected systems Abstract: A model predictive control strategy for flexible multibody structures undergoing large deformations is presented. The dynamics of such structures are highly nonlinear, with local effects introduced by the joint constraints and distributed effects arising from the structure's increased flexibility, from which arbitrary large deflections and rotations can be expected. A modal-based nonlinear reduced order model of an intrinsic description (based on velocities and strains) of geometrically-exact beams is used to underpin the internal model. This low-order model, constructed using the linearised eigenfunctions of the constrained structures, is a set of nonlinear ordinary differential equations in time (i.e. no algebraic equations are present) thus facilitating analysis and demonstrating successful control. Numerical examples are presented based on a very flexible hinged two-link manipulator.
Paper VI126-01.4
PDF · Video · Observer Based Nonlinear Control of a Rotating Flexible Beam (I)
Mattioni, Andrea	Femto-St
Toledo, Jesus	FEMTO-ST (Franche-Comté électronique Mécanique Thermique Et Opti
Le Gorrec, Yann	FEMTO-ST, ENSMM
Keywords: Observer design, Asymptotic stabilization Abstract: This paper presents an observer based nonlinear control for a flexible beam clamped on a rotating inertia. The considered model is composed by a set of Partial Differential Equations (PDEs) interconnected with an Ordinary Differential Equation (ODE), with control input in the ODE. The control problem consists in orienting the beam at the desired position, maintaining the flexible vibrations as low as possible. To this end, it is presented a nonlinear controller that depends on the beam's state. An Observer is designed to reconstruct the infinite dimensional state, and the estimated state is used in the nonlinear controller instead of the real one. Assuming well-posedness of the closed loop system, it is shown the exponential convergence of the estimated state, and the asymptotic stability of the closed loop system. Numerical simulations are presented to characterize the closed loop behaviour with different choices of observer's parameters.
Paper VI126-01.5
PDF · Video · Time Domain Approach Toward the Calculation of the Compliance Function of Flexible Motion Systems (I)
Sharifi, Seyedeh Fatemeh	University of Twente
Zwart, Hans	University of Twente
Keywords: model reduction of distributed parameter systems, Time-invariant systems, Model following control Abstract: For high-performance distributed parameter motion systems, the dynamics introduced by structural flexibilities need to be considered. Especially at the low frequency region, where most of the energy of the commonly used reference setpoint is concentrated. The contribution of non-rigid body modes at low frequencies is called the compliance function of the system. It is representative for the quasi-static behaviour of the whole non-rigid body modes. This work proposes a new method for the calculation of the compliance function. It is based on employing the differential equation representation for the flexible structure. The approach is validated for a standard damped second order ODE and a one-dimensional flexible model, i.e., the Euler-Bernoulli beam. We show that we get a major reduction in calculation in comparison with the zero frequency response calculation. The extension of this approach to the general PDE's will be the scope of the future works.
Paper VI126-01.6
PDF · Video · Well-Posedness and Input-Output Stability for a System Modelling Rigid Structures Floating in a Viscous Fluid (I)
Vergara-Hermosilla, Gaston	Universite De Bordeaux
Matignon, Denis	ISAE
Tucsnak, Marius	University of Bordeaux
Keywords: control of fluid flows and fluids-structures interactions, Infinite-dimensional systems, semigroup and operator theory Abstract: We study a PDE based linearized model for the vertical motion of a solid floating at the free surface of a shallow viscous fluid. The solid is controlled by a vertical force exerted via an actuator. This force is the input of the system, whereas the output is the distance from the solid to the bottom. The first novelty we bring in is that we prove that the governing equations define a well-posed linear system. This is done by considering adequate function spaces and convenient operators between them. Another contribution of this work is establishing that the system is input-output stable. To this aim, we give an explicit form of the transfer function and we show that it lies in the Hardy space H-infinity of the right-half plane.

VI126-02
Estimation and Control of PDE Systems	Invited Session
Chair: Demetriou, Michael A.	Worcester Polytechnic Institute
Co-Chair: Meurer, Thomas	Christian-Albrechts-University Kiel
Organizer: Demetriou, Michael A.	Worcester Polytechnic Institute
Organizer: Burns, John A	Virginia Tech
Paper VI126-02.1
PDF · Video · Stabilization of Burgers' Equation by Constrained Control (I)
Kang, Wen	University of Science and Technology Beijing
Fridman, Emilia	Tel-Aviv Univ
Keywords: stability of distributed parameter systems, Controller constraints and structure, Observer design Abstract: The work addresses constrained control of Burgers' equation by using point measurements. We suggest to divide the interval [0,1] into several subdomians, where an observer-based distributed-in-domain point control law is designed to stabilize the system. Constructive conditions are derived to ensure that the resulting closed-loop system is regionally exponentially stable. A numerical example demonstrates the efficiency of the results.
Paper VI126-02.2
PDF · Video · Dissipative PI Control for a Class of Semilinear Heat Equations with Actuator Disturbance (I)
Schaum, Alexander	Kiel University
Feketa, Petro	Christian-Albrechts-University Kiel
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: control of heat and mass transfer systems, Output feedback control, Disturbance rejection Abstract: The problem of dissipative proportional-integral (PI) output-feedback control for a class of semilinear heat equations with actuator disturbance is addressed. Sufficient conditions for strict dissipativity in the state and thus exponential stability of the closed-loop system are derived which are stated in terms of the dissipavity properties of the nonlinearity, the controller gains and the actuator and sensor shape functions (i.e., their form and localization). Based on these conditions a dissipation maximization procedure is proposed to appropriately choose the degrees of freedom using optimization algorithms. Numerical simulation results illustrate the performance of the proposed controller.
Paper VI126-02.3
PDF · Video · Event-Triggered Varying Speed Limit Control of Stop-And-Go Traffic (I)
Espitia, Nicolas	CNRS, CRIStAL UMR 9189
Yu, Huan	University of California, San Diego
Krstic, Miroslav	Univ. of California at San Diego
Keywords: backstepping control of distributed parameter systems, stability of distributed parameter systems Abstract: This paper develops event-triggered boundary control strategies for varying speed limit (VSL) located at a freeway segment. The stop-and-go traffic oscillations are suppressed by regulating the velocity of vehicles that leave the segment. The controlled velocity signal is only updated when a event triggering condition is satisfied. Compared with the continuous input signal, the event-based controller presents as a more realistic setting to implement by VSL on a digital platform which allows the adaptation time for drivers to follow the advisory speed. The traffic dynamics of density and velocity are described with linearized AW-Rascle-Zhang (ARZ) macroscopic traffic partial differential equation (PDE) model which results in a 2 times 2 hyperbolic system. The event-triggered boundary controllers rely on the emulation of the full state backstepping boundary feedback and two different Lyapunov-based event-triggered strategies to determine the time instants at which the control value must be sampled/updated. One of the event-triggered strategies makes use of a dynamic triggering condition under which it is possible to state the existence of a uniform minimal dwell-time (independent of initial conditions). The exponential stability under event-triggered control is achieved and validated with numerical simulations.
Paper VI126-02.4
PDF · Video · Suppression of Oscillations in Two-Class Traffic by Full-State Feedback (I)
Burkhardt, Mark	University of Stuttgart, Institute for System Dynamics
Yu, Huan	University of California, San Diego
Krstic, Miroslav	Univ. of California at San Diego
Keywords: backstepping control of distributed parameter systems, control of hyperbolic systems and conservation laws, control of fluid flows and fluids-structures interactions Abstract: This paper develops a full-state feedback controller that damps out oscillations in traffic density and traffic velocity whose dynamical behavior is governed by the linearized two-class Aw-Rascle (AR) model. Thereby, the traffic is considered to be in the congested regime and subdivided in two classes whereas each class represents vehicles with the same size and driver's behavior. The macroscopic second-order two-class AR model consists of four first order hyperbolic partial differential equations (PDEs) and introduces a concept of area occupancy to depict the mixed density of two-class vehicles in the traffic. Moreover, the linearized model equations show heterodirectional behavior with both positive and negative characteristic speeds in the congested regime. The control objective is to achieve convergence to a constant equilibrium in finite time. The control input is realized by ramp metering acting at the outlet of the considered track section. The backstepping method is employed to design full-state feedback for the 4x4 hyperbolic PDEs. The performance of the full-state feedback controller is verified by simulation.
Paper VI126-02.5
PDF · Video · A Backstepping-Based Observer for Estimation of Thermoacoustic Oscillations in a Rijke Tube with In-Domain Measurements (I)
de Andrade, Gustavo Artur	Federal University of Santa Catarina
Vazquez, Rafael	Universidad De Sevilla
Keywords: control of hyperbolic systems and conservation laws, backstepping control of distributed parameter systems, control and estimation of wave equations and systems of elasticity Abstract: This paper presents an observer design for the estimation of thermoacoustic instabilities in a Rijke tube. To study this problem, we consider that the acoustic dynamics is represented by the wave equation with a point source term representing the heat release. In turn, the heat release dynamics is given by a first-order ordinary differential equation (ODEs). The observer, whose design is based on the backstepping methodology, relies on measurements of acoustic pressure and velocity at an arbitrary point of the domain. The design employs a folding transformation (with two folds) around the measurements and the heat release point, allowing to write the system into a form with more states but boundary measurements and ODE couplings. Then, we formulate a well-posed and invertible integral transformation with both triangular and full terms that maps the observer error dynamics into an exponentially stable target system. The theoretical results were tested through numerical simulations in order to show the effectiveness of the design.
Paper VI126-02.6
PDF · Video · Decentralized Predictor Output Feedback for Large-Scale Systems with Large Delays (I)
Zhu, Yang	Zhejiang University
Fridman, Emilia	Tel-Aviv Univ
Keywords: Decentralized control, Systems with time-delays, Linear systems Abstract: A majority of existing literature on time-delay systems focus on the robust stability of a single plant with respect to a "small" delay. This paper proposes a decentralized predictor-based feedback to compensate large delays for large-scale interconnected systems. The full-state of each subsystem is assumed to be unmeasurable and the observer-based output feedback is employed. Two methods are used to tackle the large delays: the backstepping-based partial differential equation (PDE) method is employed for continuous-time control, which derives simpler linear matrix inequality (LMI) conditions and manages with larger delays, whereas the reduction-based ordinary differential equation (ODE) method is applied to sampled-data implementation under continuous-time measurement. Instead of treating the large-scale systems as a whole, a decentralized Lyapunov-Krasovskii method is presented to guarantee the exponential stability of the large-scale systems under decentralized predictors.
Paper VI126-02.7
PDF · Video · A Psychological Approach for the Path Planning of Human Evacuations in Contaminated Indoor Environments (I)
Dings, Amanda	Worcester Polytechnic Institute
Gatsonis, Constantina	Worcester Polytechnic Institute
Demetriou, Michael A.	Worcester Polytechnic Institute
Keywords: motion planning for distributed parameter systems, infinite-dimensional multi-agent systems and networks Abstract: This work considers a level-set based algorithm for guiding evacuees in indoor environments. The algorithm considers the accumulated inhalation of a hazardous substance such as carbon monoxide and attempts to provide an optimal path to ensure survivability. The algorithm also considers psychological decision making of evacuees. The most significant psychological contribution to overall evacuation time is the tendency of evacuees to underreact, causing decision making delays. During an emergency, evacuees with high risk perception will be directly incentivized to make evacuation decisions, while those with low risk perception will likely continue to delay decision making. This work models this phenomenon by simulating an initial accumulated concentration before the evacuee begins moving. Earlier work has shown that level-set based paths are much more likely to lead an evacuee to safety than a constant angle path, because they ensure the evacuee’s peak exposure to the hazardous substance remains low. After including the psychological delay, this work supports these results. Additionally, a higher initial concentration (i.e. a longer psychological delay) decreases the chances of survival more significantly than does a higher instantaneous concentration of the field itself.
Paper VI126-02.8
PDF · Video · Sensor Selection with Nonsmooth Design Criteria Based on Semi-Infinite Programming (I)
Ucinski, Dariusz	University of Zielona Gora
Keywords: system identification and adaptive control of distributed parameter systems, thermal and process control applications of distributed parameter systems, Convex optimization Abstract: A problem of optimal node activation in large-scale sensor networks is considered. The resulting measurements are supposed to be used to estimate unknown parameters of a spatiotemporal process described by a partial differential equation. In this setting, the sensor subset selection problem may quickly become computationally intractable when an excessively complex sensor location algorithm is employed. The is even more pronounced when the design criterion is nondifferentiable. A vital example of this criterion is the sum of an arbitrary number of smallest eigenvalues of the Fisher information matrix, being a generalization of the well-known E-optimality criterion. A simple branch-and-bound algorithm is exposed here to maximize this criterion. Its key component to produce upper bounds to the maximum of the objective function implements a relaxation procedure for solving semi-infinite programming problems. It alternates between solving a linear programming subproblem and evaluation of the eigenvalues and eigenvectors of the current information matrix, which makes it extremely easy to implement. The paper is complemented with a numerical example of computing actual sensor locations.
Paper VI126-02.9
PDF · Video · Nonlinearity Measures for Distributed Parameter and Descriptor Systems (I)
Reyero-Santiago, Pedro	Universitat Politècnica De Catalunya
Ocampo-Martinez, Carlos	Universitat Politecnica De Catalunya (UPC)
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Braatz, Richard D.	Massachusetts Institute of Technology
Keywords: Infinite-dimensional systems, thermal and process control applications of distributed parameter systems Abstract: Control design and state estimation are usually more straightforward for linear than for nonlinear dynamical systems, which has motivated the development of methods for quantifying the extent of nonlinearity in dynamical systems. Although many well-defined methods have been proposed for systems described by ordinary differential equations, such methods are not as well explored for dynamical systems described by PDEs and descriptor systems that represent most chemical processes. This paper reviews, discusses, and compares methods for the definition and computation of nonlinearity measures. The measures are categorized in terms of open- vs. closed-loop control topologies, theoretical vs. numerically computation, state transformation dependency, input scaling dependency, linearization vs. optimized linear modeling vs. average linear modeling, applicability to unstable dynamical systems, and applicability to the right-hand side of the state equation or to input-output relationships. Then extensions of the nonlinearity measures are discussed for dynamical systems described by coupled differential, integral, and algebraic equations, often referred to as descriptor/singular systems.
Paper VI126-02.10
PDF · Video · Event-Triggered Backstepping Control of 2*2 Hyperbolic PDE-ODE Systems (I)
Wang, Ji	University of California, San Diego
Krstic, Miroslav	Univ. of California at San Diego
Keywords: backstepping control of distributed parameter systems, Discontinuous control, Infinite-dimensional systems Abstract: Motivated by vibration control of a mining cable elevator avoiding frequent actions of the actuator which is a massive hydraulic cylinder at the head sheave, we present an event-triggered backstepping boundary controller for a 2 times 2 coupled hyperbolic PDE-ODE system. A two-step design is proposed including the design of a low-pass-filter-based backstepping boundary stabilization law and the sequent design of an event-trigger mechanism. The proof of the existence of a nonzero minimal dwell-time between two triggering times, and the exponential stability result of the event-based closed-loop system are given in this paper.

VI126-03
Hamiltonian Methods for the Control of Multidomain Distributed Parameter Systems	Invited Session
Chair: Le Gorrec, Yann	FEMTO-ST, ENSMM
Co-Chair: Ramirez, Hector	Universidad Federico Santa Maria
Organizer: Le Gorrec, Yann	FEMTO-ST, ENSMM
Organizer: Ramirez, Hector	Universidad Federico Santa Maria
Paper VI126-03.1
PDF · Video · Partitioned Finite Element Method for Structured Discretization with Mixed Boundary Conditions (I)
Brugnoli, Andrea	ISAE-SUPAERO
Cardoso-Ribeiro, Flavio Luiz	Instituto Tecnológico De Aeronáutica (ITA)
Haine, Ghislain	Institut Superieur De l’Aeronautique Et De L’Espace
Kotyczka, Paul	Technical University of Munich
Keywords: port Hamiltonian distributed parameter systems, control of hyperbolic systems and conservation laws Abstract: The propagation of acoustic waves in a 2D geometrical domain under mixed boundary control is here described by means of the port-Hamiltonian (pH) formalism. A finite element based method is employed to obtain a consistently discretized model. To construct a model with mixed boundary control, two different methodologies are detailed: one employs Lagrange multipliers, the other relies on a virtual domain decomposition to interconnect models with different causalities. The two approaches are assessed numerically, by comparing the Hamiltonian and the state variables norm for progressively refined meshes.
Paper VI126-03.2
PDF · Video · Discrete-Time Control Design Based on Symplectic Integration: Linear Systems (I)
Kotyczka, Paul	Technical University of Munich
Lefevre, Laurent	Univ. Grenoble Alpes
Keywords: Lagrangian and Hamiltonian systems, Digital implementation, Linear systems Abstract: We propose a novel approach to design discrete-time state feedback controllers for sampled control systems with guaranteed stability under arbitrary sampling times that fulfill the Nyquist-Shannon condition. The key idea is borrowed from symplectic integration and backward error analysis of Hamiltonian systems: The closed-loop target system is the discretized version of a continuous-time system with appropriately shaped Hamiltonian, where a symplectic scheme is used for discretization. We adopt this argumentation for a systematic discrete-time design procedure for controllable linear systems based on the implicit midpoint rule. We motivate the approach on the example of two basic linear systems under zero order hold sampling, we show the construction of target systems with desired eigenvalues based on the discrete-time controller canonical form, and we illustrate the quality of the main result on a random sixth order system.
Paper VI126-03.3
PDF · Video · Port Hamiltonian Systems with Moving Interface: A Phase Field Approach (I)
Vincent, Benjamin	Univ Claude Bernard of Lyon
Couenne, Francoise	Univ Lyon, Université Claude Bernard Lyon 1
Lefevre, Laurent	Univ. Grenoble Alpes
Maschke, Bernhard	Univ Claude Bernard of Lyon
Keywords: port Hamiltonian distributed parameter systems, thermal and process control applications of distributed parameter systems Abstract: In this paper, we give a formulation of distributed parameter systems with a moving diffuse interface using the Port Hamiltonian formalism. For this purpose, we suggest to use the phase field modeling approach. In the first part we recall the phase field models, in particular the Cahn-Hilliard and Allen-Cahn equations, and show that they may be in terms of a dissipative Hamiltonian system. In the second part we show how this Hamiltonian model may be extended to a Boundary Port Hamiltonian System and illustrate the construction on the example of crystallization.
Paper VI126-03.4
PDF · Video · An Object-Oriented Library for Heat Transfer Modelling and Simulation in Open Cell Foams (I)
Scheuermann, Tobias Michael	Technical University of Munich
Kotyczka, Paul	Technical University of Munich
Martens, Christian James	Technical University of Munich
Louati, Haithem	LAGEPP, Université Claude Bernard Lyon1
Maschke, Bernhard	Univ Claude Bernard of Lyon
Zanota, Marie-Line	CPE Lyon, Laboratoire De Génie Des Procédés Catalytiques (UMR 5
Pitault, Isabelle	Univ Lyon, Université Claude Bernard Lyon 1, CNRS
Keywords: port Hamiltonian distributed parameter systems, thermal and process control applications of distributed parameter systems, control of heat and mass transfer systems Abstract: Metallic open cell foams have multiple applications in industrial environments, e. g. as catalyst supports in chemical processes. Their regular or heterogeneous microscopic structure determines the macroscopic thermodynamic and chemical properties. We present an object-oriented python library that generates state space models for simulation and control from the microscopic foam data, which can be imported from the image processing tool iMorph. The foam topology and the 3D geometric data are the basis for discrete modeling of the balance laws using the cell method. While the material structure imposes a primal chain complex to define discrete thermodynamic driving forces, the internal energy balance is evaluated on a second chain complex, which is constructed by topological duality. The heat exchange between the solid and the fluid phase is described based on the available surface data. We illustrate in detail the construction of the dual chain complexes, and we show how the structured discrete model directly maps to the software objects of the python code. As a test case, we present simulation results for a foam with a Kelvin cell structure, and compare them to a surrogate finite element model with homogeneous parameters.
Paper VI126-03.5
PDF · Video · Modelling and Structure-Preserving Discretization of Maxwell's Equations As Port-Hamiltonian System (I)
Payen, Gabriel	ISAE SUPAERO
Matignon, Denis	ISAE
Haine, Ghislain	Institut Superieur De l’Aeronautique Et De L’Espace
Keywords: port Hamiltonian distributed parameter systems, Lagrangian and Hamiltonian systems, Infinite-dimensional systems Abstract: The modelling and discretization of the boundary controlled 3D Maxwell’s equations as a port-Hamiltonian system is addressed. The proposed scheme, based on the Partitioned Finite Element Method (PFEM) originally proposed in [Cardoso-Ribeiro et al., 2018], preserves the Dirac structure at the discrete level. Two types of damping phenomena are taken into account: Joule's effect, and a matrix-valued impedance at the boundary, both being preserved by PFEM, as presented in [Serhani et al., 2019].
Paper VI126-03.6
PDF · Video · Passive Observers for Distributed Port-Hamiltonian Systems (I)
Toledo, Jesus	FEMTO-ST (Franche-Comté électronique Mécanique Thermique Et Opti
Ramirez, Hector	Universidad Federico Santa Maria
Wu, Yongxin	ENSMM / Université Bourgogne Franche-Comté
Le Gorrec, Yann	FEMTO-ST, ENSMM
Keywords: Observer design, port Hamiltonian distributed parameter systems Abstract: The observer design for 1D boundary controlled infinite-dimensional systems is addressed using the port-Hamiltonian approach. The observer is defined by the same partial differential equations as the original system and the boundary conditions depend on the available information from sensors and actuators. The convergence of the observers is proved to be asymptotically or exponentially under some conditions. The vibrating string and the Timoshenko beam are used to illustrate the observer convergence in different scenarios.

VI126-04
Observers and Output Feedbacks for Systems Containing PDEs	Invited Session
Chair: Ahmed-Ali, Tarek	Université De Caen Normandie
Co-Chair: Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Organizer: Ahmed-Ali, Tarek	Université De Caen Normandie
Organizer: Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Paper VI126-04.1
PDF · Video · Control of Flexible Euler-Bernoulli Beam with Input/Output Delay and Stochastic Disturbances (I)
Cacace, Filippo	Universita Campus Biomedico Di Roma
Germani, Alfredo	University of L'Aquila
Papi, Marco	Universita Campus Bio-Medico Di Roma
Keywords: output regulation for distributed parameter systems, Stochastic optimal control problems, delay compensation for linear and nonlinear systems Abstract: We consider the problem of stability enhancement of an undamped flexible beam with a tip mass in presence of input delay and random disturbances. In absence of delay this problem is classically solved through output feedback based on a suitable approximation of an infinite-dimensional Kalman filter. To cope with the presence of input or output delays we derive and compare two solutions, one based on a predictor from estimates in the past and the other one based on a filter with delayed measurements. An identical delay bound in closed form is derived for both solutions and we show that by an appropriate choice of the control gain it is possible to stabilize the system in presence of arbitrarily large delays. A modular structure is proposed for the case of arbitrary gain and delay bound. Finally, we consider the problem of deriving a finite-dimensional approximation of the predictor.
Paper VI126-04.2
PDF · Video · Control of an Unstable Reaction-Diffusion PDE with Spatially-Varying Input Delay (I)
Qi, Jie	Donghua University
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Infinite-dimensional systems, Systems with time-delays, Parameter-varying systems Abstract: We design a predictor-based distributed feedback controller that guarantees exponential stability for a class of reaction-diffusion PDEs with spatially-varying input delay. First,an implicit backstepping transformation is introduced which contains the state of the target system on both sides of the definition and then an additional backstepping transformation is derived by a successive integration approach to arrive at a target system that is a distributed cascade of a 2D transport PDE into a 1D reaction-diffusion PDE. The resulting delay-compensating controller includes spatially-weighted state feedback and feedback of the earlier inputs in four differential spatial regions. The inverse transformation is also derived, to prove L2 exponential stability.
Paper VI126-04.3
PDF · Video · Adaptive Boundary Observer Design for Coupled ODEs-Hyperbolic PDEs Systems (I)
Ghousein, Mohammad	University Grenoble Alpes
Witrant, Emmanuel	Université Grenoble Alpes
Keywords: Observer design, control of hyperbolic systems and conservation laws, Time-varying systems Abstract: We consider the state estimation of nxi hyperbolic PDEs coupled with nX ordinary differential equations at the boundary. The hyperbolic system is linear and propagates in the positive x-axis direction. The ODE system is linear time varying (LTV) and includes a set of ntheta unknown constant parameters, which are to be estimated simultaneously with the PDE and the ODE states using boundary sensing. We design a Luenberger state observer, and our method is mainly based on the decoupling of the PDE estimation error states from that of the ODEs via swapping design. We then derive the observer gains through the Lyapunov analysis of the decoupled system. Furthermore, we give sufficient conditions of the exponential convergence of the adaptive observer through differential Lyapunov inequalities (DLIs) and we illustrate the theoretical results by numerical simulations.
Paper VI126-04.4
PDF · Video · Finite-Dimensional Observer-Based Controller for Linear 1-D Heat Equation: An LMI Approach (I)
Katz, Rami	Tel Aviv University
Fridman, Emilia	Tel-Aviv Univ
Keywords: Infinite-dimensional systems, model reduction of distributed parameter systems, Convex optimization Abstract: The present paper suggests a finite-dimensional observer-based controller design for 1-D linear heat equation. We propose a modal decomposition approach in the cases of boundary or non-local sensing together with non-local (non-point) actuation. The dimension of the controller, N0, is equal to the number of modes which decay slower than a given decay rate delta>0. The observer may have a larger dimension N>=N0. The observer and controller gains are found separately of each other. We suggest a direct Lyapunov approach to the full-order closed-loop system and provide linear matrix inequalities for finding N and the exponential decay rate of the closed-loop system. Differently from the existing qualitative methods, we present constructive conditions and show that these conditions are always feasible for large enough N. Numerical examples demonstrate the efficiency of our method.
Paper VI126-04.5
PDF · Video · Network-Based Deployment of the Second-Order Multi Agents: A PDE Approach (I)
Terushkin, Maria	Tel Aviv University
Fridman, Emilia	Tel-Aviv Univ
Keywords: infinite-dimensional multi-agent systems and networks, Decentralized control, control and estimation of wave equations and systems of elasticity Abstract: Deployment of a second-order nonlinear multi agent system over a desired open smooth curve in 2D or 3D space is considered. We assume that the agents have access to their velocities and to the local information of the desired curve and their displacements with respect to their closest neighbors, whereas in addition a leader is able to measure his absolute position. We assume that a small number of leaders transmit their measurements to other agents through a communication network. We take into account the following network imperfections: the variable sampling, transmission delay and quantization. We propose a static output-feedback controller and model the resulting closed-loop system as a disturbed (due to quantization) nonlinear damped wave equation with delayed point state measurements, where the state is the relative position of the agents with respect to the desired curve. To manage with the open curve we consider Neumann boundary conditions. We derive linear matrix inequalities that guarantee the input-to-state stability of the closed-loop system. The advantage of our approach is in the simplicity of the control law and the conditions. Numerical example illustrates the efficiency of the method.
Paper VI126-04.6
PDF · Video · Output-Feedback PDE Control of Traffic Flow on Cascaded Freeway Segments (I)
Yu, Huan	University of California, San Diego
Auriol, Jean	CNRS, Centrale Supelec
Krstic, Miroslav	Univ. of California at San Diego
Keywords: Output feedback control (linear case), Control of interconnected systems, backstepping control of distributed parameter systems Abstract: We develop in this paper a boundary output feedback control law for an underactuated network of traffic flow on two connected roads; one incoming and one outgoing road connected by a junction. The macroscopic traffic dynamics on each road segment are governed by Aw-Rascle-Zhang (ARZ) model, consisting of second-order nonlinear partial differential equations (PDEs) of traffic density and velocity. The control objective is to stabilize the traffic network system on both roads around a chosen reference system. Using a ramp metering located at the outlet of the outgoing road, we actuate the traffic flux leaving this considered domain. Boundary measurements of traffic flux and velocity are taken at the junction connecting the two road segments. A delay-robust full state feedback control law and a boundary observer are designed for this under-actuated network of two systems interconnected through their boundaries. Each system consists of two hetero-directional linear first-order hyperbolic PDEs. The exponential convergence to the reference system is achieved.
Paper VI126-04.7
PDF · Video · Prescribed-Time Tracking for Triangular Systems of Reaction-Diffusion PDEs (I)
Steeves, Drew	University of California, San Diego
Camacho-Solorio, Leobardo	University of California, San Diego
Benosman, Mouhacine	Mitsubishi Electric Research Laboratories (MERL)
Krstic, Miroslav	Univ. of California at San Diego
Keywords: motion planning for distributed parameter systems, Linear systems, Tracking Abstract: Approximate controllability of systems of coupled parabolic partial differential equations has been of interest for a few decades, where the existence of open-loop control laws performing approximate state transitions within a finite time is studied. In this work, we specialize to systems of reaction-diffusion equations where the connectivity structure is triangular in the reaction parameters and the controls appear at the boundary. We first generate controllers by combining a decoupling backstepping approach with differential flatness that allow us to generate admissible trajectories for system outputs from a given initial condition. As a byproduct of our approach, we achieve approximate state transitioning for the system within a finite terminal time. We enhance our control law by introducing time-varying error feedback controllers which reject variations in initial conditions within the terminal time. The resulting control law not only performs the approximate control task but also output trajectory tracking, all within the terminal time which can be prescribed independently of initial conditions.
Paper VI126-04.8
PDF · Video · Output Feedback Control of Radially-Dependent Reaction-Diffusion PDEs on Balls of Arbitrary Dimensions (I)
Vazquez, Rafael	Universidad De Sevilla
Zhang, Jing	Donghua University
Krstic, Miroslav	Univ. of California at San Diego
Qi, Jie	Donghua University of China
Keywords: backstepping control of distributed parameter systems, stability of distributed parameter systems Abstract: Recently, the problem of boundary stabilization and estimation for unstable linear constant-coefficient reaction-diffusion equation on n-balls (in particular, disks and spheres) has been solved by means of the backstepping method. However, the extension of this result to spatially-varying coefficients is far from trivial. Some early success has been achieved under simplifying conditions, such as radially-varying reaction coefficients under revolution symmetry, on a disk or a sphere. These particular cases notwithstanding, the problem remains open. The main issue is that the equations become singular in the radius; when applying the backstepping method, the same type of singularity appears in the kernel equations. Traditionally, well-posedness of these equations has been proved by transforming them into integral equations and then applying the method of successive approximations. In this case, with the resulting integral equation becoming singular, successive approximations do not easily apply. This paper takes a different route and directly addresses the kernel equations via a power series approach, finding in the process the required conditions for the radially-varying coefficients and stating the existence of the series solution. This approach provides a direct numerical method that can be readily applied, despite singularities, to both control and observer boundary design problems.
Paper VI126-04.9
PDF · Video · Observer of Coupled Hyperbolic PDEs for Deep-Sea Construction Vessel Vibrations (I)
Wang, Ji	University of California, San Diego
Krstic, Miroslav	Univ. of California at San Diego
Keywords: backstepping control of distributed parameter systems, Observer design, Infinite-dimensional systems Abstract: Motivated by vibration state estimation of a deep-sea construction vessel used to install oil drilling equipment on the seafloor, this paper presents state observer design of a 4*4 coupled heterodirectional hyperbolic PDE-ODE system, characterized by spatially-varying coefficients and a time-varying domain. The exponential stability of the observer error system is proved via Lyapunov analysis. Effective estimation of lateral-longitudinal coupled vibration states of the deep-sea construction vessel is verified in numerical simulation.

VI126-05
Distributed Parameter System	Regular Session
Chair: Meurer, Thomas	Christian-Albrechts-University Kiel
Co-Chair: Wulff, Kai	TU Ilmenau
Paper VI126-05.1
PDF · Video · Flatness-Based Algebraic Fault Identification for a Wave Equation with Dynamic Boundary Conditions
Fischer, Ferdinand	Universität Ulm
Deutscher, Joachim	Universität Ulm
Keywords: control and estimation of wave equations and systems of elasticity, controllability and observability of distributed parameter systems Abstract: This paper presents a fault identification approach for a boundary controlled wave equation with dynamic boundary conditions. The faulty system is subject to an additive time-varying actuator fault and an unknown in-domain disturbance. These signals are assumed to be the solution of a finite-dimensional signal model so that polynomial and trigonometric faults as well as disturbances can be taken into account. By making use of integral transformations an algebraic expression is derived to obtain the fault from the known input and output in finite time. The kernels determining the integral transformations are obtained by solving the so-called kernel equations. This problem is traced back to the flatness-based realization of a setpoint change for an ODE-PDE casacade. From this, a condition for fault identification is derived. A simulation example demonstrates the proposed approach.
Paper VI126-05.2
PDF · Video · A Heuristic Observer Design for an Uncertain Hyperbolic PDE Using Distributed Sensing
Holta, Haavard	NTNU
Aamo, Ole Morten	NTNU
Keywords: control of hyperbolic systems and conservation laws, control of fluid flows and fluids-structures interactions, system identification and adaptive control of distributed parameter systems Abstract: We design an adaptive observer for semi-linear 2x2 hyperbolic PDEs with parametric uncertainties in both state equations. The proposed method is an extension of a previous result where parametric uncertainties were only allowed in one of the system equation. We utilize partial state measurements of one of the distributed states to estimate the remaining unknown distributed state. The method can be applied to flow rate estimation in fluid flow systems where the pressure is measured.
Paper VI126-05.3
PDF · Video · External Boundary Regional Controllability for Nonlocal Diffusion Systems Involving the Fractional Laplacian
Ge, Fudong	China University of Geosciences
Chen, YangQuan	University of California, Merced
Keywords: controllability and observability of distributed parameter systems, fractional-order systems, Optimal control of partial differential equations Abstract: The goal of this paper is to investigate regional exact controllability from the exterior of the nonlocal diffusion system governed by parabolic partial differential equations (PDEs) with the fractional Laplacian. For this purpose, we first explore an explicit expression of solutions to the system. Use this, some equivalent conditions to achieve regional exact controllability of the considered systems are given. Then, we propose an approach on the minimum energy control problem using the Hilbert uniqueness method (HUM). It is presented that the minimum control input can be explicitly given with respect to the subregion, the actuators structure and the spectral theory of fractional Laplacian under zero Dirichlet exterior boundary conditions. An example is finally included to illustrate our theoretical results.
Paper VI126-05.4
PDF · Video · Constant Time Horizon Prediction-Based Control for Linear Systems with Time-Varying Input Delay
Kong, Sijia	MINES ParisTech
Bresch-Pietri, Delphine	MINES ParisTech
Keywords: delay compensation for linear and nonlinear systems, Delay systems, backstepping control of distributed parameter systems Abstract: We introduce a constant time horizon prediction-based controller to compensate for a time-varying input delay in a linear control system. We establish that this controller guarantees closed-loop exponential stability, provided that the time-varying delay remains sufficiently close to its average value D_0 and its rate of variation sufficiently small. This conclution only has to hold in average, in a mathematical sense that we specify.
Paper VI126-05.5
PDF · Video · Robustness to Delay Mismatch in Consensus Control under Undirected Graphs
Huang, Ran	Beijing University of Chemical Technology
Ding, Zhengtao	The University of Manchester
Keywords: delay compensation for linear and nonlinear systems, Distributed robust controller synthesis, Delay systems Abstract: This paper studies predictor-based adaptive consensus control of network-connected systems with unknown delays under undirected graphs. The approach is based on the representation of the delay state as a transport partial differential equation (PDE) and the utilization of a nonadaptive estimation delay state. Using the relative information of neighboring nodes, we propose a fully distributed adaptive consensus protocol, which is proven to achieve global consensus provided that the delay mismatch is within a small region. Simulation results performed on a group of neutrally stable systems are presented to illustrate the effectiveness of the proposed scheme.
Paper VI126-05.6
PDF · Video · Robustness of Constant-Delay Predictor Feedback with Respect to Distinct Uncertain Time-Varying Input Delays
Lhachemi, Hugo	University College Dublin
Prieur, Christophe	CNRS
Shorten, Robert	Imperial College London
Keywords: delay compensation for linear and nonlinear systems, Systems with time-delays, stability of distributed parameter systems Abstract: This paper addresses the robustness of the constant-delay predictor feedback in the case of distinct and uncertain time-varying input delays. Specifically, we consider the case of a predictor feedback that is designed based on the knowledge of the nominal value of the time-varying delay in each control input channel. We derive an LMI-based sufficient condition ensuring the exponential stability of the closed-loop system for small enough variations of the distinct time-varying input delays around their nominal value. Then we apply these results to the feedback stabilization of a class of diagonal infinite-dimensional boundary control systems exhibiting distinct time-varying delays in the boundary control inputs.
Paper VI126-05.7
PDF · Video · Extended Fractional-Order Memory Reset Control for Integer-Order LTI Systems and Experimental Demonstration
Weise, Christoph	TU Ilmenau
Wulff, Kai	TU Ilmenau
Reger, Johann	TU Ilmenau
Keywords: fractional-order systems, Digital implementation, Switching stability and control Abstract: In this work we extend the concept of fractional-order memory reset control. A fractional-order controller is applied to an integer-order plant and its memory is deleted periodically. As an extension, the controller state itself is reset based on the reference and the error signal. The closed loop can be represented by a fractional-order hybrid system with induced discrete dynamics. These are used to tune the reset law and to proof exponential stability. By means of the extended reset strategy the reset intervals can be reduced, such that less memory is needed to implement the fractional-order operators. Furthermore, a new approach for the real-time implementation of memory reset controllers is presented that achieves a decrease of the numerical error. All results are validated by simulations and experimentally.
Paper VI126-05.8
PDF · Video · Hysteresis Dispersion Compensation with Neural Network Based Controller
Amigues, Louis Duong	ISAE SUPAERO, Université De Toulouse
Pommier-Budinger, Valerie	ISAE
Bordeneuve-Guibe, Joel	ISAE-Supaéro
Keywords: hysteresis modeling and control, Data-based control, Robustness analysis Abstract: Hysteresis is a commonly encountered physical phenomenon in many systems. It results in a dependence of the state of a system to its history. This non-linearity makes it particularly difficult to control accurately. There are many ways for compensating hysteresis, one of them consists of building an inverse model of the hysteresis and using it as a feedforward controller. Coupled to a feedback mechanism, the hysteresis impact can thus be minimized. However, the performance of these controllers decreases when exposed to dispersion in the hysteresis quantity or shape. The capacity of neural networks to model non-linear phenomena is not to be proven and will be put at use. In this paper, an artificial neural network model was trained to replace the conventional hysteresis inverse model. The controller performance was evaluated on a limited-angle torque motor, which exhibits hysteresis due to the magnetization saturation of the ferromagnetic materials. The experimental results pointed out the superior robustness to system dispersion of the Neural Network based controller for time and frequency response.
Paper VI126-05.9
PDF · Video · Operator Inequality Approach for State-Feedback Stabilization of Infinite-Dimensional Systems: Synthesis Via Dual of Input-To-State Operator
Masubuchi, Izumi	Kobe University
Keywords: Infinite-dimensional systems, stability of distributed parameter systems Abstract: This paper proposes a synthesis method of stabilizing state-feedback controllers for linear infinite-dimensional systems with possible unbounded input operators. A regularity condition in the sense of the existence of step responses for all initial conditions and constant inputs, under which the closed-loop system with any bounded state-feedback is well-posed via a filter on the input channels. Operator inequalities are provided on the dual space of the input-to-state operator, where any solution to the linear inequality provides a stabilizing filtered state feedback controller.
Paper VI126-05.10
PDF · Video · Control-Oriented Model Reduction for a Class of Hyperbolic Systems with Application to Managed Pressure Drilling
Leenen, Tom	Eindhoven University of Technology
Naderi Lordejani, Sajad	Eindhoven University of Technology
Besselink, Bart	University of Groningen
Schilders, Wilhelmus	TU Eindhoven
van de Wouw, Nathan	Eindhoven Univ of Technology
Keywords: model reduction of distributed parameter systems, control of hyperbolic systems and conservation laws, Systems with time-delays Abstract: This paper presents a model reduction approach for systems of hyperbolic partial differential equations (PDEs) with nonlinear boundary conditions. These systems can be decomposed into a feedback interconnection of a linear hyperbolic subsystem and a static nonlinear mapping. This structure motivates us to reduce the overall model complexity by only reducing the linear subsystem (the PDE part). We show that the linear PDE subsystem can effectively be approximated by a cascaded structure of systems of continuous time difference equations (CTDEs) and ordinary differential equations (ODEs), where the CTDE captures the infinite-dimensional nature of the PDE model. These systems are constructed by adapting an interpolation method based on frequency-domain data. Models in the form of hyperbolic PDEs with nonlinear boundary conditions are for example encountered in managed pressure drilling (MPD). The proposed technique is verified by application to such an MPD model.
Paper VI126-05.11
PDF · Video · Reinforcement Learning-Based Model Reduction for Partial Differential Equations
Benosman, Mouhacine	Mitsubishi Electric Research Laboratories (MERL)
Chakrabarty, Ankush	Mitsubishi Electric Research Laboratories
Borggaard, Jeff	Virginia Tech
Keywords: model reduction of distributed parameter systems, thermal and process control applications of distributed parameter systems Abstract: This paper is dedicated to the problem of stable model reduction for partial differential equations (PDEs). We propose to use proper orthogonal decomposition (POD) method to project the PDE model into a lower dimensional given by an ordinary differential equation (ODE) model. We then stabilize this model, following the closure model approach, by proposing to use reinforcement learning (RL) to learn an optimal closure model term. We analyze the stability of the proposed RL closure model and show its performance on the coupled Burgers equation.
Paper VI126-05.12
PDF · Video · Motion Planning for a Class of Boundary Controlled 1D Port-Hamiltonian Systems
Biedermann, Bastian	Kiel University
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: motion planning for distributed parameter systems, control of hyperbolic systems and conservation laws, port Hamiltonian distributed parameter systems Abstract: A flatness-based approach for motion planning for a class of boundary controlled port-Hamiltonian systems with distributed parameters is presented. The goal is to achieve open-loop output tracking or finite-time transitions between steady states or operating profiles. Introducing new (fictious) boundary conditions in terms of so-called flat outputs, the port-Hamiltonian system is reformulated as a Cauchy problem in the spatial domain. The parametrization of any system variable and input by the flat output is computed using two different solution approaches. By assigning a suitable desired trajectory for the flat output, the input parametrization yields the feedforward control law to solve the motion planning task. The presented theory is applied to the wave equation with spatially varying parameters and is evaluated by numerical calculations and simulations.
Paper VI126-05.13
PDF · Video · Neumann Trace Tracking of a Constant Reference Input for 1-D Boundary Controlled Heat-Like Equations with Delay
Lhachemi, Hugo	University College Dublin
Prieur, Christophe	CNRS
Trelat, Emmanuel	University Pierre Et Marie Curie (Paris 6)
Keywords: motion planning for distributed parameter systems, delay compensation for linear and nonlinear systems, control of heat and mass transfer systems Abstract: This paper discusses the Proportional Integral (PI) regulation control of the left Neumann trace of a one-dimensional reaction-diffusion equation with a delayed right Dirichlet boundary control. Specifically, a PI controller is designed based on a finite-dimensional truncated model that captures the unstable dynamics of the original infinite-dimensional system. In this setting, the control input delay is handled by resorting to the Artstein transformation. The stability of the resulting infinite-dimensional system, as well as the tracking of a constant reference signal in the presence of a constant distributed perturbation, is assessed based on the introduction of an adequate Lyapunov function. The theoretical results are illustrated with numerical simulations.
Paper VI126-05.14
PDF · Video · Trajectory Planning for Semilinear Time-Fractional Reaction-Diffusion Systems under Robin Boundary Conditions
Fudong, Ge	China University of Geosciences
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: motion planning for distributed parameter systems, fractional-order systems, Tracking Abstract: This paper describes how to design flatness-based distributed feedforward controllers for the solution of the trajectory planning problem of semilinear time-fractional reaction-diffusion systems (TFRDSs), where the first-order time derivative of conventional reaction-diffusion system is extended to a Caputo fractional derivative of order alpha in (0,1]. To this end, an implicit system variable and control input parametrization is determined based on the spectral property of system operator with respect to a basic output and its fractional-order derivatives. The convergence of the parametrizations is guaranteed by restricting the basic output to some certain Gevrey classes. With these, we propose two approaches on solving the trajectory planning problem within a prescribed finite time interval. A simulation example is finally included to illustrate our results.
Paper VI126-05.15
PDF · Video · Internal Model Controller Design of Linearized Ginzburg-Landau Equation
Xie, Junyao	University of Alberta
Koch, Charles Robert	University of Alberta
Dubljevic, Stevan	Unversity of Alberta
Keywords: output regulation for distributed parameter systems, control of fluid flows and fluids-structures interactions, motion planning for distributed parameter systems Abstract: In this work, an output regulator design in a discrete-time setting is considered for a linearized Ginzburg-Landau equation (GLE) with point observation using the internal model principle. To address model instability, spectrum analysis is presented and utilized for the continuous-time GLE system. In addition, the Cayley-Tustin transform is used for model time discretization and no spatial approximation or model reduction is induced in the time discretization. As for the servo control design, the discrete-time Sylvester regulation equations are constructed and applied. By a state-feedback regulator, the output tracking and disturbance rejection are realized simultaneously for the Ginzburg-Landau equation, which is verified by a set of simulation studies.
Paper VI126-05.16
PDF · Video · Linear Boundary Port Hamiltonian Systems Defined on Lagrangian Submanifolds
Maschke, Bernhard	Univ Claude Bernard of Lyon
van der Schaft, Arjan J.	Univ. of Groningen
Keywords: port Hamiltonian distributed parameter systems, Lagrangian and Hamiltonian systems, Infinite-dimensional systems Abstract: Recently Port Hamiltonian systems have been extended to encompass implicit definition of the energy function of the system by defining it in terms of a Lagrangian submanifold. In this paper we extend the definition of Port Hamiltonian systems defined with respect to Lagrangian submanifold to a class of infinite-dimensional systems where the Lagrangian submanifold is defined by first-order differential operators. We show that this adds some port boundary variables and derive the energy balance equation. This construction is illustrated on the model of a flexible nanorod made of composite material.
Paper VI126-05.17
PDF · Video · Energy-Based Control of a Wave Equation with Boundary Anti-Damping
Macchelli, Alessandro	Univ. of Bologna - Italy
Le Gorrec, Yann	FEMTO-ST, ENSMM
Wu, Yongxin	ENSMM / Université Bourgogne Franche-Comté
Ramirez, Hector	Universidad Federico Santa Maria
Keywords: port Hamiltonian distributed parameter systems, Passivity-based control, stability of distributed parameter systems Abstract: In this paper, we consider the asymptotic boundary stabilisation of a one-dimensional wave equation subject to anti-damping at its free end and with control at the opposite one. The control action, implemented through a state feedback or a dynamic controller, is derived by using the port-Hamiltonian framework. More precisely, the standard energy-shaping approach plus damping assignment is adapted to cope with infinite dimensional systems with anti-damping boundary conditions. It is shown how to modify the equivalent dynamic controller to account for the instability propagation along the domain.
Paper VI126-05.18
PDF · Video · Wake Symmetrization of a Bluff Ahmed Body Based on Sliding Mode Control
Mariette, Kévin	UDL, INSA De Lyon
Bideaux, Eric	INSA of Lyon
Bribiesca Argomedo, Federico	INSA De Lyon, Ampère Lab
Eberard, Damien	Universite De Lyon, INSA De Lyon
Sesmat, Sylvie	Laboratoire Ampère
Haffner, Yann	Institute Pprime, CNRS - Universite De Poitiers - ISAE-ENSMA
Borée, Jacques	Institute Pprime, CNRS - Universite De Poitiers - ISAE-ENSMA
Castelain, Thomas	Univ Lyon, Universitée Claude Bernard Lyon I, Ecole Centrale De
Michard, Marc	Ecole Centrale Lyon
Keywords: Sliding mode control, delay compensation for linear and nonlinear systems, Nonlinear predictive control Abstract: Aerodynamic drag reduction is needed to develop future fuel efficient ground transportation vehicles. Our study targets bluff bodies with wake asymmetries due to natural bistability or cross wind contributing to the drag increase at high velocities. The originality of this work is to apply closed loop control techniques based on sliding mode control theory and a Smith like predictor scheme for delay compensation in order to force the wake symmetry. This non linear controller was tuned thanks to experimental study of pulsed jet actuators placed at the back of a modified Ahmed bluff body and shows that wake symmetrization can be achieved either in aligned or cross wind configurations.
Paper VI126-05.19
PDF · Video · Integral Quadratic Constraints on Linear Infinite-Dimensional Systems for Robust Stability Analysis
Barreau, Matthieu	KTH
Scherer, Carsten W.	Department of Mathematics, University of Stuttgart
Gouaisbaut, Frederic	LAAS CNRS
Seuret, Alexandre	Cnrs / Laas
Keywords: stability of distributed parameter systems, Robustness analysis, semigroup and operator theory Abstract: This paper proposes a framework to assess the stability of a an ordinary differential equation which is coupled to a 1D-partial differential equation (PDE). The stability theorem is based on a new result on Integral Quadratic Constraints (IQCs) and expressed in terms of two linear matrix inequalities with a moderate computational burden. The IQCs are not generated using dissipation inequalities involving the whole state of an infinite-dimensional system, but by using projection coefficients of the infinite-dimensional state. This permits to generalize our robustness result to many other PDEs. The proposed methodology is applied to a time-delay system and numerical results comparable to those in the literature are obtained.

VI126-06
Distributed Parameter Systems Applications	Regular Session
Chair: Woittennek, Frank	UMIT Tirol
Co-Chair: Rauh, Andreas	University of Rostock
Paper VI126-06.1
PDF · Video · Control of the Vertical Gradient Freeze Crystal Growth Process Via Backstepping
Ecklebe, Stefan	TU Dresden
Woittennek, Frank	UMIT
Winkler, Jan	Fakultät Elektrotechnik Und Informationstechnik, TU Dresden
Keywords: backstepping control of distributed parameter systems, thermal and process control applications of distributed parameter systems, control of heat and mass transfer systems Abstract: This contribution presents a backstepping-based state feedback design for the tracking control of a two-phase Stefan problem which is encountered in the Vertical Gradient Freeze crystal growth process. A two-phase Stefan problem consists of two coupled free boundary problems and is a vital part of many crystal growth processes due to the time-varying extent of crystal and melt during growth. In addition, a different approach for the numerical approximation of the backstepping transformations kernel is presented.
Paper VI126-06.2
PDF · Video · Open-Loop Temperature Control for a Distributed Parameter Model of a Pipe
Bachler, Simon	UMIT - Private University for Health Sciences, Medical Informati
Wurm, Jens	UMIT – Private University for Health Sciences, Medical Informati
Woittennek, Frank	UMIT
Keywords: control of heat and mass transfer systems, motion planning for distributed parameter systems, stability of distributed parameter systems Abstract: Various models describing a plug flow through a pipe are used for model-based control design in industrial processes. This contribution presents a feedforward controller based on a new modeling approach for plug flow through a pipe. The latter model combines the advantages of partial differential and delay differential equation approaches. This structure allows to derive the desired control input by an inverse calculation of the partial differential equation part of the model. Moreover, the stability of the used model is proven by a spectrum analysis of the involved system operators. Finally, the presented approach is studied in simulation and experimentally test results are provided.
Paper VI126-06.3
PDF · Video · Modeling and Control of a Thermoelectric Structure with a Peltier Element Subject to External Disturbances
Gavrikov, Alexander	Ishlinsky Institute for Problems in Mechanics RAS
Kostin, Georgy	Institute for Problems in Mechanics of the Russian Academy of Sc
Aschemann, Harald	University of Rostock
Rauh, Andreas	University of Rostock
Keywords: control of heat and mass transfer systems, Optimal control of partial differential equations, Model reduction Abstract: A nonlinear model of heat transfer in a solid structure controlled by a Peltier element is considered. The thermoelectrical converter in between two cylindrical bodies regulates temperature distribution in one cylinder, while the other body is used as the thermal capacitor. An optimal control problem is stated to minimize heat losses in the electrical circuit of the Peltier element in a given time interval. A feedforward piecewise constant control signal is designed to reach the vicinity of a desired steady state by using the a-priori prediction of variations of the external temperature. Additionally, feedback loops are designed for model linearization, trajectory stabilization, and compensation of changes in the ambient air temperature.
Paper VI126-06.4
PDF · Video · Position Control of a Planar Single-Link Flexible-Link Manipulator Based on Enhanced Dynamic Coupling Model
Meng, Qingxin	China University of Geosciences
Wu, Jundong	Concordia University
Yan, Ze	China University of Geosciences
Su, Chun-Yi	Concordia Univ
Keywords: Infinite-dimensional systems, Lyapunov methods, Controller constraints and structure Abstract: Position control of a planar single-link flexible-link manipulator always exists huge challenge due to the underactuated characteristic of the system and the vibration of the flexible link. Since the system state variables related to the vibration is underactuated, this paper considers enhancing the dynamic coupling of this system. An enhanced dynamic coupling model is established by making equivalent transformation for the real dynamic model of the system. This enhanced dynamic coupling model makes the vibration variables appear as active variables in the proposed energy-based controller. Therefore, the proposed controller achieves good vibration suppression effect. The stability analysis is presented to prove that the proposed controller can effectively achieve the position control objective, and the simulation results further demonstrate the superiority of the proposed control method.
Paper VI126-06.5
PDF · Video · Modeling and Discrepancy Based Control of Underactuated Large Gantry Cranes
Golovin, Ievgen	Otto Von Guericke University Magdeburg
Palis, Stefan	Otto Von Guericke University Magdeburg
Keywords: output regulation for distributed parameter systems, Lyapunov methods, Application of nonlinear analysis and design Abstract: An important structural dynamics problem of the large gantry cranes are horizontal elastic oscillations mainly excited by the trolley motion. They reduce the crane operation performance and lead to faster material wear of the crane construction. In this article a distributed parameter model of large gantry cranes applying Hamilton's principle is presented. In order to stabilize the system dynamics the use of a generalized error measure, called discrepancy, is proposed. Applying the associated stability theory, i.e. stability with respect to two discrepancies, a nonlinear stabilizing control for the underactuated gantry crane is derived. The proposed control strategy has been verified by simulations.
Paper VI126-06.6
PDF · Video · Nonlinear Output Feedback-Feedforward Control of Tubular Gasification Reactors
Badillo-Hernandez, Ulises	Universidad Nacional Autónoma De México
Alvarez, Jesus	Universidad Autonoma Metropolitana
Franco, Hugo	Universidad Nacional Autónoma De México
Alvarez-Icaza, Luis	Universidad Nacional Autónoma De México
Keywords: output regulation for distributed parameter systems, Output feedback control, Disturbance rejection Abstract: The problem of robustly controlling open-loop bistable tubular gasification reactors about its ignition stable SS is addressed. To attenuate the effect of measured and unmeasured disturbances on closed-loop (CL) stability and caloric yield, the air feed flow must be adjusted on the basis of flow as well as inside point temperature measurements. The consideration of the problem as an efficient finite-dimensional model-based interlaced control-observer design yields a robust dynamic nonlinear (NL) output feedback (OF)-feedforward (FF) controller: (i) made by the combination of a passive NL state feedback (SF)-feedforward (FF) controller with a NL geometric (G) state estimator, and (ii) with CL stability conditions accompanied by gain tuning and sensor location guidelines. The approach is applied, through numerical simulations, to a 10-component 1-temperature and 2-flow stratified gasification reactor, finding that the nonlinear OF dynamic controller (made of 91 ODEs and 300 AEs) robustly stabilizes the reactor with preclusion of undesired SS ignition-to-extinction caused by solid feed disturbances.
Paper VI126-06.7
PDF · Video · Robust Output Regulation of a Flexible Satellite
Govindaraj, Thavamani	Tampere University
Humaloja, Jukka-Pekka	Tampere University
Paunonen, Lassi	Tampere University
Keywords: port Hamiltonian distributed parameter systems, stability of distributed parameter systems, output regulation for distributed parameter systems Abstract: We consider a PDE-ODE model of a satellite and robust output regulation of the corresponding model. The satellite is composed of two flexible solar panels and a rigid center body. Exponential stability of the model is proved using passivity and resolvent estimates in the port-Hamiltonian framework. In addition, we construct a simple low-gain controller for robust output regulation of the satellite model.
Paper VI126-06.8
PDF · Video · Performance Analysis for Time-Delay Systems: Application to the Control of an Active Mass Damper
Ariba, Yassine	Icam
Gouaisbaut, Frederic	LAAS CNRS
Keywords: stability of delay systems, Robust control (linear case), Uncertainty descriptions Abstract: This paper proposes a method to analyze, beyond stability, the performances of linear time-delay systems. Using robust analysis techniques, a sufficient condition that analyzes the location of eigenvalues in the complex plane is presented. More precisely, a set of quadratic inequality constraints are designed to define an admissible region for the infinitely many eigenvalues of a time-delay system and the quadratic separation theorem is applied to assess that the eigenvalues are effectively belonging to that stability region. This method is then used for the control of an active mass damper. A standard state feedback control is replaced with a static output feedback plus a static delayed output feedback. This strategy avoids the full measurement of the state and shows that delays in the dynamic may be helpful for stabilization. The closed-loop system is then expressed as a time-delay system and the performance criterion is exploited to analyze the stability and the damping properties. Simulations and experimental tests support the approach.
Paper VI126-06.9
PDF · Video · Boundary Stabilization of Systems of High Order PDEs Arising from Flexible Robotics
Cristofaro, Andrea	Sapienza University of Rome
Ferrante, Francesco	Université Grenoble Alpes
Keywords: stability of distributed parameter systems, semigroup and operator theory, Lyapunov methods Abstract: Stabilization of a system of coupled PDEs of the forth-order by means of boundary control is investigated. The considered setup arises from the classical Euler-Bernoulli beam model, and constitutes a generalization of flexible mechanical systems. A linear feedback controller is proposed, and using an abstract formulation based on operator semigroup theory, we are able to prove the well-posedness and the stability of the closed-loop system. The performances of the proposed controller are illustrated by means of numerical simulations.

VI131
Computers, Cognition and Communication - Computers for Control
VI131-01 Computers for Control   Regular Session, 10 papers

VI131-01
Computers for Control	Regular Session
Chair: Rosado-Muñoz, Alfredo	ETSE. University of Valencia
Co-Chair: Vogel-Heuser, Birgit	Technical University of Munich
Paper VI131-01.1
PDF · Video · Open Process Automation: A Standards-Based, Open, Secure, Interoperable Process Control Architecture
Bartusiak, Donald	ExxonMobil Research & Engineering
Bitar, Stephen	ExxonMobil Research and Engineering
DeBari, David L.	ExxonMobil Research and Engineering
Houk, Bradley G.	ExxonMobil Research and Engineering
Heaton, Michael	Lockheed Martin Rotary and Mission Systems
Strebel, Robert	Lockheed Martin Rotary and Mission Systems
Stevens, Dennis	Lockheed Martin Rotary and Mission Systems
Fitzpatrick, Bridget	Wood Plc, Houston, TX
Sloan, Patrick	Wood Plc, Houston, TX
Keywords: Embedded computer architectures, Logical design, physical design, and implementation of embedded computer systems, Internet of things Abstract: Open Process Automation (OPA) refers to an industry initiative to improve the total lifecycle benefits from industrial control systems through the use of an open, interoperable architecture and an open business model. It is being driven by consensus-based standards organization, the Open Process Automation Forum of The Open Group, that began operations in November 2016. As of April 2020, the OPA Forum consists of 97 organization members including 22 operating companies from 5 industry segments; 6 of the 7 major distributed control system suppliers; and a host of hardware and software suppliers, and system integrators. The Forum has published a Business Guide [1], two versions of the O-PAS Technical Standard [2,3], and a Conformance Certification Policy document [4]. In parallel with the development of the standards, several operating companies, including ExxonMobil and BASF, have developed and tested prototype instances of OPA systems. This paper will provide an overview of the layered software architecture used to abstract application software from operating systems and computer hardware, and of the modular, standards-based design used to achieve loose, cohesive couplings for interoperability of independently sourced components. The paper will highlight principles and standards for information models, data transport mechanisms, and application installation and execution management to illustrate opportunities for third-party software suppliers, including academic researchers, to create software for industrial use on O-PAS conformant systems. The paper shares results of the OPA proof-of-concept and prototype systems projects done by ExxonMobil with system integrators Lockheed Martin and Wood plc. It concludes with a discussion of the relationships among OPA, NAMUR Open Architecture, and Module Type Package, including a recommendation to harmonize these initiatives into a common framework.
Paper VI131-01.2
PDF · Video · Efficient Hardware Implementation of Nonlinear Moving-Horizon State Estimation with Artificial Neural Networks
Vatanabe Brunello, Rafael Koji	UnB
Sampaio, Renato	UnB
Llanos, Carlos	UnB
Coelho, Leandro Dos Santos	Pontifical Catholic University of Parana
Hultmann Ayala, Helon Vicente	Pontifical Catholic University of Rio De Janeiro
Keywords: Embedded computer control systems and applications, Embedded computer architectures, Real-time algorithms, scheduling, and programming Abstract: In this contribution we investigate the application of radial basis functions artificial neural networks embedded in hardware for real-time moving-horizon state estimation. The solution of the optimal moving-horizon state estimation problem may be faced as the mapping from the inputs and outputs of the system to the state estimates according to the system model. This mapping may be solved offline with the optimal formulation and then approximated by any higher order function approximation algorithm, such as the ones from machine learning. An approximate version with radial basis functions neural networks is developed and implemented in a Field Programmable Gate Array (FPGA) showing good results in terms of accuracy and computational time. We show that the state estimate using the approximate version of the moving-horizon algorithm can be run using a laboratory scale kit of approximately 500 kHz for an inverted pendulum at a clock rate of about 110 MHz. The latency to provide an estimate can be further reduced when FPGAs with higher clocks are used as the artificial neural network architecture is inherently parallel.
Paper VI131-01.3
PDF · Video · Formalization of Design Patterns and Their Automatic Identification in PLC Software for Architecture Assessment
Neumann, Eva-Maria	Technische Universität München
Vogel-Heuser, Birgit	Technical University of Munich
Fischer, Juliane	Technical University of Munich
Ocker, Felix	Technical University of Munich
Diehm, Sebastian	Schneider Electric Automation GmbH
Schwarz, Michael	Schneider Electric Automation GmbH
Keywords: Embedded computer control systems and applications, Programmable logic controllers, Logical design, physical design, and implementation of embedded computer systems Abstract: Due to current trends in automation technology such as mass customization and an increasing variety of products, control software (SW) in automated Production Systems (aPS) is becoming increasingly complex. Thus, the need for suitable modularization strategies as a prerequisite for planned reuse increases. In classical high-level language programming, frequently recurring problems are often solved through reusable design patterns. In the control SW development of aPS, however, this approach is still not widely spread. Hence, this paper investigates how design patterns can be used for evaluating modularity in the context of control SW architecture by proposing criteria for classifying and formalizing patterns in aPS SW structure. On that basis, a prototypical implementation is proposed to evaluate the concept and to enable an automated pattern identification and interpretation in an industrial context.
Paper VI131-01.4
PDF · Video · Selecting Test Cases for Mechatronic Products with a Variant and Version Management Approach Based on a Consistent Toolchain
Land, Kathrin Sophie	Technical University of Munich
Vogel-Heuser, Birgit	Technical University of Munich
Gallasch, A.	Software Factory GmbH
Sagerer, M.	Hirschmann Automation and Control GmbH
Förster, D.	SCHUNK GmbH & Co. KG
Strobl, G.	Technical University of Munich
Keywords: Logical design, physical design, and implementation of embedded computer systems Abstract: The number of variants and versions for mechatronic products increases. The high variability poses a challenge for test engineers in selecting suitable test cases upon a change. If a requirement or a feature of a mechatronic product changes, it is not necessary to retest the whole product but only the changed parts. To identify the product features that are directly or indirectly affected by the change, a connection of test, requirement, and variant management is necessary. Therefore, an approach to select test cases based on an occurred change using variant and version knowledge is needed. In this paper, such an approach and its possible application in a toolchain are introduced. The toolchain is built by combining established tools developed by the Parametric Technology Corporation (PTC) that are already used to manage parts of the product life cycle. The resulting PTC Integrity Toolchain and the applicability of the concept on it were evaluated together with industrial experts with positive results.
Paper VI131-01.5
PDF · Video · An Embedded FPGA Architecture for Real-Time Model Predictive Control
Khajanchi, Hussain	The College of New Jersey
Bruno, Joseph Nicholas	The College of New Jersey
Adegbege, Ambrose Adebayo	The College of New Jersey
Keywords: Logical design, physical design, and implementation of embedded computer systems, Embedded computer control systems and applications, Real-time algorithms, scheduling, and programming Abstract: We develop a custom hardware architecture for real-time implementation of embedded Model Predictive Control (MPC) on Field Programmable Gate Array (FPGA). We propose a novel modular framework that allows for easy and rapid prototyping of control with capability for analog-to-digital conversion, numerical scaling, and digital-to-analog conversion. We demonstrate the effectiveness of the proposed framework for real-time control on a quadruple water tank system.
Paper VI131-01.6
PDF · Video · Opportunities for Industrial Control
Witte, Martin	Siemens AG
Sehr, Martin	Siemens Corporation
Ugalde Diaz, Ines	Siemens Corporation
Neidig, Jörg	Siemens AG
Niknami, Mehrdad	UC Berkeley
Höme, Stephan	Otto-von-Guericker-University Magdeburg
Lee, Edward A.	Univ. of California at Berkeley
Keywords: Programmable logic controllers, Logical design, physical design, and implementation of embedded computer systems, Internet of things Abstract: Programmable Logic Controllers are an established platform used throughout industrial automation, but rather poorly understood among researchers in the control systems community. This paper gives an overview of the state of the practice in industrial control systems while presenting a critical analysis of the dominant programming styles used in today's automation systems. We describe the patterns standardized loosely in IEC 61131-3 and, where there are ambiguities in the standard, realized in concrete vendor implementations. Ultimately, we suggest directions for further research towards enabling increasingly complex industrial control applications subject to the novel requirements of Industry 4.0 settings without compromising the safety and reliability guaranteed by the current industrial automation stack.
Paper VI131-01.7
PDF · Video · Food Tray Sealing Fault Detection Using Hyperspectral Imaging and PCANet
Benouis, Mohamed	University of M'sila
Medus, Leandro D.	ETSE School of Engineering. Univ. Valencia
Saban, Mohamed	ETSE School of Engineering. Univ. Valencia
Labiak, Grzegorz	University of Zielona Góra
Rosado-Muñoz, Alfredo	ETSE. University of Valencia
Keywords: Real-time algorithms, scheduling, and programming, Fuzzy and neural systems relevant to control and identification, Programmable logic controllers Abstract: Food trays are very common in shops and supermarkets. Fresh food packaged in trays must be correctly sealed to protect the internal atmosphere and avoid contamination or deterioration. Due to the speed of production, it is not possible to have human quality inspection. Thus, automatic fault detection is a must to reach high production volume. This work describes a deep neural network based on Principal Component Analysis Network (PCANet) for food tray sealing fault detection. The input data come from hyperspectral cameras, showing more characteristics than regular industrial cameras or the human eye as they capture the spectral properties for each pixel. The proposed classification algorithm is divided into three main parts. In the first part, a single image is extracted from the hypercube by using pixel-level fusion method: the cube hyperspectral images are transformed into two-dimensional images to use as the input to the PCANet. Second, a PCANet structure is applied to the fused image. The PCANet has two filter bank layers and one binarization layer (three stages), obtaining a feature vector. Finally, a classification algorithm is used, having the feature vector as input data. The SVM and KNN classifiers were used. The database used in this work is provided by food industry professionals, containing eleven types of contamination in the seal area of the food tray and using metallic opaque cover film. Obtained results show that the design of our framework proposed achieves accuracy of 90% (87% F-measure) and 89% (89% F-measure) for SVM and KNN, respectively. Computation time for classification shows that a food tray speed of 65 trays per second could be reached. As a final result, the influence of the dataset size is analyzed, having PCANet a similar behavior for an extended and a reduced dataset.
Paper VI131-01.8
PDF · Video · Adaptive Mirror Descent for the Network Utility Maximization Problem
Ivanova, Anastasiya	National Research University Higher School of Economics
Stinyakin, Fedor	V. Vernadsky Crimean Federal University
Pasechnyuk, Dmitry	Presidential Physics and Mathematics Lyceum No. 239
Vorontsova, Evgeniya	Catholic University of Louvain
Gasnikov, Alexander	Moscow Institute of Physics and Technology
Keywords: Real-time algorithms, scheduling, and programming, Remote and distributed control, Traffic control systems Abstract: Network utility maximization is the most important problem in network traffic management. Given the growth of modern communication networks, we consider utility maximization problem in a network with a large number of connections (links) that are used by a huge number of users. To solve this problem an adaptive mirror descent algorithm for many constraints is proposed. The key feature of the algorithm is that it has a dimension-free convergence rate. The convergence of the proposed scheme is proved theoretically. The theoretical analysis is verified with numerical simulations. We compare the algorithm with another approach, using the ellipsoid method~(EM) for the dual problem. Numerical experiments showed that the performance of the proposed algorithm against EM is significantly better in large networks and when very high solution accuracy is not required. Our approach can be used in many network design paradigms, in particular, in software-defined networks.
Paper VI131-01.9
PDF · Video · How Control-Friendly Is a Computing System? and How Control-Friendly Could It Be?
Leva, Alberto	Politecnico Di Milano
Seva, Silvano	Politecnico Di Milano
Terraneo, Federico	Politecnico Di Milano
Papadopoulos, Alessandro Vittorio	Mälardalen University
Maggio, Martina	Lund University
Keywords: Digital implementation, Networked systems Abstract: To date, not that much. Improvements are possible, but some system-theoretically grounded re-design is necessary. We discuss the matter based on our experience, and as a consequence, we come to distilling some design clues and research directions.
Paper VI131-01.10
PDF · Video · Control Strategies for Adaptive Resource Allocation in Cloud Computing
Calmon, Tiago	Federal University of Rio De Janeiro
Bhaya, Amit	Federal Univ of Rio De Janeiro
Diene, Oumar	Federal University of Rio De Janeiro
Ferreira Passoni, Jonathan	Federal University of Rio De Janeiro
Gottin, Vinicius Michel	Dell EMC
Sousa, Eduardo	Dell Technologies
Keywords: Adaptive control, Data-based control, Decentralized control Abstract: Using an infrastructure efficiently to execute jobs while respecting Service Level Agreements (SLAs) and thereby guaranteeing Quality of Service (QoS) poses a number of challenges. One such challenge lies in the fact that SLAs are set prior to the execution of a job, but the execution environment is subject to a number of possible disturbances, such as poor knowledge about actual resource necessity, demand peaks and hardware malfunctions, amongst others. Thus by using a fixed resource allocation, the manager of a shared computing environment risks violating user SLAs. Furthermore, the complexity of managing several workload executions increases with the number of workloads, implying the need for an automatic method to manage and control the execution of workloads. The execution time SLA is specially important in streaming scenarios such as web applications and continuous video processing, and is the focus of this paper. A method based on adaptive model predictive control (aMPC) is proposed here to adapt the amount of allocated resources to iterative workloads. The methodology is tested applied to Deep Learning Workloads, in standalone and multi-workload versions. The results show that using adaptive optimal control with a linearized model improves with respect to simpler control laws as well as reinforcement learning approaches.

VI132
Computers, Cognition and Communication - Computational Intelligence in Control
VI132-01 New Developments and Applications of State Estimation and Control of Uncertain Systems by Artificial Neural Networks   Invited Session, 6 papers
VI132-02 Multi-Objective Optimization Techniques in Control Systems Engineering   Open Invited Session, 6 papers
VI132-03 Recent Advances in Fuzzy Control: Theory and Applications   Open Invited Session, 15 papers
VI132-04 Reinforcement Learning and Nonlinear Optimal Control   Open Invited Session, 23 papers
VI132-05 Intelligent Control   Regular Session, 7 papers

VI132-01
New Developments and Applications of State Estimation and Control of Uncertain Systems by Artificial Neural Networks	Invited Session
Chair: Andrianova, Olga	MIEM HSE
Co-Chair: Chairez, Isaac	UPIBI-IPN
Organizer: Poznyak, Alexander S.	CINVESTAV-IPN
Organizer: Andrianova, Olga	MIEM HSE
Organizer: Sanchez, Edgar N.	CINVESTAV
Organizer: Chairez, Isaac	UPIBI-IPN
Paper VI132-01.1
PDF · Video · Dnn Projectional Observer for Advanced Ozonation Systems of Complex Contaminants Mixtures (I)
Andrianova, Olga	MIEM HSE
Poznyak, Tatyana	IPN
Poznyak, Alexander S.	CINVESTAV-IPN
Chairez, Isaac	UPIBI-IPN
Keywords: Adaptive neural and fuzzy control, Fuzzy and neural systems relevant to control and identification, Reinforcement learning control Abstract: The aim of this study is to provide a class of state observers, based on differential neural networks, to approximate a class of advanced oxidation systems, based on the application of ozone high oxidant power and catalyst (the named catalytic ozonation). The study considers the design of a state observer for uncertain systems with the restrictions of the ozonation system, including the positivity of the states, as well as the control action. The observer includes a projection operator which is motivated by the state constraints. The learning laws of the proposed differential neural networks are obtained using a class of controlled state restricted Lyapunov functions. The detailed stability analysis proves the input to state stability with respect to the modeling error, as well as the bounded uncertainties of the ozonation system. The experimental confirmation of the state estimation is also presented. The experimental case considers the ozonation of a toxic organic contaminant (therephtalic acid) which is a regular pollutant of the plastic industry wastewater.
Paper VI132-01.2
PDF · Video · Dynamic Switched Non-Parametric Identification of the Human Physiological Response under Virtual Reality Stimuli (I)
Hernandez, Gustavo	CINVESTAV
Fuentes, Rita Q.	Tecnológico De Monterrey, Escuela De Ingeniería Y Ciencias
Garcia-Gonzalez, Alejandro	Tecnológico De Monterrey, Escuela De Medicina Y Ciencias De La S
Luviano-Juárez, Alberto	UPIITA - IPN México
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control Abstract: In this work, it is proposed a Switched Differential Neural Networks structure (SDNN) to model the human physiological response in a virtual stimuli scenario. Two physiological variables are assessed: electrocardiography and electrodermal activity, which provide a reflex response after stimuli. The proposed approach is focused on the representation of two discrete primary states, relaxation and stress as the response of the virtual stimuli. A switched dynamic approach is set, in which the trigger of an stimuli generates a change in the heartbeat rate as well as in the skin conductivity, constructing the switch between the mentioned states. The SDNN allow to obtain a model structure whose dynamics corresponds to the rate of change of the physiological variables, given as result a particular class of uncertain switched systems. The proposed non-parametric identification in this switched structure is implemented and experimentally assessed showing appropriate convergence rates in, both, switching regions and the continuous states.
Paper VI132-01.3
PDF · Video · Adaptive Discontinuous Control for Homogeneous Systems Approximated by Neural Networks (I)
Ballesteros-Escamilla, Mariana	Unidad Profesional Interdisciplinaria De Biotecnología
Polyakov, Andrey	INRIA Lille Nord-Europe
Efimov, Denis	Inria
Chairez, Isaac	UPIBI-IPN
Poznyak, Alexander S.	CINVESTAV-IPN
Keywords: Fuzzy and neural systems relevant to control and identification, Adaptive neural and fuzzy control, Robust neural and fuzzy control Abstract: This study is devoted to the design of an adaptive discontinuous control based on differential neural networks (DNNs) for a class of uncertain homogeneous systems. The control is based on the universal approximation properties of artificial neural networks (ANNs) applied on a certain class of homogeneous nonlinear functions. The adaptation laws for the DNNs parameters are obtained with the application of the Lyapunov stability theory and the homogeneity properties of the approximated nonlinear system. The stability analysis of the closed loop system with the proposed controller is presented. The estimation error in the approximation of the uncertain homogeneous functions is considered in the stability analysis. The performance of the controller is illustrated by means of a numerical simulation of a homogeneous model.
Paper VI132-01.4
PDF · Video · Secondary Control of Microgrids Via Neural Inverse Optimal Distributed Cooperative Control (I)
Vega, Carlos J.	CINVESTAV-IPN Unidad Guadalajara
Djilali, Larbi	CINVESTAV Guadalajara
Sanchez, Edgar N.	CINVESTAV
Keywords: Adaptive neural and fuzzy control, Robust neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: In this paper, a new control scheme of secondary voltage and frequency control based on a discrete-time neural inverse optimal distributed cooperative structure is proposed for islanded microgrids. A neural adaptive secondary controller for each distributed generator is developed to achieve the desired goals. The proposed controllers are composed of an on-line neural identification scheme on the basis of a recurrent high-order neural network using the extended Kalman filter and a nonlinear control strategy. Additionally, the proposed control scheme does not require information of all installed distributed generators neither a distributed generator model, which improves reliability. The proposed controllers are validated through simulation for an islanded AC microgrid.
Paper VI132-01.5
PDF · Video · Differential Neural Network Identifier with Composite Learning Laws for Uncertain Nonlinear Systems (I)
Guarneros Sandoval, Alejandro	CIDETEC -Instituto Politécnico Nacional
Salgado, Ivan de Jesus	Centro De Innovacion Y Desarrollo Tecnologico En Computo - Insti
Mera, Manuel Leonardo	ESIME, Instituto Politecnico Nacional
Ahmed, Hafiz	Coventry University
Keywords: Adaptive neural and fuzzy control, Robust neural and fuzzy control, Embedded computer control systems and applications Abstract: This manuscript describes the design and numerical implementation of a novel composite differential neural network aimed to estimate nonlinear uncertain systems. A differential neural network (DNN) with a composite feedback matrix approximates the structure of non-linear uncertain systems. The feedback matrix is assumed to belong to a convex set as well as the free parameters of the DNN (weights) at any instant of time. Therefore, l-different DNN works in parallel. A composite Lyapunov function finds the convex hull approximation of the set of DNN working together to improve the approximation capabilities of classical neural networks. The main result of this study shows the practical stability of the estimation error. Numerical simulations demonstrate the approximation capabilities of the composite DNN implemented in a Van Der Pol oscillator where the presence of high-frequency components makes difficult a classical DNN approximation.
Paper VI132-01.6
PDF · Video · β-Variational Classifiers under Attack (I)
Maggipinto, Marco	University of Padova
Terzi, Matteo	University of Padova
Susto, Gian Antonio	University of Padova
Keywords: Fuzzy and neural systems relevant to control and identification Abstract: Deep Neural networks have gained incredible attention in recent years thanks to the breakthroughs obtained in the field of Computer Vision. However, it has been shown that they provide limited robustness in their predictions. In particular, it is possible to synthesise small adversarial perturbations that imperceptibly modify a correctly classified input data, making the network confidently misclassify it. This has led to a plethora of different methods to try to improve robustness or detect the presence of these perturbations. In this paper, we perform an analysis of β-Variational Classifiers, a particular class of methods that not only solve a specific classification task, but they also provide a generative component that is able to generate new samples from the input distribution. More in details, we study their robustness and detection capabilities, together with some novel insights on the generative part of the model.

VI132-02
Multi-Objective Optimization Techniques in Control Systems Engineering	Open Invited Session
Chair: Reynoso-Meza, Gilberto	Pontificia Universidade Católica De Paraná
Co-Chair: Garcia-Nieto, Sergio	Polytechnic University of Valencia
Organizer: Reynoso-Meza, Gilberto	Pontificia Universidade Católica De Paraná
Organizer: Garcia-Nieto, Sergio	Polytechnic University of Valencia
Paper VI132-02.1
PDF · Video · Multi-Objective Non Linear Dynamic Model Identification Considering Nearly Optimal Solutions. Application to a μ-CHP System Based on PEMFC (I)
Pajares, Alberto	Universitat Politecnica De Valencia
Herrero Durá, Juan Manuel	Polytechnic Univ of Valencia
Blasco, Xavier	Polytechnic Univ of Valencia
Garcia-Nieto, Sergio	Polytechnic University of Valencia
Salcedo, Jose Vicente	Technical Univ of Valencia
Keywords: Evolutionary algorithms in control and identification Abstract: Solving a wide range of engineering problems can be approached from the point of view of multi-objective optimization (MOO), i.e. trying to optimize several conflicting objectives simultaneously. Solutions to these problems are not unique and the designer must choose from several optimal solutions (Pareto set), depending on his or her preferences. However, in addition to those solutions, there are almost optimal solutions that can be preferred for several reasons. For example, if the problem is multimodal, the optimization algorithm only offers one of the possible solutions. Furthermore, the problem may present a certain degree of simplification which implies that not all preferences are reflected in the minimization objectives. The nevMOGA algorithm (multiobjective genetic algorithm of the epsilon neighborhood variable) offers the possibility of finding, apart from an approximation to the Pareto optimal set, an extra set of potentially useful near optimal solutions. This result allows a final solution more closely aligned with the designer's actual preferences. This paper shows the application of this technique to the experimental identification problem of the parameters of a complex dynamic model. In particular, it is applied to identify the thermal model of a μ-CHP (micro Combined Heat and Power) system with a PEMFC (Proton Exchange Membrane Fuel Cell) type hydrogen cell.
Paper VI132-02.2
PDF · Video · Evolutionary Multi-Objective Optimization Design of a Butane Content Soft Sensor (I)
Alves Ribeiro, Victor Henrique	Pontifícia Universidade Católica Do Paraná
Reis Marchioro, Matheus Henrique	Pontifical Catholic University of Paraná
Reynoso-Meza, Gilberto	Pontificia Universidade Católica De Paraná
Keywords: Evolutionary algorithms in control and identification Abstract: Industrial processes must be well equipped with a variety of sensors to maintain a desired quality. However, some variables cannot be easily measured due to different causes, such as acquisition and/or maintenance costs and slow acquisition time. This situation leads to a lack of real-time information in the process, which could lead to lower quality in the final product. One of such processes is the debutanizer column, where butane content measurement is highly delayed. To enable online prediction of such variables, available information from the process can be used to estimate predictive models, known as soft sensors. To this end, data-driven techniques can be used, such as statistical and machine learning. However, such techniques usually take into account a single metric when estimating the models, and there are multiple factors that play an important role when designing a soft sensor, such as stability and accuracy. To cope with such a situation, this paper proposes a multi-objective optimization design procedure, where feature selection and ensemble member combination are performed. Therefore, the multi-objective differential evolution algorithm with spherical pruning (spMODE-II) is initially employed for building a pool of non-dominated linear support vector regression (SVR) models. Subsequently, the same evolutionary algorithm is applied for selecting the weights of the previously generated models in a weighted combination ensemble. In a final multi-criteria decision making stage, a preferred ensemble is selected using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Results indicate that the proposed approach is able to produce a highly stable and accurate butane content soft sensor for the debutanizer column.
Paper VI132-02.3
PDF · Video · Evolutionary Trajectory Planning with Obstacles for a Mobile Manipulator (I)
Gonçalves, Antônio Renato	Universidade Federal De Pernambuco
Guerrero-Pena, Elaine	Universidade Federal De Pernambuco
Ribeiro Araujo, Aluizio Fausto	Universidade Federal De Pernambuco - Ufpe
Durand-Petiteville, Adrien	Federal University of Pernambuco UFPE
Keywords: Evolutionary algorithms in control and identification Abstract: Trajectory planning is a crucial issue for robotics. In recent years, researchers have used meta-heuristics, such as Multi-Objective Evolutionary Algorithms (MOEAs), to handle it. However, despite the numerous favorable features of EAs, research is needed to analyze the efficiency and effectiveness of such algorithms to find an optimal trajectory. For this reason, we present a comparative study between different Pareto-based MOEAs for trajectory planning for a mobile manipulator in an environment with obstacles. In order to generate the trajectory in the joint space, two objective functions are considered: the Cartesian velocity and the joint speed. Both functions are modified to find feasible solutions that avoid collisions. Four state-of-the-art EAs for multi-objective optimization are selected to perform the study. The planned trajectories are tested in simulation and with the actual robot TIAGo. The results suggest that Pareto-based MOEAs are suitable for offline trajectory planning, especially OSP-NSDE, which found the best solutions in the shortest time.
Paper VI132-02.4
PDF · Video · Multi-Objective Control Engineering Benchmark (I)
Reynoso-Meza, Gilberto	Pontificia Universidade Católica De Paraná
Carrillo-Ahumada, J.	Universidad Del Papaloapan
Alves Ribeiro, Victor Henrique	Pontifícia Universidade Católica Do Paraná
Zanella, Tyene	Pontificia Universidade Católica Do Paraná
Keywords: Evolutionary algorithms in control and identification Abstract: In this paper we are presenting the statement and evaluation guidelines of a control engineering benchmark, oriented for multi-objective optimisation design techniques. This is done with the aim of promoting new research on this field, by defining a benchmark to have reproducibility and comparability of the three steps involved in the multi-objective process: problem statement, optimisation process and multi-criteria decision making. The proposed benchmark is a single-input single-output process based on the Peltier effect. Rules and guidelines, merged with common practices in control systems engineering, are highlighted and disclosed in the multi-objective open invited track 2020.
Paper VI132-02.5
PDF · Video · Applications of Multi-Objective Optimisation for PID-Like Controller Tuning: A 2015-2019 Review and Analysis (I)
Marques, Tainara	Pontificia Universidade Católica De Paraná
Reynoso-Meza, Gilberto	Pontificia Universidade Católica De Paraná
Keywords: Evolutionary algorithms in control and identification Abstract: The first open invited track in multi-objective optimisation for control systems was organised in 2017 with the idea of exchanging ideas and research about how those techniques are valuable for control engineers. Given that control engineering problems are generally multi-objective problems, multi-objective optimisation offers an interesting approach via the simultaneous optimisation of all design objectives. Controller tuning is not except from this. In this paper we perform a review and analysis of the literature, limited to the IFAC environment, to appreciate and detect new tendencies in controller tuning applications via multi-objective optimisation. Time window under consideration is from 2015 to date, coinciding with a previous review on the topic, as well as the emigration of IFAC proceedings to Elsevier.
Paper VI132-02.6
PDF · Video · A New Method for Deriving Weights in Group Fuzzy Analytic Hierarchy Process and Evaluation Measures
Che, Lin	Shanghai Jiao Tong University
Zhang, Yeming	Shanghai Municipal Engineering Design Institute (Group)CO., LTD
Wang, Jingcheng	Shanghai JiaoTong Univ
Bai, Miaoshun	Shanghai Municipal Engineering Design Institute (Group)CO., LTD
Keywords: Data-Driven Decision Making, Systems Theory Abstract: The paper discusses fuzzy comparison matrices, consistency check, weight prioritization methods and weight evaluation methods in fuzzy group analytic hierarchy process. There are various methods of weight prioritization, however, they are not critically evaluated. In the paper, two measures are introduced for the evaluation of the group weights. Then, a new method is proposed to improve the process of deriving weights and use it in an application compared to another common three methods. Our results show that the new method is a good method for deriving weights of indexes.

VI132-03
Recent Advances in Fuzzy Control: Theory and Applications	Open Invited Session
Chair: Guelton, Kevin	Université De Reims Champagne-Ardenne
Co-Chair: Bernal, Miguel	Sonora Institute of Technology
Organizer: Lendek, Zsofia	Technical University of Cluj-Napoca
Organizer: Bernal, Miguel	Sonora Institute of Technology
Organizer: Guelton, Kevin	Université De Reims Champagne-Ardenne
Paper VI132-03.1
PDF · Video · Robust Fault Detection for Switched Takagi-Sugeno Systems with Unmeasurable Premise Variables: Interval-Observer-Based Approach (I)
Garbouj, Yosr	National Engineering School of Tunis
Dinh, Thach Ngoc	Conservatoire National Des Arts Et Métiers
Wang, Zhenhua	Harbin Institute of Technology
Zouari, Talel	National Engineering School of Tunis
Ksouri, Moufida	National Engineering School of Tunis
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Keywords: Knowledge-based control, Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control Abstract: This paper deals with the problem of robust fault detection for continuous-time switched Takagi-Sugeno (T-S) fuzzy models. A procedure based on interval observers is proposed. First, an interval observer is designed under the assumption that the disturbances as well as the uncertainties are unknown but bounded. Stability and nonnegativity properties are given in terms of Linear Matrix Inequalities (LMIs) taking into account disturbances attenuation. Next, residual intervals generated by the interval observer are used for fault detection decision. Finally, a numerical example is provided to show the usefulness of this approach.
Paper VI132-03.2
PDF · Video · Adaptive Nonlinear Observer Design Via a Polytopic Split of Signals (I)
Quintana, Daniel	Sonora Institute of Technology
Estrada-Manzo, Victor	Universidad Politécnica De Pachuca
Bernal, Miguel	Sonora Institute of Technology
Keywords: Adaptive neural and fuzzy control, Robust neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: This paper provides a novel solution for adaptive observer design based on a polytopic representation of the error system. Thanks to a recently appeared factorisation, the proposal is able to deal with fully nonlinear system matrices and nonlinear outputs while dropping conditions on Lipschitz bounds and persistence of excitation. Examples are provided that illustrate the effectiveness and advantages of the new methodology over former approaches.
Paper VI132-03.3
PDF · Video · Copositive Conditions for LMI-Based Controller and Observer Design (I)
Arceo, Juan Carlos	Polytechnic University Hauts-De-France
Lauber, Jimmy	Polytechnic University Hauts-De-France
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control, Knowledge-based control Abstract: In this report we illustrate that nonlinear control and observer design can be described as a Positivstellensatz problem, we consider a quadratic candidate function to stabilize nonlinear systems that have been modeled via the nonlinear sector methodology as an exact convex representation. New shape-independent conditions for satisfying positiveness in double sums are established based on the concept of copositivity. The conditions obtained are compared with previous approaches found in the literature via a numerical example.
Paper VI132-03.4
PDF · Video · Finsler-Based Sampled-Data Controller Design for Takagi-Sugeno Systems (I)
Lopes, Adriano N.D.	University of Reims Champagne-Ardenne
Guelton, Kevin	Université De Reims Champagne-Ardenne
Arcese, Laurent	Université De Reims Champagne-Ardenne
Leite, Valter J. S.	CEFET/MG - Campus Divinopolis
Bourahala, Fayçal	Université De Skikda
Keywords: Robust neural and fuzzy control, Knowledge-based control, Embedded computer control systems and applications Abstract: This paper investigates the sampled-data control of continuous-time Takagi-Sugeno (T-S) fuzzy systems. The closed-loop dynamics is rewritten as a T-S system with input time-varying delays. In this context, asynchronous membership functions appears in the closed-loop dynamics. Thus, to reduce the conservatism of design conditions involving mismatch membership functions, a dedicated relaxation scheme is proposed. Then, from a convenient Lyapunov-Krasovskii function and the application of the Finsler's Lemma, new LMI-based conditions are proposed for the design of sampled-data Parallel-Distributed-Compensation (PDC) controllers. An example is provided to illustrate the effectiveness of the proposed design methodology in simulation, as well as to highlight their conservatism improvement regarding to previous related results from the literature.
Paper VI132-03.5
PDF · Video · Control of an Automated Wheelchair (I)
Gray, Michael	Autonomad Mobility / LAMIH UMR CNRS 8201
Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Delprat, Sebastien	Université Polytechnique Haut De France
Mohammad, Sami	Université De Valenciennes Et Du Hainaut-Cambrésis, LAMIH, FRE C
Keywords: Robust neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: Due to the world’s aging population, the development of affordable and easy to use wheelchairs is becoming a priority. In this study, the control of an automated wheelchair is proposed. The model equations are derived from the Euler-Lagrange equations, then a descriptor model is formulated. Next, a Takagi-Sugeno descriptor model with a limited number of rules is derived. The control and observation of the model is studied using the delayed non-quadratic Lyapunov function. The closed loop stability is proven using the separation theorem. Lastly, simulation results are given and discussed.
Paper VI132-03.6
PDF · Video · Stabilization of TS Fuzzy Systems with Time-Delay and Nonlinear Consequents (I)
Nagy, Zoltan	Technical University of Cluj Napoca
Mátyás, Amália	The Technical University of Cluj-Napoca
Lendek, Zsofia	Technical University of Cluj-Napoca
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control, Adaptive neural and fuzzy control Abstract: This paper proposes a controller design method for Takagi-Sugeno fuzzy systems with nonlinear consequents when the input is affected by time-delay. We consider that the membership functions may depend on both current and delayed states. To handle the nonlinear consequents a slope bounded condition is used. The design conditions are formulated in terms of linear matrix inequalities. A numerical example illustrates the obtained results.
Paper VI132-03.7
PDF · Video · Comparisons of Robust Methods on Feedback Linearization through Experimental Tests (I)
Oliveira, Lucas Silva	CEFET-MG Campus Divinopolis
Bento, Anderson Vitor	CEFET-MG Campus Divinopolis
Leite, Valter J. S.	CEFET/MG - Campus Divinopolis
Gomide, Fernando	University of Campinas
Keywords: Robust neural and fuzzy control, Adaptive neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: The feedback linearization is a powerful nonlinear method based on the principle of canceling the nonlinearities of the system model. However, if the model differs from the real system, the feedback linearization is prone to fail. Several studies look to provide robustness to the feedback-linearized system, but we note a lack of evaluation among such approaches under similar conditions in practical systems. This work contributes to filling such a gap by comparing the performance of three recent approaches proposed to robustify feedback linearization loops. Therefore, we design controllers based on the robust multi-inversion (RMI), the robust dynamic inversion (RDI), and the robust granular feedback linearization (RGFL), and evaluate them through real-time experiments. The test process consists of a nonlinear surge tank where the level must be controlled. Two experiments are performed to evaluate the controllers in the tracking and regulation modes when the system is subjected to disturbances. Classical quantitative indexes evaluate the performance of the closed-loop system. The experimental tests indicate that the RGFL controller outperforms the other approaches in both regulation and tracking.
Paper VI132-03.8
PDF · Video · Analysis and Synthesis Conditions for T-S Fuzzy Continuous-Time Systems with Partially Matched Premises (I)
da Cunha, Italo Henrique	CEFET-MG
Silva, Luis	CEFET-MG
Leite, Valter J. S.	CEFET/MG - Campus Divinopolis
Klug, Michael	Federal Institute of Santa Catarina
Keywords: Fuzzy and neural systems relevant to control and identification, Knowledge-based control, Robust neural and fuzzy control Abstract: A recognized challenge in the Takagi-Sugeno (T-S) fuzzy controller design concerns the use of different membership functions (MF) for controller and system. Most of the conditions available in the literature require that the controller's MF matche the system's one. Therefore, the implementation of such controllers may lead to unsafe operational conditions whenever such a match is lost. The main contribution of this paper is to provide new convex formulations for both stability analysis and controller design for T-S fuzzy systems under unmatched MF. We assume the same number of premises, yielding conditions called partially matched premises. To reduce conservatism, we use the Lyapunov approach, and we write the MF of the controller from the MF of the system. Two examples serve to compare our approach with others found in the literature. The achieved results suggest that our method outperforms the others.
Paper VI132-03.9
PDF · Video · Local State-Feedback Stabilization of Continuous-Time Takagi-Sugeno Fuzzy Systems (I)
Gomes, Izabella 0.	University of Campinas
Oliveira, Ricardo C. L. F.	University of Campinas
Peres, Pedro L. D.	Univ. of Campinas
Tognetti, Eduardo S.	University of Brasília
Keywords: Robust neural and fuzzy control Abstract: This paper deals with the problem of local state-feedback stabilization for continuous-time nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. The approach is based on a polytopic representation for the gradient of the membership functions but, differently from most of the available methods, bounds for the time-derivatives of the membership functions are not required. A two step strategy is proposed for the control design. First, a sufficient condition provides a stabilizing state-feedback gain for the dual system. Although there is no guarantee of stability for the original system, the controller is used as an initial condition for the second step of the method. If a feasible solution is found, a stabilizing state-feedback controller and an estimate of the domain of attraction are certified by means of a fuzzy Lyapunov function with polynomial dependence on the membership functions. The proposed conditions, given in terms of parameter-dependent linear matrix inequalities (LMIs) with a scalar search, can be solved by LMI relaxations with optimization variables considered as homogeneous polynomials of fixed degree. Examples based on T-S models borrowed from the literature illustrate that the method performs better than other existing approaches in terms of providing stabilizing gains associated with larger estimates for the domain of attraction.
Paper VI132-03.10
PDF · Video · Stabilizing Unstable Biomechanical Model to Understand Sitting Stability for Persons with Spinal Cord Injury (I)
Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Blandeau, Mathias	Lamih Umr Uphf Cnrs 8201
Nguyen, Anh-Tu	LAMIH UMR CNRS 8201, University of Valenciennes
Srihi, Hajer	Université Polytechnique Hauts-De-France, CNRS, UMR 8201 LAMIH
Dequidt, Antoine	Université De Valenciennes Et Du Hainaut-Cambrésis
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control, Knowledge-based control Abstract: This paper deals with the stabilization of a new open-loop unstable non-linear biomechanical model to represent a person living with a spinal cord injury. The computational complexity of the model when using the Takagi-Sugeno formalism is increased compared to previous models which is a source of difficulty to find a control law. Several solutions are presented combining robustness, and model simplification from previous works in the form of linear matrix inequalities which are then solved using convex optimization technics. Finally, simulations results are presented to show the validity and effectiveness of the different approaches.
Paper VI132-03.11
PDF · Video · Designing Fuzzy Descriptor Observer with Unmeasured Premise Variables for Head-Two-Arms-Trunk System (I)
Nguyen, Anh-Tu	LAMIH UMR CNRS 8201, University of Valenciennes
Pan, Juntao	North Minzu University
Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Blandeau, Mathias	Lamih Umr Uphf Cnrs 8201
Zhang, Weiwei	North Minzu University
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control, Embedded computer control systems and applications Abstract: Using the technique of unknown input observer, this paper aims at estimating internal variables of people living with a complete spinal cord injury (SCI). The goal is to provide a better understanding on the sitting control strategy of SCI people. The observer design is based on a Head-Two-Arms-Trunk (H2AT) model, belonging to a class of nonlinear descriptor systems. For observer design, this model is represented in a specific Takagi-Sugeno (TS) fuzzy form with nonlinear consequents. In contrast to previous fuzzy estimation results based on conventional TS fuzzy modeling, the new TS formulation allows separating all unmeasured premise variables in the nonlinear consequent parts. This contributes to reduce the computational burden of the observer design and the structural complexity of the designed fuzzy observer. In particular, the new formulation enables a more effective way to deal with unmeasured premise variables. Using Lyapunov stability theorem, sufficient conditions to design the unknown input observer are derived in the form of linear matrix inequalities, conveniently solved by convex optimization techniques. Simulation results demonstrate the effectiveness of the proposed observer design.
Paper VI132-03.12
PDF · Video · Robust Positively Invariant Polyhedral Sets and Constrained Control Using Fuzzy T-S Models: A Bilinear Optimization Design Strategy (I)
Dorea, Carlos E. T.	Universidade Federal Do Rio Grande Do Norte
Castelan, Eugenio B.	Univ. Federal De Santa Catarina
Ernesto, Jackson G.	Federal University of Tecnology - Paraná
Keywords: Fuzzy and neural systems relevant to control and identification Abstract: We propose a numerical method to compute stabilizing state feedback control laws and associated polyhedral invariant sets for nonlinear systems represented by Fuzzy Takagi-Sugeno (T-S) models, subject to state and control constraints, and persistent disturbances. Sufficient conditions are derived under which a given polyhedral set is positively invariant under a Parallel Distributed Controller (PDC), in the form of bilinear algebraic inequalities. Then, a bilinear programming (BP) problem is proposed to compute the state feedback gains and an associated positively invariant polyhedron, with predefined complexity, which solve a constrained regulation problem for the Fuzzy T-S system. A numerical example illustrates the effectiveness of the method.
Paper VI132-03.13
PDF · Video · Adaptive Fuzzy Control for Multivariable Nonlinear Systems with Indefinite Control Gain Matrix and Unknown Control Direction (I)
Labiod, Salim	University of Jijel
Guerra, Thierry Marie	Univ of Valenciennes Hainaut-Cambresis
Keywords: Adaptive neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: In this paper, we focus on the direct adaptive fuzzy control design for a class of uncertain MIMO nonlinear systems with indefinite control gain matrix and unknown control direction. The control design is based on the approximation of an unknown ideal control law that can meet the control objective by using fuzzy systems. The adjustable parameters of the used fuzzy systems are adjusted online using the error between the unknown ideal controller and the fuzzy controller. In this paper, unlike most existing works, the Nussbaum gain technique is not used to overcome the obstacle of the unknown control direction. In fact, with the help of a matrix decomposition technique, the unknown control direction is redefined as an unknown constant vector, which is estimated online by a suitable update law. The stability of the closed-loop system is studied using the Lyapunov direct approach. Numerical simulation results are provided to illustrate the effectiveness of the proposed control design approach.
Paper VI132-03.14
PDF · Video · Switched Control Design with Guaranteed Cost for Uncertain Nonlinear Systems Subject to Actuator Saturation (I)
Martins Silva, Hyago Ramom	São Paulo State University
Ramos, Igor Thiago Minari	UNESP - Faculdade De Engenharia De Ilha Solteira
Alves, Uiliam Nelson Lendzion Tomaz	Federal Institute of Education, Science and Technology of Paraná
Cardim, Rodrigo	UNESP - Sao Paulo State University
Teixeira, Marcelo C. M.	UNESP - Univ Estadual Paulista
Assuncao, Edvaldo	State University of Sao Paulo - UNESP
Keywords: Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control, Adaptive neural and fuzzy control Abstract: This manuscript proposes a robust switched controller design with minimization of an upper bound of a quadratic performance index (guaranteed cost) related to the system output for a class of uncertain nonlinear systems with actuator saturation described by Takagi-Sugeno (TS) fuzzy models. The switched control shown eliminates the necessity of finding or estimating the membership functions, which can be uncertain or complex to obtain. In most practical implementations, systems and actuators have physical limitations. Therefore, in order to approximate the theoretical switched controller design closer to its implementation, it will be considered that the system has an operating region and control signal saturation. The proposed switched controller design will be implemented in a bench active suspension system considering actuator saturation with uncertain mass and actuator fault. A comparison will be shown between robust single feedback gain and switched controller with the same design parameters.
Paper VI132-03.15
PDF · Video · Reduced-Complexity Affine Representation for Takagi-Sugeno Fuzzy Systems (I)
Dehak, Amine	Université Polytechnique Hauts-De-France
Nguyen, Anh-Tu	LAMIH UMR CNRS 8201, University of Valenciennes
Dequidt, Antoine	Université De Valenciennes Et Du Hainaut-Cambrésis
Vermeiren, Laurent	Université De Valenciennes Et Du Hainaut-Cambrésis
Dambrine, Michel	Université De Valenciennes Et Du Hainaut-Cambrésis
Keywords: Embedded computer control systems and applications, Fuzzy and neural systems relevant to control and identification, Robust neural and fuzzy control Abstract: This paper presents a systematic approach to reduce the complexity of sector nonlinearity TS fuzzy models using existing linear dependencies between local linear submodels. The proposed approach results in a decrease of the fuzzy model rules from 2^p to (p+1) rules while maintaining equivalence to the TS fuzzy model. An LMI formulation is presented to obtain conditions for stability analysis and stabilizing controllers design with some examples to offer a comparison between the two models. The main purpose of reduced-complexity models is to keep the design and the structure of the nonlinear control and observer schemes as simple as possible for real-time implementation, especially when dealing with highly nonlinear systems with a very large number of premise variables. Two real-world robotics examples are provided to highlight the interests and the curent limitations of the proposed approach.

VI132-04
Reinforcement Learning and Nonlinear Optimal Control	Open Invited Session
Chair: Busoniu, Lucian	Technical University of Cluj-Napoca
Co-Chair: Babuska, Robert	Delft University of Technology
Organizer: Busoniu, Lucian	Technical University of Cluj-Napoca
Organizer: Babuska, Robert	Delft University of Technology
Paper VI132-04.1
PDF · Video · Cost Efficient Distributed Load Frequency Control in Power Systems (I)
Ribeiro de Aquino Figueiredo Mello, Flavio	City, University of London
Apostolopoulou, Dimitra	City, University of London
Alonso, Eduardo	City University London
Keywords: Reinforcement learning control Abstract: The introduction of new technologies and increased penetration of renewable resources is altering the power distribution landscape which now includes a larger numbers of micro-generators. The centralized strategies currently employed for performing frequency control in a cost efficient way need to be revisited and decentralized to conform with the increase of distributed generation in the grid. In this paper, the use of Multi-Agent and Multi-Objective Reinforcement Learning techniques to train models to perform cost efficient frequency control through decentralized decision making is proposed. More specifically, we cast the frequency control problem as a Markov Decision Process and propose the use of reward composition and action composition multi-objective techniques and compare the results between the two. Reward composition is achieved by increasing the dimensionality of the reward function, while action composition is achieved through linear combination of actions produced by multiple single objective models. The proposed framework is validated through comparing the observed dynamics with the acceptable limits enforced in the industry and the cost optimal setups.
Paper VI132-04.2
PDF · Video · A Reinforcement Learning Method with Closed-Loop Stability Guarantee (I)
Osinenko, Pavel	Skolkovo Institute of Science and Technology
Beckenbach, Lukas	Technische Universität Chemnitz
Göhrt, Thomas	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Reinforcement learning control, Knowledge-based control Abstract: Reinforcement learning (RL) in the context of control systems offers wide possibilities of controller adaptation. Given an infinite-horizon cost function, the so-called critic of RL approximates it with a neural net and sends this information to the controller (called ``actor''). Infinite-horizon cost functions arise frequently in financial, medical, engineering, agricultural and other fields. However, the issue of closed-loop stability under RL-methods is still not fully addressed. Since the critic delivers merely an approximation to the value function of the corresponding infinite-horizon problem, no guarantee can be given in general as to whether the actor's actions stabilize the system. The current work offers an approach, which, starting with a (not necessarily smooth) control Lyapunov function (CLF), derives an online RL-scheme in such a way that practical semi-global stability property of the closed-loop can be established. The approach logically continues the work of the authors on parameterized controllers and Lyapunov-like constraints for RL, whereas the CLF now appears merely in one of the constraints of the control scheme. The analysis of the closed-loop behavior is done in a sample-and-hold (SH) manner thus offering a certain insight into the digital realization. The case study with a non-holonomic integrator shows the capabilities of the derived method to optimize the given cost function compared to a nominal stabilizing controller.
Paper VI132-04.3
PDF · Video · Fine-Tuning Deep RL with Gradient-Free Optimization (I)
de Bruin, Tim	Delft University of Technology
Kober, Jens	TU Delft
Tuyls, Karl	University of Liverpool
Babuska, Robert	Delft University of Technology
Keywords: Reinforcement learning control Abstract: Deep reinforcement learning makes it possible to train control policies that map high-dimensional observations to actions. These methods typically use gradient-based optimization techniques to enable relatively efficient learning, but are notoriously sensitive to hyperparameter choices and do not have good convergence properties. Gradient-free optimization methods, such as evolutionary strategies, can offer a more stable alternative but tend to be much less sample efficient. In this work we propose a combination, using the relative strengths of both. We start with a gradient-based initial training phase, which is used to quickly learn both a state representation and an initial policy. This phase is followed by a gradient-free optimization of only the final action selection parameters. This enables the policy to improve in a stable manner to a performance level not obtained by gradient-based optimization alone, using many fewer trials than methods using only gradient-free optimization. We demonstrate the effectiveness of the method on two Atari games, a continuous control benchmark and the CarRacing-v0 benchmark. On the latter we surpass the best previously reported score while using significantly fewer episodes.
Paper VI132-04.4
PDF · Video · Learning Nonlinear Robust Control As a Data-Driven Zero-Sum Two-Player Game for an Active Suspension System (I)
Radac, Mircea-Bogdan	"Politehnica" University of Timisoara
Lala, Timotei	Politehnica University of Timisoara
Keywords: Reinforcement learning control, Robust neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: An optimal robust control data-driven learning solution is proposed for an active suspension system. The problem is formulated as a zero-sum two-player differential game (ZS-TP-DG), where the optimal control law and the worst-case disturbance control law must be searched for. The distinctive features of the proposed solution are: a Q-learning-like data-driven model-free (with unknown process dynamics) algorithm relying on collected input-state data from the process; neural networks being used as generic function approximators; validation on an active suspension system that is easily amenable to artificial road profile disturbance generation. The superiority of the ZS-TP-DG controller over another optimal controller learned in a disturbance-free context is validated and proven.
Paper VI132-04.5
PDF · Video · Deep Reinforcement Learning with Embedded LQR Controllers (I)
Caarls, Wouter	Pontifical Catholic University of Rio De Janeiro
Keywords: Reinforcement learning control Abstract: Reinforcement learning is a model-free optimal control method that optimizes a control policy through direct interaction with the environment. For reaching tasks that end in regulation, popular discrete-action methods are not well suited due to chattering in the goal state. We compare three different ways to solve this problem through combining reinforcement learning with classical LQR control. In particular, we introduce a method that integrates LQR control into the action set, allowing generalization and avoiding fixing the computed control in the replay memory if it is based on learned dynamics. We also embed LQR control into a continuous-action method. In all cases, we show that adding LQR control can improve performance, although the effect is more profound if it can be used to augment a discrete action set.
Paper VI132-04.6
PDF · Video · Data-Driven Dynamic Multi-Objective Optimal Control: A Hamiltonian-Inequality Driven Satisficing Reinforcement Learning Approach (I)
Mazouchi, Majid	Michigan State University
Yang, Yongliang	University of Science and Technology Beijing
Modares, Hamidreza	Michigan State University
Keywords: Reinforcement learning control Abstract: This paper presents an iterative data-driven algorithm for solving dynamic multi-objective (MO) optimal control problems arising in control of nonlinear continuous-time systems with multiple objectives. It is first shown that the Hamiltonian function corresponding to each objective can serve as a comparison function to compare the performance of admissible policies. Relaxed Hamilton-Jacobi-bellman (HJB) equations in terms of HJB inequalities are then solved in a dynamic constrained MO framework to find Pareto-optimal solutions. Relation to satisficing (good enough) decision-making framework is shown. A Sum-of-Square (SOS)-based iterative algorithm is developed to solve the formulated MO optimization with HJB inequalities. To obviate the requirement of complete knowledge of the system dynamics, a data-driven satisficing reinforcement learning approach is proposed to solve the SOS optimization problem in real-time using only the information of the system trajectories measured during a time interval without having full knowledge of the system dynamics. Finally, a simulation example is provided to show the effectiveness of the proposed algorithm.
Paper VI132-04.7
PDF · Video · Safe Reinforcement Learning Via Projection on a Safe Set: How to Achieve Optimality? (I)
Gros, Sebastien	NTNU
Zanon, Mario	IMT Institute for Advanced Studies Lucca
Bemporad, Alberto	IMT Institute for Advanced Studies Lucca
Keywords: Reinforcement learning control Abstract: For all its successes, Reinforcement Learning (RL) still struggles to deliver formal guarantees on the closed-loop behavior of the learned policy. Among other things, guaranteeing the safety of RL with respect to safety-critical systems is a very active research topic. Some recent contributions propose to rely on projections of the inputs delivered by the learned policy into a safe set, ensuring that the system safety is never jeopardized. Unfortunately, it is unclear whether this operation can be performed without disrupting the learning process. This paper addresses this issue. The problem is analysed in the context of Q-learning and policy gradient techniques. We show that the projection approach is generally disruptive in the context of Q-learning though a simple alternative solves the issue, while simple corrections can be used in the context of policy gradient methods in order to ensure that the policy gradients are unbiased. The proposed results extend to safe projections based on robust MPC techniques.
Paper VI132-04.8
PDF · Video · Interpretable Control by Reinforcement Learning (I)
Hein, Daniel	Siemens AG
Limmer, Steffen	Siemens AG
Runkler, Thomas	Siemens AG
Keywords: Reinforcement learning control, Evolutionary algorithms in control and identification, Fuzzy and neural systems relevant to control and identification Abstract: In this paper, three recently introduced reinforcement learning (RL) methods are used to generate human-interpretable policies for the cart-pole balancing benchmark. The novel RL methods learn human-interpretable policies in the form of compact fuzzy controllers and simple algebraic equations. The representations as well as the achieved control performances are compared with two classical controller design methods and three non-interpretable RL methods. All eight methods utilize the same previously generated data batch and produce their controller offline without interaction with the real benchmark dynamics. The experiments show that the novel RL methods are able to automatically generate well-performing policies which are at the same time human-interpretable. Furthermore, one of the methods is applied to automatically learn an equation-based policy for a hardware cart-pole demonstrator by using only human-player-generated batch data. The solution generated in the first attempt already represents a successful balancing policy, which demonstrates the methods applicability to real-world problems.
Paper VI132-04.9
PDF · Video · Accelerating Reinforcement Learning with Suboptimal Guidance (I)
Bøhn, Eivind	SINTEF
Moe, Signe	Norwegian University of Science and Technology
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Reinforcement learning control, Knowledge-based control Abstract: Reinforcement learning in domains with sparse rewards is a difficult problem, and a large part of the training process is often spent searching the state space in a more or less random fashion for learning signals. For control problems, we often have some controller readily available which might be suboptimal but nevertheless solves the problem to some degree. This controller can be used to guide the initial exploration phase of the learning controller towards reward yielding states, reducing the time before refinement of a viable policy can be initiated. To achieve such an exploration guidance while also allowing the learning controller to outperform the demonstrations provided to it, Nair et al. (2017) proposes to use a "Q-filter" to select states where the agent should clone the behaviour of the demonstrations. The Q-filter selects states where the critic deems the demonstrations to be superior to the agent, providing a natural way to adjust the guidance in a manner that is adaptive to the proficiency of the demonstrator. The contribution of this paper lies in adapting the Q-filter concept from pre-recorded demonstrations to an online guiding controller, and further in identifying shortcomings in the formulation of the Q-filter and suggesting some ways these issues can be mitigated --- notably by replacing the value comparison baseline with the guiding controller's own value function --- reducing the effects of stochasticity in the neural network value estimator. These modifications are tested on the OpenAI Gym Fetch environments, showing clear improvements in adaptivity and yielding increased performance in all robotics environments tested.
Paper VI132-04.10
PDF · Video · Empirical Analysis of Policy Gradient Algorithms Where Starting States Are Sampled Accordingly to Most Frequently Visited States (I)
Aittahar, Samy	University of Liège
Fonteneau, Raphael	University of Liège
Ernst, Damien	University of Liège
Keywords: Reinforcement learning control Abstract: In this paper, we propose an extension to the policy gradient algorithms by allowing starting states to be sampled from a probability distribution that may differ from the one used to specify the reinforcement learning task. In particular, we suggest that, between policy updates, starting states should be sampled from a probability density function which approximates the state visitation frequency of the current policy. Results generated from various environments clearly demonstrate a performance improvement in terms of mean cumulative rewards and substantial update stability compared to vanilla policy gradient algorithms where the starting state distributions are either as specified by the environment or uniform distributions over the state space. A sensitivity analysis over a subset of the hyper-parameters of our algorithm also suggests that they should be adapted after each policy update to maximise the improvements of the policies.
Paper VI132-04.11
PDF · Video · An Approximate Dynamic Programming Approach for Dual Stochastic Model Predictive Control (I)
Arcari, Elena	ETH Zurich
Hewing, Lukas	ETH Zurich
Zeilinger, Melanie N.	ETH Zurich
Keywords: Reinforcement learning control Abstract: Dual control explicitly addresses the problem of trading off active exploration and exploitation in the optimal control of partially unknown systems. While the problem can be cast in the framework of stochastic dynamic programming, exact solutions are only tractable for discrete state and action spaces of very small dimension due to a series of nested minimization and expectation operations. We propose an approximate dual control method for systems with continuous state and input domain based on a rollout dynamic programming approach, splitting the control horizon into a dual and an exploitation part. The dual part is approximated using a scenario tree generated by sampling the process noise and the unknown system parameters, for which the underlying distribution is updated via Bayesian estimation along the horizon. In the exploitation part, we fix the resulting parameter estimate of each scenario branch and compute an open-loop control sequence for the remainder of the horizon. The key benefit of the proposed sampling-based approximation is that it enables the formulation as one optimization problem that computes a collection of control sequences over the scenario tree, leading to a dual model predictive control formulation.
Paper VI132-04.12
PDF · Video · Biomimetic Optimal Tracking Control Using Mean Field Games and Spiking Neural Networks (I)
Zhou, Zejian	University of Nevada, Reno
Fadali, Mohammed Sami	Univ of Nevada
Xu, Hao	University of Nevada, Reno
Keywords: Real-time algorithms, scheduling, and programming, Reinforcement learning control Abstract: This paper investigates decentralized optimal tracking control for multi-agent systems (MAS)s with a large population. Unlike conventional decentralized control, two major challenges must be addressed when the population size of the MAS is large: the "curse of dimensionality" and environmental uncertainties. The paper develops a novel online learning decentralized adaptive optimal control strategy to address these challenges by combining the emerging Mean Field Games (MFG) theory with a novel Biomimetic Actor-Critic-Mass (B-ACM) learning algorithm. Mean-field control is developed as a decentralized optimal controller that can effectively reduce the computational complexity and the communication effort. A Biomimetic neural network that mimics the human brain, which is much more efficient than traditional Artificial Neural Networks (ANNs), is designed using Spiking Neural Networks (SNN)s. The information is encoded into a sparse spikes vector similar to the human brain. The SNN technique and mean-field control are merged into one unified framework, B-ACM. The B-ACM includes three regions of neurons in coordination with mean-field control: 1) Reward region to approximate the optimal cost function, 2) MAS Population Estimation region to predict the effects from other agents, and 3) Action region to compute the optimal control. Moreover, the paper introduces a novel SNN weight update law based on gradient descent. The effectiveness of the proposed scheme is validated through numerical simulations.
Paper VI132-04.13
PDF · Video · An Online Evolving Framework for Advancing Reinforcement-Learning Based Automated Vehicle Control (I)
Han, Teawon	The Ohio State University
Nageshrao, Subramanya Prasad	Ford
Filev, Dimitar	Ford Motor Company
Ozguner, Umit	Ohio State Univ
Keywords: Evolutionary algorithms in control and identification, Reinforcement learning control Abstract: In this paper, an online evolving framework is proposed to detect and revise a controller's imperfect decision-making in advance. The framework consists of three modules: the evolving Finite State Machine (e-FSM), action-reviser, and controller modules. The e-FSM module evolves a stochastic model (e.g., Discrete-Time Markov Chain) from scratch by determining new states and identifying transition probabilities repeatedly. With the latest stochastic model and given criteria, the action-reviser module checks validity of the controller's chosen action by predicting future states. Then, if the chosen action is not appropriate, another action is inspected and selected. In order to show the advantage of the proposed framework, the Deep Deterministic Policy Gradient (DDPG) w/ and w/o the online evolving framework are applied to control an ego-vehicle in the car-following scenario where control criteria are set by speed and safety. Experimental results show that inappropriate actions chosen by the DDPG controller are detected and revised appropriately through our proposed framework, resulting in no control failures after a few iterations.
Paper VI132-04.14
PDF · Video · Cross Entropy Optimization of Action Modification Policies for Continuous-Valued MDPs (I)
Mirkamali, Kamelia	Khaje Nasir Toosi University
Busoniu, Lucian	Technical University of Cluj-Napoca
Keywords: Reinforcement learning control, Evolutionary algorithms in control and identification Abstract: We propose an algorithm to search for parametrized policies in continuous state and action Markov Decision Processes (MDPs). The policies are represented via a number of basis functions, and the main novelty is that each basis function corresponds to a small, discrete modification of the continuous action. In each state, the policy chooses a discrete action modification associated with a basis function having the maximum value at the current state. Empirical returns from a representative set of initial states are estimated in simulations to evaluate the policies. Instead of using slow gradient-based algorithms, we apply cross entropy method for updating the parameters. The proposed algorithm is applied to a double integrator and an inverted pendulum problem, with encouraging results.
Paper VI132-04.15
PDF · Video · Combining System Identification with Reinforcement Learning-Based MPC (I)
Martinsen, Andreas Bell	NTNU
Lekkas, Anastasios M.	Norwegian University of Science and Technology
Gros, Sebastien	Assistant Pr. Chalmers University, Göteborg
Keywords: Reinforcement learning control, Adaptive neural and fuzzy control, Robust neural and fuzzy control Abstract: In this paper we propose and compare methods for combining system identification (SYSID) and reinforcement learning (RL) in the context of data-driven model predictive control (MPC). Assuming a known model structure of the controlled system, and considering a parametric MPC, the proposed approach simultaneously: a) Learns the parameters of the MPC using RL in order to optimize performance, and b) fits the observed model behaviour using SYSID. Six methods that avoid conflicts between the two optimization objectives are proposed and evaluated using a simple linear system. Based on the simulation results, hierarchical, parallel projection, nullspace projection, and singular value projection achieved the best performance.
Paper VI132-04.16
PDF · Video · A Digital Receding-Horizon Learning Controller for Nonlinear Continuous-Time Systems (I)
Zhang, Xinglong	National University of Defense Technology
Li, Wenzhang	National University of Defense Technology
Xu, Xin	National University of Defense Technology
Jiang, Wei	National University of Defense Technology
Keywords: Reinforcement learning control Abstract: The integration of reinforcement learning (RL) and model predictive control (MPC) is promising for solving nonlinear optimization problems in an efficient manner. In this paper, a digital receding horizon learning controller is proposed for continuous-time nonlinear systems with control constraints. The main idea is to develop a digital design for RL with actor-critic design (ACD) in the framework of MPC to realize near-optimal control of continuous-time nonlinear systems. Different from classic RL for continuous-time systems, the actor adopted is learned in discrete-time steps, while the critic evaluates the learned control policy continuously in the time domain. Moreover, we use soft barrier functions to deal with control constraints and the robustness of the actor-critic network is proven. A simulation study is considered to show the effectiveness of the proposed approach.
Paper VI132-04.17
PDF · Video · Structured Online Learning-Based Control of Continuous-Time Nonlinear Systems (I)
Farsi, Milad	Hybrid Sys Lab. (6470), Applied Mathematics Department, Universi
Liu, Jun	University of Waterloo
Keywords: Reinforcement learning control Abstract: Model-based reinforcement learning techniques accelerate the learning task by employing a transition model to make predictions. In this paper, a model-based learning approach is presented that iteratively computes the optimal value function based on the most recent update of the model. Assuming a structured continuous-time model of the system in terms of a set of bases, we formulate an infinite horizon optimal control problem addressing a given control objective. The structure of the system along with a value function parameterized in the quadratic form provides a flexibility in analytically calculating an update rule for the parameters. Hence, a matrix differential equation of the parameters is obtained, where the solution is used to characterize the optimal feedback control in terms of the bases, at any time step. Moreover, the quadratic form of the value function suggests a compact way of updating the parameters that considerably decreases the computational complexity. Considering the state-dependency of the differential equation, we exploit the obtained framework as an online learning-based algorithm. In the numerical results, the presented algorithm is implemented on four nonlinear benchmark examples, where the regulation problem is successfully solved while an identified model of the system is obtained with a bounded prediction error.
Paper VI132-04.18
PDF · Video · Multi-Agent Formation Control with Obstacles Avoidance under Restricted Communication through Graph Reinforcement Learning (I)
Wang, Huimu	University of Chinese Academy of Science
Qiu, Tenghai	Institute of Automation, Chinese Academy of Sciences
Liu, Zhen	Institute of Automation, Chinese Academy of Sciences
Pu, Zhiqiang	Institute of Automation, Chinese Academy of Sciences
Yi, Jianqiang	Institute of Automation, Chinese Academy of Sciences
Keywords: Reinforcement learning control, Real-time algorithms, scheduling, and programming Abstract: Multi-agent formation control with obstacles avoidance (MAFC-OA) is one of the attractive tasks of multi-agent cooperation. Although a number of algorithms can achieve formation control effectively, they ignore the nature structure feature of the graph formed by agents. Given this problem, a model, MAFC-OA, which is composed of observation attention network, action attention network and Multi-long short-term memory (Multi-LSTM) is proposed. With MAFC-OA, the agents can be trained to form the desired formation and avoid dynamic obstacles in the environments with restricted communication. Specifically, the above two attention networks not only incorporate the influence of the nearby agents’ observation and actions, but also enlarge the agents’ receptive field (communication range) through the chain propagation characteristics to promote cooperation among agents. Moreover, the Multi-LSTM allows the agents to take obstacles into consideration in the order of distance and to avoid the obstacles effectively. Simulations demonstrate that the agents can form the desired formation and avoid dynamic obstacles effectively.
Paper VI132-04.19
PDF · Video · A Reinforcement Learning Method with Closed-Loop Stability Guarantee for Systems with Unknown Parameters (I)
Göhrt, Thomas	Technische Universität Chemnitz
Griesing-Scheiwe, Fritjof	TU Chemnitz
Osinenko, Pavel	Skolkovo Institute of Science and Technology
Streif, Stefan	Technische Universität Chemnitz
Keywords: Reinforcement learning control, Knowledge-based control, Adaptive neural and fuzzy control Abstract: This work is concerned with the application of reinforcement learning (RL) techniques to adaptive dynamic programming (ADP) for systems with partly unknown models. In ADP, one seeks to approximate an optimal infinite horizon cost function, the value function. Such an approximation, i. e., critic, does not in general yield a stabilizing control policies, i. e., stabilizing actors. Guaranteeing stability of nonlinear systems under RL/ADP is still an open issue. In this work, it is suggested to use a stability constraint directly in the actor-critic structure. The system model considered in this work is assumed to be only partially known, specifically, it contains an unknown parameter vector. A suitable stabilizability assumption for such systems is an adaptive Lyapunov function, which is commonly assumed in adaptive control. The current approach formulates a stability constraint based on an adaptive Lyapunov function to ensure closed-loop stability. Convergence of the actor and critic parameters in a suitable sense is shown. A case study demonstrates how the suggested algorithm preserves closed-loop stability, while at the same time improving an infinite-horizon performance.
Paper VI132-04.20
PDF · Video · Path-Following Control of Fish-Like Robots: A Deep Reinforcement Learning Approach (I)
Zhang, Tianhao	Peking University
Tian, Runyu	China Aerodynamics Research and Development Center
Wang, Chen	Peking University
Xie, Guangming	Peking University
Keywords: Reinforcement learning control, Autonomous underwater vehicles, Trajectory Tracking and Path Following Abstract: In this paper, we propose a deep reinforcement learning (DRL) approach for path-following control of a fish-like robot. The desired path may be a randomly generated Bezier curve. First, to implement the locomotion control of the fish-like robot, we design a modified Central Pattern Generated (CPG) model, using which the fish achieves varied swimming behaviors just by adjusting a single control input. To reduce the reality gap between simulation and the physical system, using the experimental data of the real fish-like robot, we build a surrogate simulation environment, which also well balances the accuracy and the speed of training. Second, for the path-following control, we select the advantage actor-critic (A2C) approach and train the control policy in the surrogate simulation environment with a straight line as the desired path. Then the trained control policy is directly deployed on a physical fish-like robot to follow a randomly generated Bezier curve. The experimental results show that our proposed approach has good practical applicability in view of its efficiency and feasibility in controlling the physical fish-like robot. This work shows a novel and promising way to control biomimetic underwater robots in the real world.
Paper VI132-04.21
PDF · Video · Urea Injection Control Based on Deep-Q Networks for SCR Aftertreatment Systems (I)
Bae, Shin Young	Seoul National University
Jeong, Dong Hwi	Seoul National University
Kim, Yeonsoo	Seoul National University
Lee, Byung Jun	Seoul National University
Lim, Sanha	Seoul National University
Jung, Changho	Hyundai Motor Company
Kim, Chang Hwan	Hyundai Motor Company
Kim, Yong-Wha	Hyundai Motor Company
Lee, Jong Min	Seoul National University
Keywords: Reinforcement learning control Abstract: The regulations on NOx emissions from diesel vehicles have been stringent in recent years. Various techniques such as lean NOx trap (LNT) and selective catalytic reduction (SCR) have been developed to lessen the NOx emissions. The urea-based SCR method, which utilizes NH3 as reducing agent to remove NOx, is widely used. Determining optimal amount of injected urea that keeps NOx at outlet below regulated NOx emission and also minimizes the amount of dosed urea is important. Model predictive control (MPC) is popularly used to determine the optimal amount of injected urea. However, applying MPC to real vehicle driving may be difficult because the on-line computation of MPC is too costly to be conducted in the engine control unit (ECU), the computation performance of which is significantly low at present. Therefore, reinforcement learning (RL) is considered as an alternative to on-line control method. In this paper, deep Q-networks (DQN), which is an off-policy RL with discrete action space and suitable to solve high dimensional problem, is applied to determine the amount of urea injection in the SCR system. The simulation of urea injection control with DQN has been conducted with respect to inlet NOx emissions of real driving data.
Paper VI132-04.22
PDF · Video · Deep Reinforcement Learning and Randomized Blending for Control under Novel Disturbances
Sohege, Yves	Insight-Centre for Data Analytics
Provan, Gregory	University College Cork
Quiñones-Grueiro, Marcos	Universidad Tecnológica De La Habana José Antonio Echeverría (CU
Biswas, Gautam	Vanderbilt University
Keywords: Reinforcement learning control, Adaptive neural and fuzzy control Abstract: Enabling autonomous vehicles to maneuver in novel scenarios is a key unsolved problem. A well-known approach, Weighted Multiple Model Adaptive Control (WMMAC), uses a set of pretuned controllers and combines their control actions using a weight vector. Although WMMAC offers an improvement to traditional switched control in terms of smooth control oscillations, it depends on accurate fault isolation and cannot deal with unknown disturbances. A recent approach avoids state estimation by randomly assigning the controller weighting vector; however, this approach uses a uniform distribution for control-weight sampling, which is sub-optimal compared to state-estimation methods. In this article, we propose a framework that uses deep reinforcement learning (DRL) to learn weighted control distributions that optimize the performance of the randomized approach for both known and unknown disturbances. We show that RL-based randomized blending dominates pure randomized blending, a switched FDI-based architecture and pre-tuned controllers on a quadcopter trajectory optimization task in which we penalise deviations in both position and attitude.
Paper VI132-04.23
PDF · Video · Cascade Attribute Network: DecomposingReinforcement Learning Control Policiesusing Hierarchical Neural Networks
Chang, Haonan	University of Michigan, Ann Arbor
Xu, Zhuo	UC Berkeley
Tomizuka, Masayoshi	Univ of California, Berkeley
Keywords: Reinforcement learning control Abstract: Reinforcement learning methods have been developed to achieve great success in training control policies in various automation tasks. However, a main challenge of the wider application of reinforcement learning in practical automation is that the training process is hard and the pretrained policy networks are hardly reusable in other similar cases. To address this problem, we propose the cascade attribute network (CAN), which utilizes its hierarchical structure to decompose a complicated control policy in terms of the requirement constraints, which we call attributes, encoded in the control tasks. We validated the effectiveness of our proposed method on two robot control scenarios with various add-on attributes. For some control tasks with more than one add-on attribute attribute, by directly assembling the attribute modules in cascade, the CAN can provide ideal control policies in a zero-shot manner.

VI132-05
Intelligent Control	Regular Session
Chair: McLoone, Seán Francis	Queen's University Belfast
Co-Chair: Sanchez, Edgar N.	CINVESTAV
Paper VI132-05.1
PDF · Video · High-Order Sliding Modes Based On-Line Training Algorithm for Recurrent High-Order Neural Networks
Alanis, Alma Y.	Universidad De Guadalajara
Rios-Huerta, Daniel	University of Guadalajara
Rios, Jorge D.	Universidad De Guadalajara
Arana-Daniel, Nancy	University of Guadalajara
Lopez-Franco, Carlos	CUCEI, Universidad De Guadalajara
Sanchez, Edgar N.	CINVESTAV
Keywords: Adaptive neural and fuzzy control, Robust neural and fuzzy control, Fuzzy and neural systems relevant to control and identification Abstract: This work presents a discrete on-line training algorithm for recurrent high-order neural networks (RHONN). The proposed training algorithm is based on the arbitrary order differentiators of high-order sliding modes (HOSM) theory. Due to HOSM-based differentiators can approximate derivatives in finite time, the proposed training algorithm avoids the compute of the derivatives, unlike conventional training algorithms. The proposed HOSM-based algorithm is implemented for the training of a RHONN identifier, and its performance is compared with the results using the extended Kalman filter (EKF) training algorithm. Results of a implementation of the identifier for the Lorenz system and an implementation of the identifier for a tracked robot using experimental data are presented.
Paper VI132-05.2
PDF · Video · Signal Generation for Switched Reluctance Motors Using Parallel Genetic Algorithms
Eichhorn, Mike	Technische Universität Ilmenau
Purfürst, Sandro	NIDEC driveXpert GmbH
Shardt, Yuri A.W.	Technical University of Ilmenau
Keywords: Evolutionary algorithms in control and identification Abstract: Switched reluctance motors (SRM) are an inherent part in robotics and automation systems where energy and cost efficiency is required. This motor type has no windings and permanent magnets on the rotor which results in a simple and robust structure. However, SRMs require a complex electronic control system to generate a specified number of voltage pulses for each motor phase. This paper presents the signal generation of multiple phases using only one current sensor in an asymmetric half bridge (AHB). In addition to maintain the predetermined phase voltages, sufficient current measurement windows and a minimal current ripple for the individual phases are further optimization criteria for signal generation. The generation of a state vector which controls the individual semiconductor for each motor phase to achieve a required phase voltage and simultaneously fulfill the multi-objective optimization criteria is challenging. Due to the vast number of possible solutions, a genetic algorithm (GA) was used to find state combinations that are suitable for the formulated optimization criteria. The results were discussed and recommendations about the genotype representation and the used genetic operators were given. Interested readers will find detailed information about the software technical implementation using the Global Optimization Toolbox from MATLAB.
Paper VI132-05.3
PDF · Video · An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training
Zocco, Federico	Queen's University Belfast
McLoone, Seán Francis	Queen's University Belfast
Keywords: Fuzzy and neural systems relevant to control and identification Abstract: Motivated by the potential for parallel implementation of batch-based algorithms and the accelerated convergence achievable with approximated second order information a limited memory version of the BFGS algorithm has been receiving increasing attention in recent years for large neural network training problems. As the shape of the cost function is generally not quadratic and only becomes approximately quadratic in the vicinity of a minimum, the use of second order information by L-BFGS can be unreliable during the initial phase of training, i.e. when far from a minimum. Therefore, to control the influence of second order information as training progresses, we propose a multi-batch L-BFGS algorithm, namely MB-AM, that gradually increases its trust in the curvature information by implementing a progressive storage and use of curvature data through a development-based increase ("dev-increase") scheme. Using six discriminative modelling benchmark problems we show empirically that MB-AM has slightly faster convergence and, on average, achieves better solutions than the standard multi-batch L-BFGS algorithm when training MLP and CNN models.
Paper VI132-05.4
PDF · Video · On Bridge Surface Crack Detection Based on an Improved YOLO V3 Algorithm
Zhang, Yuexin	Fuzhou University
Huang, Jie	Fuzhou University
Cai, Fenghuang	Fuzhou University
Keywords: Fuzzy and neural systems relevant to control and identification Abstract: An improved bridge surface crack detection algorithm based on a further developed You Only Look Once version 3 algorithm (YOLO v3) is proposed to realize the fast and accurate detection of bridge surface cracks for timely repair application scenarios. The proposed algorithm is combined with MobileNets and convolutional block attention module (CBAM), which can detect bridge surface cracks in real time. The standard convolution is replaced by the depthwise separable convolution of MobileNets so as to reduce the number of network parameters. Moreover, in order to solve the problem of precision decline caused by depthwise separable convolution, the inverted residual block of MobileNetV2 is introduced. Furthermore, the proposed algorithm selectively learn the feature by multiplying the attention map with the input feature map through CBAM, and focus on channel and spatial attention mechanisms simultaneously. Finally, the feasibility of the algorithm is verified by experiment.
Paper VI132-05.5
PDF · Video · An Evaluation of Classification Methods for 3D Printing Time-Series Data (I)
Mahato, Vivek	University College Dublin
Obeidi, Muhannad Ahmed	Dublin City University
Brabazon, Dermot	Dublin City University
Cunningham, Padraig	University College Dublin
Keywords: Knowledge-based control Abstract: Additive Manufacturing presents a great application area for Machine Learning because of the vast volume of data generated and the potential to mine this data to control outcomes. In this paper we present preliminary work on classifying infrared time-series data representing melt-pool temperature in a metal 3D printing process. Our ultimate objective is to use this data to predict process outcomes (e.g. hardness, porosity, surface roughness). In the work presented here we simply show that there is a signal in this data that can be used for the classification of different components and stages of the AM process. In line with other Machine Learning research on time-series classification we use k-Nearest Neighbour classifiers. The results we present suggests that Dynamic Time Warping is an effective distance measure compared with alternatives for 3D printing data of this type.
Paper VI132-05.6
PDF · Video · A Concept for Fault Diagnosis Combining Case-Based Reasoning with Topological System Models
Zinn, Jonas	Technical University of Munich
Vogel-Heuser, Birgit	Technical University of Munich
Ocker, Felix	Technical University of Munich
Keywords: Knowledge-based control, Reinforcement learning control, Logical design, physical design, and implementation of embedded computer systems Abstract: Automated failure recovery plays an important role in improving Overall Equipment Effectiveness and is a building block of industry 4.0. However, in an increasingly dynamic market, failure recovery mechanisms need to be able to adapt to system changes. Starting with fault diagnosis in automated Production Systems for assembly and logistics, this paper proposes a novel approach to combining Model-based Reasoning on topological system models with Case-based Reasoning. The topological models are leveraged for case adaption, which significantly reduces the engineering effort of adding new fault types to the system, compared to signal-based methods. Furthermore, the approach does not rely on complete fault models existing in advance; thus, the case database can be continuously built up during operation.
Paper VI132-05.7
PDF · Video · Forecasting Electricity Demand in Households Using MOGA-Designed Artificial Neural Networks (I)
Bot, Karol	University of Algarve
Ruano, Antonio	Univ of Algarve
Ruano, Maria da Graça	University of Algarve
Keywords: Fuzzy and neural systems relevant to control and identification, Evolutionary algorithms in control and identification Abstract: The prediction of electricity demand plays an essential role in the building environment. It strongly contributes to making the building more energy-efficient, having the potential to increase both thermal and visual comfort of the occupants, while reducing energy consumption, by allowing the use of model predictive control. The present article focuses on the use of computational intelligence methods for prediction of the power consumption of a case study residential building, during a horizon of 12 hours. Two exogeneous variables (ambient temperature and day code) are used in the NARX model Two different time steps were considered in the simulations, as well as constrained and unconstrained model design. The study concluded that the smaller timestep and the constrained model design obtain the best power demand prediction performance. The results obtained compare very favourably with similar approaches in the literature.

VI133
Computers, Cognition and Communication - Telematics: Control Via Communication Networks
VI133-01 Methods and Engineering in Industrial Wireless Communication   Invited Session, 4 papers
VI133-02 Models and Methods for the Engineering of Cyber-Physical Systems with Increasing Autonomy   Open Invited Session, 4 papers
VI133-03 IT-Based Remote Control and Communication Technology   Regular Session, 4 papers

VI133-01
Methods and Engineering in Industrial Wireless Communication	Invited Session
Chair: Schulze-Zipper, Darina	Ifak, Institut F. Automation Und Kommunikation e.V. Magdeburg
Co-Chair: Georges, Jean-Philippe	University of Lorraine
Organizer: Schulze-Zipper, Darina	Ifak, Institut F. Automation Und Kommunikation e.V. Magdeburg
Paper VI133-01.1
PDF · Video · Link Scheduling Algorithm for Industrial Wireless Networks Applied to Factory Automation (I)
Cainelli, Gustavo Pedroso	UFRGS
Feldman, Max	Universidade Federal Do Rio Grande Do Sul
Künzel, Gustavo	Federal Institute of Science, Technology and Education, Rio Gr
Müller, Ivan	Federal University of Rio Grande Do Sul
Pereira, Carlos Eduardo	Federal Univ. of Rio Grande Do Sul - UFRGS
Netto, João César	UFRGS
Keywords: Real-time algorithms, scheduling, and programming, Telecommunication-based automation systems, Remote sensor data acquisition Abstract: Industrial Wireless Networks are an alternative to wired networks for process automation and factory automation. In this type of network, the network manager is responsible for creating and maintaining the network. One of the tasks of the network manager is the scheduling process. It is desirable that this process be carried out as fast as possible. In factory automation applications, this process becomes even more critical as cycle times are much shorter and the network topology changes more often compared to process automation applications. Therefore, one metric that should be considered when evaluating scheduling algorithms is the expected execution time under certain network conditions. This paper proposes a method that perform a pre-scheduling before the newtork start operating, in order to reduce the processing time of scheduling algorithms. When devices are joined to the network, they receive reserved timeslots in the pre-scheduling process making the search for available slots faster. We also compared the method proposed with scheduling algorithms applied in Industrial Wireless Networks, with the objective of identifying the behavior of the evaluated algorithms for different scenarios, considering the execution time as the main metric. Results show that the technique of pre-scheduling may be appropriate for networks where scheduling algorithms will often be required.
Paper VI133-01.2
PDF · Video · Adaptive Channel Map for Time Slotted Channel Hopping Industrial Wireless Networks (I)
Feldman, Max	Universidade Federal Do Rio Grande Do Sul
Cainelli, Gustavo Pedroso	UFRGS
Künzel, Gustavo	Federal Institute of Science, Technology and Education of Rio Gr
Müller, Ivan	Federal University of Rio Grande Do Sul
Pereira, Carlos Eduardo	Federal Univ. of Rio Grande Do Sul - UFRGS
Keywords: Telecommunication-based automation systems, Remote sensor data acquisition, Remote and distributed control Abstract: The use of wireless networks in industrial environments is a reality today because of its advantages, but with the use of such networks, the problem of coexistence becomes inevitable. This paper presents a system to deal with the problems brought on by the networks coexistence, and thus avoid a reduction in the robustness of the network in which this issue has been accomplished. An adaptive channel mapping system is proposed in industrial wireless networks, where the affected channels are removed from the channel map used. A case study of the adaptive channel mapping system in a WirelessHART network is performed.
Paper VI133-01.3
PDF · Video · A Study on the Application of Rateless Coding in Non-Cellular MIMO Systems for Machine-Type Communication (I)
Karrenbauer, Michael	University of Kaiserslautern
Melnyk, Sergiy	German Research Center for Artificial Intelligence
Krummacker, Dennis	German Research Center for Artificial Intelligence
Weinand, Andreas	University of Kaiserslautern
Schotten, Hans	Univ of Kaiserslautern
Keywords: Internet of things Abstract: For industrial applications, communication requirements are considerably different than in most other domains. Whereas in office environments and the consumer market networks are designed towards the maximum throughput, in Industry 4.0 scenarios, traffic inflicts real-time requirements, demands particular high reliability and low latency. Industrial applications of the past as well as in most current production facilities are interconnected via cable. Wireless communication in this surrounding is still a big challenge, due to the mentioned communication demands. The high demands on reliability and latency require adaptations both to the MAC layer and to the baseband signal processing of the radio system being used. Of particular importance here is the error protection coding of the radio system, the investigation of which is the subject of the given work. This needs to achieve particularly high reliability but also must not consume too much computation time, while introducing only a reasonable amount of redundancy. In order to strive for this goal, this paper examines the utilization of Fountain codes (which belong to the family of rateless codes) with very short packets (in the order of less than 100 bytes). Investigated is the impact in terms of packet error rate. It is numerically shown that the joint erasure- and error-correction coding outperforms the sole usage of either one coding scheme. Interestingly, this is true in the presence of a Rayleigh channel but also in the presence of an AWGN channel. Finally, the performance of such a method is compared to that of space time block coding.
Paper VI133-01.4
PDF · Video · Delay and Backlog Control of Aggregation Systems for Wireless Communications (I)
Georges, Jean-Philippe	University of Lorraine
Divoux, Thierry	Université De Lorraine - CNRS
Breck, Damien	University of Lorraine, CRAN, UMR 7039
Keywords: Traffic control systems, Real-time algorithms, scheduling, and programming, Remote and distributed control Abstract: The aggregation system implemented in wireless communication networks aims to optimise the network efficiency regarding the encapsulation information and the medium access mechanisms. This paper proposes to evaluate the performances of such (A-MSDU like) system from a dedicated frame point of view, which is important in order to predict the Quality of Service offered to a client or to an application. Regarding the incoming flows, enabling or disabling the aggregation system, and tuning in real-time the aggregates size, makes possible to satisfy both the users' requirement and the network provider efficiency. In the case of voice or video class wireless communication where some loss of data is acceptable, numerous simulations using Riverbed Modeler leaded to express several recommendations embedded in an algorithm which sets dynamically the aggregation parameters in order to adjust it to the incoming traffic.

VI133-02
Models and Methods for the Engineering of Cyber-Physical Systems with Increasing Autonomy	Open Invited Session
Chair: Pereira, Carlos Eduardo	Federal Univ. of Rio Grande Do Sul - UFRGS
Co-Chair: Fay, Alexander	Helmut Schmidt Universitaet
Organizer: Fay, Alexander	Helmut Schmidt Universitaet
Organizer: Diedrich, Christian	Otto-von-Guericke-University Magdeburg
Organizer: Niggemann, Oliver	Fraunhofer IOSB-INA
Organizer: Pereira, Carlos Eduardo	Federal Univ. of Rio Grande Do Sul - UFRGS
Organizer: Weyrich, Michael	University of Stuttgart
Organizer: Vyatkin, Valeriy	University of Auckland
Paper VI133-02.1
PDF · Video · Automation Architecture and Engineering for Modular Process Plants - Approach and Industrial Pilot Application (I)
Hoernicke, Mario	ABB AG Corporate Research, Ladenburg, Germany
Stark, Katharina	ABB Corporate Research Center Germany
Wittenbrink, Alexander	INVITE GmbH
Bloch, Henry	Institute of Automation Technology Helmut Schmidt University
Hensel, Stephan	Technische Universität Dresden, Chair of Process Control System
Menschner, Anna	Semodia GmbH
Fay, Alexander	Helmut Schmidt Universitaet
Knohl, Torsten	Bayer AG
Urbas, Leon	Technische Universität Dresden
Keywords: Production planning and control Abstract: This contribution presents an architecture and engineering approach for modular automation systems that meet the requirements of modular production plants. The architecture is based on the German guideline VDI/VDE/NAMUR 2658 that describes the interfaces between process modules and the process orchestration layer. The approach has been tested within an industrial pilot application of Bayer AG. The novel automation engineering approach as well as the results of the pilot are shown in this contribution.
Paper VI133-02.2
PDF · Video · A Toolchain for the Development of Agent-Based Smart Grid Control Solutions (I)
Törsleff, Sebastian	Helmut-Schmidt-University
Derksen, Christian	University of Duisburg
Ludwig, Marcel	University of Wuppertal
Linnenberg, Tobias	Helmut Schmidt University Hamburg
Wassermann, Erik	Helmut-Schmidt-University
Loose, Nils	University Duisburg-Essen
Fay, Alexander	Helmut Schmidt Universitaet
Keywords: Smart energy grids, Embedded computer control systems and applications, Knowledge-based control Abstract: The energy transition necessitates a variety of control solutions to integrate renewables-based energy generation and unlock demand-side flexibility. To contribute to solving this challenge, the authors built a toolchain for developing smart grid control solutions. This toolchain consists of methodological, conceptual and technological components. In this contribution, we detail the way in which the toolchain facilitates the continuous utilization of control software artifacts across simulations, testbeds and deployment. This capability has the potential to significantly reduce engineering effort and build trust in agent-based control solutions for smart grids.
Paper VI133-02.3
PDF · Video · Orchestration vs. Choreography - Functional Association for Future Automation Systems (I)
Stutz, Andreas	Siemens AG
Fay, Alexander	Helmut Schmidt Universitaet
Barth, Mike	Helmut-Schmidt-University
Maurmaier, Mathias	Siemens AG - Digital Industries - Technology and Innovations
Keywords: Telecommunication-based automation systems, Remote and distributed control, Programmable logic controllers Abstract: Production flexibility, engineering efficiency and faster time-to-market are customer needs in order to survive on the market. Highly flexible system architectures are the key to fulfill these needs. Today’s procedural flexibility, like in the IEC 61512 standard, is not sufficient. Extending flexibility is a must, whereas central orchestration systems reach their limits. Besides orchestration there is a second association method, the choreography. The focus of this contribution is the question of how choreography can be applied in the automation context. Starting point of this contribution is a terminology foundation in the domain of micro-service automation systems followed by a characterization of orchestration and choreogra-phy in the automation context. In this paper, we show that both methods complement each other ideally. Central orchestration is used to coordinate decentralized choreographies – complexity reduction combined with high flexibility.
Paper VI133-02.4
PDF · Video · Formal Definition of the Term "Semantics" As a Foundation for Semantic Interoperability in the Industrial Internet of Things (I)
Schröder, Tizian	Otto-von-Guericke-University
Diedrich, Christian	Otto-von-Guericke-University Magdeburg
Keywords: Embedded computer control systems and applications, Internet of things, Logical design, physical design, and implementation of embedded computer systems Abstract: Semantic interoperability is seen as the key to realizing the ideas of the Industrial Internet of Things (IIoT). In order to equip technical systems with such a capability, a precise definition of the term "semantics" is needed. Complex IIoT devices can only be developed properly on a formal foundation. Existing approaches that intend to specify the term "semantics" are often more intuitively motivated. These include, for example, the knowledge pyramid or the Levels of Conceptual Interoperability Model (LCIM). The paper provides a formal definition of the term "semantics" and relates these existing approaches critically to the proposed definition.

VI133-03
IT-Based Remote Control and Communication Technology	Regular Session
Chair: Knorn, Steffi	Uppsala University
Co-Chair: Georges, Jean-Philippe	University of Lorraine
Paper VI133-03.1
PDF · Video · Modelling and Synchronisation of Delayed Packet-Coupled Oscillators in Industrial Wireless Sensor Networks
Zong, Yan	Northumbria University
Dai, Xuewu	Northumbria University
Canyelles-Pericas, Pep	Northumbria University
Busawon, Krishna K.	Northumbria University
Binns, Richard James	Northumbria University
Gao, Zhiwei	Northumbria University
Keywords: Internet of things, Embedded computer control systems and applications, Remote and distributed control Abstract: In this paper, a Packet-Coupled Oscillators (PkCOs) synchronisation protocol is proposed for time-sensitive Wireless Sensor Networks (WSNs) based on Pulse-Coupled Oscillators (PCO) in mathematical biology. The effects of delays on synchronisation performance are studied through mathematical modelling and analysis of packet exchange and processing delays. The delay compensation strategy (i.e., feedforward control) is utilised to cancel delays effectively. A simple scheduling function is provided with PkCOs to allocate the packet transmission event to a specified time slot, by configuring reference input of the system to a non-zero value, in order to minimise the possibility of packet collision in synchronised wireless networks. The rigorous theoretical proofs are provided to validate the convergence and stability of the proposed synchronisation scheme. Finally, the simulations and experiments examine the effectiveness of PkCOs with delay compensation and scheduling strategies. The experimental results also show that the proposed PkCOs algorithm can achieve synchronisation with the precision of 26.3us (1 tick).
Paper VI133-03.2
PDF · Video · A Simple Classification of Discrete System Interactions and Some Consequences for the Solution of the Interoperability Puzzle
Johannes, Reich	SAP SE
Schröder, Tizian	Otto-von-Guericke-University
Keywords: Internet of things, Remote and distributed control Abstract: In this article, we introduce a classification of system interactions to guide the discourse on their interfaces and interoperability. It is based on a simple, but nevertheless complete classification of system interactions with respect to information transport and processing. Information transport can only be uni- or bidirectional and information processing is subclassified along the binary dimensions of state, determinism and synchronicity. For interactions with bidirectional information flow we are able to define a criterion for a layered structure of systems: we name a bidirectional interaction "horizontal" if all interacting systems behave the same with respect to state, determinism and synchronicity and we name it "vertical" — providing a semantic direction — if there is a behavioral asymmetry between the interacting systems with respect to these properties. It is shown that horizontal interactions are essentially stateful, asynchronous and nondeterministic and are described by protocols. Vertical interactions are essentially top-down-usage, described by object models or operations, and bottom-up-observation, described by anonymous events. The interaction classification thereby helps to better understand the significant relationships that are created between interacting discrete systems by their interactions and guides us on how to talk about discrete systems, their interfaces and interoperability. To show its conceptual power, we apply the interaction classification to assess several other architectural models, communication technologies and so called software design or architectural styles like SOA and REST.
Paper VI133-03.3
PDF · Video · Categorization of Industrial Communication Requirements As Key to Developing Application Profiles
Underberg, Lisa	Ifak E.V
Willmann, Sarah	Ifak - Institut F. Automation U. Kommunikation
Keywords: Telecommunication-based automation systems Abstract: Complex control algorithms base on the measurements of distributed sensors and the execution by distributed actuators. Consequently, communication networks are a vital part of modern automation applications. Currently, data are often exchanged using wired Industrial Ethernet networks, while the trend is moving towards wireless communication networks, as they provide flexible, mobile communication by retrofittable components. This trend entails the necessity to formally test the performance of a communication network, as the quantitative key performance indicators of wireless technologies are typically smaller than of wired technologies. By this performance testing, a suitable technology is identified ahead of its implementation in a real application environment. But formal performance testing must base on precisely defined communication requirements, as only this allows a meaningful assessment of the testing results. However, these specifications are currently not available, although the specification of industrial automation applications’ communication requirements is now being discussed for more than a decade. By reviewing the discussion of communication requirements, this paper clarifies, why the specification of requirements is complex and provides the reader with necessary information enabling to follow and to join the ongoing discussion. Furthermore, a promising approach mitigating the current challenges is presented. The proposed approach is of interest to developers of automation algorithms, since the algorithms implicitly assume the existence of a suitable communication technology. The proposed approach enables developers to easily fit their specific control application to a given requirement profile by comparing the given and the target characteristic parameters. This paper intends to sensitize with regard to taking the communication needs into account when developing automation algorithms.
Paper VI133-03.4
PDF · Video · Using SDN for Controlling the Carbon Footprint of the Internet
Hossain, Md Mohaimenul	Université De Lorraine, CRAN, CNRS, CRAN
Georges, Jean-Philippe	University of Lorraine
Rondeau, Eric	Cran-Cnrs Umr 7039
Divoux, Thierry	Université De Lorraine - CNRS
Keywords: Telecommunication-based automation systems, Evolutionary algorithms in control and identification, Real-time algorithms, scheduling, and programming Abstract: Several works have been done in order to balance the energy consumption of the network with traffic which aims to have a positive impact on the CO2 emission. However, CO2 and energy consumption cannot be considered proportionate if the means of electricity production differs. In this paper, we have proposed two different metrics namely Carbon Emission Factor and Non-Renewable Energy usage percentage for achieving green network. We have designed an algorithm considering these metrics as objective functions. We have considered a software defined network approach and provided a set of data and control plane for each metric. Their performances are then analyzed and compared with respect to green policy enabled Shortest Path First algorithm. All the experiments are conducted on GéANT network with realistic demand size. A comprehensive analysis of the quality of service parameters like the end to end delay and packet loss is also done for each metric of the algorithm.

VI142
Mechatronics, Robotics and Components - Mechatronic Systems
VI142-01 Advanced Motion Control Techniques for Precision Mechatronic Systems   Invited Session, 10 papers
VI142-02 Modeling, Analysis and Control of Smart and Adaptive Structures and Components   Invited Session, 6 papers
VI142-03 Optical Pointing and Scanning in Optomechatronic Systems   Invited Session, 7 papers
VI142-04 Advanced Robot Modeling and Control   Open Invited Session, 6 papers
VI142-05 Mechatronics and Intelligent Systems in Railways   Open Invited Session, 7 papers
VI142-06 Mechatronics Tools and Control Related to Robotic Manipulation    Open Invited Session, 8 papers
VI142-07 Modeling, Identification, Estimation and Control in Micromechatronic Systems   Open Invited Session, 15 papers
VI142-08 Reference Prefiltering for Precision Motion Control   Open Invited Session, 5 papers
VI142-09 Biomedical Mechatronics   Regular Session, 4 papers
VI142-10 Identification, Estimation and Control for Mechatronic Systems   Regular Session, 31 papers
VI142-11 Modeling and Design Methods for Mechatronic Systems   Regular Session, 8 papers
VI142-12 Motion Control   Regular Session, 27 papers
VI142-13 Vibration Control   Regular Session, 7 papers

VI142-01
Advanced Motion Control Techniques for Precision Mechatronic Systems	Invited Session
Chair: Atsumi, Takenori	Chiba Institute of Technology
Co-Chair: Seki, Kenta	Nagoya Institute of Technology
Organizer: Atsumi, Takenori	Chiba Institute of Technology
Organizer: Seki, Kenta	Nagoya Institute of Technology
Organizer: Yabui, Shota	Nagoya University
Paper VI142-01.1
PDF · Video · Performance Comparison between Triple-Stage Actuator Systems in HDDs (I)
Atsumi, Takenori	Chiba Institute of Technology
Yabui, Shota	Nagoya University
Keywords: Motion Control Systems, Vibration control, Mechatronic systems Abstract: In this paper, we present a comparison study between three triple-stage actuator systems of the magnetic-head positioning system in hard disk drives (HDDs). As of year 2019, we have four kinds of actuators for the magnetic-head positioning system: voice coil motor (``VCM"), ``Milli" actuator with two piezoelectric (PZT) elements, ``Micro" actuator with two PZT elements, and a ``Thermal" actuator that consists of heaters embedded in the magnetic head and move read/write elements a few nanometers in a horizontal direction with thermal expansion. This means that we are able to build three kinds of triple-stage actuator systems: ``VCM + Milli + Micro", ``VCM + Milli + Thermal", and ``VCM + Micro + Thermal". In order to find the best triple-stage actuator system for upcoming 1000 kTPI (track pitch: 25 nanometer) HDD era, we examine case studies and estimate the position error signals and movements of actuators of the track-following control systems under the external vibration in a file server. In this case study, it is shown that achievable disturbance-rejection performances of these triple-stage-actuator systems depend on not only the frequency responses the actuators but also the stroke limitations of the actuators. As a result, we found that the triple-stage actuator system that consist of the VCM, the Milli actuator, and the Micro actuator has the best performance for 1000 kTPI HDD.
Paper VI142-01.2
PDF · Video · Precise Motion Control of Wafer Stages Via Adaptive Neural Network and Fractional-Order Super-Twisting Algorithm (I)
Kuang, Zhian	Harbin Institute of Technology
Sun, Liting	University of California, Berkeley
Gao, Huijun	Harbin Institute of Technology
Tomizuka, Masayoshi	Univ of California, Berkeley
Keywords: Motion Control Systems, Identification and control methods, Mechatronics for Mobility Systems Abstract: To obtain precise motion control of wafer stages, an adaptive neural network and fractional-order super-twisting control strategy is proposed. Based on sliding mode control (SMC), the proposed controller aims to address two challenges in SMC: 1) reducing the chattering phenomenon, and 2) attenuating the influence of model uncertainties and disturbances. For the first challenge, a fractional-order terminal sliding mode surface and a super-twisting algorithm are integrated into the SMC design. To attenuate uncertainties and disturbances, an add-on control structure based on the radial basis function (RBF) neural network is introduced. Stability analysis of the closed-loop control system is provided. Finally, experiments on a wafer stage testbed system are conducted, which proves that the proposed controller can robustly improve the tracking performance in the presence of uncertainties and disturbances compared to conventional and previous controllers.
Paper VI142-01.3
PDF · Video · Improving Wafer Stage Performance with Multiple Hybrid Integrator-Gain Systems (I)
van den Eijnden, Sebastiaan	Eindhoven University of Technology
Francke, Michiel	ASML
Nijmeijer, Hendrik	Eindhoven Univ of Technology
Heertjes, Marcel	Eindhoven University of Technology
Keywords: Motion Control Systems, Mechatronic systems, Mechatronics Abstract: An experimental demonstration is given of a nonlinear feedback controller applied to a short-stroke wafer stage system of an industrial wafer scanner. The controller design adopts a classical linear PID-based configuration in which both the integrator and low-pass filter are replaced with hybrid integrator-gain-based filter elements. The reduced phase lag associated with these filters gives rise to increased design flexibility, and potentially enables a substantial increase in low-frequency disturbance suppression. The nonlinear controller is designed by means of a quasi-linear loop-shaping approach, while stability of the full nonlinear closed-loop system is verified by solving a set of linear matrix inequalities. Performance of the controlled system is discussed on the basis of measurement results obtained from a wafer stage system.
Paper VI142-01.4
PDF · Video · Controller Design Method for Stroke Reduction of Micro-Actuator in HDD (I)
Yabui, Shota	Nagoya University
Atsumi, Takenori	Chiba Institute of Technology
Inoue, Tsuyoshi	Nagoya University
Keywords: Motion Control Systems, Vibration control, Mechatronics Abstract: For realizing high information society, recording capacity of the hard disk drives (HDDs) is required to increase. The capacity of the HDDs depends on positioning accuracy of magnetic head which read/write the digital data on disks. To improve the positioning accuracy, the head positioning control system employs a dual-stage actuator system. The dual-stage actuator system is consisting of the voice coil motor (VCM) and the micro-actuator. The micro-actuator has possibility to move accurately the magnetic head in higher frequency. On the other hand, the stroke limitation can be problem for increasing the control bandwidth: improvement of the positioning accuracy. Especially, the stroke limitation is a major constraint to compensate for low frequency vibration. There is the tradeoff between the stroke limitation and the positioning accuracy. To overcome the problem, this study proposes the controller design method for stroke reduction of the micro-actuator. The proposed design method can adjust the main working frequency for each actuator. In this system, the VCM can mainly compensate for the low frequency vibration. The micro-actuator mainly focuses on stabilization of the control system in higher frequency, the working doesn't require the large stroke. The effectiveness is verified in the compensation of the representative internal and external vibration. The proposed method can reduce the stroke of the micro-actuator by about 60% with comparison to the conventional design method with keeping the positioning accuracy.
Paper VI142-01.5
PDF · Video · Development of Precise Control System for Compact Magnetic-Levitation Stage System (I)
Ogawa, Hironori	Hitachi, Ltd
Takahashi, Motohiro	Hitachi, Ltd
Kato, Takanori	Hitachi, Ltd
Keywords: Micro and Nano Mechatronic Systems, Motion Control Systems, Identification and control methods Abstract: Nanometer-scale positioning accuracy is required for semiconductor manufacturing systems and ultra-precision machine tools. One way to improve the accuracy is to support the table with a noncontact guide system that prevents the occurrence of guide friction and heat transfer from the lower table or base structure. For this purpose, we are developing a compact magnetic-levitation (maglev) stage that can be installed for nanometer-scale positioning of an XY stage system. The stage system contains an XY coarse stage driven by linear motors and a 6-DOF maglev fine stage driven by VCMs. The maglev stage has a compact structure and its levitation mass is less than 1 kg, which is dramatically more lightweight than existing maglev stages. Our stage system also has long strokes, such as 200 mm in the X and Y directions on a horizontal plane. In this paper, we describe a precise control system for the maglev fine stage and XY coarse stage and present its evaluation results. The control system consists of a levitation-stabilizing controller and an FF controller for improving the responsiveness of the coarse stage. The evaluation results demonstrate that the developed stage is capable of nanometer-scale positioning.
Paper VI142-01.6
PDF · Video · Automatic Adjustment Method for Cascade Control System Based on Iterative Setting of Stability-Margin Criterion Circle (I)
Kitayoshi, Ryohei	Yaskawa Electric Corporation
Fujimoto, Hiroshi	The University of Tokyo
Keywords: Vibration control, Application of mechatronic principles, Motion Control Systems Abstract: Demand for servo motors has increased in recent years as rising factory automation. With the increase in demand, controller adjustment work before the start of the production line has also been growing. Accordingly, we propose a novel automatic adjustment method that enables us to optimize controller parameters and controller structure and to overcome the conservativeness of the circle condition in the cascade control system. Previously, the performance of the controller based on the circle condition could be conservative. Therefore, we solve this problem by setting a criterion circle designed by stability margin iteratively and adjusting controller parameters and controller structure until stability margin is close enough to design value. The effectiveness of the proposed method is verified by the experiment with the high precision positioning device.
Paper VI142-01.7
PDF · Video · Development of Three-Degree-Of-Freedom Zero-Compliance Mechanism for Micro Force Measurement with a Cantilever (I)
Mizuno, Takeshi	Saitama Univ
Hayashi, Yoichiro	Saitama University
Takasaki, Masaya	Saitama Univ
Ishino, Yuji	Saitama University
Yamaguchi, Daisuke	Saitama University
Keywords: Mechatronics, Application of mechatronic principles, Mechatronic systems Abstract: A multi-degree-of-freedom zero-compliance mechanism is developed for measuring micro force with a cantilever. The force acting on a tip of the cantilever is usually estimated from the displacement of the tip caused by the force. However, the position and attitude of the tip vary after force acts on the tip from the original ones. To keep them invariant, a three-degree-of-freedom zero compliance mechanism is designed, fabricated and installed into a force measurement system. In the developed measurement system, the force is estimated from the displacement/attitude of a detection point of the zero-compliance mechanism. It is confirmed analytically and experimentally that both vertical displacement and attitude of the detection point are proportional to the force applied to the tip.
Paper VI142-01.8
PDF · Video · High Precision Positioning Using Acceleration and Displacement Sensors in Piezo-Driven Stage Systems (I)
Seki, Kenta	Nagoya Institute of Technology
Iwasaki, Makoto	Nagoya Institute of Technology
Keywords: Motion Control Systems, Mechatronic systems, Vibration control Abstract: This paper presents a control design approach to compensate for the phase delay and resonant vibration in the piezo-driven stage systems. A target piezo-driven stage is installed in a capacitive sensor to detect the accurate stage displacement, however, the sensing system generally includes a phase delay due to the data conversion process and lowpass filters in the amplifier to remove the sensor noise. In this study, a MEMS acceleration sensor signal is integrated into the displacement signal detected by a capacitive sensor to improve the phase characteristics at a high frequency range, and the composite filters are designed to synthesize two sensor signals. In addition, the acceleration minor-loop is added to robustly suppress the resonant vibration against the frequency variations. The effectiveness of the design approach is verified by conducting experiments using a commercial piezo-driven stage system.
Paper VI142-01.9
PDF · Video · Output Perfect Tracking Control for a Plant with PWM-Type Input (I)
Tamekuni, Kohta	Utsunomiya University
Suzuki, Masayasu	Utsunomiya University
Hirata, Mitsuo	Utsunomiya University
Keywords: Motion Control Systems, Mechatronics, Micro and Nano Mechatronic Systems Abstract: It is a well-established fact that an unstable zero may appear when a minimum-phase continuous-time system is discretized by a zero-order hold. Therefore, a feedforward controller cannot be obtained based on the inverse system; this is because it becomes unstable. Herein, an exact linearization method for a continuous-time system with a pulse-width modulation-type (PWM-type) input has been proposed showing that unstable zeros of the linearized discrete-time system can be moved to the stable region by altering the pulse-centers location. This enables the construction of a stable feedforward controller that achieves an output perfect tracking control. However, the current paper shows a trade-off between the stability of the stabilized zero and the maximum pulse-width. This prevents the unstable zero from moving to a high stability region, and shows some oscillation at the output of the feedforward controller. To address this, a zero-phase error filter has been introduced to reduce the oscillation. Further, a nonlinear deadbeat controller is also proposed, which can be applied to second and higher order systems. The effectiveness of the proposed methods are presented in this paper by performing simulations.
Paper VI142-01.10
PDF · Video · Iterative Feedback Tuning of Cascade Control for Position and Velocity of Two-Mass System (I)
Jung, Hanul	DGIST
Jeon, Kiho	Daegu Gyeongbuk Institute of Science and Technology
Oh, Sehoon	DGIST
Keywords: Mechatronic systems, Motion Control Systems, Mechatronics Abstract: The inaccuracy of position and velocity controllers due to the vibration in the two-mass system in industrial robots cause devastating problems in both safety and productivity. To solve this problem, a method for tuning a cascade controller applied to two-mass systems based on Iterative Feedback Tuning (IFT) is proposed. The proposed new iterative tuning method utilized a modified cost function to optimize the gains in a cascade control system and to address the complexity of the two-mass system due to higher-order dynamics. The performance of the proposed iterative tuning method is verified through several simulations.

VI142-02
Modeling, Analysis and Control of Smart and Adaptive Structures and Components	Invited Session
Chair: von Scheven, Malte	Institute for Structural Mechanics, University of Stuttgart
Co-Chair: Böhm, Michael	University of Stuttgart
Organizer: Sawodny, Oliver	Univ of Stuttgart
Organizer: Böhm, Michael	University of Stuttgart
Paper VI142-02.1
PDF · Video · Optimal Design of Adaptive Structures vs. Optimal Adaption of Structural Design (I)
Geiger, Florian	Institute for Structural Mechanics, University of Stuttgart
Gade, Jan	Institute for Structural Mechanics, University of Stuttgart
von Scheven, Malte	Institute for Structural Mechanics, University of Stuttgart
Bischoff, Manfred	Institute for Structural Mechanics, University of Stuttgart
Keywords: Design methodologies, Smart Structures, Modeling Abstract: Taking advantage of adaptivity in the field of civil engineering is an ongoing research topic. Integration of adaptive elements in the load-bearing structure is already well established in many other engineering fields. First investigations promise large material saving potentials also in the field of civil engineering, especially when it comes to high-rise buildings or wide spanned structures like roofs or bridges. In times of emission problems and shortage of materials, the potentials of adaptive civil structures open various new possibilities. In the design and optimization process of adaptive civil structures, we address the differences between classical approaches for passive systems and new practices considering adaptivity. By using a suitable actuator placement, it is possible to manipulate the displacements of the structure as well as the force distribution within the structure. Both material and energy savings can be accomplished with an integrated design of the adaptive structure taking into account the actuation, suitable combination of structural design and actuator placement. For demonstration of the differences in the design process and in the resulting optimized structure, we use a small case study on a truss structure, which is inspired by a high-rise building, and consider static loads.
Paper VI142-02.2
PDF · Video · Decentralized Control Design for Adaptive Structures with Tension-Only Elements (I)
Wagner, Julia Laura	University of Stuttgart
Böhm, Michael	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Vibration control, Design methodologies, Mechatronic systems Abstract: Adaptivity in civil engineering structures is realized by the integration of sensors, actuators and a control scheme. The large dimensions of such structures cause high installation effort for cabling and challenges in control through transmission delays. Furthermore, modern lightweight structures typically include elements that bear tension forces only, leading to a nonlinear model for control design. In this contribution, we propose a decentralized control scheme for civil engineering structures which can handle nonlinearities through tension-only elements in control design. A large structure is subdivided into local substructures, incorporating nonlinear elements each. The Craig-Bampton model order reduction is applied to the substructures, which can only be conducted by intelligent separation of degrees of freedom for inner and boundary nodes, where degrees of freedom influenced by tension-only elements are set as boundary nodes. Linearizing input transformations are designed by means of local substructures, forcing the nonlinear model to the dynamics of a local linear target system. Linear feedback controllers can be designed based on the linear target system. These decentralized linearizing input transformations and feedback controllers are applied to the combined nonlinear structure. This approach is illustrated numerically on an adaptive high-rise structure.
Paper VI142-02.3
PDF · Video · Design and Control of a Prototype Structure That Adapts to Loading through Large Shape Changes (I)
Reksowardojo, Arka P.	école Polytechnique Fédérale De Lausanne
Senatore, Gennaro	école Polytechnique Fédérale De Lausanne
Srivastava, Apoorv	Indian Institute of Technology Bombay
Smith, Ian F. C.	Ecole Polytechnique Fédérale De Lausanne
Unterreiner, Henry	Arup UK
Carroll, Chris	Arup UK
Keywords: Smart Structures, Identification and control methods, Design methodologies Abstract: This paper reports on experimental testing that was carried out on a prototype adaptive structure designed to counteract the effect of loading through controlled large shape changes. The prototype is 6.6 m truss equipped with 12 linear actuators which has been designed through a method that combines geometry optimization and non-linear shape control. The structure is designed to adapt into target shapes that are optimal under each load case. Shape adaptation is achieved through controlled length changes of linear actuators that strategically replace some of the structure elements. The actuator placement is optimized to control the structure into the required target shapes. This way, material utilization is maximized and thus material energy embodied is reduced. Experimental testing is carried out to verify numerical findings and investigate the feasibility of the design method. The applied load is inferred through a classification model based on supervised learning. A control algorithm based on a linear-sequential form of geometry optimization is proposed. Experimental results show that this method successfully allows for real-time shape adaptation to achieve stress homogenization under various loading conditions.
Paper VI142-02.4
PDF · Video · A Bilinear Approach to Model Predictive Control for Thermal Conditioning of Adaptive Buildings (I)
Oei, Marius	University of Stuttgart
Günther, Janine	University of Stuttgart
Böhm, Michael	University of Stuttgart
Park, Sumee	Fraunhofer Institute for Building Physics
Sawodny, Oliver	Univ of Stuttgart
Keywords: Modeling, Human-centred automation and design Abstract: The high resource and energy consumption of the building sector in both construction and operation is a growing problem worldwide. The largest contributor to operational energy consumption is thermal conditioning of the indoor space. In this context, inefficient control algorithms or parametrizations become a serious problem requiring thermal simulation models of buildings for system sizing and control parameter adjustments. However, the high complexity of the underlying dynamic models makes the design of model-based controllers difficult. Furthermore, typically used control schemes such as PI-control cannot incorporate all types of actuators that an adaptive building may provide. In this work, we derive a bilinear thermal model for adaptive ultra-lightweight buildings from the linearized model output of the Modelica library BuildingSystems by incorporating environmental and internal disturbances as well as a number of possible actuators for an adaptive building into the model as time-varying bilinear inputs. Based on the bilinear model, a model-predictive control algorithm is devised that incorporates disturbance forecasts. Exemplary simulations for a summer day show the efficacy of the control algorithm in employing indirect actuation.
Paper VI142-02.5
PDF · Video · Active Vibration Control of a Convertible Structure Based on a Polytopic LPV Model Representation (I)
Jirasek, Robert	Brandenburg University of Technology
Schauer, Thomas	Technische Universitaet Berlin
Bleicher, Achim	Brandenburg University of Technology
Keywords: Vibration control, Modeling, Smart Structures Abstract: This paper deals with modeling and control of lightweight convertible structures for the application in civil and structural engineering. Such structures are prone to vibrations due to their lightweight design. In addition, they exhibit transformation state dependent dynamic behavior. In order to guarantee a reliable operation, the use of active vibration control (AVC) is an effective means. For the example of a simplifed convertible structure, modeling is demonstrated using the linear parameter-varying (LPV) framework. Based on local linear time-invariant (LTI) models, derived from a fnite element model of the convertible structure, a polytopic LPV model is established. This LPV model is then utilized to design a polytopic LPV output-feedback controller for AVC during the structure's transformation. The effectiveness of the designed controller is validated in simulation.
Paper VI142-02.6
PDF · Video · Facade-Integrated Semi-Active Vibration Control for Wind-Excited Super-Slender Tall Buildings (I)
Zhang, Yangwen	Brandenburg University of Technology
Schauer, Thomas	Technische Universitaet Berlin
Wernicke, Laurenz	Technische Universität Berlin
Wulff, Wulf	Brandenburg University of Technology
Bleicher, Achim	Brandenburg University of Technology
Keywords: Smart Structures, Vibration control Abstract: Nowadays, skyscrapers are getting higher and more slender due to inner-city concentration, which makes the structure more susceptible to dynamic excitations. The design of super slender skyscrapers is governed primarily by wind excitation. A traditional Tuned Mass Damper (TMD) has been installed in many skyscrapers to mitigate wind-induced vibrations, which has been proven to be very reliable. However, it needs large additional mass and huge installation space near the top of the building, which makes TMD not that optimal for super slender skyscrapers. In this paper, a semi-active distributed-Multiple Tuned Facade Damper (d-MTFD) using movable facade elements as damping mass is investigated. The facade elements at the upper stories of the building are parallel movable to the primary structure. Electrical Machines (EM) as variable damper are integrated in their connections to realize semi-active vibration control, which makes the system more effective and robust. For real application, a practical design criterion is that the relative displacement of the facade elements cannot be too large, otherwise it makes the occupants feel uncomfortable. Therefore, multi-objective Genetic Algorithm (GA)-optimized on-off groundhook semi-active control is applied, where two control objectives are optimized. One control objective is to minimize the peak top floor acceleration and the other control objective is to minimize the maximum peak relative displacement of all the facade elements. As a result, a Pareto Front shows that better vibration suppression performance and smaller facade relative displacement can be achieved using the multi-objective optimized controller.

VI142-03
Optical Pointing and Scanning in Optomechatronic Systems	Invited Session
Chair: Csencsics, Ernst	Vienna University of Technology
Co-Chair: Maeda, Yoshihiro	Nagoya Institute of Technology
Organizer: Ito, Shingo	TU Wien
Organizer: Csencsics, Ernst	Vienna University of Technology
Organizer: Maeda, Yoshihiro	Nagoya Institute of Technology
Paper VI142-03.1
PDF · Video · Motion-Blur Compensation System Using a Rotated Acrylic Cube with Visual Feedback (I)
Hayakawa, Tomohiko	The University of Tokyo
Nakane, Haruka	The University of Tokyo
Ishikawa, Masatoshi	Univ. of Tokyo
Keywords: Perception and sensing, Motion Control Systems, Mechatronics for Mobility Systems Abstract: In an imaging system, motion blur occurs in an image when the target moves relative to the system, whereas there are restrictions and problems related to the long exposure time required by the method and the post-processing required after image processing. Therefore, in this research, we use the phenomenon by which the optical axis passing through an acrylic cube installed between the camera and the imaging target moves in parallel with the target's motion based on the difference in refractive index and Snell's law by rotating the cube. Thus, we propose a method to compensate for motion blur. Furthermore, we proposed a visual feedback method that can compensate for motion blur accurately for an unknown target speed by using a Laplacian filter and the template matching, as well as a constant speed. It was confirmed that the motion blur was significantly compensated in the experiment at a speed between 0 - 556 mm/s. Our result can be applied for the inspection systems which can capture the target's image precisely with high efficiency.
Paper VI142-03.2
PDF · Video · Noise Reduction of Learning Control for Periodic Motion of Galvanometer Scanner (I)
Ito, Shingo	TU Wien
Yoo, Han Woong	TU Wien
Schitter, Georg	Vienna University of Technology
Keywords: Motion Control Systems, Mechatronics, Design methodologies Abstract: For highly precise motion of a galvanometer scanner that tracks a periodic motion reference, learning control significantly decreases the tracking error. To achieve higher quality motion by reducing the angular sensor noise, this paper investigates inversion-based iterative control (IIC) that can learn only at the fundamental and harmonic frequencies of the periodic motion reference. This enables to separate the compensable tracking error from the noise to be eliminated during learning in the frequency domain. The analysis in the paper reveals a tradeoff for the noise reduction in the IIC design, and this paper proposes an equation to quickly tune a design parameter in the tradeoff for better performance. Furthermore, the effectiveness of the IIC algorithm is experimentally demonstrated for a galvanometer scanner. When the galvanometer scanner tracks a 20Hz triangular motion of +/-10 degrees, the IIC successfully decreases the residual tracking error by 41% to 2.83x10^-4 deg, by utilizing the noise reduction.
Paper VI142-03.3
PDF · Video · Dynamic Performance Estimation: A Design Tool for Mechatronic Scanners (I)
Csencsics, Ernst	Vienna University of Technology
Schitter, Georg	Vienna University of Technology
Keywords: Design methodologies, Mechatronic systems, Motion Control Systems Abstract: This paper presents an integrated framework for the dynamic performance estimation (DPE) of mechatronic scanners in the design phase, which is based on frequency domain models of system components and signals in the system. It considers stochastic noise sources (e.g. sensor noise) as well as deterministic signals (e.g. reference trajectory) and propagates each signal to the desired performance output (e.g. actuator current) via obtained transfer functions. The framework is evaluated for a 2 inch fast steering mirror (FSM) dedicated as optical scanner by comparing estimated and measured values for positioning uncertainty, rms coil current and rms tracking error. The estimated positioning uncertainty for the FSM with a range of 52.4 mrad deviates only 0.74 µrad from the measured value. The estimated values for three tested raster trajectories also show good agreement with the measurements resulting in averaged relative deviations of 12% for the rms current values and between 15-17% for the rms tracking error.
Paper VI142-03.4
PDF · Video · Surveillance System for Multiple Targets by Galvanometer Scanners (I)
Matsuka, Daisuke	Hitachi, Ltd
Mimura, Masahiro	Hitachi, Ltd
Keywords: Motion Control Systems, Mechatronics Abstract: To prepare for terrorist and/or criminal attacks using unmanned aerial vehicles (UAVs), we have developed the Galvano Camera System. This system, which detects suspicious UAVs, is based on the high-speed and precise positioning technology of the galvanometer scanners. The proposed system is able to observe multiple moving objects simultaneously, using the high response of the galvanometer scanners, and display objects in a single monitor. We have proved the effectiveness of the system through field tests.
Paper VI142-03.5
PDF · Video · Peak Filter Tuning Based on Disturbance Spectrum for MIMO High-Precision Scan Stage (I)
Mae, Masahiro	The University of Tokyo
Ohnishi, Wataru	The University of Tokyo
Fujimoto, Hiroshi	The University of Tokyo
Sakata, Koichi	NIKON
Hara, Atsushi	NIKON
Keywords: Micro and Nano Mechatronic Systems, Application of mechatronic principles, Identification and control methods Abstract: In high-precision positioning systems such as scanning machines, the feedback controller tuning needs a lot of time and skills. In particular, a feedback controller tuning with six-degree-of-freedoms (x,y,theta_z,z,theta_x,theta_y) is difficult because of the numbers of controller parameters in each axis. The feedback controllers designed as single-input single-output controllers in each axis may not achieve sufficient performance in multi-input multi-output systems, and stability may not be satisfied because of a coupling problem between each axis. The repetitive disturbance makes the performance worse in a constant velocity scanning motion, and they are conventionally rejected by a peak filter in other applications of high-precision systems such as a hard disk drive. In this paper, we propose a tuning method of a peak filter to suppress a repetitive disturbance which satisfies robust stability conditions for six-degree-of-freedom systems by using convex optimization. The effectiveness of the proposed method is verified by the error in the constant velocity scanning motion.
Paper VI142-03.6
PDF · Video · Autonomous Cascade Structure Feedback Controller Design with Genetic Algorithm-Based Structure Optimization (I)
Maeda, Yoshihiro	Nagoya Institute of Technology
Kunitate, Shu	Nagoya Institute of Technology
Kuroda, Eitaro	Nagoya Institute of Technology
Iwasaki, Makoto	Nagoya Institute of Technology
Keywords: Identification and control methods, Motion Control Systems, Design methodologies Abstract: Designing a precise feedback (FB) controller that realizes the required properties such as a wide bandwidth and robust stability/sensitivity for resonant modes is a key design issue in achieving the fast and precise positioning performance of galvano scanners used in laser drilling. The aim of this study is to develop an efficient controller structure optimization method in an autonomous cascade structure FB controller design. The genetic algorithm efficiently searches the optimal structure for a target plant with high-order resonant modes in a short time according to the fitness of the controller parameter optimization problem. The effectiveness of the proposed method is demonstrated through a comparison with the conventional full search-based structure optimization method using a laboratory galvano scanner.
Paper VI142-03.7
PDF · Video · Novel Motorization Axis for a Coarse Pointing Assembly in Optical Communication Systems (I)
Kramer, Lukas	TNO
Peters, Joost	TNO
Voorhoeve, Robbert	Eindhoven University of Technology
Witvoet, Gert	TNO
Kuiper, Stefan	Delft University of Technology
Keywords: Mechatronic systems, Motion Control Systems, Application of mechatronic principles Abstract: The demand for higher data transfer between satellites and ground stations is ever increasing. To address this, (Free-Space) Optical Communication (OC) technology is emerging. Pointing mechanisms with Low Size, Weight and Power (SWaP), high accuracy and low recurring costs are key enablers for constellations of OC systems. In this paper, TNO presents a novel motorization concept for Coarse Pointing Assemblies using a switched reluctance actuation principle combined with a magnetic hall sensor. Results on a single axis test setup show promising performance in terms of sensor accuracy, pointing jitter and motor control. The presented concept is a potential enabler for future motorization of Coarse Pointing Assemblies.

VI142-04
Advanced Robot Modeling and Control	Open Invited Session
Chair: Pashkevich, Anatol	IMT-Atlantique
Co-Chair: Kolyubin, Sergey	ITMO University
Organizer: Klimchik, Alexandr	Innopolis University
Organizer: Pashkevich, Anatol	IMT-Atlantique
Organizer: Kolyubin, Sergey	ITMO University
Organizer: Gaponov, Igor	Innopolis University
Paper VI142-04.1
PDF · Video · Robot Calibration Combining Kinematic Model and Neural Network for Enhanced Positioning and Orientation Accuracy (I)
Gadringer, Stefan	Johannes Kepler University Linz
Gattringer, Hubert	Johannes Kepler University Linz
Mueller, Andreas	Johannes Kepler University Linz
Naderer, Ronald	FerRobotics Compliant Robot Technology GmbH
Keywords: Identification and control methods, Intelligent robotics, Robotics technology Abstract: Traditionally, the calibration of robots is pursued either using model-based or model-free methods. Only a few attempts to combine both approaches were reported, particularly the combination of geometric calibration and artificial neural network (ANN). The latter was mostly used to compensate the positioning error, however. This paper introduces an ANN for compensation of residual positioning as well as orientation error. Moreover, the ANN compensation can be applied with or without prior geometric calibration. An automatic measurement procedure was developed and nearly 14000 robot poses were measured using a laser tracker. Five-fold cross validation on the training data was applied to find the best parameters of the ANN. These tests indicate that better accuracy is achievable by combining geometric calibration and ANN. Applying this combination on the test data reduced the maximum/average position error to 6.28%/4.26% and the maximum/average orientation error 7.41%/3.34% of the original values (obtained without calibration).
Paper VI142-04.2
PDF · Video · Dynamic Parameter Identification of a Novel Motion-Mode-Changing Quasi-Omnidirectional Mobile Platform (I)
Pucher, Florian	Johannes Kepler University Linz
Gattringer, Hubert	Johannes Kepler University Linz
Mueller, Andreas	Johannes Kepler University Linz
Keywords: Mobile robots, Identification and control methods, Modeling Abstract: In process automation of logistic systems autonomous mobile platforms play an important role with high demands on flexibility and maneuverability. Limited space can be a restriction for non-omnidirectional vehicles. In this paper a quasi-omnidirectional platform is considered which can switch between four different motion-modes: wheel alignment in a standstill, a car-like steered longitudinal motion, lateral motion and pure rotation. With the requirement of carrying heavy payloads, feed-forward control becomes an important part of the control concept. This paper presents an approach for parameter identification of this motion-mode-changing system. The equations of motion are formulated using a redundantly parameterized model, which is linear in inertia and friction parameters. For each motion-mode a kinematic model is used for elimination of the constraint forces. Not all parameters can be identified in every configuration. The main idea is to use a combination of simple vehicle movements in the parameter identification process. The identified dynamic parameters are then validated using a more complex movement where all parameters are needed and a configuration which has not been used for identification. Experimental results for a prototype are shown.
Paper VI142-04.3
PDF · Video · Trajectory Planning for a Segway Model Exploiting Inherent Feedforward Structure (I)
Zauner, Christian	Johannes Kepler University Linz
Mueller, Andreas	Johannes Kepler University Linz
Gattringer, Hubert	Johannes Kepler University Linz
Jörgl, Matthias	Trotec Laser GmbH
Keywords: Motion Control Systems, Mobile robots, Modeling Abstract: Time/energy optimal trajectory planning for a Segway model (inverted pendulum on two independently actuated wheels) is addressed. Basis for this planning is the dynamical model for this under-actuated, non-holonomic multibody system. In order to reduce the calculation effort for the optimization, an input/output transformation is applied, which leads to a control system in strict feedforward form. The full system state can thus be described by two outputs, which are parameterized by two B-splines. The system is required to move on the ground within a predefined area. For the optimization the control points of the B-Splines serve as optimization variables and the cost functional is comprised of the overall energy of the robot and the terminal time. Additionally to the maximum motor velocities and torques, the maximum ground reaction forces give rise to the constraints. The latter are crucial to ensure that the wheels do not slip.
Paper VI142-04.4
PDF · Video · Time-Optimal Path Following for Robotic Manipulation of Loosely Placed Objects: Modeling and Experiment (I)
Gattringer, Hubert	Johannes Kepler University Linz
Mueller, Andreas	Johannes Kepler University Linz
Oberherber, Matthias	Engel Austria GmbH
Kaserer, Dominik	B&R Industrial Automation
Keywords: Intelligent robotics, Identification and control methods, Robotics technology Abstract: A consistent method is presented for solving the so-called general waiter problem, which resembles the general task of manipulating several objects that are loosely placed on a robot, rather than grasped or fixed otherwise. The waiter problem consists of moving a tray (mounted at the end-effector of a robot) with a number of cups, from one pose to another as fast as possible such that the cups do not slide at any time. The geometric path of the tray motion is prescribed while the attitude of the tray must vary. The basis for any optimization and real-time control is a reliable dynamic model of the robot. Therefore a parameter identification is performed using optimized persistent excitation trajectories. The optimization problem is solved with a multiple shooting method which determines the robot trajectory. For the considered wrist-partitioned robot, the motion is described by the joint coordinates of the translation part and the angles describing the orientation of the tray. This combination of joint and task space coordinates is beneficial for solving the optimal control problem (convergence is increased). The optimization accounts for the technical limitations of the robot as well as the limiting friction of the cups. Experimental results with 4 cups for a time-optimal motion are shown. A crucial aspect is the use of a model-based control strategy, along with the identified parameters.
Paper VI142-04.5
PDF · Video · Position-Based Motion Control for Parallel Manipulators under Parametric Uncertainties and with Finite-Time External Disturbance Rejection (I)
Dobriborsci, Dmitrii	ITMO University
Kolyubin, Sergey	ITMO University
Gorokhova, Natalia	ITMO University
Korotina, Marina	ITMO University
Bobtsov, Alexey	ITMO University
Keywords: Identification and control methods, Mechatronic systems, Robots manipulators Abstract: We consider the task of motion control for non-prehensile manipulation using parallel kinematics mechatronic setup, in particular, stabilization of a ball on a plate under unmeasured external harmonic disturbances. System parameters are assumed to be unknown, and only a ball position is measurable with a resistive touch sensor. To solve the task we propose a novel passivity-based output control algorithm that can be implemented for unstable linearized systems of an arbitrary relative degree. In contrast to previous works, we describe a new way to parametrize harmonic signal generators and an estimation algorithm with finite-time convergence. This scheme enables fast disturbance cancellation under control signal magnitude constraints.
Paper VI142-04.6
PDF · Video · Rigid-Joint-Model Feedforward with Elastic-Joint-Model Feedback for Motion Control of a 6-DOF Industrial Robot (I)
Oaki, Junji	Toshiba Corporation
Keywords: Identification and control methods, Vibration control, Robots manipulators Abstract: This paper presents a fast and exact trajectory control scheme for articulated robot arms with elastic joints due to reduction gears. This scheme provides a practical solution for sophisticated motion control of general industrial robots using motor-side measurements only. We previously proposed a torsion-angular velocity feedback (TVFB) scheme for suppressing residual vibration in the tip of a 2-DOF robot arm, using a physically parameterized nonlinear observer. To execute exact trajectory control, we also combined a feedforward scheme based on a rigid-joint model with TVFB, due to the complexity of implementing feedforward based on an elastic-joint model. TVFB suppressed arm-tip vibrations caused by feedforward mismatch between the rigid- and elastic-joint models. In this paper, we extend the scope of the combined scheme to a 6-DOF industrial robot. We implement a real-time controller with complete direct and inverse dynamic models for the feedback and feedforward. The effectiveness of our approach was successfully validated in several experiments.

VI142-05
Mechatronics and Intelligent Systems in Railways	Open Invited Session
Chair: Dixon, Roger	University of Birmingham
Co-Chair: Goodall, Roger	Loughborough Univ
Organizer: Dixon, Roger	University of Birmingham
Organizer: Goodall, Roger	Loughborough Univ
Paper VI142-05.1
PDF · Video · Simultaneous Estimation of Wheel-Rail Adhesion and Brake Friction Behaviour (I)
Schwarz, Christoph	German Aerospace Center
Keck, Alexander	German Aerospace Center, Institute of System Dynamics and Contro
Keywords: Mechatronics for Mobility Systems, Identification and control methods, Modeling Abstract: In the field of longitudinal train dynamics the brake process is not only a safety critical aspect but it also determines the capacity of the rail network. Therefore, a reduction of the brake distance increases the safety level and the network capacity at the same time. However, to implement an advanced brake control set-up, the knowledge of the wheel-rail adhesion and the brake pad-disc friction is usually necessary. Since the direct measurement of these determining parameters is not reasonable due to technical and economic reasons, the present work presents an estimator framework for their online identification. To ensure a robust and reliable performance of the estimator, a generic wagon model is designed and the observability of the nonlinear system is evaluated. Furthermore, a reasonable synthesis of an extended Kalman filter is discussed that takes account of the system characteristics. In the end, the test results from a roller rig verify the accurate and robust performance of the developed estimator and confirm the great potential of such a concept in the context of mechatronic railway systems.
Paper VI142-05.2
PDF · Video · A Robotic Device for the Structural Dynamics Inspection of Railway Pantographs through Nonlinearity Tests (I)
Santamato, Giancarlo	Scuola Superiore Sant'Anna
Chiaradia, Domenico	Scuola Superiore Sant'Anna
Solazzi, Massimiliano	Scuola Superiore Sant'Anna
Frisoli, Antonio	Scuola Superiore Sant'Anna
Keywords: Mechatronic systems, Identification and control methods, Robotics technology Abstract: The railway industry is progressively embracing mechatronics solutions to improve maintenance operations. In this context, we present a robotic device that introduces structural dynamics analysis in railway pantograph inspection. Specifically, an innovative macro-micro actuation extends the bandwidth performance of actual devices, while a force control strategy proved to support the execution of nonlinearity tests via the estimation of the Frequency Response Function for different levels of the input force. Thereupon we show that the exploitation of nonlinearity can enhance the detection of even a minor localized fault.
Paper VI142-05.3
PDF · Video · Innovative Technologies for Railway Track Switches (I)
Hamadache, Moussa	University of Birmingham
Ambur, Ramakrishnan	University of Birmingham
Olaby, Osama	University of Birmingham
Dutta, Saikat	University of Birmingham
Shih, Jou-Yi	University of Birmingham
Stewart, Edward	The University of Birmingham
Dixon, Roger	University of Birmingham
Keywords: Mechatronic systems, Mechatronics Abstract: In this extended abstract paper, a few of the developed switches and crossings (S&C) mechatronic technologies within the Switch and Crossing Optimal Design Evaluation (S-CODE) project will be presented, where they were titled as demonstrators. Current conventional S&C are working for a long time with reasonable performances. They kept their mechanism with little changes. However, there are still many drawbacks that should be dealt with, especially its reliability and safety. Thus, the S-CODE project looked at developing radical future S&C technologies that can be integrated into existing rail network platforms, but also can achieve significant improved performances. These technologies will either accommodate potential faults in S&C through integrating condition monitoring (CM) and/or a fault tolerant control (FTC) strategies, in addition to define the optimal locations for sensors to be placed; or completely propose new actuating mechanisms (i.e., high redundancy actuator (HRA) and Maglev actuator); and/or consider a novel locking concept that base on the magneto-rheological fluid (MR) damper to improve railway track switching performances, especially with the strong tendency to introduce high-speed trains.
Paper VI142-05.4
PDF · Video · Novel Actuation Mechanism for Railway Track Switch System Based on Maglev Technology (I)
Olaby, Osama	University of Birmingham
Hamadache, Moussa	University of Birmingham
Ambur, Ramakrishnan	University of Birmingham
Dutta, Saikat	University of Birmingham
Stewart, Edward	The University of Birmingham
Dixon, Roger	University of Birmingham
Keywords: Application of mechatronic principles, Mechatronic systems, Smart Structures Abstract: This extended abstract presents a concept of a novel mechanism for railway track switching based on Maglev technology. The main advantage of using this technology is the lack of contact between the actuator and the movable parts of the physical system and thus no wear and friction. This increases efficiency, reduces maintenance costs, and increases the useful life of the track switch system. The proposed new idea is based on using several Maglev actuators to switch the track that makes the new concept more reliable than the conventional switch form the point of view lacking the mechanical link between the actuator and the switch rail. The rail could be switched simply by magnetic principles by attracting the switch rail towards its appropriate location. A control algorithm is developed to achieve the rail track switching mechanism and validated to demonstrate the proof of the novel proposed technology of railway track switching.
Paper VI142-05.5
PDF · Video · Towards an Energy-Based Indicator of Track Quality in Turnouts (I)
Asadzadeh, Seyed Mohammad	Technical University of Denmark
Galeazzi, Roberto	Technical University of Denmark
Barkhordari, Pegah	Technical University of Denmark
Keywords: Modeling, Information and sensor fusion, Decision making support Abstract: This paper investigates track vibration energy as a potential novel indicator of turnout's track quality. Exploiting measurements of train-induced track vertical accelerations at different sections of a turnout, the track vibration energy is estimated and its variation over time analysed through the creation of statistical empirical distributions. A clear increase in vibration energy can be observed over a period of two years. An analysis of the turnout track geometry through a standard indicator adopted by the railway industry is then performed, and an increase in longitudinal level over the same investigation period clearly indicates track degradation due to cumulative loading. Last, a correlation analysis is performed between the estimated vibration energy and the indicator of track quality based on geometry data. Such analysis shows a significant correlation between the two indexes, thereby addressing the possibility of developing a novel condition monitoring tool for track quality based on track vibration energy. The whole investigation is based on full-scale measurements of track vertical acceleration and track geometry performed over a period of two years in a turnout of the Danish railway infrastructure.
Paper VI142-05.6
PDF · Video · Railways Discovering Mechatronics and Monitoring – an Overview (I)
Goodall, Roger	Loughborough Univ
Dixon, Roger	University of Birmingham
Hamadache, Moussa	University of Birmingham
Ward, Christopher Patrick	Loughborough University
Keywords: Mechatronics Abstract: The railway industry has been significantly slower than the competing modes of air and road in taking advantage of mechatronics and health monitoring, although a number of possibilities are now "hot topic" research areas being considered worldwide. This paper describes some current research work and a range of opportunities ranging from "low level" (vehicle sub-systems) through to "high level" system wide benefits This paper is intended to set the scene for the Track on "Mechatronics and Intelligent Systems in Railways"
Paper VI142-05.7
PDF · Video · On the Optimization of the Semi-Active Suspension for a Railway Vehicle (I)
Soyic Leblebici, Asli	Eskisehir Osmangazi University
Turkay, Semiha	Anadolu University
Keywords: Vibration control, Modeling, Application of mechatronic principles Abstract: In this study, a nine-degrees-of-freedom full wagon railway model with linear parameters is used to study the vehicle's vibrational response on the random rail data collected by Turkish State Railways Research Center (TCDD-DATEM). The performance of suspension system is determined by comparing the body vertical, pitch and roll accelerations, and suspension travels to assess ride comfort and handling properties of the vehicle. The semi-active suspension system is designed for three different controllers; skyhook, groundhook and hybrid since these approaches feature simplicity and lower cost compared to their active counterparts. For the proposed controllers, their effectiveness is validated by simulation results performed in MATLAB by comparing the achieved time responses.

VI142-06
Mechatronics Tools and Control Related to Robotic Manipulation	Open Invited Session
Chair: Benoussaad, Mourad	University of Toulouse
Co-Chair: Bearee, Richard	Arts Et Metiers ParisTech Lille
Organizer: Mourad, Benoussaad	ENIT / Toulouse INP
Organizer: Grossard, Mathieu	CEA LIST
Organizer: Rakotondrabe, Micky	ENIT / Toulouse INP
Paper VI142-06.1
PDF · Video · Resolved-Acceleration Control of Serial Robotic Manipulators Using Unit Dual Quaternions (I)
Chandra, Rohit	SIGMA Clermont
Corrales Ramon, Juan Antonio	SIGMA Clermont
Mezouar, Youcef	Blaise Pascal Univ
Keywords: Robots manipulators, Motion Control Systems Abstract: A new method for resolved-acceleration control of serial chain manipulators has been proposed which uses dual quaternion representation of screw-based motion variables, i.e. pose, velocity and acceleration. The corresponding coupled controller considers both translation and orientation errors simultaneously for trajectory tracking and utilizes spatial acceleration to compute the feedforward compensation term for feedback linearization. The proposed coupled control law was validated on a robotic arm along a pre-defined trajectory. The controller demonstrated an improved trajectory tracking performance as compared to the conventional decoupled resolved-acceleration controller which treats translation and orientation error separately.
Paper VI142-06.2
PDF · Video · Curvature and Force Estimation for a Soft Finger Using an EKF with Unknown Input Optimization (I)
Loo, Junn Yong	Monash University
Ding, Ze Yang	Monash University Malaysia
Davies, David Gwyn Evan	Monash University
Nurzaman, Surya Girinatha	Monash University
Tan, Chee Pin	Monash University
Keywords: Perception and sensing, Identification and control methods, Robotics technology Abstract: Sensory data such as bending curvature and contact force are essential for controlling soft robots. However, it is inconvenient to measure these variables because sensorizing soft robots is difficult due to their inherent softness. An attractive alternative is to use an observer/filter to estimate the variables that would have been measured by those sensors. Nevertheless, an observer/filter requires a model which can be analytically demanding for soft robots due to their high nonlinearity. In this paper, we propose an Unknown Input Extended Kalman Filter (UI-EKF) consisting of an EKF interconnected with a UI-optimizer to respectively estimate the state (curvature) and unknown input (contact force) for a pneumatic-based softfinger based on an identified nonlinear model. We also prove analytically that the estimation errors are bounded. Experimental results show that the UI-EKF can perform the estimation with high accuracy, even when the identified system model is not accurate and the sensor measurement is noisy. In other words, the proposed framework is able to estimate proprioceptive (internal) and exteroceptive (external) variables (curvature and contact force respectively) of the robot using a single sensor (flex), which is still an open problem in soft robotics.
Paper VI142-06.3
PDF · Video · A Six-Dimensional Motion Measurement Device with Micrometer-Accuracy (I)
Lei, Wei-Tai	LEI&SO Co., Ltd
Chen, Cheng-Wei	National Taiwan University
Keywords: Perception and sensing, Mechatronics, Robotics technology Abstract: This paper presents a novel six-dimensional Motion Measurement Device (MMD). The MMD consists mainly of an upper plate, a lower plate, and six ball bars. Each ball bar has two high precision balls at its ends and uses a linear optical scale as the displacement sensor. The six ball bars connect the two plates to form the parallel measuring kinematics of a Stewart platform. The MMD can be mounted on the main spindle of a multi-axis CNC machine tool or the end-effector of a robotic manipulator. When the dynamical system is driven by the motion controller, the MMD simultaneously measures the lengths of the ball bars and obtains the actual pose of the tool. The MMD can be used for six-dimensional pose measurement in kinematic calibration. It also enables closed-loop position/orientation control for the end-effector of a robotic manipulator.
Paper VI142-06.4
PDF · Video · Vibration Reduction Control for Redundant Flexible Robot Manipulators (I)
Rahmouni, Mohamed Amine	Ecole Nationale Supèrieure d'Arts Et Métiers
Bearee, Richard	Arts Et Metiers ParisTech Lille
Grossard, Mathieu	CEA LIST
Lucet, Eric	CEA
Keywords: Vibration control, Motion Control Systems, Mechatronics Abstract: In this paper, both vibration reduction and task accuracy improvement for flexible redundant manipulators, using the resolution of redundancy, is addressed. The exciting force of flexural motion, which is induced by the motion of the manipulator, causes undesired deflection at the end-effector. The null space inherent in redundancy feature is exploited to damp out the vibration while maintaining the end-effector posture. In order to exploit all the degrees of freedom in the null space, a feedback control design based on torque optimisation has been introduced using analytical method for the redundancy resolution. The simulation analysis is presented to test the effectiveness of the proposed approach.
Paper VI142-06.5
PDF · Video · RISE Feedback Control of Cable-Driven Parallel Robots: Design and Real-Time Experiments (I)
Hassan, Ghina	Laboratoire d'Informatique, De Robotique Et De Microélectronique
Chemori, Ahmed	UM2
Chikh, Lotfi	Tecnalia
Herve, Pierre-Elie	TECNALIA
El Rafei, Maher	Lebanese University, Faculty of Engineering 1, CRSI Lab
Francis, Clovis	Lebanese University, Faculty of Engineering, Branch 1
Pierrot, Francois	LIRMM
Keywords: Robots manipulators, Motion Control Systems, Autonomous robotic systems Abstract: Control of Cable-Driven Parallel Robots (CDPRs) is considered as a challenging task due to their highly nonlinear dynamic behavior, abundant uncertainties, low-stiff cables, parameters variation, cable tensions, and actuation redundancy. Hence, a robust controller is needed to obtain higher performance despite the above mentioned issues. In this paper, we propose a Robust Integral of the Sign of the Error (RISE) control scheme to resolve the problem of reference trajectory tracking. RISE feedback control is a robust nonlinear continuous controller which can guarantee a semi-global asymptotic tracking under limited assumptions on the system structure. This could provide the closed-loop system robustness towards parametric uncertainties and external disturbances. The proposed control solution is designed and implemented in real-time experiments on a fully constrained 4-DOF Cable-Driven Parallel Robot (CDPR) named PICKABLE. The obtained experimental results show that the proposed controller outperforms the classical PID controller and the first-order Sliding Mode Control (SMC) in terms of tracking performances and robustness towards payload variations.
Paper VI142-06.6
PDF · Video · Design of a Capacitance Sensor for Human Intention Detection of Daily Living Activities (I)
Jung, Pyeong-Gook	LISSI, UPEC
Amirat, Yacine	University of Paris Est Creteil
Mohammed, Samer	Université Paris-Est Créteil - UPEC
Keywords: Human Mechatronics, Brain-machine interaction, Human-centred automation and design Abstract: As many countries enter an aging society, the demand of wearable robots are increasing. To apply wearable robots in daily life, the intention recognition of the wearers is of great important. Although this research field has been extensively studied in the last decade, still the physical intention recognition based approaches are facing different challenges and in particular when used in assistive and rehabilitation scenarios. In this paper, we propose to monitor muscular activities of the shank and movement of the ankle joint by using capacitance sensors. The proposed capacitance sensor monitor the electrodermal activities under the human skin. The human skin has capacitance when an external current is applied and muscular activities can change the capacitance. To verify the proposed capacitance sensor, the human joint angle was measured by two inertial sensors and the capacitance sensor on the shank at once. The electromyogram(EMG) signals were also compared to verify the performance of the intention detection device based on the capacitance sensors.
Paper VI142-06.7
PDF · Video · Feedforward and H_inf Feedback Robotic Force Control in a 1-Dof Physical Interaction Using a Nonlinear Human Model (I)
Benoussaad, Mourad	University of Toulouse
Rakotondrabe, Micky	University of Toulouse
Keywords: Identification and control methods, Shared control, cooperation and degree of automation, Human-centred automation and design Abstract: Robot interacting with flexible object, and particularly with human in movement, is an increasing topic in several applications of today. It is particularly interesting and challenging in term of modeling and control because of the human variability, uncertainty and non-linearity. In the current work, we propose an original approach to model and control the interaction between a 1-dof robotic system and a human. While the human model includes a nonlinear biomechanical model, the nonlinearity is accounted and compensated for in a feedforward controller. Then a robust H_inf feedback control is added in order to allow the closed-loop satisfy some specified performances under possible uncertainties and under external disturbance such as noise. The feedforward-feedback control is afterwards extensively verified in simulation which confirm its efficiency.
Paper VI142-06.8
PDF · Video · Compliance Control for Robust Assembly with Redundant Manipulators (I)
Listmann, Kim Daniel	ABB Schweiz AG
Hans, Florian	TU Braunschweig, Institute of Control Engineering
Wahrburg, Arne	ABB Corporate Research
Keywords: Robots manipulators, Application of mechatronic principles, Motion Control Systems Abstract: Given the problem of static and dynamic contact stability of manipulators, this work extends classical hybrid force/motion control by introducing an additional feedback part to allow smooth environmental contact of the robot. The extension is the outcome of an in-depth stability analysis of velocity-controlled manipulators in passive environments and can be considered the first of its kind. In addition to this theoretical contribution, the application to a redundant 7-DoF robot confirms the achievable benefit compared to the classical implementation w.r.t. transient effects (like positional deviation or exerted force) in the event of an environmental contact.

VI142-07
Modeling, Identification, Estimation and Control in Micromechatronic Systems	Open Invited Session
Chair: Hultmann Ayala, Helon Vicente	Pontifical Catholic University of Rio De Janeiro
Co-Chair: Fleming, Andrew John	University of Newcastle
Organizer: Hultmann Ayala, Helon Vicente	Pontifical Catholic University of Paraná
Organizer: Oomen, Tom	Eindhoven University of Technology
Organizer: Fleming, Andrew John	University of Newcastle
Organizer: Rakotondrabe, Micky	ENIT / Toulouse INP
Paper VI142-07.1
PDF · Video · Complex Valued State Space Model for Weakly Nonlinear Duffing Oscillator with Noncollocated External Disturbance (I)
Yoo, Han Woong	TU Wien
Schitter, Georg	Vienna University of Technology
Keywords: Modeling, Micro and Nano Mechatronic Systems, Application of mechatronic principles Abstract: This paper proposes a slow flow model for a weakly nonlinear and parametrically driven Duffing oscillator and a complex valued state space model for the oscillator with noncollocated external disturbances. The combination of the parametrically driven duffing oscillator and noncollocated disturbances can be observed in resonant MEMS mirrors with a reinforcement structure to reduce dynamic mirror deformation. The model is based on a rational function approximation for the angular derivative of the out-of-plane comb drive capacitance, enabling qualitative analysis at large amplitudes while the stability analysis is maintained as the conventional cubic function approximation. The slow flow model is extended including a single tone noncollocated disturbance and is linearized at an equilibrium point for a small disturbance. The linearized disturbance model is reformulated by a complex valued state space model to cope with general wideband disturbances, allowing various analytic methods in traditional system theory. The simulation results demonstrate a good agreement between the proposed models and the ODE simulation, verifying the accuracy and benefits of the proposed models.
Paper VI142-07.2
PDF · Video · Capacitive Charge-Based Self-Sensing for Resonant Electrostatic MEMS Mirrors (I)
Schroedter, Richard	Vienna University of Technology
Yoo, Han Woong	TU Wien
Brunner, David	TU Wien
Schitter, Georg	Vienna University of Technology
Keywords: Micro and Nano Mechatronic Systems, Application of mechatronic principles, Identification and control methods Abstract: This paper proposes capacitive charge-based self-sensing by integration of the comb drive intrinsic displacement current for resonant electrostatic MEMS mirrors in order to solve the problem of robust feedback for laser scanning in mobile light detection and ranging (Lidar) application. A two-channel switched current integrator circuit is implemented to determine the deflection angle and to distinguish the rotation direction from the asymmetric comb drive charge. Parameters of the MEMS mirror are calibrated with the deflection angle by an optical PSD setup. The resonant electrostatic MEMS mirror is parametrically driven by a square wave high voltage signal, which means, that the charge measurement is only available during the time with non-zero drive signal. From the partly available charge measurements, a nonlinear observer is developed to estimate the mirror state at all time for a potential feedback control. The feasibility for online position estimation is proven by simulation using experimental charge and deflection angle measurements resulting in less than 2 % error at full amplitude operation. Finally, the performance of the proposed method is discussed for realization of active MEMS mirror feedback control, overcoming imprecise motions due to structural nonlinearities as well as external disturbances like vibration and climate variation.
Paper VI142-07.3
PDF · Video · Deep Learning Applied to Data-Driven Dynamic Characterization of Hysteretic Piezoelectric Micromanipulators (I)
Soares Barbosa, Matheus Patrick	PUC-Rio
Rakotondrabe, Micky	University of Toulouse
Hultmann Ayala, Helon Vicente	Pontifical Catholic University of Rio De Janeiro
Keywords: Identification and control methods, Micro and Nano Mechatronic Systems, Perception and sensing Abstract: The presence of nonlinearities such as hysteresis and creep increases the difficulty in the dynamic modeling and control of piezoelectric micromanipulators, in spite of the fact that the application of such devices requires high accuracy. Moreover, sensing in the microscale is expensive, making model feedback the only viable option. On the other hand, data-driven dynamic models are powerful tools within system identification that may be employed to construct models for a given plant. Recently, considerable effort has been devoted in extending the huge success of deep learning models to the identification of dynamic systems. In the present paper, we present the results of the successful application of deep learning based black-box models for characterizing the dynamic behavior of micromanipulators. The excitation signal is a multisine spanning the frequency band of interest and the selected model is validated with semi static individual sinusoidal curves. Various architectures are tested to achieve a reasonable result and we try to summarize the best approach for the fine tuning required for such application. The results indicate the usefulness and predictive power for deep learning based models in the field of system identification and in particular hysteresis modeling and compensation in micromanipulation applications.
Paper VI142-07.4
PDF · Video · Multivariable Experiment Design with Application to a Wafer Stage: A Sequential Relaxation Approach for Dealing with Element-Wise Constraints (I)
Dirkx, Nic	ASML
Oomen, Tom	Eindhoven University of Technology
Keywords: Identification and control methods, Motion Control Systems, Mechatronic systems Abstract: Optimal Experiment Design (OED) is an essential aspect in accurate Frequency Response Function (FRF) identification of complex systems. The aim of this paper is to optimally design experiments for FRF identification of multivariable motion systems subject to element-wise power constraints. This design problem involves solving a non-convex and generally NP-hard optimization problem. An algorithm to solving this problem approximately is presented based on sequential semi-definite relaxations. Experimental results on a wafer stage show an improvement of the FRF quality using the proposed techniques over traditional excitation design methods.
Paper VI142-07.5
PDF · Video · Towards Observer-Based Tunneling Current Calibration in an Experimental STM Device (I)
Besancon, Gildas	Ense3, Grenoble INP
Voda, Alina	University Joseph Fourier Grenoble 1
Popescu, Andrei	Grenoble INP
Keywords: Micro and Nano Mechatronic Systems, Identification and control methods Abstract: In the context of experimental modeling for a Scanning Tunneling Microscope (STM) prototype, a reduced order observer is proposed for parameter adaptation in the tunneling current model. The underlying dynamical model is first recalled, and the proposed observer is then presented, and discussed. The approach is finally illustrated with real data taken from the prototype.
Paper VI142-07.6
PDF · Video · System Identification and Control Design for a Tip Tilt Nanopositioning System (I)
Su, Yu Hsiang	The University of Manchester
Morales Aldana, David Felipe	University of Manchester
Heath, William Paul	University of Manchester
Keywords: Micro and Nano Mechatronic Systems, Identification and control methods, Design methodologies Abstract: The nanopositioning stage is one of the essential components in the application of nanotechnology and nanoscience. Past research has focused on the control design for the nanopositioning stages with translation motion. However, this paper examines the system identification and control design for a tip tilt nanopositioning stage with an experimental case study based on the Queensgate NPS-θγ-2M prototype nanopositioning stage that has two degrees of freedom (DOF) of tip tilting motion. The paper presents the multi-input multi-output (MIMO) position model and compares two control design methods for the tip tilt nanopositioning stage, namely single input single output (SISO) integral control and MIMO robust H-infinity control with loop shaping design. The robust H-infinity control has the advantage of increasing the response speed and improving the bandwidth while considering the whole multivariable model in the design scheme and maintaining the control robustness. The experiment results demonstrate that the MIMO robust H-infinity control has a better control performance in terms of the response time and bandwidth, compared with the classical SISO integral control.
Paper VI142-07.7
PDF · Video · Commutation-Angle Iterative Learning Control for Intermittent Data: Enhancing Piezo-Stepper Actuator Waveforms (I)
Aarnoudse, Leontine	Eindhoven University of Technology
Strijbosch, Nard	Eindhoven University of Technology
Verschueren, Edwin	Thermo Fisher Scientific
Oomen, Tom	Eindhoven University of Technology
Keywords: Micro and Nano Mechatronic Systems, Identification and control methods, Motion Control Systems Abstract: Piezo-stepper actuators are used in many nanopositioning systems due to their high resolution, high stiffness, fast response, and the ability to position a mover over an infinite stroke by means of motion reminiscent of walking. The aim of this paper is to develop a control approach for attenuating disturbances that are caused by the walking motion and are therefore repeating in the commutation-angle domain. A new iterative learning control approach is developed for the commutation-angle domain, that addresses the iteration-varying and non-equidistant sampling that occurs when the piezo-stepper actuator is driven at varying drive frequencies by parameterizing the input and error signals. Experimental validation of the framework on a piezo-stepper actuator leads to significant performance improvements.
Paper VI142-07.8
PDF · Video · Image-Based Parametric Pattern Recognition for Micro and Nano Defect Detection (I)
Belikov, Sergey	SPM Labs
Su, Chanmin	Shenzhen Academy of Robotics
Enachescu, Marian	Politechnica University of Bucharest
Keywords: Micro and Nano Mechatronic Systems, Identification and control methods, Modeling Abstract: Detection and characterization of defects at micro- and nano-scale is one of the most important tasks of the production process control technologies at these scales. Examples include flat panel displays (FPD) and MEMS (defects at micro scale), and hard disk drive substrates up to 95 mm in diameter (defects at nano scale). Although different measurement technologies are applied, such as infrared thermography at micro-scale and Atomic Force Microscopy (AFM) at nano-scale, a similar technique of image-based defect recognition and location can be utilized, namely parametric pattern recognition, where the defect is defined by a specific set of inequalities in the space of selected measurable variables. We describe the technique and demonstrate it for the following applications: 1) mechanical defects (high friction) in MEMS; 2) electrical defect locations (shorts, opens) on FPD; and 3) nano-asperities on hard disk drive surfaces. The first two use infrared thermography, and the third uses multi-channel AFM scanning. Both large and small fields of view images are needed for analysis.
Paper VI142-07.9
PDF · Video · Hysteresis in Nanopositoining Systems Driven by Dual-Stack Differential Driving Piezoelectric Actuators (I)
Hemmasian Ettefagh, Massoud	School of Artificial Intelligence and Automation, Huazhong Unive
Bazaei, Ali	The University of Newcastle Australia
Wang, Zhiyue	School of Artificial Intelligence and Automation, Huazhong Unive
Chen, Zhiyong	The University of Newcastle
Zhang, Hai-Tao	Huazhong (Central China) Univeristy of ScienceandTechnology
Régnier, Stéphane	Université Pierre Et Marie CURIE, Institut Des Systèmes Intellig
Boudaoud, Mokrane	Université Pierre Et Marie CURIE, Institut Des Systèmes Intellig
Keywords: Micro and Nano Mechatronic Systems, Smart Structures, Modeling Abstract: The existence of hysteresis phenomenon in piezoelectric actuators of nanopositioners adversely affects their performance, e.g. image distortion in Atomic Force Microscopy. A usual approach to circumnavigate hysteresis nonlinearity is feedforward compensation where the performance depends extensively on the accuracy of the hysteresis model. To achieve accurate modeling of hysteresis in nanopositioners driven by piezoelectric stacks, we used a dual-stack differential driving configuration. Comparing hysteresis in single-stack piezoelectric actuators with dual-stack piezoelectric actuators in differential driving configuration, we observed a more symmetric behavior for the hysteresis in dual-stack differential driving actuators. Then, we modeled the differential driving configuration by utilizing coupled electromechanical equations with hysteresis models applied to them. In particular, Duhem and Prandtl-Ishlinskii (P-I) methods were used for hysteresis modeling. Based on the models and experimental data, we observed that the maximum value of the Duhem modeling error reduced from 9.63% for the nondifferential configuration to 1.85% for the differential configuration. For the P--I method, the maximum modeling error decreased from 7.46% to 2.77%. This observation shows that the dual-actuated differential driving configuration improves hysteresis modeling accuracy. Therefore, this configuration is a suitable choice for the applications where accuracy is of prime importance.
Paper VI142-07.10
PDF · Video · Fractional-Order Control: Nyquist Constrained Optimization (I)
Moltumyr, Andreas Hanssen	Norwegian University of Science and Technology - NTNU
Ragazzon, Michael Remo Palmén	NTNU, Norwegian University of Science and Technology
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Keywords: Micro and Nano Mechatronic Systems Abstract: The adoption of fractional calculus in control systems has enabled the synthesis of new controllers with fractional-order derivatives and integrals. Several optimization-based methods for tuning of linear fractional-order controllers have been explored. However, few have considered the stability of the closed-loop system during optimization. This paper presents a model-driven method for tuning of fractional-order controllers based on a heuristic optimization technique and the experimental use of Nyquist’s stability criterion to enforce closed-loop stability of fractional-order systems. The proposed frequency domain tuning method enables tuning of linear fractional-order controllers with few to medium number of parameters. The method can handle both fractional-order linear and integer-order linear plant models and controllers. To assist the experimental use of Nyquist’s stability criterion, a function for drawing a Logarithmic amplitude polar diagram has been developed. Simulation results of the method applied to a nanopositioning system in atomic force microscopy suggest that the proposed method can be used for optimization of fractional-order controllers while enforcing closed-loop stability. Given that the system can be stabilized with the given controller. Matlab code building on the FOTF toolbox and global optimization toolbox is provided.
Paper VI142-07.11
PDF · Video · Adaptive Tube Model Predictive Control for Manipulating Multiple Nanowires with Coupled Actuation in Fluid Suspension (I)
Wu, Juan	State University of New York at Binghamton
Yu, Kaiyan	State University of New York at Binghamton
Keywords: Micro and Nano Mechatronic Systems, Motion Control Systems, Identification and control methods Abstract: Automated, highly precise online manipulation of multiple nano and microscale objects is essential to achieve scalable nanomanufacturing. One of the biggest limitations of the wireless external actuation is its global and coupled influence in the workspace, which limits the capability to robustly control multiple nano and microparticles independently and simultaneously. Another challenge for the highly precise manipulation of nanoparticles is due to their uncontrolled variations in structures or compositions that result in different dynamic behaviors. In this paper, we present an adaptive tube model predictive control scheme for the simultaneous manipulation of multiple nanowires under coupled electric fields in fluid suspension. The proposed strategy estimates the unknown mobilities of the individual nanowires online, formulates dynamic tubes that update based on the online estimated mobilities and nonlinear dynamics, and addresses the coupled actuation from the global electric field with dynamic separated tubes constructed for each nanowire. Simulations results show that as the number of simultaneously manipulated nanowires increases, the manipulation time increases and the maximum disturbance the system could reject decreases rapidly.
Paper VI142-07.12
PDF · Video · Frequency Response Data-Based Disturbance Observer Design Via Convex Optimization (I)
Wang, Xiaoke	The University of Tokyo
Ohnishi, Wataru	The University of Tokyo
Koseki, Takafumi	The University of Tokyo
Keywords: Identification and control methods, Design methodologies, Motion Control Systems Abstract: To estimate and compensate disturbances effectively, disturbance observer (DOB) has been widely employed in industrial field. This paper is dedicated to designing DOB by directly utilizing frequency response data. By transforming all the non-convex constraints into convex form, the bandwidth of DOB is maximized through iterative convex optimization process. Simulation results have verified the effectiveness of the proposed method.
Paper VI142-07.13
PDF · Video · Temperature-Dependent Modeling of Thermoelectric Elements (I)
Evers, Enzo	Eindhoven University of Technology
Slenders, Rens	Eindhoven University of Technology
van Gils, Rob	Eindhoven University of Technology
Oomen, Tom	Eindhoven University of Technology
Keywords: Identification and control methods, Modeling, Mechatronic systems Abstract: Active thermal control is crucial in achieving the required accuracy and throughput in many industrial applications, e.g., in the medical industry, high-power lighting industry, and semiconductor industry. Thermoelectric Modules (TEMs) can be used to both heat and cool, alleviating some of the challenges associated with traditional electric heater based control. However, the dynamic behavior of these modules is non-affine in their inputs and state, complicating their implementation. To facilitate advanced control approaches a high fidelity model is required. In this work an approach is presented that increases the modeling accuracy by incorporating temperature dependent parameters. Using an experimental identification procedure, the parameters are estimated under different operating conditions. The resulting model achieves superior accuracy for a wide range of temperatures, demonstrated using experimental validation measurements.
Paper VI142-07.14
PDF · Video · Multi-Time Scale Control of Dual-Stage Nanopositioning Systems
Mitrovic, Aleksandra	Villanova University
Milanovic, Milos	Villanova University
Leang, Kam K.	University of Utah
Clayton, Garrett	Villanova University
Keywords: Micro and Nano Mechatronic Systems, Identification and control methods, Modeling Abstract: In this paper, a novel multi-time scale control technique is applied to a serial dual-stage nanopositioning system. Dual-stage nanopositioning systems combine a high-speed, short-range actuator and a low-speed, long-range actuator to achieve long-range and high-speed positioning. This results in a system that has relatively complicated dynamics due to the physical interaction between the two actuators and their different time-scales. In addition, models of these actuators can be ill-conditioned, which can lead to issues with numerical simulations and controller design. These issues make dual-stage nanopositioning systems well suited to multi-time scale control algorithms. In the proposed algorithm, the system is split (decoupled) into a set of subsystems, where each subsystem has an individual time scale and is independently controlled via state feedback. This alleviates the issues associated with ill-conditioning and simplifies controller design. This paper introduces the novel multi-time scale control design concept and its application to single-axis dual-stage nanopositioners -- although it can be easily expanded to more complex systems, e.g., multi-axes, nanopositioning devices. The proposed control technique is validated through simulations of an experimentally obtained serially coupled dual-stage nanopositioning model.
Paper VI142-07.15
PDF · Video · Nanoforce Estimation Using Interval Observer: Application to Force Sensor Based on Diamagnetic Levitation
Amokrane, Fawzia	Femto-St Institute
Drouot, Adrien	Institut FEMTO-ST
Abadie, Joël	Femto-St Institute
Piat, Emmanuel	FEMTO-ST, ENSMM
Keywords: Micro and Nano Mechatronic Systems, Modeling Abstract: This paper presents a new design to measure slowly time-varying vertical nanoforces. The proposed sensor is based on diamagnetic levitation. It uses auto-stabilized magnetic springs and relies on a macroscopic seismic mass: a capillary tube used in a vertical configuration. When a vertical external force is applied to it, the capillary tube acts as a transducer that converts this unknown input force into a vertical displacement that is measured. Relying on this measurement, a Generic Linear Extended State Observer based on an interval approach is proposed to reconstruct this unknown input force and the state of the considered system. This is achieved without any a priori knowledge on the vertical force, i.e. magnitude and bounds. The efficiency of the proposed interval observer is illustrated by experimental results.

VI142-08
Reference Prefiltering for Precision Motion Control	Open Invited Session
Chair: Singh, Tarunraj	State Univ. of New York at Buffalo
Co-Chair: Vyhlidal, Tomas	Czech Technical Univ in Prague, Faculty of Mechanical Engineering
Organizer: Singh, Tarunraj	State Univ. of New York at Buffalo
Organizer: Vyhlidal, Tomas	Czech Technical Univ in Prague, Faculty of Mechanical Engineerin
Paper VI142-08.1
PDF · Video · Multivariable Dynamic Input Shaping for Two-Axis Fast Steering Mirror (I)
Dautt-Silva, Alicia	University of California San Diego
de Callafon, Raymond	University of California, San Diego
Keywords: Optimal control theory, Linear systems, Time-invariant systems Abstract: A two-axis Fast Steering Mirror (FSM) is a commonly used mechanical component used in optical imaging and laser beam steering. This paper shows how inverse kinematic analysis and dynamic input shaping can be used to compute the two-axis input signals for the actuation of a FSM to be able to track a desired output trajectory. The approach is based on quasi-static kinematic analysis and dynamic modeling of a two-axis FSM multivariable motion from experimental step response data. It is shown how open-loop tracking can be improved by properly designed dynamic input shaping signals that take into account the inverse kinematics and dynamic response of the FSM.
Paper VI142-08.2
PDF · Video · Robust Controller Design for Feedback Architectures with Signal Shapers (I)
Goubej, Martin	University of West Bohemia
Schlegel, Milos	University of West Bohemia in Pilsen
Vyhlidal, Tomas	Czech Technical Univ in Prague, Faculty of Mechanical Engineerin
Keywords: Systems with time-delays, Robust control (linear case) Abstract: Available feedback architectures with time delay based signal shapers are outlined and studied with the objective to determine the channels in which the flexible mode compensation (by the shaper) takes place. As the main result, a systematic methodology for the robust controller design is proposed and tested for three most common feedback architectures with signal shapers. The validation is performed on a Gantry crane anti-sway problem, considering four types of distributed delay shapers. It is demonstrated that for the selected robustness H-infinity measure, the applicable parameter range is considerably reduced by placing the signal shaper to the loop. Still, the obtained characteristics and responses of shaper feedback architectures show that a viable controller setting can well be found by the considered control design method.
Paper VI142-08.3
PDF · Video · Recent Results in Reference Prefiltering for Precision Motion Control (I)
Singh, Tarunraj	State Univ. of New York at Buffalo
Vyhlidal, Tomas	Czech Technical Univ in Prague, Faculty of Mechanical Engineerin
Keywords: Systems with time-delays Abstract: Input Shaping/Time-Delay Filtering is now an established approach for shaping reference inputs to minimize residual vibrations for rest-to-rest maneuvers, velocity and periodic tracking controllers, and to minimize excitation of high frequency un-modelled modes. At the core of successful reference shaping approaches have been the encapsulation of robustness to model parameter uncertainties. Special attention has also been paid to incorporation of the input shapers within closed loops of various configurations. This paper reviews existing designs for input shaping and highlights some of the latest contributions related to input shaping for precision motion control.
Paper VI142-08.4
PDF · Video · Inverse Shaper Based Active Vibration Control of Flexible Structures with a Collocated Sensor-Actuator Pair (I)
Kutlucan, Arzuman Can	Istanbul Technical University
Alikoc, Baran	Czech Technical University in Prague
Gören Sümer, Leyla	Istanbul Technical Univ
Keywords: Optimal control of partial differential equations, Vibration control Abstract: We propose a new control design for active vibration suppression of flexible structures with a collocated sensor-actuator pair. The proposed controller is based on the inverse form of a well-known input zero vibration (ZV) shaper. The inverse ZV shaper is utilized with a serially interconnected all-pass filter. This way, the appropriate controller frequency response properties for vibration suppression of collocated flexible systems is achieved, when the controller is applied in the positive feedback path. We propose two different cost functions to optimize the parameters of the proposed controller for efficient vibration suppression. The performance of the controller is investigated in both frequency and time domains through the vibration control of a cantilever beam model with a collocated piezoelectric sensor-actuator pair. Furthermore, its performance is compared with a recently improved version of the positive position feedback controller, which is a state-of-the-art work. It is shown via the simulations that the proposed controller suppresses vibrations more efficiently.
Paper VI142-08.5
PDF · Video · Command-Shaping Control of Linear Resonant Actuators for Haptic Force Generation (I)
Schlagenhauf, Franziska	Google LLC
Singhose, William E.	Georgia Institute of Technology
Sorensen, Khalid	Georgia Institute of Technology
Dobson, Kelly	Google LLC
Keywords: Vibration control, Motion Control Systems, Human Mechatronics Abstract: Generating haptic forces in portable electronic devices and wearables is often accomplished with small vibrating motors, such as linear resonant actuators (LRAs). While these motors are favorably small, lightweight, inexpensive, and low-power, they are limited in the types of forces they can generate. Command-shaping techniques are presented that can either accentuate or attenuate haptic forces generated by LRAs. The proposed methods are advantageous because they generate force profiles that cannot be produced by standard haptic libraries. The methods are experimentally verified using a laser vibrometer.

VI142-09
Biomedical Mechatronics	Regular Session
Chair: Konigorski, Ulrich	Technische Universität Darmstadt
Co-Chair: Schauer, Thomas	Technische Universitaet Berlin
Paper VI142-09.1
PDF · Video · Implementation and Evaluation of a Sensorless, Nonlinear Stroke Controller for an Implementable, Undulating Membrane Blood Pump
Scheffler, Mattias	Pimm Umr Cnrs
Mechbal, Nazih	Arts Et Métiers ParisTech
Monteiro, Eric	PIMM - ENSAM Paris
Rebillat, Marc	Arts Et Métiers ParisTech (ENSAM) Paris
Pruvost, Remi	CorWave
Keywords: Application of mechatronic principles, Identification and control methods, Biomedical Mechatronics Abstract: In this contribution, a methodology from identification to sensorless control for a vibrating membrane pump prototype is presented and evaluated, with the objective to drive an innovative cardiac assist device. For this purpose, a model of the pump is presented to design an observer-based stroke controller that only uses current measurement. Model parameters are identified experimentally with a dedicated test bench and are used to tune the controller. The control strategy is evaluated on a hydraulic test bench.
Paper VI142-09.2
PDF · Video · Control of a Transtibial Prosthesis with Monoarticular and Biarticular Actuators
Zeiss, Julian	Technische Universität Darmstadt
Weigand, Florian	Technische Universität Darmstadt
Grimmer, Martin	Technische Universität Darmstadt
Konigorski, Ulrich	Technische Universität Darmstadt
Keywords: Human Mechatronics, Assitive technology and rehabilitation engineering, Biomedical Mechatronics Abstract: Common active ankle joint prostheses comprise monoarticular actuators mimicking the function of the human soleus and tibialis anterior muscles, but lack the function of the biarticular human gastrocnemius muscle. Although these devices can mimic human ankle biomechanics in the sagittal plane, persons with transtibial amputation still show compensatory movements and asymmetric gait patterns. The goal of our research is to investigate the benefits of a biarticular transtibial prosthesis comprising mono- and biarticular actuators. This contribution presents the hardware configuration, control design and bypass testing of a biarticular prosthesis prototype with two actuators. A control structure consisting of a model-based feedforward control and a feedback controller to control the actuator torque is introduced. Modeling of the actuators and identification of all relevant system parameters is demonstrated. A reference trajectory based on healthy human ankle biomechanics and a control allocation are introduced. The system's capability to track desired torques is demonstrated in a walking experiment. It is able to generate human ankle torques and ankle angles with a variable distribution of torque between the mono and biarticular actuator. Based on these results, further investigations on the torque allocation to improve the gait patterns of persons with transtibial amputation can be conducted.
Paper VI142-09.3
PDF · Video · A Novel Approach for Gait Phase Estimation for Different Locomotion Modes Using Kinematic Shank Information
Weigand, Florian	Technische Universität Darmstadt
Zeiss, Julian	Technische Universität Darmstadt
Grimmer, Martin	Technische Universität Darmstadt
Konigorski, Ulrich	Technische Universität Darmstadt
Keywords: Human Mechatronics, Assitive technology and rehabilitation engineering, Biomedical Mechatronics Abstract: This paper presents a novel approach for continuous gait phase estimation for human level walking, stair ascent and stair descent relying only on the kinematic variables of the shank, which are measurable by a single Inertial Measurement Unit (IMU) placed at the shank. We use data from an experiment with an instrumented stair to train Artificial Neural Networks (ANNs) and to obtain the data necessary for a k-Nearest-Neighbour (kNN) method. Both methods are used for a continuous gait phase estimation separately for each of the three locomotion modes level walking, stair ascent and stair descent. The so called pseudo-velocities are introduced, a substitution for translational velocities as input values. The presented gait phase estimation with ANNs achieves a good performance (mean absolute error < 6%) for all three locomotion modes for one test subject and is much faster in comparison to a kNN approach. The use of ANNs seams promising regarding performance and speed for a future implementation on an active prosthesis.
Paper VI142-09.4
PDF · Video · Model Identification of 2-DOF Lower Limb Exoskeleton with Neighborhood Field Optimization Algorithm
Chen, Zhenlei	University of Electronic Science and Technology of China
Xiong, Huiyu	University of Electronic Science and Technology of China
Wang, Xinran	University of Electronic Science and Technology of China
Guo, Qing	University of Electronic Science and Technology of China
Shi, Yan	Beihang University
Yan, Yao	University of Electronic Science and Technology of China
Liu, Gan	University of Electronic Science and Technology of China
Jiang, Dan	University of Electronic Science and Technology of China
Keywords: Mechatronic systems, Identification and control methods, Human Mechatronics Abstract: For the lower limb exoskeleton, the system control performance and stability of human-robot coordinated movement is often degraded by some model parametric uncertainties. To address this problem, the model parameter identification method based on Neighborhood Field Optimization (NFO) algorithm is proposed to obtain the accurate model parameters of 2-DOF exoskeleton, which guides the model-based controller design. For the 2-DOF lower limb exoskeleton experimental platform, the model is constructed by Lagrange equation. Meanwhile, the excitation trajectory with the setting mechanical constraints is designed by NFO to guarantee the identification accuracy. Meanwhile, the Huber fitness function is adopted to suppress the influence of the disturbance points in sampling dataset with respect to the identification accuracy. Finally, the NFO algorithm with the Huber fitness function is verified by 2-DOF lower limb exoskeleton experimental platform.

VI142-10
Identification, Estimation and Control for Mechatronic Systems	Regular Session
Chair: Sofrony, Jorge Ivan	Universidad Nacional De Colombia
Co-Chair: Pagilla, Prabhakar R.	Texas A&M University
Paper VI142-10.1
PDF · Video · A Novel Force and Motion Control Strategy for Robotic Chamfering of Gears
Hu, Jie	Texas A&M University
Pagilla, Prabhakar R.	Texas A&M University
Keywords: Mechatronic systems, Robotics technology, Intelligent robotics Abstract: Accurate positioning of the work piece in the robotic work cell is currently required to perform machining operations such as chamfering in order to obtain high quality products. However, registration and work piece fixturing errors are inevitable and lead to uncertainty in the desired robot end-effector trajectory which will lead to poor quality of the finished product. This paper proposes a method for robotic gear chamfering that can compensate for the registration error of the work piece while avoiding use of expensive and time-consuming metrology devices for accurately registering the gear in the robot workspace. We highlight the problems in chamfering with work piece uncertainty when traditional contour following methods are employed. A novel chamfering trajectory based on a part identification procedure is proposed that can account for the gear registration uncertainty. A force control strategy is employed in identifying the gear center and gear root positions. Based on this identification, we employ a novel force/motion strategy that can simultaneously chamfer two edges of the adjacent gear teeth. We have conducted a number of real-time experiments with a six degree-of-freedom robot to evaluate the proposed strategy, and representative chamfering experimental results are presented and discussed.
Paper VI142-10.2
PDF · Video · Detection, Localization and Volume Estimation of Deflagrations
Krooß, Jakob	Helmut Schmidt Universität
Kuemmerlen, Felix	WIS
Fay, Alexander	Helmut Schmidt Universitaet
Keywords: Identification and control methods Abstract: Deflagration-like combustions pose a serious threat in various (e.g. industrial) scenarios. Detecting, locating and distinguishing these in their developing phase may significantly reduce the resulting damage to material and individuals. In this work, an image processing based algorithm for detection, localization and volume estimation of deflagrations with a multi-camera-system is proposed. The proposed algorithm has been tested with image sequences of real deflagrations as well as possible false alarm scenarios. In comparison to state of the art methods, false alarm safety, localization quality and robustness to noise have been improved significantly.
Paper VI142-10.3
PDF · Video · Two-Stage Robot Controller Auto-Tuning Methodology for Trajectory Tracking Applications
Roveda, Loris	SUPSI-IDSIA
Forgione, Marco	SUPSI-USI
Piga, Dario	SUPSI-USI
Keywords: Identification and control methods, Autonomous robotic systems, Motion Control Systems Abstract: Autonomy is increasingly demanded to industrial manipulators. Robots have to be capable to regulate their behavior to different operational conditions, without requiring high time/resource-consuming human intervention. Achieving an automated tuning of the control parameters of a manipulator is still a challenging task. This paper addresses the problem of automated tuning of the manipulator controller for trajectory tracking. A Bayesian optimization algorithm is proposed to tune firstly the low-level controller parameters (i.e., robot dynamics compensation), then the high-level controller parameters (i.e., the joint PID gains), providing a two-stage robot controller auto-tuning methodology. In both the optimization phases, the algorithm adapts the control parameters through a data-driven procedure, optimizing a user-defined trajectory-tracking cost. Safety constraints ensuring, e.g., closed-loop stability and bounds on the maximum joint position errors, are also included. The performance of the proposed approach is demonstrated on a torque-controlled 7-degree-of-freedom FRANKA Emika robot manipulator. The 4 robot dynamics parameters (i.e., 4 link-mass parameters) are tuned in 40 iterations, while the robot control parameters (i.e., 21 PID gains) are tuned in 90 iterations. Comparable trajectory tracking-errors results with respect to the FRANKA Emika embedded position controller are achieved.
Paper VI142-10.4
PDF · Video · Gaussian Process Based Disturbance Compensation for an Inverted Pendulum
Aschemann, Harald	University of Rostock
Tarin, Cristina	University of Stuttgart
Keywords: Identification and control methods, Design methodologies, Mechatronic systems Abstract: This paper considers an inverted pendulum with velocity input to demonstrate the validity of a new method for estimating unknown disturbances such as nonlinear friction and damping. With only one run of a given swing-up strategy, the input and output data of the system are collected. They are the basis for a Gaussian process modelling that is used to estimate the unknown disturbance term. The learned Gaussian process model can be used subsequently to predict this disturbance and serve for an online disturbance compensation. Simulation results and a comparison with a classical observer-based disturbance compensation indicate the benefits of the proposed approach.
Paper VI142-10.5
PDF · Video · Adaptive Distributed Control for Large-Scale Systems with Unknown Interconnection
Arevalo-Castiblanco, Miguel Felipe	Universidad Nacional De Colombia
Tellez-Castro, Duvan Andres	Universidad Nacional De Colombia
Mojica-Nava, Eduardo	Universidad Nacional De Colombia
Sofrony, Jorge Ivan	Universidad Nacional De Colombia
Keywords: Identification and control methods, Design methodologies, Mechatronics Abstract: This paper presents a distributed adaptive control law for large-scale systems with unknown interconnection parameters. An adaptive control law is designed to follow-up a model reference for a network through a controller that adjusts its parameters according to the dynamics of the reference, the neighborhood and the physical interconnection. This work presents a Model Reference Adaptive Control methodology for heterogeneous systems, such that the synchronization of the agents in the network is achieved even in the case where the interconnection is unknown. Stability properties of the proposed control law are validated via Lyapunov methods and boundedness of the synchronization errors is guaranteed. The authors propose a validation scheme of adaptive control for different references in a context of level control in tank networks and a synchronization analysis of the estimated constants.
Paper VI142-10.6
PDF · Video · Speed and Torque Estimation of Variable Frequency Drives with Effective Values of Stator Currents
Kouhi, Yashar	Ruhr Universität Bochum
Müller, Jens	Ruhr-Universität Bochum
Leonow, Sebastian	Ruhr University Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Identification and control methods, Mechatronics Abstract: We introduce a new method for torque and speed estimation of induction motors under voltage/frequency (V/f) open-loop control. In contrast to existing approaches that need the phase current, the proposed algorithm only requires the effective value (root mean square) of the stator current and the synchronous frequency, which are usually available from variable frequency inverter (VFI) at no additional cost. Our approach is particularly useful for inverter-fed motor-pumps in which the load varies slowly. We demonstrate the proposed algorithm is able to estimate the pump torque, speed, differential pressure and flow rate in a hydraulic process with a progressive cavity pump.
Paper VI142-10.7
PDF · Video · Constrained Design of Multisine Signals for Frequency-Domain Identification of Electric Drive Trains
Tantau, Mathias	Leibniz University Hanover
Petersen, Thomas	Lenze Automation GmbH
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Identification and control methods, Mechatronics, Application of mechatronic principles Abstract: The paper at hand deals with the optimization of multisine signals for identification of electric drive trains, considering constraints on position, velocity, acceleration and torque. The advantage of maximizing the effective value while respecting the constraints rather than minimizing the crest factor of the input signal is delineated. Results with two algorithms suitable for this optimization task are presented for different sets of dynamic constraints. It is shown that the proposed modified clipping algorithm is much faster than the L-infinity optimization which is dedicated to simultaneous optimization of several different signals, while being slightly less performant in terms of effective value.
Paper VI142-10.8
PDF · Video · Flatness-Based Trajectory-Tracking Control of Dielectric Elastomer Actuators
Scherer, Peter Michael	Saarland University
Irscheid, Abdurrahman	Saarland University
Rizzello, Gianluca	Saarland University
Rudolph, Joachim	Saarland University
Keywords: Identification and control methods, Mechatronics, Motion Control Systems Abstract: In recent years, actuators based on dielectric elastomers have become popular for both research and industrial applications. Due to their nonlinear behavior, they are typically used in on/off actuation. Established feedback control methods such as PID provide an effective and robust way to drive these actuators under constant setpoint requirements. However, such control methods exhibit poor trajectory tracking performance. This shortcoming is addressed in this work with a flatness-based nonlinear control design for a circular membrane actuator based on dielectric elastomers. By exploiting a nonlinear electro-mechanical model of the device, a tracking control law is designed in both feed-forward and feedback form. Moreover it is shown how the flatness-based feed-forward control may be used to extend a conventional PID control to improve its tracking performance. The presented methods are validated and compared experimentally with a real actuator prototype. Tracking accuracy better than 10 μm along a 1 mm stroke trajectory (i. e. less than 1%) is shown. This result is a significant improvement over existing PID control laws.
Paper VI142-10.9
PDF · Video · Online Inertial Parameter Estimation for Robotic Loaders
Calvo-Sánchez, Martín	Pontificia Universidad Católica De Chile
Torres-Torriti, Miguel	Pontifical Catholic Univ of Chile
Auat Cheein, Fernando	Universidad Tecnica Federico Santa Maria
Keywords: Identification and control methods, Modeling, Mechatronic systems Abstract: Payload estimation is essential to measure productivity, evaluate efficiency in industrial operations and adapting control laws according to the carried weight. One particular problem is to identify how much mass is carried in a mining machine while it is being operated without using strain gauge sensors which require frequent calibration and are prone to failure due to mechanical stress. This paper presents an on-line method to estimate a loader's payload mass, rotational inertia and viscous friction coefficients employing inertial, torque and speed measurements. The proposed approach introduces a mutual information criterion to select those acceleration and velocity measurements that jointly with the excitation force ensure the identifiability of the parameters. The approach relies on the recursive least-squares algorithm for fast update of the parameters. The proposed strategy is also compared to the implementations based on variants of the least-squares estimator, such as the feasible generalized least squares and the total least squares approach. The approach is tested in simulation and validated in experiments with an industrial semi-autonomous skid-steer loader Cat 262C for different loads. Results show that using the recursive least squares it is possible to estimate the parameters with the same level of accuracy than OLS approach, while not needing a large buffer for estimation. Mass is effectively estimated with an RMS error below 1% the total mass of the machine.
Paper VI142-10.10
PDF · Video · Gray-Box Model Identification and Payload Estimation for Delta Robots
Falezza, Fabio	University of Verona
Vesentini, Federico	University of Verona
Di Flumeri, Alessandro	SIPRO S.r.l
Leopardi, Luca	SIPRO S.r.l
Fiori, Gianni	SIPRO S.r.l
Mistrorigo, Gianfrancesco	SIPRO S.r.l
Muradore, Riccardo	University of Verona
Keywords: Identification and control methods, Modeling, Motion Control Systems Abstract: Delta Robots belong to a class of parallel robots widely used in industrial production processes, mostly for pick-and-place operations. The most relevant characteristics are the high speed and the extremely favorable ratio between the maximum payload and the weight of the robot itself. A reliable dynamic model is needed to implement torque controllers that reduce unnecessary high accelerations and so mechanical vibrations. Moreover, when the mass of the pickable object is unknown, it is crucial to identify with sufficient precision the dynamic contribution of the payload and to accordingly adapt the dynamic model in order to guarantee high performance.
Paper VI142-10.11
PDF · Video · Control of an Underactuated 4 Cable-Driven Parallel Robot Using Modified Input-Output Feedback Linearization
Kumar, Atal Anil	Arts Et Métiers ParisTech, Université De Lorraine, LCFC, F-57000
Antoine, Jean-François, Olivier	University of Lorraine
Abba, Gabriel	Ecole Nationale Supérieure Des Arts Et Métiers
Keywords: Identification and control methods, Modeling, Robots manipulators Abstract: This paper presents the control of an underactuated four Cable-Driven Parallel Robot (CDPR) using a modified input-output feedback linearization technique. The effect of internal dynamics (due to the underactuated degrees of freedom of the CDPR) on the behavior of the moving platform is presented to highlight the need of an improved controller to stabilize the system outputs. A modified control scheme is then proposed as a solution to obtain stable system outputs. A structure with two separate branches is modeled to simultaneously act on the control inputs and the mathematical calculations are done using the well-established equations of nonlinear control theory. Following this, the response of the system to the modified control law is then verified by simulation. A comparison between the classical and modified feedback linearization is shown to illustrate the significant improvement in the stabilization of the various parameters such as the cable tensions and platform orientations.
Paper VI142-10.12
PDF · Video · Feedforward Compensation of Torque Harmonics in Permanent Magnet Synchronous Machines
Dieterle, Oliver	Pforzheim University
Greiner, Thomas	Pforzheim University
Heidrich, Peter	Pforzheim University
Keywords: Identification and control methods, Motion Control Systems Abstract: This paper presents a method for compensation of torque ripples in electrical drives with permanent magnet synchronous machine. A standard field-oriented current control is complemented by a nonlinear feedforward control that influences the reference voltage. The compensation method has the advantage that it requires very little additional computing power and memory. Harmonic voltage components are provoked in a way that torque ripples are suppressed, while the instantaneous voltage vector magnitude of the nominal control is not changed. Additionally, an algorithm for time-saving identification of the operating point-dependent optimal compensation parameters is proposed.
Paper VI142-10.13
PDF · Video · Robust Adaptive Control of a Hydraulic Press
Macchelli, Alessandro	Univ. of Bologna - Italy
Barchi, Davide	SACMI Imola S.C
Marconi, Lorenzo	Univ. Di Bologna
Bosi, Gildo	SACMI Imola S.C
Keywords: Identification and control methods, Motion Control Systems, Mechatronic systems Abstract: The aim of this paper is to illustrate the design and the simulative validation of an adaptive controller developed for an hydraulic press. With respect to controllers actually implemented, the proposed solution assures similar performances in nominal conditions, but it is simpler to be tuned and it is able to estimate the leakage inside the hydraulic piston. Such an estimate is used to maintain the performances acceptable in a wide set of operative conditions and for predictive maintenance. By using singular perturbation arguments, we show robustness to slowly increasing leakage gains, which is a typical situation in a real-world application. The control scheme is validated on a simulative Simscape model.
Paper VI142-10.14
PDF · Video · An Adaptive Controller for Robotic Manipulators with Unknown Kinematics and Dynamics
Wang, Sihan	University of Bristol
Zhang, Kaiqiang	UKAEA
Herrmann, Guido	University of Manchester
Keywords: Identification and control methods, Robots manipulators, Information and sensor fusion Abstract: The ability for kinematics to adapt is important for robotic systems applied in complex environments. This paper focuses on the trajectory control problems of a robotic system with varying kinematics at the end-effector. A new adaptive control approach is developed for robotic manipulators with unknown kinematics and dynamics. This is achieved by using a model-free adaptive controller combined with a kinematics observer. The introduced kinematics observer allows for estimating the kinematic parameters, even under some unconventional application scenarios where typical image processing based techniques are not applicable. Stability of the model-free control with kinematics observer is proven. Control performance and estimation results have been assessed for a wider range of scenarios in a simulation environment which incorporates full nonlinear arm dynamics, finite sampling time and sensor noise.
Paper VI142-10.15
PDF · Video · Evaluation of Nonlinear System Identification to Model Piezoacoustic Transmission
Soares Barbosa, Matheus Patrick	PUC-Rio
Pereira da Costa, Daniel	PUC-Rio
Hultmann Ayala, Helon Vicente	Pontifical Catholic University of Rio De Janeiro
Keywords: Identification and control methods, Smart Structures, Mechatronics Abstract: Piezoeletric materials are used on high-precision and high-dynamics applications, such as for acoustic transmission. This paper covers the challenges of creating a black-box model for a simultaneous acoustic transmission problem, with data acquired in a laboratory setup. The system performance is analyzed for three different models: AutoRegressive Moving Average with eXogenous inputs (ARMAX) model, Nonlinear AutoRegressive with eXogenous inputs (NARX) model with artificial neural network structure, and Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX) models. The best results of each models are compared with respect to precision in free-run simulation. The prediction results show that the most complex NARMAX model had the best results, what encourages further research in creating nonlinear mathematical data-driven abstractions for the piezoacoustic transmission application.
Paper VI142-10.16
PDF · Video · Higher Order PD and iPD Controller Tuning
Huba, Mikulas	Slovak Univ. of Tech
Skrinarova, Jarka	UMB Banska Bystrica
Bistak, Pavol	Slovak University of Technology in Bratislava
Keywords: Design methodologies, Motion Control Systems, Identification and control methods Abstract: This paper deals with tuning of proportional-derivative (PD) and ``intelligent'' proportional-derivative (iPD) controller for the double integrator plus dead time (DIPDT) system. iPD corresponds to a PD controller augmented with a disturbance-observer based integral (I) action based on finite impulse response (FIR) filter. Since noise reduction requires working with as short sampling period as possible, the design of controllers is appropriate to implement in the continuous-time domain with a suitable discretization. In this way, when the noise attenuation filters are approximated by an equivalent dead time added to the plant dead time, stabilizing controllers with higher order output derivatives may be introduced simply and without excessive noise-induced control effort. Together with filtration of the reconstructed disturbance it significantly improves the overall loop performance.
Paper VI142-10.17
PDF · Video · Robust PID Control of Multicompartment Lung Mechanics Model Using Runge-Kutta Neural Disturbance Observer
Dilmen, Erdem	Pamukkale University
Keywords: Hardware-in-the-loop simulation, Identification and control methods, Biomedical Mechatronics Abstract: This paper proposes Runge-Kutta neural disturbance observer to enhance the robustness of PID control of a system with general multicompartment lung mechanics. It is designed to observe the states of any continous time, single-input single-output system where the states cannot be measured but can be observed through the single output and there exists parametric uncertainity or disturbance affecting the underlying system. It utilizes artificial neural network to estimate the disturbance online. Once an accurate disturbance estimation is obtained, it is incorporated in the system state equation and passed through the well-known Runge-Kutta integrator to predict the state values. Hence, the predicted states are obtained considering the disturbance and more robust state observation is achieved. The proposed observer is simple and easy to implement. Adaptation of the neural network is performed using gradient descent with an adaptive learning rate which guarantees convergence. The simulation results demonstrate that the proposed observer gains a significant success in enhancing the robustness of PID control at even high level of disturbance. Note that, multicompartment lung mechanics system is a stand-in model that can mimic the behavior of human lung. Thus, it is appropriate for hardware-in-the-loop simulation which opens a path to the real-patient-tests of mechanical respiratory systems in the future.
Paper VI142-10.18
PDF · Video · UKF-SVM Based Generalized Predictive Control of Multicompartment Lung Mechanics Model
Dilmen, Erdem	Pamukkale University
Keywords: Hardware-in-the-loop simulation, Identification and control methods, Biomedical Mechatronics Abstract: In this paper, least-squares support vector machine (LS-SVM), whose parameters are updated by unscented Kalman filter (UKF), is adopted in the generalized predictive control (GPC) of a system with general multicompartment lung mechanics. Gaussian kernel function is employed since it presents a good approximation to the inner product of nonlinear mapping possessed in the SVM formulation. In the SVM literature, it is well known that the width parameter sigma of the Gaussian kernel function has an important effect on the performance. However, it is not possible to train that parameter together with the other parameters of SVM when using linear least squares. This is why we use UKF for parameter adaptation in the SVM formulation. At each time instant of the control task, all parameters of the LS-SVM model, including sigma, are tuned simultaneously. Another reason to employ UKF is; it avoids the suboptimal solutions caused by linearization based filters, e.g., extended Kalman filter. Due to these facts, we train the SVM model using UKF and it will be referred to as the UKF-SVM model. Simulation results concerning the application of UKF-SVM based GPC to a multicompartment lung mechanics model yields plausible performance using small amount of support vectors even when there are time-varying parameters and disturbance of high level affecting the system. The adopted approach can also be useful when there is not any knowledge of the system dynamics, i.e., black box. Note that, multicompartment lung mechanics system is a stand-in model that can mimic the behavior of human lung. Thus, it is appropriate for hardware-in-the-loop simulation which opens a path to the real-patient-tests of mechanical respiratory systems in the future.
Paper VI142-10.19
PDF · Video · Adaptive RBF Neural Network Control Method for Pneumatic Position Servo System
Ren, Hai-Peng	Xi'an University of Technology
Jiao, Shan-shan	Xi'an University of Technology
Wang, Xuan	Xi'an University of Technology
Li, Jie	Xi'an University of Technology
Keywords: Mechatronics, Motion Control Systems, Identification and control methods Abstract: With the development of control theory and the pneumatic element, the application of pneumatic systems has attracted more attention because of the performance to price ratio improvement. Despite of these, there are still challenge to deal with the nonlinearity of the system, the uncertainty of the parameters, the input saturation and the unknown control direction in the tracking control of pneumatic system. In this paper, the nonlinearity and model uncertainty are treated with adaptive radial basis function neural network (RBFNN), meanwhile, the unknown control direction and input saturation are dealt with the Nussbaum function and Gauss error function, respectively. The stability of the designed controller is proved by Lyapunov theory. Finally, the experimental and comparison results show the effectiveness and superiority of the proposed method.
Paper VI142-10.20
PDF · Video · Multiple Quadrotors Carrying a Flexible Hose: Dynamics, Differential Flatness and Control
Kotaru, Venkata Naga Prasanth	University of California Berkeley
Sreenath, Koushil	University of California, Berkeley
Keywords: Modeling, Flying robots, Autonomous robotic systems Abstract: Using quadrotors UAVs for cooperative payload transportation using cables has been actively gaining interest in the recent years. Understanding the dynamics of these complex multiagent systems would help towards designing safe and reliable systems. In this work, we study one such multi-agent system comprising of multiple quadrotors transporting a flexible hose. We model the hose as a series of smaller discrete links and derive a generalized coordinate-free dynamics for the same. We show that certain configurations of this under-actuated system are differentially-flat. We linearize the dynamics using variation-based linearization and present a linear time-varying LQR to track desired trajectories. Finally, we present numerical simulations to validate the dynamics, flatness and control.
Paper VI142-10.21
PDF · Video · Control System Analysis and Design of Quadcopter in the Presence of Unmodelled Dynamics and Disturbances
Ali, Muhammad Zargham	Pakistan Institute of Engineering and Applied Sciences (PIEAS),
Ahmed, Aftab	Georgia Institute of Technology
Afridi, Hamad Khan	Pakistan Institute of Engineering & Applied Sciences (PIEAS)
Keywords: Modeling, Flying robots, Guidance navigation and control Abstract: UAVs especially quadcopters have recently caught the attention of researchers and manufacturers due to their various commercial and military applications like surveillance, photography and many others. They have small sizes since have low cost, easy manufacturing, extreme maneuverability and VTOL capabilities. This paper addresses the problem of unmod- elled dynamics and disturbances while designing an appropriate control law for the quadcopter UAV having very coupled nonlinear dynamics. Most of the controllers available in the literature ignore Coriolis terms in the model and small signal approximations are made to linearize or simplify the model about certain operating conditions. But such control system has a very limited performance and fails to deliver the desired results even for small disturbances and parametric variations since the assumptions no longer remain valid. We have derived an extensive nonlinear model of quadcopter with least approximations in terms of linear velocities in body frame, position in the inertial frame, the Euler angles and their rates. We have designed a feedback linearization based nonlinear controller using a novel approach. This has further been cascaded with sliding mode control and backstepping based control to handle uncertainties. The simulation results of this controller have also been included for a known quadcopter model.
Paper VI142-10.22
PDF · Video · Nonlinear Control Using Coordinate-Free and Euler Formulations: An Empirical Evaluation on a 3D Pendulum
Siravuru, Avinash	Carnegie Mellon University
Sreenath, Koushil	University of California, Berkeley
Keywords: Modeling, Guidance navigation and control, Identification and control methods Abstract: Pendulum dynamics are widely utilized in robotics control literature to test and evaluate novel control design techniques. They exhibit many interesting features commonly seen in real-world nonlinear systems and yet they are simple enough for quick prototyping, further analysis, and benchmarking. In this work, we study the impact of a 3D pendulum's orientation parametrization on stabilization performance. Mainly, we show that using a global or coordinate-free formulation for dynamics and control is not only singularity-free but also more input-efficient. We validate this empirically by running over 700 stabilization simulations across the full configuration space of a 3D pendulum and compare the performance of a geometric and a Euler-parametrized controller. We show that the geometric controller is able to leverage the inherent manifold curvature and flow along geodesics for efficient stabilization.
Paper VI142-10.23
PDF · Video · Model Selection Ensuring Practical Identifiability for Models of Electric Drives with Coupled Mechanics
Tantau, Mathias	Leibniz University Hanover
Popp, Eduard	Leibniz University Hanover, Institute of Mechatronic Systems
Perner, Lars	Lenze Automation GmbH
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Modeling, Identification and control methods, Application of mechatronic principles Abstract: Physically motivated models of electric drive trains with coupled mechanics are ubiquitous in industry for control design, simulation, feed-forward, model-based fault diagnosis etc. Often, however, the effort of model building prohibits these model-based methods. In this paper an automated model selection strategy is proposed for dynamic simulation models that not only optimizes the accuracy of the fit but also ensures practical identifiability of model parameters during structural optimization. Practical identifiability is crucial for physically motivated, interpretable models as opposed to pure prediction and inference applications. Our approach extends structural optimization considering practical identifiability to nonlinear models. In spite of the nonlinearity, local and linear criteria are evaluated, the integrity of which is investigated exemplarily. The methods are validated experimentally on a stacker crane.
Paper VI142-10.24
PDF · Video · Experimentally Validated Sliding Mode Control of Multi-Rotor UAV with Control Signal Constraints
Zhu, Yuankang	Royal Melbourne Institute of Technology
Wang, Liuping	RMIT University
Mishra, Jyoti Prakash	Royal Melbourne Institute of Technology
Keywords: Modeling, Identification and control methods, Flying robots Abstract: This paper proposes a cascade control strategy for multi-rotor unmanned aerial vehicles, where the inner-loop system is regulated by a sliding mode controller with disturbance observer and the outer-loop controller is a PID controller. Operational constraints are incorporated in the implementation for safety protection of the electronics. Experimental results are obtained to demonstrate the efficacy of the proposed design in comparison to a traditional cascade PID control system.
Paper VI142-10.25
PDF · Video · Rijke Organ: Modeling and Control of Array of Rijke Tubes
Pučejdl, KriŠtof	Czech Technical University in Prague
Hurak, Zdenek	Czech Technical University in Prague
Zemanek, Jiri	Czech Technical Univeristy in Prague
Keywords: Modeling, Identification and control methods, Mechatronics Abstract: Rijke tube is a popular physical experiment demonstrating a spontaneous generation of sound in an open vertical pipe with a heat source. This laboratory instance of thermoacoustic instability has been researched due to its significance in practical thermoacoustic systems. We revisit the experiment, focusing on the possible use of the Rijke tube as a musical instrument. The novelty presented in this paper consists in shifting the goal from sound suppression to active sound generation. This called for modifying the previously investigated methods for stabilization of thermoacoustic oscillations into their excitation and control of their amplitude. On our way towards this goal, we developed a time-domain mathematical model that considers the nonlinear and time-varying aspects of the Rijke tube. The model extends the existing modeling and analysis approaches, which are mainly based in frequency domain. We also present an extension of the basic laboratory setup in the form of an array of Rijke tubes equipped with a single speaker used to control multiple Rijke tubes with different natural frequencies simultaneously.
Paper VI142-10.26
PDF · Video · Trajectory Tracking and Adjustable Stiffness Control of a Pneumatically Actuated Robot
Raisch, Adrian	University of Stuttgart
Thallemer, Axel	The Hong Kong University of Science and Technology
Kostadinov, Aleksandar	National University of Singapore, DID Division of Industrial Des
Sawodny, Oliver	Univ of Stuttgart
Keywords: Mechatronic systems, Identification and control methods, Motion Control Systems Abstract: Variable stiffness actuation and soft robotics are growing fields of interest in research due to their close link to the feasibility of human-machine-interaction. In this paper, we give the modeling and control of a pneumatically actuated robot with three degrees of freedom based on the antagonist principle. The use of pneumatic actuators brings the benefit of an inherit softness and utilizing the mean force of the antagonists, we can influence the stiffness of the overall system. We present a cascaded control concept using feedback linearization for the pneumatics, decoupling the mechanical dynamics, and taking into account the constructive limitations to the available torque. The control concept is then applied to the robot in an experimental setup and its performance is validated.
Paper VI142-10.27
PDF · Video · Feedforward Control for Single Particle Tracking Synthetic Motion
Vickers, Nicholas	Boston University
Andersson, Sean	Boston University
Keywords: Application of mechatronic principles, Identification and control methods Abstract: Single particle tracking (SPT) is a method to study the transport of biomolecules with nanometer resolution. Unfortunately, recent reports show that systematic errors in position localization and uncertainty in model parameter estimates limits the utility of these techniques in studying biological processes. There is a need for an experimental method with a known ground-truth that tests the total SPT system (sample, microscope, algorithm) on both localization and estimation of model parameters. Synthetic motion is a known ground-truth method that moves a particle along a trajectory. This trajectory is a realization of a Markovian stochastic process that represents models of biomolecular transport. Here we describe a platform for creating synthetic motion using common equipment and well-known, simple methods that can be easily adopted by the biophysics community. In this paper we describe the synthetic motion system and calibration to achieve nanometer accuracy and precision. Steady state input-output characteristics are analyzed with both line scans and grid scans. The resulting relationship is described by an affine transformation, which is inverted and used as a prefilter. Model inverse feed forward control is used to increase the system bandwidth. The system model was identified from frequency response function measurements using an integrated stepped-sine with coherent demodulation built into the FPGA controller. Zero magnitude error tracking controller method was used to invert non-minimum phase zeros to achieve a stable discrete time feed forward filter.
Paper VI142-10.28
PDF · Video · Design of a PI-Controller Based on Time-Domain Specification Utilizing the Parameter Space Approach
Popp, Eduard	Leibniz University Hanover, Institute of Mechatronic Systems
Tantau, Mathias	Leibniz University Hanover
Wielitzka, Mark	Leibniz University Hanover
Giebert, Dennis	IAV Automotive Engineering
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Application of mechatronic principles, Identification and control methods, Modeling Abstract: In automotive application PI and PID controllers are widely used. Commonly the controller parametrization is performed in a heuristic manner in the vehicle at different operating points. Model-based approaches offer many advantages like a reduced effort of the design process and a more systematically investigation of the parameter set. Circumventing experiments at the vehicle is not feasible, however the goal is to achieve a significant reduction of this part of work. The aim of this paper is to find the controller parameter region, that ensures compliance with defined measures of the controller performance in time domain. On the basis of the parameter space approach these measures need to be transferred into the s-domain, which is shown exemplary for a second order system and a PI-controlled integrator system. The latter serves as a simple vehicle drive train model for the design of the engine idle speed controller.
Paper VI142-10.29
PDF · Video · Observer Design for Non-Stationary Oscillating Disturbances in Mixing Processes
Skalecki, Patric	University of Stuttgart
Sonja, Laicher	University of Stuttgart
Wörner, Mark	Liebherr-Mischtechnik GmbH
Sawodny, Oliver	Univ of Stuttgart
Keywords: Application of mechatronic principles, Modeling, Mechatronic systems Abstract: Information on the progression of the mixing process and quality are essential for mass concrete production. The power profile during the course of mixing can be used to evaluate the mixing process and its quality. Thus, a method for monitoring the average power transferred into the mixing material is presented, which enables an online mixture control based on the mechanical properties of the materials. An extensive experimental program on a 60l laboratory twin-shaft mixer and a large-scale construction site mixer was performed to characterize mixer specific effects. For example, losses and speed dependent mixer shaft effects are examined. The portability and scalability of the results of the laboratory mixer is demonstrated by a comparison with a large construction site mixer. Based on the experimental insights, a signal model is derived which accounts for the characteristic disturbances in the power profile. Secondly, an extended Kalman filter is designed to estimate the disturbances online to separate these from the mean power signal, which can be used for evaluation of the concrete mixing progress. Finally, experimental results for different operating conditions and a comparison to classical signal filters such as a moving average filter and a low pass filter are presented, which show the increased performance of the presented approach.
Paper VI142-10.30
PDF · Video · Development and Stabilization of a Low-Cost Single-Tilt Tricopter
Abara, Daniel	University of Manchester
Kannan, Somasundar	SnT University of Luxembourg
Lanzon, Alexander	University of Manchester
Keywords: Mechatronic systems, Flying robots, Modeling Abstract: In this paper, a low-cost single-tilting tricopter aerial vehicle is developed with optical flow estimation for indoor navigation. A dynamic model is derived and experimental data is used to obtain the actuator constants. A CAD model is then developed and is used to obtain the moments of inertia with respect to the three main axes. A control allocation algorithm is also proposed to solve the problem of the number of control inputs being more than the number of actuators since the single rotor tilt tricopter has only four actuators (3 rotors and 1 servo). A cascaded-PID control scheme is then used to stabilize the tricopter in hover mode. The simulation results yield realistic control inputs and the outputs have acceptable performance. The feasibility of the proposed scheme is then validated with some experiments on the developed tricopter platform in hover.
Paper VI142-10.31
PDF · Video · Virtual Torque Sensor for Electrical Bicycles (I)
Misgeld, Berno	RWTH Aachen University
Bergmann, Lukas	RWTH Aachen University
Szilasi, Bence	RWTH Aachen University
Leonhardt, Steffen	RWTH Aachen
Greven, Dietmar	Amprio GmbH
Keywords: Parameter and state estimation, Kinetic modeling and control of biological systems, Model formulation, experiment design Abstract: We present a novel approach to the reconstruction of the physical pedalling torque in an electrically powered bicycle. The external force due to the road slope that is acting on the bicycle is estimated employing the reconstruction of the inclination angle with an orthogonal filter. This orthogonal filter uses an adaptive weighting between gyroscope and accelerometer sensor data. The applied weighting function is based on the bicycle's acceleration, estimated from a bicycle velocity sensor. Based on a nonlinear physical model of the bicycle, the cyclist's pedalling torque is reconstructed with an Unscented Kalman Filter. Experimental results from the inclination angle estimator and virtual torque sensor for different road slopes underline the performance of the proposed approach.

VI142-11
Modeling and Design Methods for Mechatronic Systems	Regular Session
Chair: Sawodny, Oliver	Univ of Stuttgart
Co-Chair: Jadlovská, Slávka	Technical University of Kosice, FEEI
Paper VI142-11.1
PDF · Video · Minimizing Observation Spillover for Pose Control of Elastic Bodies Using Optimal Sensor Placement
Schmidt, Kevin	University of Stuttgart
Inan, Nese	University of Stuttgart
Schüle, Johannes	University of Stuttgart
Böhm, Michael	University of Stuttgart
Kharitonov, Alexander	University of Applied Sciences Würzburg-Schweinfurt
Sawodny, Oliver	Univ of Stuttgart
Keywords: Design methodologies, Mechatronic systems, Mechatronics Abstract: The impact of elastic modes limits the performance of position control of elastic bodies in a significant way. Local dampers are a typical way to suppress this issue, but lead to non-proportional damping and complex oscillation modes with varying nodal lines. To this end, the placement of the sensors is of major importance in high-precision applications. In this contribution, we present an optimal sensor placement algorithm which uses Gramian-based observability measures to overcome this issue. Singular sensing configurations with respect to the pose are avoided by considering the mappings’ local invertibility explicitly. Furthermore, we are in the position to cope with the highly relevant issue of constrained installation space and to handle complex 2D and 3D geometries by using model order reduction techniques. By means of an illustrative example, the significantly reduced influence of the elastic deformations on the controller is demonstrated at last.
Paper VI142-11.2
PDF · Video · Model-Based Dependability Assessment of Phased-Mission Unmanned Aerial Vehicles
Steurer, Mikael	Technische Universität Dresden
Morozov, Andrey	Technische Universität Dresden
Janschek, Klaus	Technische Universität Dresden
Neitzke, Klaus-Peter	Hochschule Nordhausen
Keywords: Mechatronic systems, Design methodologies, Modeling Abstract: Assessment of non-functional reliability and safety requirements in the early development phases helps to prevent conceptually wrong decisions and, as a consequence, significantly reduces overall development costs. The application of model-based system analysis techniques demonstrates promising results for complex avionics systems, especially software-intensive Unmanned Aerial Vehicles (UAV). Such systems are commonly designed to accomplish a specific mission consisting of multiple mission phases. The concept of phased mission systems enables the specification of individual requirements for different phases. For instance, the reliability requirements or system specifications are different for UAV flights over an agricultural field and a highway. Therefore, modern analytical methods have to distinguish between different mission phases and enable the analysis of phased missions. In this paper, we propose a new model-based method that allows system engineers to assess a conceptional design specification of the UAV concerning the fulfillment of phase-specific requirements. The proposed approach exploits modern probabilistic model checking techniques for the quantification of several dependability metrics. The method supports the systematic analysis of system specifications that contain both structural and behavioral system properties. A case study demonstrates the feasibility of the proposed method.
Paper VI142-11.3
PDF · Video · A Hybrid Dynamical Model for Hysteretic Thermal Shape Memory Alloy Wire Actuators
Mandolino, Michele Arcangelo	Saarland University
Ferrante, Francesco	Université Grenoble Alpes
Rizzello, Gianluca	Saarland University
Keywords: Mechatronic systems, Modeling, Mechatronics Abstract: In this paper, we present a novel hybrid dynamical model for hysteretic actuators consisting of spring-loaded Shape Memory Alloy (SMA) wires. The hybrid description is obtained by reformulating a set of physics-based ODEs resulting from the Müller-Achenbach-Seelecke (MAS) model of SMA material. Although the MAS model provides an accurate and consistent description of the system hysteresis, its use for simulation and control is limited due to the highly nonlinear and stiff nature of the resulting ODEs. By means of the hybrid reformulation, the numerical stiffness can be effectively eliminated while keeping all the benefits of the physics-based description. The different operating modes and transitions are first described from a physical point of view and then used to develop the flow and jump dynamics of the resulting hybrid model. Numerical simulations show that both hybrid and physics-based models provide nearly identical results. In addition, it is observed that the former requires simulation times that are up to two orders of magnitude smaller than the latter.
Paper VI142-11.4
PDF · Video · Modeling of a Rope-Free Passenger Transportation System with Closed Kinematic Chain
Missler, Jonas	University of Stuttgart
Jetter, Markus	Thyssenkrupp Elevator AG
Sawodny, Oliver	Univ of Stuttgart
Keywords: Mechatronic systems, Modeling, Mechatronics for Mobility Systems Abstract: Passenger comfort is one of the main concerns in the acceptance of a new passenger transportation system (PTS). Especially in vertical transportation systems, classically realized by cable elevators, the highest possible ride quality is expected by the market. In the rope-free PTS the rope of the standard elevator is replaced by a linear motor, which directly provides the driving force. The new propulsion and in particular the possibility of horizontal movement inside the shaft, demands a new design of the vehicle. This paper will present a model of the PTS with the focus on passenger comfort and therefore on the aspect of active vibration damping. The presented model also includes an actuator model of the damping components, which form with a closed kinematic chain together with the PTS. Measurements on the real MULTI test system of the novel PTS, which is installed in the test tower in Rottweil, Germany, are used to identify the model parameters.
Paper VI142-11.5
PDF · Video · Modeling of Benchmark Underactuated Systems Via Different Approaches
Cimborová, Karina	Technical University of Kosice, FEEI, DCAI
Jadlovská, Slávka	Technical University of Kosice, FEEI
Keywords: Modeling, Design methodologies Abstract: The presented paper deals with the area of research on multibody mechanical systems focused on underactuated systems, where the impact of the missing actuator is compensated by means of mathematical modeling. Several approaches based on the dynamics of individual bodies make it possible to obtain the mathematical model of the mechanical system. This paper focuses on summarizing and comparing Lagrange's and Kane's method, describing the steps that need to be applied to obtain a model for a particular mechanical system in each case. The methods are subsequently applied to selected benchmark underactuated systems such as cart-pole, acrobot, and reaction wheel pendulum, where the aim is to show that both produce the same equations of motion. The corresponding procedures are implemented in MATLAB as part of a custom application with graphical user interface.
Paper VI142-11.6
PDF · Video · Towards the Analogy of Electrostatic and Electromagnetic Transducers
Schroedter, Richard	Vienna University of Technology
Csencsics, Ernst	Vienna University of Technology
Schitter, Georg	Vienna University of Technology
Keywords: Modeling, Mechatronic systems, Application of mechatronic principles Abstract: Electromechanical, or mechatronic, transducers exchange energy between the mechanical and electrical domain via electrostatic and electromagnetic transduction principles, which are the basis for actuators and sensors. This paper reveals the simple analogy between electrostatic and electromagnetic transducers. Summarizing the well-known Gauß, Ampere's, Ohm's, Chua's, Newton's, Hook's and the damping laws into a signal-flow diagram with linearized coefficients, the model shows the transducers reciprocity and physical behavior of damped spring-mass mechatronic systems. The presented modeling approach simplifies the derivation of transfer functions, the pull-in phenomenon, and the coupling factors for the design of feedback methods for mechatronic systems. The analogies are shown by comparing an electrostatic and an electromagnetic parallel-plate actuator, represented by a torsional MEMS scanning mirror and a hybrid reluctance fast steering mirror, respectively. The paper discusses the actuators performance and compares the transducer coefficients and the intrinsic stiffness regarding pull-in.
Paper VI142-11.7
PDF · Video · A Model to Control Self-Erecting Tower Cranes with Elastic Structure
Thomas, Matthias	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Modeling, Vibration control Abstract: Control of large-scale tower cranes is still an open research field. Due to their lightweight structure and their large geometry structural deformations occur and need to be considered for anti-sway feedback control. Especially, for self-erecting tower cranes no proper model has been published yet. In this paper, a flexible multi-body model for this type of crane is derived and a modal analysis is performed. The results are compared to measurement data of an industrial tower crane.
Paper VI142-11.8
PDF · Video · Mechanical Design Optimization for a Five-Link Walking Bipedal Robot
Khusainov, Ramil	Innopolis University
Mamedov, Shamil	Innopolis University
Sellami, Sami	Innopolis University
Klimchik, Alexandr	Innopolis University
Keywords: Mobile robots, Design methodologies, Mechatronic systems Abstract: Hybrid zero dynamics is an established theoretical framework that allows to perform dynamic legged locomotion by enforcing virtual constraints through feedback controllers. One of the major functions of the framework is finding virtual constraints that result in the most efficient locomotion in terms of energy expenditure. This paper argues that the problem of reducing such transportation costs requires the optimization of mechanical parameters along with gait parameters. Our study showed that a simultaneous optimization of mechanical and gait parameters results, on average, in threefold reduction in the energy consumption for the whole range of achievable velocities.

VI142-12
Motion Control	Regular Session
Chair: Aguilar, Luis T.	Instituto Politecnico Nacional
Co-Chair: Janschek, Klaus	Technische Universität Dresden
Paper VI142-12.1
PDF · Video · Global Practical Tracking for a Hovercraft with Unmeasured Linear Velocity and Disturbances
Xie, Wei	University of Macau
Cabecinhas, David	Instituto Superior Tecnico
Cunha, Rita	Instituto Superior Técnico, Universidade De Lisboa
Silvestre, Carlos	University of Macau
Keywords: Motion Control Systems, Autonomous robotic systems, Modeling Abstract: This paper addresses the design and experimental validation of a trajectory tracking controller for an underactuated hovercraft with unmeasured linear velocity and subject to time-varying disturbances. The unmeasured linear velocity and disturbances are recovered by designing nonlinear observers. A control law is proposed that, in closed-loop with the velocity and disturbance observers, can robustly steer the hovercraft toward and stay within a neighborhood of a reference trajectory. To demonstrate the performance and robustness of the proposed control strategy, we present and analyze experimental results obtained with a model-scale hovercraft.
Paper VI142-12.2
PDF · Video · A Hybrid Adaptation Strategy for Repetitive Control of an Uncertain-Delay Lagrangian System
Tilli, Andrea	University of Bologna
Ruggiano, Elena	University of Bologna
Conficoni, Christian	Alma Mater Studiorum Bologna
Bosso, Alessandro	Alma Mater Studiorum - University of Bologna
Keywords: Motion Control Systems, Design methodologies, Mechatronic systems Abstract: In this work, we present a novel repetitive control (RC) strategy to achieve accurate position tracking of a 1-DOF Lagrangian system. Such controller is able to cope with model uncertainties and unknown transmission delays in the control architecture. The classic repetitive structure is augmented with an observer of the residual disturbance, to be compensated by means of the RC action. The repetitive unit is updated at hybrid instants, so that the disturbance observer is close to its steady-state before a new repetitive correction is applied. In addition, communication delay is also estimated by the proposed control structure. This way, practical asymptotic stability of the overall system can be achieved with a simple proportional correction of the RC, also under perturbations of the steady-state estimate due to model uncertainties. In light of the aforementioned properties, the proposed RC-based controller is shown to be an easy-to-tune, robust solution capable of improving the tracking performance for the given case of study.
Paper VI142-12.3
PDF · Video · Nonlinear Observer-Based Control of an Under-Actuated Hovercraft Vehicle
Pröhl, Lukas	University of Rostock
Aschemann, Harald	University of Rostock
Keywords: Mechatronic systems, Motion Control Systems, Modeling Abstract: This paper presents a model-based approach to the nonlinear tracking control for the bodyfixed velocities of an under-actuated hovercraft vehicle. To enable a corresponding state feedback with accurate velocity signals, an observer-based sensor fusion is envisaged using acceleration measurements as well as data from an optical flux sensor. The horizontal and the vertical motion of the vehicle are modeled accordingly, and decentralized state-space representations are used for a subsequent nonlinear control design, where flatness-based techniques are employed for simplicity. To ensure steady-state accuracy, integral parts are introduced in the stabilizing feedback laws. The performance of the proposed control structure is investigated by simulation using an identified model of a corresponding experimental vehicle. In addition, also first experimental results are provided.
Paper VI142-12.4
PDF · Video · Computationally Efficient Model Predictive Control for Real Time Implementation Experimentally Applied on a Hydraulic Differential Cylinder
Bakhshande, Fateme	Duisburg-Essen University
Spiller, Mark	University of Duisburg-Essen
King, Yen-Lin	Duisburg-Essen University
Söffker, Dirk	Univ of Duisburg-Essen
Keywords: Motion Control Systems, Identification and control methods Abstract: In the field of model predictive control (MPC), the computational effort of solving the optimization problem considering long prediction horizon is often challenging, making the implementation in real time infeasible. On the other side, a longer prediction horizon leads to better control performance. Therefore, a trade off between computational effort and control performance should accurately be achieved for the selection of prediction horizons within model predictive algorithms. This paper presents a new scheme for model predictive control (structured MPC) considering a fixed set of rules for assumed control structures simplifying the optimization problem and therefore reducing the computational effort of MPC while maintaining advantages of adaptive and optimal behavior due to MPC in combination with evaluation using prediction horizons. The suitable control input is defined considering a performance measure. Experimental results using a hydraulic differential cylinder test rig validate the advantages of the introduced approach for real time application of MPC in comparison to standard controllers.
Paper VI142-12.5
PDF · Video · Simple Saturated PID Control for Fast Transient of Motion Systems
Su, Y. X.	Xidian Univ
Zheng, Chunhong	Xidian Univ
Mercorelli, Paolo	Leuphana University of Lueneburg
Keywords: Motion Control Systems, Identification and control methods Abstract: This paper proposes a simple saturated proportional-integral-derivative (PID) control for set-point stabilization of motion systems subject to actuator constraint. The proposed controller consists of a saturated proportional-derivative (PD) term and a saturated integral (I) term that robustly compensates the constant or slow time-varying unknown disturbances. It is shown that the proposed saturated PID (SPID) controller globally asymptotic stabilizes the set-point of motion systems without violation of actuator constraint. The appealing feature of the proposed approach is that it embeds the PD term within a single saturation function, which allows us to choose the proportional and derivative gains freely for faster transient and higher steady-state set-point precision. Numerical comparisons of an illustrative example demonstrate the improved performance of the proposed approach.
Paper VI142-12.6
PDF · Video · Nonlinear Adaptive Robust Motion Control for Hydraulic Winch in Oil and Gas Wireline Operation
Bu, Fanping	Schlumberger
Keywords: Motion Control Systems, Identification and control methods, Design methodologies Abstract: This paper presents the design and implementation of a nonlinear model based adaptive robust controller (ARC) for tool motion control driven by a hydrostatic transmission used in an Oil and Gas wireline operation. A detailed physical system model was built for controller design and testing. ARC controller was designed to address both parametric uncertainties and uncertain nonlinearities inherent in the nonlinear system dynamics. The controller software development and testing followed a Model-Based Design (MBD) procedure. A micro-service architecture based on docker containers was adopted for the controller software which facilitated continuous integration and deployment. The preliminary testing results show the effectiveness of the ARC controller design.
Paper VI142-12.7
PDF · Video · Tuning of CgLp Based Reset Controllers: Application in Precision Positioning Systems
Bahnamiri, Mahmoud Shirdast	University of Minho
Karbasizadeh, Nima	Delft University of Technology
Ahmadi Dastjerdi, Ali	Delft University of Technology
Saikumar, Niranjan	TU Delft
HosseinNia, S. Hassan	Delft University of Technology
Keywords: Motion Control Systems, Identification and control methods, Mechatronic systems Abstract: This paper presents the tuning of a reset-based element called ``Constant in gain and Lead in phase" (CgLp) in order to achieve desired precision performance in tracking and steady state. CgLp has been recently introduced to overcome the inherent linear control limitation - the waterbed effect. The analysis of reset controllers including ones based on CgLp is mainly carried out in the frequency domain using describing function with the assumption that the relatively large magnitude of the first harmonic provides a good approximation. While this is true for several cases, the existence of higher-order harmonics in the output of these elements complicates their analysis and tuning in the control design process for high precision motion applications, where they cannot be neglected. While some numerical observation-based approaches have been considered in literature for the tuning of CgLp elements, a systematic approach based on the analysis of higher-order harmonics is found to be lacking. This paper analyzes the CgLp behaviour from the perspective of first as well as higher-order harmonics and presents simple relations between the tuning parameters and the gain-phase behaviour of all the harmonics, which can be used for better tuning of these elements. The presented relations are used for tuning a controller for a high-precision positioning stage and results used for validation.
Paper VI142-12.8
PDF · Video · Adaptive Robust Motion Control of a Pump Direct Drive Electro-Hydraulic System with Meter-Out Pressure Regulation
Helian, Bobo	Zhejiang University
Chen, Zheng	Zhejiang University
Yao, Bin	Purdue University
Keywords: Motion Control Systems, Mechatronic systems Abstract: In industry, pump-controlled hydraulic systems are generally considered energy efficient but are not accurate due to their inherent characteristics such as low response frequencies, thus pump control hydraulic systems have been traditionally applied in situations that require high power but limited accuracy. Besides, for the conventional pump-controlled cylinder systems, especially opencircuit systems, the cylinder vibration and cavitation may result due to the negative load when the cylinder moves with a high deceleration trajectory. Therefore, it is difficult to simultaneously keep the advantages of energy-saving and high motion tracking accuracy. This paper proposes a novel control strategy for a servo motor-pump and proportional valves combination control system. The cylinder is directly driven by a variable speed pump to give full play to the advantage of energy-saving by pump control. The meter-out pressure is controlled by proportional valves to provide the required resistance for motion tracking. A pressure regulation method is proposed, consisting of an optimized meter-out pressure planning and a pressure tracking controller. Both the pump controller and the meter-out pressure controller use the adaptive robust control (ARC) algorithm to achieve high motion control accuracy.
Paper VI142-12.9
PDF · Video · Feedforward Control Design for Shaking Table by Data Driven Control Considering Control Input Limitation
Ishihara, Shinji	Hitachi, Ltd., Research & Development Group, Center for Technolo
Tahara, Koichi	Hitachi Industrial Products, Ltd
Hironaka, Koji	Hitachi Industrial Products, Ltd
Keywords: Motion Control Systems, Mechatronics, Mechatronic systems Abstract: The burden of control adjustment of shaking table is increasing with the background of lack of skilled operators. With such background, there is a strong demand for a method to achieve desired control performance regardless of the operator's skill. The data-driven control is a promising approach to meet this requirement. However, even though an actual controller has an input limit, the data-driven control cannot handle it. Therefor, we proposed a novel method that considers the input limit based on data-driven prediction and an optimal problem with a penalty function. We verified the effectiveness of the proposed method through experiments using a small shaking test device.
Paper VI142-12.10
PDF · Video · An Underwater Quadrotor Control with Wave-Disturbance Compensation by a UKF
Ohhira, Takashi	Keio University
Kawamura, Akihiro	Keio University
Shimada, Akira	Shibaura Institute of Technology
Murakami, Toshiyuki	Keio Univ
Keywords: Motion Control Systems, Mobile robots, Design methodologies Abstract: This paper proposes an unscented Kalman filter (UKF) with disturbance estimation for an underwater quadrotor control system by utilizing backstepping control. Autonomous underwater vehicles (AUVs) have been attracted attention to scientific and commercial applications. The tasks in those applications are such as surveys and inspections for various objects underwater in narrow space.　 In this study, a quadrotor type robot, in which high-performance results are obtained for aerial application, is regarded as AUVs. The quadrotor robot is a smaller system than general AUVs and has suitable merits for work in a narrow place.　 On the other hand, since the quadrotor system is small and light in weight, it is more susceptible to underwater waves than conventional AUVs. Therefore, consideration of a technique to suppress or to reject the influences of the waves in the control systems is a must. This paper proposes a UKF system including a second-order model of input disturbance for estimating the influence of waves and an accurate quadrotor state simultaneously. Additionally, the disturbance estimation performance assists in make robustness as its estimated disturbance is rejected to actual disturbance. Finally, the usefulness of the proposed system is shown via simulations of position control for the underwater quadrotor affected by a wave effect model.
Paper VI142-12.11
PDF · Video · Gait Generation for Underactuated Compass-Like Robots Using Dissipative Forces in the Controller
Nacusse, Matías Antonio	Conicet; Labotatorio De Automatizacion Y Control (LAC), Departam
Arpenti, Pierluigi	University of Naples Federico II
Ruggiero, Fabio	Universita' Di Napoli Federico II
Lippiello, Vincenzo	University of Naples Federico II
Keywords: Motion Control Systems, Mobile robots, field robotics Abstract: This work addresses the problem of gait generation in underactuated compass-like biped robots using dissipative forces in the controller. Three different controllers are presented. The first one is a simultaneous interconnection and damping assignment passivity-based control with dissipative forces. The second one is an energy pumping-and-damping control, while the third one is an energy pumping or damping control action. Numerical case studies, comparisons, and critical discussions evaluate the performance of the proposed approaches.
Paper VI142-12.12
PDF · Video · Spatiotemporal Light Navigation System for Tracking Control of Mobile Robots
Okuda, Takahiro	Osaka University
Minami, Yuki	Osaka University
Ishikawa, Masato	Osaka University
Keywords: Motion Control Systems, Mobile robots, Guidance navigation and control Abstract: In this paper, we propose a spatiotemporal light navigation system for tracking control of a low-performance robot. The spatiotemporal light navigation system is composed of a projector and a mobile robot equipped with a light sensor. The projector casts a binary image on the field, and the mobile robot detects the information of the image via the light sensor and is supposed to decide its action by means of a simple embedded logic. First, we formulated the tracking control problem as a problem to design the casting image and sensor position of the robot. Then, we proposed a design method of casting images based on halftone image processing and analyzed the stability of the tracking control system. Finally, we experimented with verifying the effectiveness of the proposed method.
Paper VI142-12.13
PDF · Video · Task-Priority Control of Redundant Robotic Systems Using Control Lyapunov and Control Barrier Function Based Quadratic Programs
Basso, Erlend A.	Norwegian University of Science and Technology
Pettersen, Kristin Y.	Norwegian Univ. of Science and Tech
Keywords: Motion Control Systems, Mobile robots, Robotics technology Abstract: This paper presents a novel task-priority control framework for redundant robotic systems based on a hierarchy of control Lyapunov function (CLF) and control barrier function (CBF) based quadratic programs (QPs). The proposed method guarantees strict priority among different groups of tasks such as safety-related, operational and optimization tasks. Moreover, a soft priority measure in the form of penalty parameters can be employed to prioritize tasks at the same priority level. As opposed to kinematic control schemes, the proposed framework is a holistic approach to control of redundant robotic systems, which solves the redundancy resolution, dynamic control and control allocation problems simultaneously. Numerical simulations of a hyper-redundant articulated intervention autonomous underwater vehicle (AIAUV) is presented to validate the proposed framework.
Paper VI142-12.14
PDF · Video · Motion Control of Mechanical Systems with a Cable Contacting the Ground
Mikami, Maria	Aoyama Gakuin University
Yamamoto, Takeshi	Aoyama Gakuin University
Sugawara, Yoshiki	Aoyama Gakuin University
Takeda, Masakazu	Aoyama Gakuin University
Keywords: Motion Control Systems, Modeling, Mechatronics Abstract: The usage of unmanned aerial vehicles (UAVs) varies from construction inspection to disaster response. Cable attachment benefits the UAV with longer operation time and larger data transmission, while the tension, inertia, and contact forces of the cable work to disturb its operation. This paper introduces a numerical modelling method of a cable with frictional contact forces using an absolute nodal coordinate formulation (ANCF), and extracts and evaluates the influences of the cable on the mechanical system’s motion. The contacting cable length, that affects frictional contact forces, is derived using a catenary curve. The numerical analysis results present errors and vibrations at the connection point of the cable and the rigid body. These are the influences when the cable contacts the ground. In this paper, the compensation system, and its validity for mitigating these influences, using an unscented Kalman filter (UKF) to estimate the state of the cable, are presented. Although there was a small error in the mechanical system’s final position in relation to the target position, the numerical analysis indicated that the proposed control system stabilizes the mechanical system’s motion.
Paper VI142-12.15
PDF · Video · Model-Based Control of a Pendulum by a 3-DoF Cable Robot Using Exact Linearization
Hamann, Marcus	University of Augsburg
Winter, David Lukas	University of Augsburg
Ament, Christoph	Universitaet Augsburg
Keywords: Motion Control Systems, Modeling, Robotics technology Abstract: In this paper we present the modeling and control of a pendulum by a cable robot. The control is based on an exact linearization of the nonlinear MIMO system. The resulting closed-loop system is subsequently extended by a pendulum damping. The pose of the pendulum is determined by the connection point of the cables at the pendulum and a reflector at the end of the pendulum. Due to the model-based control and the capability of an external absolute measurement of the reflector by means of laser trackers, a high positioning accuracy is achievable, which is unique in the field of cable robots.
Paper VI142-12.16
PDF · Video · Dual-Stage Soft Landing for a Pick-And-Place Manipulator
Polak, Adam	Czech Technical University in Prague, Faculty of Electrical Eng
Hromcik, Martin	Czech Technical Univ
Novak, Ondrej	EZconn Technologies CZ
Hurak, Zdenek	Czech Technical University in Prague
Keywords: Motion Control Systems, Robots manipulators, Mechatronic systems Abstract: In this paper we document a systematic solution to a particular motion control problem called soft landing encountered in the design of pick-and-place machines for the semiconductor industry. The problem has already been studied for a single actuator, and a solution for the case of voice-coil motors has already been implemented in commercial drivers. Here we investigate a more complex setup consisting of two translation stages, which make the problem over-actuated; furthermore, the inner stage (actuated by a voice coil motor) is preloaded with a weight- compensating spring. Our systematic approach is based on the concept of reaction force observer. Its functionality is demonstrated using numerical simulations and laboratory experiments. We compare the proposed method with a baseline solution based on a simple extension of an existing method. A related Simulink model and Matlab scripts are available for free download to help reproduce the results.
Paper VI142-12.17
PDF · Video · Flat Filtering Cascade Control of Fourth Order Systems
Ramirez-Neria, Mario	CINVESTAV-IPN
Luviano-Juárez, Alberto	UPIITA - IPN México
Lozada-Castillo, Norma	Instituto Politecnico Nacional
Ochoa, Gilberto	Universidad Politecnica Del Valle De Mexico
Sira-Ramirez, Hebertt J.	CINVESTAV-IPN
Keywords: Motion Control Systems, Robots manipulators, Mechatronics Abstract: In this article, the analysis and implementation of an alternative Flat Filtering Control for a class of partially known fourth order flat systems is given. The Flat filtering control uses the cascade property of the system, which leads to a simplified control design in which high order time derivatives are algebraically simplified in terms of low order measurable states and the subsequent integral compensation. The control proposal is implemented and validated experimentally in a fourth order mechanical system (rotatory flexible joint) with accurate tracking results.
Paper VI142-12.18
PDF · Video · Synchronized Mobile Manipulators for Kinematic Cooperative Tasks: Control Design and Analysis
Obregon, Jonathan	CINVESTAV
Morales, America	CINVESTAV SALTILLO
Keywords: Motion Control Systems, Robots manipulators, Mobile robots Abstract: In this paper we present a synchronization feedback control scheme for kinematic cooperative mobile manipulator robots performing a global task of manipulation and transportation, where an object is taken to a desired 6D pose. We define the motion of the object which is translated to each end-effector as desired coordinates, that trajectory is generated on-line and is a function of every robot in the scene. The group of robots follow the object’s motion where the control of each robot is also a function of every other robot, meanwhile they are constrained to a common object. This leads to a complicated interaction scheme, so we thoroughly analyze the effects of the interactions that alter the behavior of each robot, and determine under what conditions those effects help to increase the performance of the proposed control scheme, such that the motions are coordinated to minimize the total energy and stabilize themselves as the common object reaches its objective. For this we performed a stability analysis and tested our control scheme through simulations.
Paper VI142-12.19
PDF · Video · Optimal Scheduling and Model Predictive Control for Trajectory Planning of Cooperative Robot Manipulators
Tika, Argtim	University of Kaiserslautern
Gafur, Nigora	University of Kaiserslautern
Yfantis, Vassilios	Technische Universität Kaiserslautern
Bajcinca, Naim	University of Kaiserslautern
Keywords: Motion Control Systems, Robots manipulators, Robotics technology Abstract: A hierarchical control approach for cooperative pick-and-place tasks in narrow shared workspaces is proposed. A scenario with two robot arms performing pick-and-place tasks with moving objects while ensuring collision-free planning and execution of their respective trajectories is specifically addressed. To this end, we consider a hierarchical architecture with two-layer optimization-based control policies involving task scheduling in the top layer and path planning, along with the motion constraints, at the bottom one. For task allocation, a distance minimization algorithm is introduced, leading to an integer optimization problem with linear constraints and a bilinear cost function. On the other hand, we invoke model-based collision-free minimum-time planning of robot trajectories. Hereby, inverse robot dynamics and time scaling appear to be useful tools. The former accounts for the compensation of nonlinear robot dynamics, while the latter converts the trajectory planning to a fixed-time optimization problem, thus enabling synchronous robot task executions.
Paper VI142-12.20
PDF · Video · Sensing and Decentralized Control of a Five-Axis Monolithic Nanopositioning Stage
Omidbeike, Meysam	University of Newcastle
Yong, Yuen Kuan	The University of Newcastle
Fleming, Andrew John	University of Newcastle
Keywords: Motion Control Systems, Vibration control, Mechatronics Abstract: This article describes the design and calibration of a five degree-of-freedom linear and angular displacement sensor utilizing piezoresistive strain gages. A simple decentralized controller is then implemented to follow linear and angular reference signals. The foremost difficulty with piezoresistive sensors is their high-temperature sensitivity. In addition, they are sensitive to motion in multiple degrees of freedom, which must be decoupled before use as a displacement sensor. A new sensing design is proposed which provides decoupled measurements of linear and angular displacements in multi-axis monolithic nanopositioning stages. The proposed method employs system identification and feedforward techniques to calibrate each axis and minimize cross-coupling.
Paper VI142-12.21
PDF · Video · Field Oriented Economic Model Predictive Control for Permanent Magnet Synchronous Motors
Geweth, Daniel	Bosch GmbH
Zanelli, Andrea	University of Freiburg
Frison, Gianluca	University of Freiburg
Vollmer, Ulrich	Bosch GmbH
Diehl, Moritz	University of Freiburg
Keywords: Hardware-in-the-loop simulation, Mechatronic systems, Motion Control Systems Abstract: This paper proposes a novel nonlinear model predictive control approach for permanent magnet synchronous machines (PMSM). The optimization problem is formulated as a field oriented economic model predictive control (FO-EMPC) problem and therefore a target selector is not necessary. A dq-model of the PMSM with spherical voltage and current constraints is taken into account. A terminal set and a terminal penalty are introduced to mitigate stability and convergence issues with a short prediction horizon. The performance of the proposed control scheme is demonstrated in a simulation study on a personal computer and in a hardware-in-the-loop simulation, which show that the transition time is reduced by more than one order of magnitude with respect to state-of-the-art approaches, especially when the voltage constraint becomes active.
Paper VI142-12.22
PDF · Video · Nonlinear Control Formulation Based on Sliding Mode Control Applied to a 2-DOF Control Moment Gyroscope
D, Gobiha	Research Scholar, Indian Institute of Technology Madras
G, Rohith	Research Scholar, Indian Institute of Technology Madras
Sinha, Nandan Kumar	IIT Madras
Keywords: Hardware-in-the-loop simulation, Motion Control Systems, Design methodologies Abstract: Though conceptualization of nonlinear sliding mode control has gained great emphasis in mechatronics and nonlinear systems in general, little attention is given to real time implementation owing to its inadequacy in handling mismatched uncertainties. This work contemplates on a robust nonlinear control scheme with sliding mode control and extended Kalman filter in closed-loop to estimate and handle bounded uncertainties. Stability of this closed-loop framework is established through Lyapunov analysis. The proposed formulation is first validated on a simulation platform and then implemented on a 2-DOF experimental gyroscope setup. Efficacy of this approach is evident from its rigorous tracking performance attained with a smooth and bounded control profile, despite induced uncertainties in various forms.
Paper VI142-12.23
PDF · Video · Robust Tracking Control of Mechanical Hybrid Systems Driven by Electrical Actuators
Herrera, Leonardo Esau	Naval Postgraduate School
Orlov, Yury	CICESE
Montaño Godinez, Oscar Eduardo	CICESE
Aguilar, Luis T.	Instituto Politecnico Nacional
Verdés Kairuz, Ramón Imad	Instituto Politécnico Nacional
Keywords: Mechatronic systems, Motion Control Systems Abstract: The primary concern of the work is the robust synthesis of hybrid electromechanical systems, operating under unilateral position constraints. The synthesis relies on the nonlinear H_infty paradigm to be extended in the presence of impact phenomena, perturbations in the continuous and discrete phases, and the dynamics of the electrical actuators that drive the motion of the system. Performance issues of the proposed nonlinear H_infty-controller are illustrated in an experimental study of an impacting inverted pendulum.
Paper VI142-12.24
PDF · Video · Tilt Control of Magnetically Suspended Platform Using Zeropower Control
Oka, Koichi	Kochi University of Technology
Lin, James	Kochi University of Technology
Harada, Akinori	Kochi University of Technology
Keywords: Mechatronics, Motion Control Systems, Mechatronic systems Abstract: This paper proposes a new type of tilt control mechanism for zeropower controlled noncontact magnetic suspension system. A suspended platform using zeropower control keeps horizontal level using the proposed mechanism, even if an arbitrary load is added to the platform. The proposed mechanism uses hybrid magnets whose locations are controlled as the platform level is horizontal. Positioning control of additional permanent magnets also achieves inclination control of the platform. First, conceptual proposal of proposed mechanism is explained and a prototype system is introduced. Hardware and system limitations are discussed and simulation results are provided which confirm the feasibility of the proposed control strategy.
Paper VI142-12.25
PDF · Video · Performance Optimization Methodology for Discrete-Time Sliding Mode Control in Industrial Servo Systems under Control Input Saturation and Disturbance
Han, Ji-seok	Seoul National University
Oh, Tae-Ho	Seoul National University
Kim, Young-Seok	Seoul National University
Lim, Hyun-Taek	Seoul National University
Yang, Dae-Young	Seoul National University
Lee, Sang-Hoon	RS Automation
Cho, Dong-il Dan	Seoul National Univ
Keywords: Mechatronics, Motion Control Systems, Mechatronic systems Abstract: This paper presents a performance optimization methodology for the discrete-time sliding mode control (SMC) with the decoupled disturbance compensator (DDC) and the auxiliary state (AS) for an industrial position control system under control input saturation and disturbance. The discrete-time SMC with DDC and AS (SDA) method prevents windup phenomena in the switching function and the disturbance estimation error. Therefore, it provides robust performance under control input saturation, disturbances, as well as parametric uncertainties. However, it is difficult to relate several design parameters to the desired performance. In this paper, a systematical design framework for the discrete-time SDA method is developed. Based on the phase portrait of the error state, the error can be made to converge to zero with a fast speed and less oscillation under control input saturation by an offline tuning process. An optimization process is performed in terms of the peak value of the control input. Both numerical simulations and experimental results show the effectiveness of the developed tuning methodology for the discrete-time SDA method.
Paper VI142-12.26
PDF · Video · Multistable Energy Shaping of Passive Linear Systems with Hybrid Mode Selector
Massaroli, Stefano	The University of Tokyo
Califano, Federico	University of Twente
Faragasso, Angela	The Univeristy of Tokyo
Yamashita, Atsushi	The University of Tokyo
Asama, Hajime	The University of Tokyo
Keywords: Modeling, Motion Control Systems, Mechatronics Abstract: This paper presents a novel control strategy for stable linear time-invariant systems operating with a finite number of set points. Inspired by the theory of passivity-based control, the proposed method aims at simultaneously and asymptotically stabilize all the desired working modes by means of a static nonlinear state feedback law. An asynchronous external signal is then employed to trigger a hybrid controller in order to switch between the different working modes. The proposed approach is validated by means of simulations performed on the ubiquitous mass-spring-damper system.
Paper VI142-12.27
PDF · Video · Comparison of Optimal Actuation Patterns for Flagellar Magnetic Micro-Swimmers
El Alaoui-Faris, Yacine	Inria Sophia Antipolis
Giraldi, Laetitia	Université Cote d'Azur, LJAD, INRIA Sophia-Antipolis
Régnier, Stéphane	Université Pierre Et Marie CURIE, Institut Des Systèmes Intellig
Pomet, Jean-Baptiste	INRIA
Keywords: Modeling, Motion Control Systems, Micro and Nano Mechatronic Systems Abstract: In this article, we present a simplified model of a flagellar micro-swimmer actuated by external magnetic fields that is based on shape discretization and an approximation of the hydrodynamical forces. We numerically solve the optimal control problem of finding the actuating magnetic fields that maximizes its horizontal propulsion speed over a fixed time under different constraints on the magnetic field amplitudes and compare the optimal solutions. All the simulated magnetic fields out-perform the standard sinusoidal actuation method that is prevalent in the litterature and in experiments. Moreover, non-planar constraints on the control leads to novel optimal trajectories for flagellar low-Reynolds swimmers and perform significantly better than planar actuation.

VI142-13
Vibration Control	Regular Session
Chair: Hakvoort, Wouter	University of Twente
Co-Chair: Sawodny, Oliver	Univ of Stuttgart
Paper VI142-13.1
PDF · Video · Decentralized LQG Control for Adaptive High-Rise Structures
Warsewa, Alexander	University of Stuttgart, Institute for System Dynamics
Wagner, Julia Laura	University of Stuttgart
Böhm, Michael	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Tarin, Cristina	Technical University of Valencia
Keywords: Smart Structures, Vibration control, Information and sensor fusion Abstract: Adaptivity of buildings introduces new challenges and opportunities for both architects and engineers. With the possibility of active load compensation, new types of lightweight structures can be realized. However, those demand suitable control engineering methods to ensure safe and robust control. In this contribution, we introduce an approach for decentralized linear quadratic Gaussian (LQG) control of adaptive structures. Many state of the art methods in decentralized structural control focus on damping the response of substructures that are either derived by decomposition of a global finite element (FE) model or later assembled to form a complete structure. In contrast, we derive local models by means of model order reduction techniques which allows for fully decentralized control without the need to communicate states or estimate interaction forces. We demonstrate the decentralized control of local subsystems for an adaptive structures demonstrator building in simulations. Performance and energy demand are found to be comparable to a centralized controller which makes the presented approach well suitable for application. Monte Carlo simulations with both varying model parameters and system eigenvalues were conducted to analyze the robustness of the decentralized LQG controllers.
Paper VI142-13.2
PDF · Video · Development of a HiL Load Simulator for Experimental Investigation of Translational Oscillating Systems
Masoud, Abd Elkarim	Technical University of Berlin
Courant, Robert	Technical University of Berlin
Maas, Jürgen	Technical University of Berlin - TU Berlin
Keywords: Vibration control, Hardware-in-the-loop simulation, Motion Control Systems Abstract: In this paper, the principle of a hardware in the loop (HiL) load simulator is applied on an amplitude-controlled translational oscillatory actuator (TOA). For this purpose, an electromechanical actuator is designed and build, that can emulate different oscillating load characteristics. To describe the system, consisting of a translational oscillatory actuator and the HiL actuator, a nonlinear model is derived. Next, a general averaged model is set up comprising several time-varying Fourier coefficient. The controller is based on a linearized averaged model and considers a multi variable structure to control both amplitude and phase of the applied force. Finally, the concept is validated using simulations and experiments. The results show, that the designed controller with the realised hardware can robustly emulate a desired load on an amplitude-controlled TOA under investigation. Because of its high sensitivity to temperature, a force measurement using strain gauges was not applicable. Instead, the output equation of the nonlinear state space model was used to estimate the load force.
Paper VI142-13.3
PDF · Video · Active Vibration Isolation by Model Reference Adaptive Control
Hakvoort, Wouter	University of Twente
Boerrigter, Gijs	DEMCON Advanced Mechatronics B.V
Beijen, Michiel	DEMCON Advanced Mechatronics
Keywords: Vibration control, Mechatronics Abstract: his paper proposes model reference adaptive control (MRAC) to actively isolate payloads from floor vibrations and direct disturbance forces. Adaptive feedforward control is used to counteract measured disturbances, whereas an adaptive feedback controller suppresses unmeasured disturbances using skyhook damping. In the considered rigid single degree of freedom system, the ideal controller gains only depend on the stiffness and damping properties of the suspension. The MRAC strategy is validated experimentally on a hard mounted vibration isolation system. Attenuation of acceleration levels beyond -40 dB are obtained in a wide frequency band 5-100 Hz and the root-mean-square (RMS) acceleration in the frequency region of interest (0.1-100 Hz) is reduced 32 times with respect to passive isolation.
Paper VI142-13.4
PDF · Video · Bayesian Optimization Approach to Input Shaper Design for Flexible Beam Vibration Suppression
Pásztori, Zsolt	CERN
Ruggiero, Fabio	Universita' Di Napoli Federico II
Lippiello, Vincenzo	University of Naples Federico II
Di Castro, Mario	CERN
Keywords: Vibration control, Mobile robots, field robotics Abstract: This paper tackles the problem of suppressing vibrations of a flexible beam mounted on a mobile robot for inspection purposes. The adopted approach is an input shaper design along with Bayesian optimization. The latter methodology is employed to find out the optimal shaping parameter, taking into account non-ideal behaviors as controller hysteresis and time delays. Experimental results bolster the performance of the proposed approach.
Paper VI142-13.5
PDF · Video · Lyapunov-Based Stability Analysis for Conveying Fluid Pipe with Nonlinear Energy Sink
Duan, Nan	Dalian University of Technology
Wu, Yuhu	Dalian University of Technology
Sun, Xi-Ming	Dalian University of Technology
Zhong, Chongquan	School of Electronics and Information Engineering Dalian Univers
Wang, Wei	Dalian University of Technology
Keywords: Vibration control, Modeling Abstract: This paper considers the stability of a conveying fluid pipe with nonlinear energy sink (NES), which is a passive vibration controller. Based on the Galerkin approximation method, the high-order partial differential equation (PDE) model of the conveying fluid pipe-NES system is converted into an ordinary differential equation (ODE) form. Then, based on the first order characterization of convexity and energy disturbances technique under the framework of Lyapunov stability theory, global exponential stability of the conveying fluid pipe-NES system is obtained.
Paper VI142-13.6
PDF · Video · Tip Tracking Control of a Linear-Motor-Driven Flexible Manipulator with Controllable Damping
Zhu, Xiaocong	Zhejiang University
Shen, Xinda	Zhejiang University
Wang, Linyuan	Zhejiang University
Cao, Jian	Hefei University of Technology
Keywords: Vibration control, Modeling, Mechatronic systems Abstract: In this paper, a linear-motor-driven flexible robotic manipulator with controllable damping is presented. The dynamic model of the flexible manipulator with magnetorheological(MR) dampers is established through analyzing the force constraint of controllable MR damping and the rigid-flexible coupling dynamics of entire system via Lagrange method and assumed mode method. A controller for the flexible manipulator with MR dampers is developed to realize the dual targets of vibration suppression and accurate tip tracking for the flexible manipulator. The controller integrated output redefine adaptive robust control based on the system dynamics with damping control law according to motion state of the flexible system. Simulation results verifies the effectiveness of the proposed control method.
Paper VI142-13.7
PDF · Video · Active Damping of Parallel Robots Driven by Elastic Cables Using On-Off Actuators through Model Predictive Control Allocation
Khayour, Imane	University of Strasbourg
Durand, Sylvain	INSA Strasbourg & ICube
Cuvillon, Loïc	ICUBE, Univesity of Strasbourg
Gangloff, Jacques	University of Strasbourg
Keywords: Vibration control, Robots manipulators, Modeling Abstract: This work studies the vibration rejection on elastic cable-driven parallel robots (CDPRs). Additional cold-gas thrusters are embedded on the robot in order to improve the rejection bandwidth. Such Unilateral Force Generators (UFGs) work as on-off actuators. Under the framework of optimal control, a Model Predictive Control (MPC) is designed to compute the control law and allocate the control signals to the available actuators by assigning their binary on-off states, thus forming a Mixed Integer Quadratic Programming (MIQP)-based MPC controller. Simulations highlight the benefits of the proposed predictive approach that yields a better rejection, fuel efficiency, and a reduced switching between ON and OFF states with respect to previous approaches.

VI143
Mechatronics, Robotics and Components - Robotics
VI143-01 System Theory for Soft Robotics   Invited Session, 5 papers
VI143-02 Adaptive Neural Networks and Their Applications   Open Invited Session, 5 papers
VI143-03 Mathematical Robotics   Open Invited Session, 9 papers
VI143-04 Flying Robots   Regular Session, 26 papers
VI143-05 Guidance, Navigation and Control in Robotics   Regular Session, 12 papers
VI143-06 Sensor Fusion for Robotics   Regular Session, 8 papers
VI143-07 Mobile Robots Planning, and Control   Regular Session, 30 papers
VI143-08 Robot Manipulators and Control   Regular Session, 37 papers
VI143-09 Robotic Technology   Regular Session, 8 papers
VI143-10 Telerobotics   Regular Session, 5 papers

VI143-01
System Theory for Soft Robotics	Invited Session
Chair: Ishikawa, Masato	Osaka University
Co-Chair: Takesue, Naoyuki	Tokyo Metropolitan University
Organizer: Mochiyama, Hiromi	University of Tukuba
Organizer: Ishikawa, Masato	Osaka University
Organizer: Masuda, Yoichi	Osaka University
Organizer: Takesue, Naoyuki	Tokyo Metropolitan University
Organizer: Yagi, Keisuke	Ibaraki University
Paper VI143-01.1
PDF · Video · On Brainless-Control Approach to Soft Bodies: A Novel Method to Generate Motion Patterns by Pneumatic Reflex Devices (I)
Masuda, Yoichi	Osaka University
Ishikawa, Masato	Osaka University
Keywords: Robotics technology, Mechatronics Abstract: Controlling soft robots is a challenging task, for it is embedded in a highly coupled system composed of elastic body, controller, and environment. The system is often unsteady, uncertain, and unpredictable, and it is even difficult to define clear boundaries among the body components and the environment. For generating periodic motion patterns of elastic bodies without determination of a detailed system model, we introduce a method called brainless control approach. In our previous study along this approach, we discovered an interesting phenomenon that a musculoskeletal quasi-quadruped robot emerges high-speed running motion without any electronic sensor or microprocessor. In other words, we did not equip it with any explicit controller; instead, we designed the mechanical ``reflex'' devices and embed them in the distal parts of the robot body. This result was surely suggestive, however, there still remain a lot of unsolved questions such as why and how the robot can self-organize its motion pattern between the joints and the limbs. In this paper, we investigate fundamental characteristics of this pneumatic reflex device, to establish a basis for further discussion concerning the self-organizing principle.
Paper VI143-01.2
PDF · Video · The Elastic Rod Approach Toward System Theory for Soft Robotics (I)
Mochiyama, Hiromi	University of Tsukuba
Keywords: Modeling, Identification and control methods, Design methodologies Abstract: In this paper, an approach toward system theory for soft robotics is considered. An overview of a theoretical scenario is presented by focusing on an elastic rod which is regarded as one of the most essential objects for soft mechanical elements of soft robots. The presented topics include geometry of its backbone curve, kinematics, shape, mechanics (mainly its statics), and discretization, with emphasizing on some important system properties of an elastic rod which will be useful for shape computation and stiffness identification.
Paper VI143-01.3
PDF · Video · Compact Swimming Robot with Continuum Water Jet Nozzle for Rapid Turns (I)
Sakai, Yusuke	University of Tsukuba
Takesue, Naoyuki	Tokyo Metropolitan University
Mochiyama, Hiromi	University of Tsukuba
Keywords: Mechatronics, Robotics technology Abstract: In this paper, a swimming robot capable of rapid turns not only horizontally but also vertically in an underwater environment is proposed. The robot utilizes a wire-driven continuum water jet nozzle, which can be oriented in an arbitrary direction and allows the robot to turn in a small radius. In this study, the deformation characteristics of the nozzle were first experimentally investigated, and the nozzle was then implemented in the robot. The performance of the robot was experimentally investigated in an underwater environment. The results indicated that it was capable of a high angular velocity, and could accomplish 180 degree turns within a tactical diameter that was smaller than its body length.
Paper VI143-01.4
PDF · Video · Evaluation of the Impulsive Force Induced by the Snap-Through Buckling of Closed-Elastica (I)
Yagi, Keisuke	Ibaraki University
Mori, Yoshikazu	Ibaraki University
Mochiyama, Hiromi	University of Tsukuba
Keywords: Mechatronics, Design methodologies, Robotics technology Abstract: The present study proposes the evaluation of the impulsive force induced by the snap-through buckling mechanism of closed-elastica in terms of the momentum. A cable-mass system with slackness is developed as a benchmark setup, where the snap-through buckling mechanism imposes the impulsive force on the mass through the wire. The recorded time response of the mass provides the momentum of the snap-through buckling according to the conservation law. Experiments are carried out with several kinds of mass parameters, and the impulsive force induced by the snap-through buckling is successfully evaluated in the proposed context.
Paper VI143-01.5
PDF · Video · Development of Streamline-Shaped Miniature Underwater Robot Propelled by Resonance of Elastic Body (I)
Takesue, Naoyuki	Tokyo Metropolitan University
Inaba, Ayumi	Tokyo Metropolitan University
Kobayashi, Yumi	Tokyo Metropolitan University
Mochiyama, Hiromi	University of Tsukuba
Keywords: Mechatronic systems, Mobile robots, field robotics Abstract: This paper proposes the streamline-shaped aquatic robot that is propelled by a vibrator and a resonance of elastic tail fin. The plastic head was fabricated by a 3D printer. The elastic tail peduncles were made of silicone rubber as elastic body. A radio control system, a vibrator and a battery were implemented to the robot. As a result, the robot successfully swam. Furthermore, the influences of glass bubbles mixture ratio, shape of the fins, with/without additional weight, position of vibrator to swimming performance were observed.

VI143-02
Adaptive Neural Networks and Their Applications	Open Invited Session
Chair: Ge, Shuzhi Sam	National University of Singapore
Co-Chair: Liang, Xiaoling	Dalian Maritime University
Organizer: Ge, Shuzhi Sam	National University of Singapore
Organizer: Liang, Xiaoling	Dalian Maritime University
Paper VI143-02.1
PDF · Video · Off-Policy Q-Learning for Anti-Interference Control of Multi-Player Systems (I)
Li, Jinna	Liaoning Shihua University
Xiao, Zhenfei	Liaoning Shihua University
Chai, TianYou	Northeastern University, Shenyang, China
Lewis, Frank L.	Univ of Texas at Arlington
Jagannathan, Sarangapani	Missouri University of Science and Technology
Keywords: Differential or dynamic games, Control problems under conflict and/or uncertainties Abstract: This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally they reach the Nash equilibrium of the game resulting in satisfying disturbance attenuation condition. In order to find the solution to the Nash equilibrium, the anti-interference control problem is first transformed into an optimal control problem. Then an off-policy Q-learning algorithm is proposed in the framework of typical adaptive dynamic programming (ADP) and game architecture, such that control policies of all players can be learned using only measured data. Comparative simulation results are provided to verify the effectiveness of the proposed method.
Paper VI143-02.2
PDF · Video · Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics (I)
Roehrl, Manuel	Technical University of Munich
Runkler, Thomas	Siemens AG
Brandstetter, Veronika	Siemens AG
Tokic, Michel	Siemens AG
Obermayer, Stefan	Siemens AG
Keywords: Machine learning, Grey box modelling, Modeling, Identification and control methods, Knowledge modelling and knowledge based systems Abstract: Identifying accurate dynamic models is required for the simulation and control of various technical systems. In many important real-world applications, however, the two main modeling approaches often fail to meet requirements: first principles methods suffer from high bias, whereas data-driven modeling tends to have high variance. Additionally, purely data-based models often require large amounts of data and are often difficult to interpret. In this paper, we present physics-informed neural ordinary differential equations (PINODE), a hybrid model that combines the two modeling techniques to overcome the aforementioned problems. This new approach directly incorporates the equations of motion originating from the Lagrange mechanics into a deep neural network structure. Thus, we can integrate prior physics knowledge where it is available and use function approximation-e. g., neural networks-where it is not. The method is tested with a forward model of a real-world physical system with large uncertainties. The resulting model is accurate and data-efficient while ensuring physical plausibility. With this, we demonstrate a method that beneficially merges physical insight with real data. Our findings are of interest for model-based control and system identification of mechanical systems.
Paper VI143-02.3
PDF · Video · Autonomous Reinforcement Control of Underwater Vehicles Based on Monocular Depth Vision (I)
Zhu, Pengli	Dalian Maritime University
Yao, Shuhan	Dalian Maritime University
Liu, Yancheng	Dalian Maritime University
Liu, Siyuan	Dalian Maritime University
Liang, Xiaoling	Dalian Maritime University
Keywords: Guidance navigation and control, Networked robotic system modeling and control, Perception and sensing Abstract: In this paper, a monocular depth prediction based end-to-end reinforcement control framework is proposed for autonomous control of underwater vehicles in the unknown environment. In the control framework, with the input of camera sensor RGB videos, a monocular depth prediction network is proposed to generate underwater depth images and a sequential reinforcement learning controller is also developed for autonomous obstacle-avoiding navigation and movement control. Simulated and experimental results demonstrate that the proposed control scheme can achieve remarkable performance on collision-avoidance navigation and autonomous control in the unknown environment.
Paper VI143-02.4
PDF · Video · Optimized Control for Human-Multi-Robot Collaboration Via Multi-Agent Adaptive Dynamic Programming (I)
Liu, Xing	Xi'an Jiaotong University
Ge, Shuzhi Sam	National University of Singapore
Keywords: Shared control, cooperation and degree of automation, Intelligent robotics, Autonomous robotic systems Abstract: In this paper we consider the problem of controlling the dynamic behavior of the robot agents while collaborating with the human worker. The presented dynamic behavior control method leads to achieving optimized interaction performance of the human-multi-robot collaboration system. We investigate in depth the dynamics equation of the robot agents collaborating with the human worker. Considering the unknown parameters in the system dynamics, the adaptive dynamic programming method is utilized to deal with the optimized interaction control problems during human-multi-robot collaboration process. To achieve the coordination of the multi robot agents, multi-agent adaptive dynamic programming method is employed in this paper. The neural networks with one hidden layer are utilized to approximate both the unknown system dynamics as well as the optimized cost function. The simulation studies verify the effectiveness of the presented algorithm.
Paper VI143-02.5
PDF · Video · Robust Adaptive Control of Voltage-Type MLS Based on Wavelet Neural Network (I)
Ma, Zhenwei	Qufu Normal University, College of Engineering
Zhang, Zhengqiang	Qufu Normal University
Cai, Xiu Shan	Zhejiang Normal Univ
Keywords: Identification and control methods Abstract: In this paper, a novel robust adaptive controller based on wavelet neural network is proposed for voltage-type magnetic levitation system with unknown control direction. First, coordinate transformation is used to simplify the model of the voltage-type magnetic levitation system. Second, the mean value theorem and Nussbaum function are used to deal with the problem of the implicit control input of nonlinear function and unknown control direction, the approximation to the unknown nonlinear function is realized by wavelet neural network. Finally, all the signals of the closed loop system are bounded according to Lyapunov function method.

VI143-03
Mathematical Robotics	Open Invited Session
Chair: Robertsson, Anders	LTH, Lund University
Co-Chair: Matveev, Alexey S.	St.Petersburg Univ
Organizer: Matveev, Alexey S.	St.Petersburg Univ
Organizer: Shiriaev, Anton	NTNU
Organizer: Robertsson, Anders	LTH, Lund University
Organizer: Fradkov, Alexander L.	Russian Academy of Sciences
Organizer: Chemori, Ahmed	UM2
Paper VI143-03.1
PDF · Video · Temporally Coupled Dynamical Movement Primitives in Cartesian Space (I)
Karlsson, Martin	Lund University
Robertsson, Anders	LTH, Lund University
Johansson, Rolf	Lund University
Keywords: Robotics technology, Shared control, cooperation and degree of automation, Autonomous robotic systems Abstract: Control of robot orientation in Cartesian space implicates some difficulties, because the rotation group SO(3) is not contractible, and only globally contractible state spaces support continuous and globally asymptotically stable feedback control systems. In this paper, unit quaternions are used to represent orientations, and it is first shown that the unit quaternion set minus one single point is contractible. This is used to design a control system for temporally coupled dynamical movement primitives (DMPs) in Cartesian space. The functionality of the control system is verified experimentally on an industrial robot.
Paper VI143-03.2
PDF · Video · Oscillation Control in the Underactuated "Ball and Beam" System (I)
Tsarik, Vladimir	Saint-Petersburg State University
Keywords: Motion Control Systems, Identification and control methods, Modeling Abstract: The problem of oscillatory motion construction and stabilization for the underactuated "Ball and Beam" system is considered. Virtual holonomic constraints approach is used. System's dynamics equations are derived, their transverse linearization is implemented, the controllability is proven, the stabilization algorithm is constructed. Obtained results are confirmed with computer simulation.
Paper VI143-03.3
PDF · Video · Cascaded Constrained Optimization for Cheetah-Inspired Galloping Robot Leg Mechanism (I)
Egorov, Artem	ITMO University
Borisov, Ivan	ITMO University
Kolyubin, Sergey	ITMO University
Stramigioli, Stefano	University of Twente
Keywords: Design methodologies, Modeling, Mobile robots Abstract: The paper describes one of the key steps in creating a bio-inspired galloping robot, namely parametric optimization of a multi-link leg mechanism. We introduce the cascaded constrained optimization procedure for finding optimal values for geometric parameters of a femur, knee, and foot segments for given design constraints and various gait specifications. The presented approach is computationally efficient and guarantees convergence to the unique solution. Steps on free parameters, constraints, and cost function selection are discussed. The efficiency of the proposed procedure is illustrated via a series of simulations. The proposed approach can also be implemented for the design of wearable robots like upper- and lower-limb exoskeletons and rehabilitation systems that should follow sometimes sophisticated human-like trajectories.
Paper VI143-03.4
PDF · Video · Dynamic Modeling of Hyper-Elastic Soft Robots Using Spatial Curves (I)
Caasenbrood, Brandon	Eindhoven University of Technology
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Nijmeijer, Hendrik	Eindhoven Univ of Technology
Keywords: Modeling, Robots manipulators, Robotics technology Abstract: Soft robots differ fundamentally from traditional robotics by their mechanical composition of hyperelastic materials. Due to their mechanical composition, soft robots are inherently compliant and they can perform large continuum-bodied motion. This paper provides a systematic framework to model the nonlinear dynamics of a soft robot using differential geometry of spatial curves. Although some frameworks exist for describing the kinematics, the development of dynamic models intended for control-oriented applications is relatively scarce and to some extent underdeveloped. Current literature often neglects the nonlinear and time-variant mechanical nature imposed by these hyperelastic materials. Numerical simulations of the proposed dynamic modeling approach are presented for a study case soft robot, and the model is experimentally validated. Furthermore, this framework is applicable to other soft robotic systems undergoing similar hyper-flexible and continuum-bodied motion.
Paper VI143-03.5
PDF · Video · Cooperative Decentralized Reactive Circumnavigation of Unpredictably Moving and Deforming Speedy Extended Objects (I)
Matveev, Alexey S.	St.Petersburg Univ
Magerkin, Valentin	Saint Petersburg State University
Keywords: Mobile robots, Intelligent robotics, Guidance navigation and control Abstract: A team of speed- and acceleration-limited robots travel in a plane that hosts an unpredictably moving and deforming extended targeted object. In its local frame, every robot has access to its own velocity and is able to identify the relative coordinates of the objects within a given finite visibility range, as well as the nearest point of the object. A sliding mode communication-free sensor-based strategy is presented that drives the robots to a desired distance from the targeted object and ensures its subsequent circumnavigation with maintaining this distance and effective self-distribution around the object. The proposed control law individually operates at any robot and is reactive, i.e., it directly converts the current sensory data into the current control in a reflex-like fashion. The performance of the proposed navigation law is rigorously justified by a global convergence result and is confirmed via computer simulation tests.
Paper VI143-03.6
PDF · Video · On Excessive Transverse Coordinates for Orbital Stabilization of Periodic Motions (I)
Sætre, Christian Fredrik	NTNU
Shiriaev, Anton	NTNU
Keywords: Motion Control Systems, Identification and control methods, Robotics technology Abstract: This paper explores transverse coordinates for the purpose of orbitally stabilizing periodic motions of nonlinear control-affine dynamical systems. It is shown that the dynamics of any (minimal or excessive) set of transverse coordinates, which are defined in terms of a particular parameterization of the motion and a state-dependent projection operator recovering the parameterizing variable, admits a (transverse) linearization along the target motion, with explicit expressions stated. Special focus is then placed on a generic excessive set of orthogonal coordinates, revealing a certain limitation of the "excessive" transverse linearization for the purpose of control design. To overcome this limitation, a linear comparison system is introduced and conditions are stated for when the asymptotic stability of its origin corresponds to the asymptotic stability of the origin of linearized transverse dynamics. This allows for the construction of feedback controllers utilizing this comparison system which, when implemented on the dynamical system, renders the desired motion asymptotically stable in the orbital sense.
Paper VI143-03.7
PDF · Video · Gradient-Free Tracking of Unsteady Environmental Level Sets in Dynamic Environments by a Nonholonomic Robot (I)
Matveev, Alexey S.	St.Petersburg Univ
Kapitonov, Aleksandr	ITMO University
Berman, Ivan	ITMO University
Chernov, Valerii	ITMO University
Keywords: Guidance navigation and control, Mobile robots, Autonomous robotic systems Abstract: A non-holonomic under-actuated planar robot is propelled via interaction of its actuators with a dynamic surrounding medium; a control input is the angular velocity of robot's self-rotation relative to the medium. Meanwhile, the motion of the medium is unknown and unpredictable; the relative surge speed is time-varying and treated as uncertain. There is an unpredictably varying scalar environmental field. From a remote initial location, the robot should reach the isoline where the field assumes a pre-specified value, and then should repeatedly run its length. Robot measures only the field value at the current location and has no access to the field gradient or parameters of the medium motion. To solve this task, at first conditions are established that are necessary for the mission to be feasible with the given limitations on the robot's dynamics. Then a navigation law is presented that solves the mission under slight and partly unavoidable enhancement of these conditions. This law is computationally inexpensive and directly converts the current sensory data into the current control in a reflex-like fashion. The performance of the law is rigorously justified by a global convergence result and is confirmed via computer simulation tests.
Paper VI143-03.8
PDF · Video · Underactuated Mechanical Systems: Whether Orbital Stabilization Is an Adequate Assignment for a Controller Design? (I)
Mamedov, Shamil	Innopolis University
Khusainov, Ramil	Innopolis University
Gusev, Sergei V.	St. Petersburg State Univ
Klimchik, Alexandr	Innopolis University
Maloletov, Alexander	Innopolis University
Shiriaev, Anton	NTNU
Keywords: Motion Control Systems, Mechatronics Abstract: The paper contributes to developing algorithms for motion planning and motion control for mechanical systems with two and more passive degrees of freedom by exploring a challenging example in details. As shown, some of arguments of motion planning methods developed for systems of underactuation degree one can be generalized for novel demanding settings, while corresponding arguments and concepts for controller design should be substantially reconsidered and updated. Rigorous theoretical results are well supported by numerical studies.
Paper VI143-03.9
PDF · Video · Sensorless Control of Permanent Magnet Synchronous Motors Based on Finite-Time Robust Flux Observer (I)
Pyrkin, Anton	ITMO University
Bobtsov, Alexey	ITMO University
Ortega, Romeo	Supelec
Vedyakov, Alexey	ITMO University
Cherginets, Dmitry	ITMO University
Bazylev, Dmitry	ITMO University
Petranevsky, Igor	ITMO University
Keywords: Observer design Abstract: A sensorless control algorithm is developed based on novel finite-time robust flux observer for the non-salient permanent magnet synchronous motor (PMSM). Total flux equality and motor model are used to find the linear regression-like model with respect to the flux. Applying dynamic regressor extension and mixing method, we obtain two independent scalar equations and construct a finite-time flux observer. The flux estimate is used to reconstruct the rotor position and velocity with well-known trigonometric relation and phase-locked loop observer, respectively. To complete a sensorless control design, we pass these estimates to standard field orient control. The efficiency and robustness of the proposed approach are demonstrated through the set of numerical simulations.

VI143-04
Flying Robots	Regular Session
Chair: Cenedese, Angelo	University of Padova
Co-Chair: Schoellig, Angela P.	University of Toronto
Paper VI143-04.1
PDF · Video · Real-Time Trajectory Generation for Multiple Drones Using Bezier Curves
Sabetghadam, Bahareh	Institute Superior Tecnico
Cunha, Rita	Instituto Superior Técnico, Universidade De Lisboa
Pascoal, Antonio M.	Instituto Superior Técnico (IST-ID) VAT 509830072
Keywords: Autonomous robotic systems, Guidance navigation and control, Flying robots Abstract: Practical applications of drones are expanding into many new areas due to their fast-evolving technology. Looking further into the future, it is very likely that applications will require more than one drone to tackle a specific task, calling for reliable and efficient algorithms that can generate collision-free trajectories for multiple drones, under timing constraints of real-time applications. In this paper, we study a motion planning method based on the B'ezier parametrization of spatial paths with a special focus on the less addressed issue in this method, (inefficient) constraint evaluation, that might hinder its use in real-time trajectory generation for multi-drone applications. We take advantage of the Bezier curves properties to obtain a small-scale optimization problem and find a finite set of inequalities that guarantee constraints satisfaction. We also propose a method to lower the conservatism in the resulting set of inequalities without the need to use unnecessary high-degree B'ezier curves. Numerical results illustrate the efficacy of the presented method in reducing the computational costs associated with generating collision-free trajectories for multiple drones and re-planning them online with a receding horizon.
Paper VI143-04.2
PDF · Video · Reachability As a Unifying Framework for Computing Helicopter Safe Operating Conditions and Autonomous Emergency Landing
Kirchner, Matthew	University of California, Santa Barbara
Ball, Eddie	NAVAIR
Hoffler, Jacques	NAVAIR
Gaublomme, Donald	NAVAIR
Keywords: Autonomous robotic systems, Guidance navigation and control, Flying robots Abstract: We present a numeric method to compute the safe operating flight conditions for a helicopter such that we can ensure a safe landing in the event of a partial or total engine failure. The unsafe operating region is the complement of the backwards reachable tube, which can be found as the sub-zero level set of the viscosity solution of a Hamilton-Jacobi (HJ) equation. Traditionally, numerical methods used to solve the HJ equation rely on a discrete grid of the solution space and exhibit exponential scaling with dimension, which is problematic for the high-fidelity dynamics models required for accurate helicopter modeling. We avoid the use of spatial grids by formulating a trajectory optimization problem, where the solution at each initial condition can be computed in a computationally efficient manner. The proposed method is shown to compute an autonomous landing trajectory from any operating condition, even in non-cruise flight conditions.
Paper VI143-04.3
PDF · Video · Vision-Driven NMPC for Autonomous Aerial Navigation in Subterranean Environments
Kanellakis, Christoforos	Luleå University of Technology
Karvelis, Petros	Technological Educational Institute of Epirus
Sharif Mansouri, Sina	Luleå University of Technology
Agha-mohammadi, Ali-akbar	NASA-JPL, Caltech
Nikolakopoulos, George	Luleå University of Technology
Keywords: field robotics, Flying robots, Autonomous robotic systems Abstract: This work establishes a novel robocentric Non-linear Model Predictive Control (NMPC) framework for fast fully autonomous navigation of quadrotors in featureless dark tunnel environments. Additionally, this work leverages the processing of a single camera to generate direction commands along the tunnel axis, while regulating the platform's altitude. The extracted visual dynamics are coupled in the sequel with the NMPC problem, structured around the Proximal Averaged Newton-type method for Optimal Control (PANOC), which is a fast numerical optimization method that is not sensitive to ill conditioning and is suitable for embedded NMPC implementations. Multiple fully realistic simulation results demonstrate the effectiveness of the proposed method in challenging environments.
Paper VI143-04.4
PDF · Video · The Reconfigurable Aerial Robotic Chain: Shape and Motion Planning
Kulkarni, Mihir	Birla Institute of Technology and Science (BITS) Pilani
Dinh Huan, Nguyen	University of Nevada-Reno
Alexis, Konstantinos	University of Nevada, Reno
Keywords: Flying robots Abstract: This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that simultaneously presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potential of distributed sensing and processing, and allow system extendability. We contribute an approach to address the motion planning problem of such a connected robotic system of systems, making full use of its reconfigurable nature, to find collision free paths in a fast manner despite the increased number of degrees of freedom. The presented approach exploits a library of aerial robotic chain configurations, optimized either for cross-section size or sensor coverage, alongside a probabilistic strategy to sample random shape configurations that may be needed to facilitate continued collision-free navigation. Evaluation studies in simulation involve traversal of constrained and obstacle-laden environments, having narrow corridors and cross sections.
Paper VI143-04.5
PDF · Video · Collision Avoidance for Multiple Micro Aerial Vehicles Using Fast Centralized Nonlinear Model Predictive Control
Lindqvist, Björn	Luleå University of Technology
Sharif Mansouri, Sina	Luleå University of Technology
Sopasakis, Pantelis	Queen’s University Belfast
Nikolakopoulos, George	Luleå University of Technology
Keywords: Flying robots Abstract: This article proposes a novel control architecture using a centralized nonlinear model predictive control (CNMPC) scheme for controlling multiple micro aerial vehicles (MAVs). The control architecture uses an augmented state system to control multiple agents and performs both obstacle and collision avoidance. The optimization algorithm used is OpEn, based on the proximal averaged Newton type method for optimal control (PANOC) which provides fast convergence for non-convex optimization problems. The objective is to perform position reference tracking for each individual agent, while nonlinear constrains guarantee collision avoidance and smooth control signals. To produce a trajectory that satisfies all constraints a penalty method is applied to the nonlinear constraints. The efficacy of this proposed novel control scheme is successfully demonstrated through simulation results and comparisons, in terms of computation time and constraint violations, are provided with respect to the number of agents.
Paper VI143-04.6
PDF · Video · Approximated Constrained Optimal Control Subject to Variable Parameters
Kallies, Christian	Otto-von-Guericke-Universität Magdeburg
Ibrahim, Mohamed	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Flying robots, Autonomous robotic systems, Embedded robotics Abstract: Implementing optimal controllers on embedded systems can be challenging as it requires the solution of an optimization problem in real-time. Furthermore, the a priory verification of stability, e.g. not relying on the possibly numerical solution of an optimization problem is often not possible. We propose a non-linear control synthesis based on an approximated explicit solution of a constrained optimal control problem, which can be efficiently implemented and verified. The control law is derived based on a series expansion of an infinite horizon optimal control problem via Al'brekht's Method. In comparison to existing approaches we consider parametric uncertainties. The proposed method provides under certain conditions an approximated solution of the Hamilton–Jacobi–Bellman (HJB) equation. The feedback control law uses a finite number of terms of the series expansion, and therefore the evaluation does not require intensive online computation. Furthermore, the optimal control strategy does not only achieve an approximated infinite horizon performance but is also parameterized in terms of the varying parameters which are assumed to be known. We provide a proof of convergence and existence of the optimal control law. Simulation results with a non-linear quadcopter example show the effectiveness of the proposed strategy.
Paper VI143-04.7
PDF · Video · Dual Quaternion Delay Compensating Maneuver Regulation for Fully Actuated UAVs
Michieletto, Giulia	University of Padova
Lissandrini, Nicola	University of Padova
Antonello, Andrea	University of Padova
Antonello, Riccardo	University of Padova
Cenedese, Angelo	University of Padova
Keywords: Flying robots, Autonomous robotic systems, Guidance navigation and control Abstract: In aerial robotics, path following constitutes a popular task requiring a vehicle to pursue a given trajectory. Resting upon the fulfillment of a desired time law, trajectory tracking techniques often turn out to be ineffective in presence of external disturbances, favoring the adoption of maneuver regulation strategies wherein the desired trajectory is parameterized in terms of the path-variable. In this scenario, this work proposes a new delay-compensating maneuver regulation controller for fully actuated aerial vehicles, whose aim is to guarantee the perfect tracking of a given path in the shortest time interval. The innovative aspect of such a solution relies on the introduction of a recovery term that compensates for possible delays in the task execution. The dual-quaternion formalism is adopted to model the dynamics of the aerial platforms allowing feedback linearization of the whole system, including both position and attitude, with a single controller. The tests conducted in Gazebo physics simulator show that the proposed controller outperforms the popular trajectory tracking PID regulators.
Paper VI143-04.8
PDF · Video · Redundant Disturbance Rejection Controller Applied to Quadrotors for 3D Trajectory Tracking
Bouzid, Yasser	CSCS Laboratory, Ecole Militaire Polytechnique
Siguerdidjane, Houria	CentraleSupelec
Guiatni, Mohamed	CSCS Laboratory, Ecole Militaire Polytechnique, Bordj El Bahri
Zareb, Mehdi	Electronic Department, University of Science and Technology, B.P
Lamraoui, Habib Choukri	Harbin Engineering University
Keywords: Flying robots, Autonomous robotic systems, Guidance navigation and control Abstract: The objective is to develop a control algorithm for quadrotors that guarantees a good compromise robustness/performance in presence of external disturbances. Thus, we investigate and apply a nominal model-based control strategy doted by a robustness boosting mechanism. This latter, uses an Extended State-based Observer (ESO) to estimate the uncertainties and the various disturbances. The obtained controller is augmented by an additional input, which is derived via a sliding modes framework to handle the estimation errors and ensure asymptotic stability. The primary results are shown through numerical simulations.
Paper VI143-04.9
PDF · Video · Nonlinear Model Predictive Control for the Landing of a Quadrotor on a Marine Surface Vehicle
Gillini, Giuseppe	University of Cassino and Southern Lazio
Arrichiello, Filippo	Univ of Cassino and Southern Lazio
Keywords: Flying robots, Autonomous robotic systems, Mobile robots Abstract: The paper addresses the design of a control strategy for a quadrotor autonomous aerial vehicle to land on a target marine surface vehicle. In particular, a Nonlinear Model Predictive Control law that takes into account the marine vehicle trajectory and the sea state has been designed to let the quadrotor land on the target vehicle when this reaches a wave peak. The sea state has been modeled using monochromatic sinusoidal waves, and the maximum wave height and period are taken into account by the quadrotor control law to compute the position and the timing of the next vertical peak in the target vehicle trajectory. The results of numerical simulations performed in ROS/Gazebo environment are shown to validate the control strategy effectiveness.
Paper VI143-04.10
PDF · Video · Development and Design Optimization of 2Y Hexarotor with Robustness against Rotor Failure
Mochida, Shunsuke	Tokyo Institute of Technology
Matsuda, Remma	Panasonic Mobile Communications
Ibuki, Tatsuya	Tokyo Institute of Technology
Sampei, Mitsuji	Tokyo Inst. of Tech
Keywords: Flying robots, Design methodologies, Mobile robots Abstract: This paper presents a novel hexarotor unmanned aerial vehicle (UAV) with robustness against an arbitrary rotor-failure, called full robustness, and a design method to maximize its manipulability while ensuring the full robustness. First, the dynamical model of a hexarotor UAV and the novel structure with 2Y shape and twisted angles are presented. A hexarotor with this structure is named as 2Y hexarotor. The 2Y hexarotor has higher flight efficiency than other existing hexarotor structures with full robustness. Second, the full robustness of the 2Y hexarotor is proved, and a quantitative measure to evaluate the full robustness is introduced. Then, the quantitative measure for the full robustness is used to calculate the optimal twisted angles. Finally, the dynamic manipulability measure (DMM) is introduced to evaluate the maneuverability. A design method is defined as the maximization of the DMM under constraints regarding the quantitative measure for the full robustness and the condition to avoid overlapping rotors. The design method is applied to the 2Y hexarotor with the optimal twisted angles.
Paper VI143-04.11
PDF · Video · Universal Adaptive Fault-Tolerant Control of a Multicopter UAV
Nguyen, Duc Tien	Polytechnique Montréal
Saussie, David Alexandre	Polytechnique Montréal
Saydy, Lahcen	Ecole Polytechnique of Montreal
Keywords: Flying robots, Guidance navigation and control Abstract: This paper presents a universal adaptive fault-tolerant control (FTC) design for multicopter unmanned aerial vehicles (UAVs). The proposed architecture consists of a two-loop control structure: a fault-tolerant controller generates normalized virtual control inputs to track the desired trajectory subject to actuator faults, and an adaptive augmentation controller deals with system uncertainties and also balances the design requirements for specific platform. The FTC approach is based on gain-scheduling control in the framework of structured H-infinity synthesis. In order to implement the overall control system on most types of multicopter UAVs, an adaptive mapping algorithm is proposed. High fidelity simulations and experimental results, performed on various multicopters with different payload and configuration, show the effectiveness and robustness of the proposed approach in accommodating different levels of actuator degradation including total failures of the rotors as well as unknown mass and inertia, all using a single controller with fixed coefficients.
Paper VI143-04.12
PDF · Video · Leadership Hierarchy-Based Formation Control Via Adaptive Chaotic Pigeon-Inspired Optimization
Zhao, Jianxia	Beihang University
Duan, Haibin	Beihang University(formerly Beijing University of Aeronautics An
Chen, Lin	Beihang University
Huo, Mengzhen	Beihang University
Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems Abstract: Formation control of multi-agent systems (MASs) is a significant research subject in the field of cooperative control. In this paper, we propose a novel consensus-based formation control approach with minimal resource cost and excellent adaptability for second-order nonlinear multi-agent systems. Specifically, an improved constrained adaptive chaotic pigeon-inspired optimization algorithm (ACPIO) is proposed for tuning parameters, which promotes the automation of controller design and alleviates the workload of conventional designer. Moreover, a variant of pinning control method integrating with hierarchical leadership model of pigeon flocks is introduced, which achieves excellent adaptability and reduces computational complexity simultaneously. Additionally, sufficient conditions are derived for achieving the desired formation pattern based on Lyapunov stability theory and matrix theory. Numerical simulation results demonstrate the feasibility and effectiveness of the proposed method for formation control of second-order nonlinear MASs.
Paper VI143-04.13
PDF · Video · Cylindrical Bounded Quaternion Control for Tracking and Surrounding a Ground Target Using UAVs
Abaunza, Hernan	Sorbonne Universites, Universite De Technologie De Compiegne
Castillo, Pedro	Universite De Technologie De Compiegne
Theilliol, Didier	University of Lorraine
Belkadi, Adel	Université De Lorraine
Ciarletta, Laurent	Mines Nancy, Universite De Lorraine
Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems Abstract: A cooperative tracking algorithm for multiple quadrotors autonomously tracking and surrounding a target ground vehicle is presented in this paper. A nonlinear bounded controller is proposed using geometrical functions to stabilize the translational and rotational dynamics using bounded 3-dimensional control inputs, employing quaternion properties and operators in its design, Lyapunov theory is used to prove system stability. The navigation challenge is tackled by proposing a cost function based on the desired behavior of the aerial vehicles for tracking and surrounding the target, which is solved by finding the optimal solution with a Particle Swarm Optimization algorithm. Simulations and experimental results corroborate the good performance of the scheme.
Paper VI143-04.14
PDF · Video · Attitude Stabilization of Quadrotor with Input Time Delay
Sharma, Manmohan	Indian Institute of Technology Guwahati
Kar, Indrani	Indian Institute of Technology, Guwahati
Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems Abstract: A predictor feedback control for attitude stabilization of quadrotors with input time delay has been proposed in this paper by representing the attitude using rotation matrices to avoid the singularities and ambiguities associated with Euler angles and quaternions. The closed loop system is shown to be asymptotically stable with respect to a norm defined in the text. The norm has been defined in terms of states and past control efforts and hence explicitly results in Lyapunov Krasovskii functional for the system. A cascade of PDE-ODE system and the concept of transport delay has been used in the proof.
Paper VI143-04.15
PDF · Video · Robust Global Tracking Control for a Quadrotor Based on Uncertainty and Disturbance Estimator
Lu, Qi	Sichuan University
Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems Abstract: In this paper, an uncertainty and disturbance estimator (UDE)-based robust global tracking control strategy for a quadrotor is presented. Utilizing the quaternion framework, the attitude and position controllers are developed to achieve the global singularity-free and computational efficient quadrotor control while the UDE is adopted to deal with model uncertainties and external disturbances. In order to handle the highly nonlinear quaternion-based quadrotor dynamics, the backstepping technique is utilized for the attitude controller derivation. The thrust-vectoring approach is employed for the position controller derivation. The effectiveness of the proposed approach is demonstrated using the attitude recovery experiment with large angle initial conditions.
Paper VI143-04.16
PDF · Video · A Nonlinear Control Design Strategy for Piloting Fixed Wing Aircrafts
Hamissi, Aicha	Polytechnic Military School
Busawon, Krishna K.	Northumbria University
Bouzid, Yasser	CSCS Laboratory, Ecole Militaire Polytechnique
Zaouche, Mohammed	Automatic Control Laboratory EMP, 16000, Algeria
Hamerlain, Mustapha	CDTA
Melkou, Lamia	Centre De Développement Des Technologies Avancées
Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems Abstract: This paper proposes a novel nonlinear feedback control strategy for velocity and attitude control of fixed wing aircrafts. The key feature of the control design strategy is the introduction of a virtual control input in order to deal with the underactuation property of such vehicles and to indirectly control the orientation of the aircraft. As such, the proposed strategy consists of three control loops each realising a specific task. Simulation results on Jetstream-3102 aircraft show very good performance in terms of convergence towards the desired reference trajectories and in terms of robustness with respect to modeling uncertainties.
Paper VI143-04.17
PDF · Video · Barrier-Lyapunov Function Based Dynamic Surface Control of Quad-Rotorcraft
Dasgupta, Ranjan	Tata Consultancy Services Ltd
Roy, Sayan Basu	Indraprastha Institute of Information Technology Delhi
Bhasin, Shubhendu	Indian Institute of Technology Delhi
Keywords: Flying robots, Guidance navigation and control, Motion Control Systems Abstract: A novel framework is proposed in this paper for control of a quad-rotorcraft where hierarchical design is constructed via barrier Lyapunov function (BLF) combined with dynamic surface control (DSC). DSC solves the requirement of higher order differentiability of reference pose and avoiding the complexity that arises due to the "explosion of terms" coming out from repeated derivatives of reference attitude and desired thrust vector. BLF satisfies attitude constraint in real-time and thereby ensures non-singularity of velocity transformation leading to feasible control design. Stability analysis shows that all the signals in the closed-loop system are uniformly ultimately bounded and tracking error converges asymptotically. The performance of the BLF-based DSC is illustrated with a suitable example.
Paper VI143-04.18
PDF · Video · Least Conservative Linearized Constraint Formulation for Real-Time Motion Generation
Barros Carlos, Barbara	Sapienza, Università Di Roma
Sartor, Tommaso	University of Freiburg
Zanelli, Andrea	University of Freiburg
Diehl, Moritz	University of Freiburg
Oriolo, Giuseppe	Sapienza University of Rome
Keywords: Flying robots, Guidance navigation and control, Motion Control Systems Abstract: Today robotics has shown many successful strategies to solve several navigation problems. However, moving into a dynamic environment is still a challenging task. This paper presents a novel method for motion generation in dynamic environments based on real-time nonlinear model predictive control (NMPC). At the core of our approach is a least conservative linearized constraint formulation built upon the real-time iteration (RTI) scheme with Gauss-Newton Hessian approximation. We demonstrate that the proposed constraint formulation is less conservative for planners based on Newton-type method than for those based on a fully converged NMPC method. Additionally, we show the performance of our approach in simulation, in a scenario where the Crazyflie nanoquadcopter avoids balls and reaches its desired goal in spite of the uncertainty about when the balls will be thrown. The numerical results validate our theoretical findings and illustrate the computational efficiency of the proposed scheme.
Paper VI143-04.19
PDF · Video · Flight Control of Flapping-Wing Robot with Three Paired Direct-Driven Piezoelectric Actuators
Jimbo, Tomohiko	Toyota Central R&D Labs., Inc
Ozaki, Takashi	Toyota Central R&D Labs
Amano, Yasushi	Toyota Central R&D Labs. INC
Fujimoto, Kenji	Kyoto University
Keywords: Flying robots, Micro and Nano Mechatronic Systems, Mobile robots Abstract: To realize safe mobile sensing in spaces around people, a flapping-wing robot with a weight of 1.15 g, wingspan of 115 mm, and three paired actuators is designed and fabricated in this study. The paired-wing actuators enable the suppression of wing-body and wing-wing coupling vibrations, as well as enhance the lift force. A model-based design of a stable flight controller was considered, where the lift force was assumed to work at an acting point on spatio-temporal average. Furthermore, an adaptive control law was employed for parameters that could not be measured. The effectiveness of the proposed controller was demonstrated through flight experiments.
Paper VI143-04.20
PDF · Video · The Problem of Reliable Design of Vector-Field Path Following in the Presence of Uncertain Course Dynamics (I)
Wang, Ximan	TU Delft
Roy, Spandan	Delft University of Technology (TU Delft)
Farì, Stefano	German Aerospace Center (DLR)
Baldi, Simone	Delft University of Technology
Keywords: Guidance navigation and control, Flying robots, Autonomous robotic systems Abstract: Reliable guidance of fixed-wing Unmanned Aerial Vehicles (UAVs) is challenging, as their high maneuverability exposes them to several dynamical changes and parametric uncertainties. Reliability of state-of-the-art guidance methods is often at stake, as these methods heavily rely on precise UAV course dynamics, assumed in a decoupled first-order form with known time constant. To improve reliability of guidance for fixed-wing UAVs, this work proposes a novel vector field law that can handle uncertain course time constant and state-dependent uncertainty in the course dynamics arising from coupling. Stability is studied in the Lyapunov framework, while reliability of the proposed method is tested on a software-in-the loop UAV simulator. The simulations show that, in the presence of such uncertainty, the proposed method outperforms the standard vector field approaches.
Paper VI143-04.21
PDF · Video · Sequence-Constrained Trajectory Planning and Execution for a Quadrotor UAV with Suspended Payload
Ubbink, Johan Bernard	Stellenbosch University
Engelbrecht, Jacobus Adriaan Albertus	Stellenbosch University
Keywords: Guidance navigation and control, Flying robots, Autonomous robotic systems Abstract: The paper presents the design of a trajectory planner and feedback control system to autonomously navigate a quadrotor UAV with a suspended payload through a confined environment consisting of horizontal and vertical tunnels. The trajectory planning task is formulated as an optimal control problem and is solved by applying an A* search algorithm. A novel sequence-constrained action space is implemented to encourage the use of input shaping actions, which is an open-loop control technique for reducing vibrations in a response. To execute the planned trajectory, a trajectory regulator is designed to work in conjunction with the trajectory planner. The trajectory regulator uses feedback control to provide disturbance rejection and robustness to parameter uncertainty. The planning and execution is verified in simulation, using a system that is constrained to two dimensions. The trajectory planner successfully plans a collision-free path for the quadrotor with suspended payload through an environment with obstacles, tunnels and vertical chimneys. The regulator successfully controls the quadrotor with suspended payload to follow the planned trajectory through the environment in the presence of external wind disturbances.
Paper VI143-04.22
PDF · Video · A Perception-Aware Flatness-Based Model Predictive Controller for Fast Vision-Based Multirotor Flight
Greeff, Melissa	University of Toronto
Barfoot, Tim	University of Toronto
Schoellig, Angela P.	University of Toronto
Keywords: Perception and sensing, Flying robots, Autonomous robotic systems Abstract: Despite the push toward fast, reliable vision-based multirotor flight, most vision-based navigation systems still rely on controllers that are perception-agnostic. Given that these controllers ignore their effect on the system's localisation capabilities, they can produce an action that allows vision-based localisation (and consequently navigation) to fail. In this paper, we present a perception-aware flatness-based model predictive controller (MPC) that accounts for its effect on visual localisation. To achieve perception awareness, we first develop a simple geometric model that uses over 12 km of flight data from two different environments (urban and rural) to associate visual landmarks with a probability of being successfully matched. In order to ensure localisation, we integrate this model as a chance constraint in our MPC such that we are probabilistically guaranteed that the number of successfully matched visual landmarks exceeds a minimum threshold. We show how to simplify the chance constraint to a nonlinear, deterministic constraint on the position of the multirotor. With desired speeds of 10 m/s, we demonstrate in simulation (based on real-world perception data) how our proposed perception-aware MPC is able to achieve faster flight while guaranteeing localisation compared to similar perception-agnostic controllers. We illustrate how our perception-aware MPC adapts the path constraint along the path based on the perception model by accounting for camera orientation, path error and location of the visual landmarks. The result is that repeating the same geometric path but with the camera facing in opposite directions can lead to different optimal paths flown.
Paper VI143-04.23
PDF · Video · Stereo Visual-Inertial Fusion for UAV State Estimation
Zhu, Jinyao	Technische Universität Dresden
Yao, Chao	Technische Universität Dresden
Janschek, Klaus	Technische Universität Dresden
Keywords: Information and sensor fusion, Perception and sensing, Flying robots Abstract: Visual-inertial fusion is frequently used for state estimation in aerial robotic applications due to the low-cost, simple hardware setup as well as the high accuracy. This work proposes a stereo visual-inertial fusion system based on the monocular method VINS-Mono, which tightly combines the visual and inertial measurements. Timing statistics are provided for the system running on an Intel NUC Mini-PC. The system real-time capability fulfills the requirements of the closed-loop control for a UAV. The proposed fusion system is evaluated in the public EuRoC MAV dataset and compared with several representative state-of-the-art open-sourced state estimators. According to the results, our method achieves competitive performance with relative low estimation errors in a computationally efficient manner.
Paper VI143-04.24
PDF · Video · LiDAR-Based Navigation of Tethered Drone Formations in an Unknown Environment
Bolognini, Michele	Politecnico Di Milano
Fagiano, Lorenzo	Politecnico Di Milano
Keywords: Autonomous Vehicles, Robot Navigation, Programming and Vision, Networks of robots and intelligent sensors Abstract: The problem of navigating a formation of interconnected tethered drones, named STEM (System of TEthered Multicopters), in an unknown environment is considered. The tethers feed electrical power from a ground station to the drones and also serve as communication links. The presence of more than one interconnected drone provides enough degrees of freedom to navigate in a cluttered area. The leader drone in the formation must reach a given point of interest, while the followers must move accordingly, avoiding interference with the obstacles. The challenges are the uncertainty in the environment, with obstacles of unknown shape and position, the use of LiDAR (Light Detection And Ranging) sensors, providing only partial information of the surroundings of each drone, and the presence of the tethers, which must not impact with the obstacles and pose additional constraints to how the drones can move. To cope with these problems, a novel real-time planning algorithm based on numerical optimization is proposed: the reference position of each drone is chosen in a centralized way via a convex program, where the LiDAR scans are used to approximate the free space and the drones are moved towards suitably defined intermediate goals in order to eventually reach the point of interest. The approach is successfully tested in numerical simulations with a realistic model of the system.
Paper VI143-04.25
PDF · Video · Robust Adaptive Control of a Multirotor with an Unknown Suspended Payload
Erasmus, Anthonie Philippus	Stellenbosch University
Jordaan, Hendrik Willem	Stellenbosch University
Keywords: Learning and adaptation in autonomous vehicles Abstract: This paper addresses the problem of a multirotor carrying an unknown suspended payload, allowed to swing in one axis. The payload is unknown in the sense that its parameters, such as the payload mass and cable length, are unknown and its state, the swing angles, are not available for measurement. The suspended payload alters the flight dynamics of the vehicle considerably and the flight controllers need to minimize this effect. A robust model reference adaptive control technique is designed and implemented to minimize the effect of the suspended payload on the vehicle while allowing the controller to adapt to account for the unknown payload. The controller is modified to reject external disturbances and to be robust in the presence of sensor noise and drift. In simulation, this technique proves to dampen the oscillations caused by the payload. A quadrotor was built to practically demonstrate the effectiveness of the controller. The PX4 flight control stack is considered for the firmware of the vehicle. The model reference adaptive controller was implemented and succeeded to dampen the oscillations caused by the payload in a practical flight.
Paper VI143-04.26
PDF · Video · Reachability-Based Collision Recovery Strategy of a Quadrotor
Li, Binbin	Southwest Jiaotong University
Ma, Lei	Southwest Jiaotong University
Wang, Duo	Southwest Jiaotong University
Sun, Yongkui	Southwest Jiaotong University
Keywords: Tele-robotics, Traffic control systems Abstract: Collisions with surrounding objects pose huge threat to flying quadrotors, especially in unknown environments. Unfortunately, quadrotors equipped with sensors (cameras, radars, etc.) cannot effectively detect small objects such as wires and branches. In this paper, a global stability control strategy is proposed for collision recovery based on the reachability theory. Reachability analysis is used to divide the collision recovery process into three modes:1)collision, 2)idling, 3)recovery. Safe switching conditions between different modes are generated by using solution of the Hamilton-Jacobi} equation. A safe control law is presented based on the quaternion, which is proven to be globally stable and can quickly recovered from any attitude. Feasibility and performance of the proposed method are verified by experiments with collision maneuvers.

VI143-05
Guidance, Navigation and Control in Robotics	Regular Session
Chair: Petrovic, Ivan	Univ. of Zagreb
Co-Chair: Kemmetmueller, Wolfgang	TU Wien, Automation and Control Institute
Paper VI143-05.1
PDF · Video · Quaternion Based Three-Dimensional Impact Angle Constrained Guidance
Surve, Prajakta Shankar	Indian Institute of Technology Bombay, Mumbai
Maity, Arnab	Indian Institute of Technology Bombay
Kumar, Shashi Ranjan	Indian Institute of Technology Bombay
Keywords: Guidance navigation and control Abstract: This paper proposes quaternion based three-dimensional guidance strategies, which ensure target interception with zero miss distance. Unlike most of the existing guidance strategies, the guidance command in this paper is derived using coupled engagement dynamics, which helps to maintain satisfactory performance for the engagements where decoupling is no longer valid. To avoid the well known possible singularities due to Euler's representation, a quaternion based representation of three-dimensional engagement is utilised. This facilitates the proposed guidance strategy to remain applicable and effective for wider range. In addition, guidance strategy is also derived to ensure target interception at a desired impact angle, which is expressed in terms of desired line-of-sight quaternion. Simulation results are shown to evaluate the efficacy of proposed guidance strategies for various engagement scenarios.
Paper VI143-05.2
PDF · Video · Compound Robust Flight Time and Heading Angle Constrained Guidance Law
Ji, Yi	Beijing Institute of Technology
Pei, Pei	Beijing Institute of Technology
Lin, Defu	Beijing Institute of Technology
Zhao, Jianting	Beijing Institute of Technology
Wang, Wei	Beijing Institute of Technology
Keywords: Guidance navigation and control Abstract: This work studies accurate interception problem for salvo-attack missions and proposes a robust guidance law in the presence of impact time and angle constraints. First, the dynamic model for planar homing endgame guidance is built. Different with conventional guidance dynamic model, this work takes the derivative with respect to range, rather than time. Next, the trajectory of desired line-of-sight is formed and a time-to-go prediction method is introduced. On this basis, according to sliding mode methodology, a sliding manifold consisting the knowledge of time-to-go and line-of-sight angle is built and an integrated Lyapunov control method based guidance law is deduced to force this sliding manifold converge to a small region around zero in finite time, so that the missile will intercept target with a desired flight time and a heading angle. Detailed theoretical analysis and numerical simulations verified above properties.
Paper VI143-05.3
PDF · Video · Integrated Guidance and Control Using Adaptive Backstepping Approach for Maneuvering Target Interception
Pei, Pei	Beijing Institute of Technology
Ji, Yi	Beijing Institute of Technology
He, Shaoming	Cranfield University
Wang, Jiang	Beijing Institute of Technology
Lin, Defu	Beijing Institute of Technology
Keywords: Guidance navigation and control Abstract: A novel approach to address the problem of integrated guidance and control(IGC) for a missile is studied in this paper. By taking target maneuver, aerodynamic uncertainty and fin servo dynamic uncertainty as external disturbances in the adaptive backstepping design procedure, the proposed controller requires no information on target maneuver and provides robustness against other uncertainties. Furthermore, the derivatives of the virtual control laws in the backstepping differentiation process are estimated by a smooth second-order sliding mode differentiator, this simplifies the calculation and avoids the explosion of terms phenomenon in the conventional backstepping method. The closed-loop stability of the overall system is supported by the Lyapunov stability theory. Numerical simulations of an air-to-air interception scenario are presented in the simulation part to verify the superior performance and the robustness of proposed IGC law.
Paper VI143-05.4
PDF · Video · Robot Navigation among External Autonomous Agents through Deep Reinforcement Learning Using Graph Attention Network
Zhang, Tianle	Institute of Automation, Chinese Academy of Sciences, Beijing
Qiu, Tenghai	Institute of Automation, Chinese Academy of Sciences
Pu, Zhiqiang	Institute of Automation, Chinese Academy of Sciences
Liu, Zhen	Institute of Automation, Chinese Academy of Sciences
Yi, Jianqiang	Institute of Automation, Chinese Academy of Sciences
Keywords: Guidance navigation and control, Intelligent robotics, Mobile robots Abstract: Finding collision-free and efficient paths in an uncertain dynamic environment is a challenge for robot navigation tasks, especially when there are external autonomous agents that also have decision-making abilities in the same environment. Recent works present deep reinforcement learning (DRL) as a framework to learn an effective policy for robot navigation. However, they still have some unsolved problems. For example, the information of the environment is described as a lumped vector with everything stacked together and the performance of the policy learned through DRL is unreliable in new environments. This paper develops a novel method based on DRL with graph attention network (GAT) to solve the problem of robot navigation among external autonomous agents (other agents). Specifically, GAT is adopted to describe the robot and other agents as a specific graph, and extract the spatial structural influence features of other agents on the robot from the graph. Multi-head attention mechanism is utilized to calculate the weights of interactions between the robot and other agents. This GAT uses observations of an arbitrary number of other agents in dynamic environments. Furthermore, the proposed method is combined with optimal reciprocal collision avoidance to improve its safety in new environments. Various simulations demonstrate that our method has good performance and robustness in different environments.
Paper VI143-05.5
PDF · Video · Deep Learning Based Keypoint Rejection System for Underwater Visual Ego-Motion Estimation
Leonardi, Marco	NTNU
Fiori, Luca	University of Siena
Stahl, Annette	Norwegian University of Science and Technology
Keywords: Guidance navigation and control, Perception and sensing, Intelligent robotics Abstract: Most visual odometry (VO) and visual simultaneous localization and mapping (VSLAM) systems rely heavily on robust keypoint detection and matching. With regards to images taken in the underwater environment, phenomena like shallow water caustics and/or dynamic objects like fishes can lead to the detection and matching of unreliable (unsuitable) keypoints within the visual motion estimation pipeline. We propose a plug-and-play keypoint rejection system that rejects keypoints unsuitable for tracking in order to obtain a robust visual ego-motion estimation. A convolutional neural network is trained in a supervised manner, with image patches having a detected keypoint in its center as input and the probability of such a keypoint suitable for tracking and mapping as output. We provide experimental evidence that the system prevents to track unsuitable keypoints in a state-of-the-art VSLAM system. In addition we evaluated several strategies aimed at increasing the inference speed of the network for real-time operations.
Paper VI143-05.6
PDF · Video · Multi-Stage Event-Triggered Model Predictive Control for Automated Trajectory Drilling
Morabito, Bruno	Otto-von-Guericke-Universität Magdeburg
Koegel, Markus J.	Otto-von-Guericke-Universität Magdeburg
Blasi, Svenja	Otto-von-Guericke-Universität Magdeburg
Klemme, Vanja	Baker Hughes Company
Hansen, Christian	Baker Hughes Company
Hoehn, Oliver	Baker Hughes Company
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Autonomous robotic systems, Motion Control Systems, Mobile robots Abstract: In upstream Oil and Gas operations a well is drilled following a planned trajectory. The trajectory is designed to avoid hard formations and other wells while minimizing drilling time. The uncertainty of the environment, e.g. unknown rock hardness, effects negatively the efficiency of operation: drilling time increases due to frequent corrective control actions that must be taken to counteract disturbances and risk increases since process constraints may be violated. This paper proposes an event-triggered multi-stage model predictive control that aims at tackling both challenges. The event-triggering strategy tries to minimize the number of control actions sent to the actuators, while the multi-stage strategy improves constraints satisfaction despite uncertainties. The method is tested in simulation where unknown changes in rock hardness are considered. In comparison to a standard model predictive control approach, we show that using the combined event-triggered and multi-stage approach we improve constraints satisfaction and decrease the number of control actions.
Paper VI143-05.7
PDF · Video · Data Links Enhanced Relative Navigation for Robotic Formation Applications
Hao, Ning	Harbin Institute of Technology
Xing, Rui	Harbin Institute of Technology
Yao, Haodi	Harbin Institute of Technology
He, Fenghua	Harbin Institute of Technology
Yao, Yu	Harbin Institute of Technology
Keywords: Guidance navigation and control, Autonomous robotic systems, Information and sensor fusion Abstract: With the rapid development and widespread application of robotic formation, relative navigation has attracted extensive attention. In this paper, the relative navigation problem is investigated for robotic formation applications. First of all, a data link enhanced relative navigation scheme is proposed. Secondly, the underlying estimation problem behind the relative navigation is derived. Then, a recursive navigation algorithm based on maximum a posterior estimation is provided for different multi-sensor combinations. Finally, simulation experiments are performed to show the effectiveness of the proposed relative navigation method.
Paper VI143-05.8
PDF · Video · Sliding Mode Control of a Ball Balancing Robot
Lal, Ioana	Technical University of Cluj-Napoca
Codrean, Alexandru	Technical University of Cluj Napoca
Busoniu, Lucian	Technical University of Cluj-Napoca
Keywords: Mobile robots, Identification and control methods, Guidance navigation and control Abstract: This paper presents a sliding mode control design for a ball-balancing robot (ballbot), with associated real-time results. The sliding mode control is designed based on the linearized plant model, and is robust to matched uncertainties. The design is considerably simpler than other nonlinear control strategies presented in the literature, and the experimental results for stabilization and tracking show much better performances than those obtained with linear control (in particular, a linear quadratic regulator).
Paper VI143-05.9
PDF · Video · Performance-Guaranteed Consensus Control Inspired by the Mammalian Limbic System for a Class of Nonlinear Multi-Agents
Rubio Scola, Ignacio	Mechatronics Department, CEFET-MG
Garcia Carrillo, Luis Rodolfo	Texas A&M University - Corpus Christi
Hespanha, Joao	University of California, Santa Barbara
Lozano, Rogelio	Univ De Technologie De Compiegne
Keywords: Intelligent robotics, Identification and control methods, Networked robotic system modeling and control Abstract: Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance--guaranteed emotional learning--inspired control (ELIC) strategies for autonomous multi--agent systems (MAS), where each agent incorporates an ELIC structure to support the consensus controller. The objective of each ELIC structure is to identify and compensate model differences between the theoretical assumptions taken into account when tuning the consensus protocol, and the real conditions encountered in the real system to be stabilized. Stability of the closed-loop MAS is demonstrated using a Lyapunov analysis. Simulation results based on the consensus task of a group of inverted pendulums demonstrate the effectiveness of the proposed ELIC for stabilization of nonlinear MAS.
Paper VI143-05.10
PDF · Video · Enforcing Constraints Over Learned Policies Via Nonlinear MPC: Application to the Pendubot
Turrisi, Giulio	Sapienza, Università Di Roma, DIAG
Barros Carlos, Barbara	Sapienza, Università Di Roma
Cefalo, Massimo	Sapienza University of Rome
Modugno, Valerio	Sapienza, Università Di Roma
Lanari, Leonardo	Sapienza Università Di Roma
Oriolo, Giuseppe	Sapienza University of Rome
Keywords: Intelligent robotics, Robotics technology, Motion Control Systems Abstract: In recent years Reinforcement Learning (RL) has achieved remarkable results. Nonetheless RL algorithms prove to be unsuccessful in robotics applications where constraints satisfaction is involved, e.g. for safety. In this work we propose a control algorithm that allows to enforce constraints over a learned control policy. Hence we combine Nonlinear Model Predictive Control (NMPC) with control-state trajectories generated from the learned policy at each time step. We prove the effectiveness of our method on the Pendubot, a challenging underactuated robot.
Paper VI143-05.11
PDF · Video · Fast Motion Planning for a Laboratory 3D Gantry Crane in the Presence of Obstacles
Vu, Minh Nhat	Automation & Control Institute (ACIN), TU Wien, Austria
Zips, Patrik	Automation and Control Institute, Vienna University of Technolog
Lobe, Amadeus Cosimo	Austrian Institute of Technology GmbH
Beck, Florian	Vienna University of Technology
Kemmetmueller, Wolfgang	TU Wien, Automation and Control Institute
Kugi, Andreas	Vienna University of Technology
Keywords: Robotics technology, Identification and control methods, Intelligent robotics Abstract: In this paper, a concept is presented for the fast motion planning of a 3D laboratory crane in a static environment with obstacles taking into account the dynamic constraints on the state variables and control inputs. The focus is set on the possibility of a fast (re)planning if the starting and/or target state is changing. The proposed concept consists of two parts: an offline trajectory planner to set up a database of collision-free, time optimal trajectories from the starting to the target space, with an average computing time of 0.17 s for one trajectory, and an online planner based on a constrained quadratic program, with an average computing time of 7 ms for one trajectory. Simulation results for a validated mathematical model demonstrate the feasibility of the proposed approach.
Paper VI143-05.12
PDF · Video · Reinforcement Learning-Assisted Composite Adaptive Control for Time-Varying Parameters
Kim, Seong-hun	Seoul National University
Lee, Hanna	Seoul National University
Kim, Youdan	Seoul National University
Keywords: Guidance, navigation and control of vehicles, Learning and adaptation in autonomous vehicles, Navigation, Guidance and Control Abstract: Adaptive control methods have received a lot of interest to control uncertain systems with parametric uncertainties. In particular, composite adaptation law that incorporates a memory storing the past trajectory data is promising, because it has an exponential convergent rate for both the tracking error and the parameter estimation under a mild condition of excitation. In this study, this research direction is extended to cope with uncertain parameters that change over time, which is difficult to solve with traditional memory-based methods. The problem is formulated into a Markov decision process, and a reinforcement learning algorithm is adopted to solve the optimal decision making problem. The proposed formulation preserves the stability of the original composite adaptive system, and the reinforcement learning agent can learn the optimal composite strategy.

VI143-06
Sensor Fusion for Robotics	Regular Session
Chair: Noack, Benjamin	Karlsruhe Institute of Technology (KIT)
Co-Chair: Cho, Dong-il Dan	Seoul National Univ
Paper VI143-06.1
PDF · Video · Bounded-Error Target Localization and Tracking in Presence of Decoys Using a Fleet of UAVs
Ibenthal, Julius	Onera
Meyer, Luc	Univ Paris Saclay
Kieffer, Michel	CNRS - CentraleSupélec - Université Paris-Sud, Institut
Piet-Lahanier, Helene	ONERA
Keywords: Information and sensor fusion, Flying robots, Autonomous robotic systems Abstract: This paper addresses the problem of searching and tracking of an a priori unknown number of targets spread over some geographical area using a fleet of UAVs. State perturbations and measurement noises are assumed to belong to bounded sets. In the monitored geographical area, some decoys may be interpreted as false targets when observed under specific conditions. A robust bounded-error estimation approach is proposed to evaluate, at each time step, sets guaranteed to contain the actual state of already localized true or false targets. A set containing the states of targets still to be discovered is also evaluated. These sets are used to determine the control inputs of UAVs so as to minimize the estimation uncertainty at future time steps. Simulations involving several UAVs show that the proposed robust set-membership estimator is able to estimate the state of all actual targets and to efficiently identify and eliminate decoys.
Paper VI143-06.2
PDF · Video · Generalized Visual-Tactile Transformer Network for Slip Detection
Cui, Shaowei	Chinese Academy of Science
Wei, Junhang	Institute of Automation, Chinese Academy of Sciences
Li, Xiaocan	Institute of Automation, Chinese Academy of Sciences
Wang, Rui	Institute of Automation, Chinese Academy of Sciences
Wang, Yu	Institute of Automation Chinese Academy of Sciences
Wang, Shuo	The State Key Laboratory of Management and Control for Complex S
Keywords: Information and sensor fusion, Perception and sensing, Multi-modal interaction Abstract: Slip detection plays a vital role in robotic dexterous grasping and manipulation, and it has long been a challenging problem in the robotic community. Different from traditional tactile perception-based methods, we propose a Generalized Visual-Tactile Transformer (GVT-Transformer) network to detect slip based on visual and tactile spatiotemporal sequences. The main novelty of GVT-Transformer is its ability to address unaligned vision and tactile data in various formats captured by various tactile sensors. Furthermore, we train and test our proposed network on a public and our visual-tactile grasping datasets. The experimental results show that our method is more suitable for sliding detection tasks than previous visual-tactile learning methods and more versatile.
Paper VI143-06.3
PDF · Video · Human Intention Estimation Using Fusion of Pupil and Hand Motion
Trombetta, Daniel	University of Connecticut
Rotithor, Ghananeel	University of Connecticut
Salehi, Iman	University of Connecticut
Dani, Ashwin	University of Connecticut
Keywords: Information and sensor fusion, Robotics technology, Human operator support Abstract: This paper addresses the problem of human intention inference in the context of human-robot collaboration by fusing information from both hand motion obtained using skeletal tracking and eye gaze obtained using pupil tracking to predict a human's current intention. Intention is modeled as a motion profile that converges to a goal location. A Kalman filter is used on eye gaze data to obtain gaze point estimates. The gaze estimates are transformed into a reference frame common to the hand data. An IMM filter that tracks hand motion is designed which takes advantage of the gaze filter's model probabilities by fusing them with its own. The fusion is performed with user chosen parameters that determine the degree to which each filter's predictions are weighed over time. An experiment is designed to show the utility of the proposed algorithm in a setting in which multiple reaching tasks are completed in an unknown order. The results show that the proposed algorithm can accurately predict the human's intention before the tasks are completed.
Paper VI143-06.4
PDF · Video · Improved Pose Graph Optimization for Planar Motions Using Riemannian Geometry on the Manifold of Dual Quaternions
Li, Kailai	Karlsruhe Institute of Technology (KIT)
Cox, Johannes	Technical University of Berlin
Noack, Benjamin	Karlsruhe Institute of Technology (KIT)
Hanebeck, Uwe	Karlsruhe Institute of Technology (KIT)
Keywords: Information and sensor fusion, Robotics technology, Intelligent robotics Abstract: We present a novel Riemannian approach for planar pose graph optimization problems. By formulating the cost function based on the Riemannian metric on the manifold of dual quaternions representing planar motions, the nonlinear structure of the SE(2) group is inherently considered. To solve the on-manifold least squares problem, a Riemannian Gauss-Newton method using the exponential retraction is applied. The proposed Riemannian pose graph optimizer (RPG-Opt) is further evaluated based on public planar pose graph data sets. Compared with state-of-the-art frameworks, the proposed method gives equivalent accuracy and better convergence robustness under large uncertainties of odometry measurements.
Paper VI143-06.5
PDF · Video · Robust Object Tracking with Continuous Data Association Based on Artificial Potential Moving Horizon Estimation
Abe, Ryoya	Tokyo City University
Kikuchi, Tomoya	Tokyo City University
Nonaka, Kenichiro	Tokyo City University
Sekiguchi, Kazuma	Tokyo City University
Keywords: Perception and sensing, Information and sensor fusion, Autonomous robotic systems Abstract: In this paper, a novel object tracking method based on moving horizon estimation (MHE) is introduced that integrates data association into numerical optimization on Bayesian state estimation. Object tracking is a classical problem that often appears in radar and vision systems for which either deterministic or probabilistic approach has been applied. While the former often encounter a failure of association, the latter avoids it by computing the expectation concerning the observations, but it requires the prior knowledge of the probabilistic distribution and may suffer from outliers. In this paper, a partially deterministic approach is built on MHE to resolve these concerns. Data association is realized by a potential function comprising the superposition of Gaussian distributions centered at each observed feature. The potential function is embedded into the stage cost of MHE; the optimal data association is conducted using the sequence of observations within the horizon. Thus robust object tracking is achieved utilizing multi-sampling data and integration of both dynamics and explicit constraints reflecting physical limitations. The advantage of the proposed method is verified through object tracking experiments on the crowded environment, where occlusion and misrecognition frequently occur.
Paper VI143-06.6
PDF · Video · Outdoor 3D Reconstruction Method Based on Multi-Line Laser and Binocular Vision
Jian, Xu	China University of Geosciences
Chen, Xin	China University of Geosciences
He, Wenpeng	China University of Geosciences
Gong, Xuan	China University of Geosciences
Keywords: Perception and sensing, Information and sensor fusion, Identification and control methods Abstract: Three-dimensional (3D) reconstruction of substation fittings is of great significance for live working robots. However, the key problem is that active 3D cameras cannot work in outdoor strong light environment, and the passive 3D cameras cannot extract features of weak texture targets. This paper proposes an outdoor 3D reconstruction method based on multi-line laser and binocular vision. To solve the problem that weak texture target has few features, we use multi-line laser to create artificial features. To reduce the interference of natural light on the laser in the images, the frame-difference method is proposed for natural light filtering. Then we use the gray-centroid method to position the multi-line laser accurately. Finally, the binocular vision model is used to complete 3D reconstruction of the target. The experiments show that, compared with traditional 3D reconstruction methods, our 3D reconstruction method can realize 3D reconstruction of outdoor weak texture targets effectively.
Paper VI143-06.7
PDF · Video · An Observer Design for Visual Simultaneous Localisation and Mapping with Output Equivariance
van Goor, Pieter	Australian National University
Mahony, Robert	Australian National University
Hamel, Tarek	Université De Nice Sophia Antipolis
Trumpf, Jochen	The Australian National University
Keywords: Perception and sensing, Information and sensor fusion, Mobile robots Abstract: Visual Simultaneous Localisation and Mapping (VSLAM) is a key enabling technology for small embedded robotic systems such as aerial vehicles. Recent advances in equivariant filter and observer design offer the potential of a new generation of highly robust algorithms with low memory and computation requirements for embedded system applications. This paper studies observer design on the symmetry group proposed in (van Goor et al., 2019, CDC), in the case where inverse depth measurements are available. Exploiting this symmetry leads to a simple fully non-linear gradient based observer with almost global asymptotic and local exponential stability properties. Simulation experiments verify the observer design, and demonstrate that the proposed observer achieves similar accuracy to the widely used Extended Kalman Filter with significant gains in processing time (linear verses quadratic bounds with respect to number of landmarks) and qualitative improvements in robustness.
Paper VI143-06.8
PDF · Video · Harsh-Environment Visual Odometry for Field Robots Using Data Fusion of Gyroscope & Magnetometer
Kim, Chul Hong	Seoul National University
Kim, Jee-seong	Seoul National University
Cho, Dong-il Dan	Seoul National Univ
Keywords: Mobile robots, Information and sensor fusion, field robotics Abstract: This paper presents a harsh-environment visual odometry method that is robust to the robot orientation as well as the camera movement in an outdoor environment. The accuracy of visual odometry in robots can be enhanced by using additional sensor measurements such as an encoder, gyroscope, and/or magnetometer. This strategy can even reduce the computational time. However, in an outdoor environment, the moving robot can experience vibration, which causes unsynchronized data fusion between the camera and additional sensors. This unsynchronized data fusion causes errors in the robot orientation, which can lead to unwanted large drift errors in localization. To overcome this problem, firstly two distinctively different characteristics of the gyroscope and the magnetometer are combined to estimate the robot orientation. The initial robot orientation is estimated by integration of the gyroscope input, and this initial robot orientation is corrected using the magnetometer data in bundle adjustment. Secondly, the poses of the robot and the camera are estimated separately, and these separately estimated poses of the robot and the camera are used in feature matching and bundle adjustment to reduce drift errors in localization in the outdoor environment. The performance of the proposed method is demonstrated using dataset-based experiments.

VI143-07
Mobile Robots Planning, and Control	Regular Session
Chair: Shim, Hyungbo	Seoul National University
Co-Chair: Danes, Patrick	LAAS-CNRS & Toulouse III Paul Sabatier University
Paper VI143-07.1
PDF · Video · Flatness-Based Active Disturbance Rejection Control for a Wheeled Mobile Robot Subject to Slips and External Environmental Disturbances
Abadi, Amine	Université D'Orléans
El Amraoui, Adnen	Ecole Centrale De Lille (EC-Lille)
Mekki, Hassen	University of Sousse
Ramdani, Nacim	Université D'Orléans
Keywords: Mobile robots, Guidance navigation and control Abstract: This work suggests flatness-based Active Disturbance Rejection Control (ADRC) to deal with the problem of trajectory tracking for Wheeled Mobile Robot (WMR). Based on the differential flatness theory, the nonlinear WMR system is transformed into two integral-chains, which makes the creation of a state feedback controller easier. In order to improve the WMR tracking, slip and external environmental disturbance must be considered in the controller design. Therefore, an Extended State Observer (ESO) is created to estimate the obtained linearized system state and the extended state known as lumped uncertainties. The latter represent the total effects of slip and the external environmental disturbances to WMR. After that, according to the ESO result, a complementary element is added to the state feedback controller to compensate the effects of lumped disturbances. Simulation results are introduced to demonstrate the advantages of combining ADRC with flatness control.
Paper VI143-07.2
PDF · Video · Gait Control of a Fully Actuated Walking Robot
Hui, Sally	University of Toronto
Al Lawati, Mohamed	Sultan Qaboos University, University of Alberta
Broucke, Mireille	University of Toronto
Keywords: Mobile robots, Guidance navigation and control, Autonomous robotic systems Abstract: This paper considers the problem of feedback control of a fully actuated biped robot such that a virtual holonomic constraint (VHC) is enforced concomitant with control of the stance leg using a reach control methodology. The reach controller achieves safety and liveness specifications on the stance leg speed and the step size, resulting in a polytopic state space for the restricted hybrid dynamics on the VHC constraint manifold. It is shown that both the restricted system and the full hybrid system exhibit a stable, hybrid limit cycle. The design method can provide a way to compliantly adjust gait speed, for instance, to gently transition between different gaits, while maintaining transients within safe bounds.
Paper VI143-07.3
PDF · Video · Gaussian Processes Incremental Inference for Mobile Robots Dynamic Planning
Petrovic, Luka	University of Zagreb, Faculty of Electrical Engineering and Comp
Maric, Filip	University of Zagreb, Faculty of Electrical Engineering and Comp
Markovic, Ivan	University of Zagreb Faculty of Electrical Engineering and Compu
Petrovic, Ivan	Univ. of Zagreb
Keywords: Mobile robots, Guidance navigation and control, Autonomous robotic systems Abstract: Trajectory optimization methods for motion planning attempt to generate trajectories that minimize a suitable objective function. While such methods efficiently find solutions in static environments, they need to be ran from scratch multiple times in the presence of moving obstacles, which incurs unnecessary computation and slows down execution. In this paper, we propose a trajectory optimization algorithm that anticipates the movement of obstacles and solves the planning problem in an iterative manner. We employ continuous-time Gaussian processes as trajectory representations both for the mobile robot and moving obstacles for which future locations are predicted according to a given model. We formulate the simultaneous moving obstacles tracking and mobile robot motion planning problem as probabilistic inference on a factor graph. Since trajectories of moving obstacles are optimized concurrently to motion planning, the proposed approach works in a predictive manner. After computing the initial solution, we use incremental inference for online replanning after an estimate of the moving obstacle position is provided. Our experimental evaluation demonstrates that the proposed approach supports online motion generation in the presence of moving obstacles.
Paper VI143-07.4
PDF · Video · VFH+D: An Improvement on the VFH+ Algorithm for Dynamic Obstacle Avoidance and Local Planning
Díaz, Daniel	Universidad De Costa Rica
Marín, Leonardo	Universidad De Costa Rica
Keywords: Mobile robots, Guidance navigation and control, Motion Control Systems Abstract: This paper highlights some limitations of the VFH+ algorithm on the domain of local obstacle avoidance. An enhanced algorithm dubbed VFH+D is proposed, which considers a different way of calculating the obstacle vector magnitude and a decay algorithm for dynamic obstacle avoidance. Experiments were conducted to compare both algorithms on two different mecanum wheeled robots, VFH+D achieved higher average speeds and lower distance traveled to reach the goal.
Paper VI143-07.5
PDF · Video · Person Following from a Nonholonomic Mobile Robot with Ultimately Bounded Tracking Error
Tari, Joel	LAAS-CNRS, AKKA Research
Danes, Patrick	LAAS-CNRS & Toulouse III Paul Sabatier University
Keywords: Mobile robots, Human operator support Abstract: In robotics, "person following" depicts the servoing of the relative situation of a robot w.r.t. a moving person. This property may be hard to achieve, especially when the estimation of the person ego-motion is weak (e.g., due to limited prior knowledge or computational resources). This paper introduces a nonholomic mobile robot controller, which ensures an intuitive and safe behavior through an insightful robot-centered problem statement. Under realistic bounded-error readings of hidden constant person velocities, ultimate boundedness of the state vector norm can be ensured in the neighborhood of its equilibrium.
Paper VI143-07.6
PDF · Video · Control-Based Approach to Numerical Integration of Rolling Equations
Pesterev, Alexander	Institute of Control Sciences, Russian Academy of Sciences
Matrosov, Ivan Vladimirovich	Javad GNSS
Morozov, Yuriy	Institute of Control Sciences
Keywords: Mobile robots, Modeling Abstract: In the paper, an approach to numerical integration of equations governing motion of constrained mechanical systems is suggested. In the framework of this approach, unknown reaction forces acting on the system are treated as controls, and the algebraic equations that these reactions satisfy, as control goals. On the basis of the suggested approach, a technique for numerical solving equations of rolling is developed. The discussion is illustrated by the example of application of the algorithm to solving the problem of a heavy wheel with a pendulum (a prototype of a ball-shaped robot) rolling along a curvilinear profile without slippage.
Paper VI143-07.7
PDF · Video · Control of Two-Wheeled Mobile Robots Moving in Formation
Kozlowski, Krzysztof R.	Poznan Univ of Technology
Kowalczyk, Wojciech	Poznan University of Technology
Keywords: Mobile robots, Motion Control Systems, Autonomous robotic systems Abstract: This paper presents control algorithm for multiple non-holonomic mobile robots moving in formation. Method from Canudas et al. (1994) is used to track desired trajectory. In the new algorithm this approach is combined with collision avoidance. Artificial potential functions are used to generate repulsive component of the control. Stability analysis is based on Lyapunov-like function. Effectiveness of the presented method is illustrated by simulation results for a large formation of mobile platforms. Robots avoid collisions with each other and with static obstacles. Position and orientation reach values close to steady state in 50s.
Paper VI143-07.8
PDF · Video · Simultaneous Distributed Localization, Mapping and Formation Control of Mobile Robots Based on Local Relative Measurements
Guo, Miao	University of Groningen
Jayawardhana, Bayu	University of Groningen
Lee, Jin Gyu	University of Cambridge
Shim, Hyungbo	Seoul National University
Keywords: Networked robotic system modeling and control, Autonomous robotic systems Abstract: This paper investigates the problem of localizing a team of robots in an indoor environment while simultaneously keeping a robust formation and performing group motion. A distributed observer is proposed to estimate the positions of mobile robots as well as the landmarks under a common global frame. Every robot uses its available local relative measurements, as well as the estimated relative measurements to its neighbors in order to keep a robust formation. Simultaneously, each robot estimates the positions of all the landmarks based on the available on-board relative measurements but also based on the estimated positions from its neighbors. We provide the L2-stability analysis of the closed-loop system where the group is also allowed to maneuver in the unknown environment. Simulation results are also given to show the efficacy of the method.
Paper VI143-07.9
PDF · Video · Sensor-Based Exploration of an Unknown Area with Multiple Mobile Agents
Olcay, Ertug	Technical University of Munich
Bodeit, Jens	Technical University of Munich
Lohmann, Boris	Technische Universität München
Keywords: Networked robotic system modeling and control, Guidance navigation and control, Autonomous robotic systems Abstract: The research field of effective coverage of a certain area has received considerable attention, especially in exploration tasks. The ability of robots to localize themselves in a map and to plan elaborated motions are the basics of many coverage approaches. Cooperative, multiple robots can be employed in order to accelerate exploration missions. Over the past years, many methods have been investigated for this purpose. However, either the robots know the obstacle locations or they are not capable of identifying their environment completely. In this study, we propose a sensor-based framework to cover a given space simultaneously with multiple mobile agents in a cooperative fashion without any prior knowledge of the environment. With our approach, the agents are capable of avoiding collisions with different shaped obstacles and autonomously constructing a map of the whole area by identifying inaccessible domains in the map.
Paper VI143-07.10
PDF · Video · Obstacle Avoidance of Swarms Using Pinning Control
Cabral, Kleber	Royal Military College
Givigi, Sidney	Queen's University
Jardine, Peter Travis	Royal Military College of Canada
Keywords: Networked robotic system modeling and control, Guidance navigation and control, Mobile robots Abstract: In swarm control tasks, local objectives, on each agent, can interfere with the group's collective objectives. For example, in an environment with obstacles, the motion of the whole group can be affected by local obstacle encounters (happening in a few agents). In this work, we investigate the navigation of swarms in the presence of obstacles. We propose a novel control strategy to avoid obstacles while reducing swarm fragmentation, i.e., limiting the division of the swarm into disconnected groups. We model the swarm as a network where each vehicle is topologically connected with the neighbours that are within the agent's sensing range. We actively monitor the agents' connections in order to identify the necessity of redesigning the network, splitting a larger group into groups with fewer agents. Also, we use a path planning algorithm to provide the trajectory to guide the agents to the final destination. At the end of this paper, we show the results of simulation trials to demonstrate the performance of our control strategy.
Paper VI143-07.11
PDF · Video · Attitude Stability Control for Multi-Agent Six Wheel-Legged Robot
Chen, Zhihua	Beijing Institute of Technology
Wang, Shoukun	Beijing Institute of Technology
Wang, Junzheng	Beijing Institute of Technology
Xu, Kang	Beijing Institute of Technology
Keywords: Robotics technology, Motion Control Systems, Mobile robots Abstract: Multi wheeled-legged robot systems are MIMO complex systems with multi information fusion. In this paper, a multi-sensor information fusion based wheeled-legged cooperative control strategy is proposed to solve the problem of attitude stability control for the six wheeled-legged robot-BIT-NAZA-II. First, when the robot is wheel motion, the overall attitude of the robot is adjusted by controlling the vertical degree of freedom(DOF) for the Stewart platform. Second, when the wheel movement is on uneven road, the foot end is easy to be suspended or raised. The impedance control method based on the position inner loop is used to solve the problem of leg suspension or raised. Third, in order to ensure the maximum motion space of single leg, the central height controller is designed. Moreover, the control strategy is mainly completed by the central CPU and six bottom CPUs. Six bottom CPUs receive the force information of each leg, and calculate the position of each leg by combining the impedance controller. Meanwhile, the central CPU receives the attitude angle information, calculates the position of each leg by using the attitude controller, takes two different position commands as the input of the central height controller, outputs the calculated position of the central height controller to six bottom CPUs through UPD communication, and the bottom CPU is used to calculate the variation of Stewart platform DOF. Finally, the experimental results of the control strategy in the six wheeled-legged robot system are given, and the feasibility and effectiveness of the control strategy are verified.
Paper VI143-07.12
PDF · Video · Communication Constrained Distributed Spatial Field Estimation Using Mobile Sensor Networks
Notomista, Gennaro	Georgia Institute of Technology
Egerstedt, Magnus	Georgia Institute of Technology
Keywords: Autonomous robotic systems, Perception and sensing, Motion Control Systems Abstract: In this paper we address the problem of distributed estimation of spatial fields using mobile sensor networks with communication constraints. These constraints consist of a maximum communication bandwidth which limits the amount of data that can be exchanged between any two nodes of the network at each time instant. An algorithm to select the most significant data to be transferred between neighboring sensor nodes is developed starting from derived analytical error bounds. Moreover, the motion of the network nodes is controlled using a coverage control algorithm with the objective of minimizing the estimation uncertainty of each of the nodes. The resulting communication constrained distributed estimation algorithm is deployed on a team of ground mobile robots in the Robotarium, and its performance is evaluated both in terms of estimation accuracy of a simulated spatial field, and of the amount of data transferred.
Paper VI143-07.13
PDF · Video · Subterranean MAV Navigation Based on Nonlinear MPC with Collision Avoidance Constraints
Sharif Mansouri, Sina	Lulea University
Kanellakis, Christoforos	Luleå University of Technology
Fresk, Emil	Luleå University of Technology
Lindqvist, Björn	Luleå University of Technology
Kominiak, Dariusz	Luleå University of Technology
Koval, Anton	Luleå University of Technology
Sopasakis, Pantelis	Queen’s University Belfast
Nikolakopoulos, George	Luleå University of Technology
Keywords: field robotics, Autonomous robotic systems Abstract: Micro Aerial Vehicles (MAVs)navigation in subterranean environments is gaining attention in the field of aerial robotics, however, there are still multiple challenges for collision free navigation in such harsh environments. This article proposes a novel baseline solution for collision free navigation with Nonlinear Model Predictive Control (NMPC). In the proposed method, the MAV is considered as a floating object, where the velocities on the x, y axes and the position on altitude are the references for the NMPC to navigate along the tunnel, while the NMPC avoids the collision by considering kinematics of the obstacles based on measurements from a 2D lidar. Moreover, a novel approach for correcting the heading of the MAV towards the center of the mine tunnel is proposed, while the efficacy of the suggested framework has been evaluated in multiple field trials in an underground mine in Sweden.
Paper VI143-07.14
PDF · Video · Evaluation of Underwater Cable Burying ROV through Sea Trial at East Sea
Cho, Gun Rae	Korea Institute of Robot and Convergence
Lee, Mun-Jik	Korea Institute of Robot and Convergence
Kang, Hyungjoo	Korea Institute of Robot and Convergence
Ki, Geonhui	Korea Institute Robotics and Technology Convergence
Kim, Min-Gyu	Korea Institute of Robot and Convergence
Li, Ji-Hong	Korea Institute of Robot and Convergence
Keywords: field robotics, Robotics technology, Intelligent robotics Abstract: Underwater cable burying is one of main cable protection methods in the offshore cable installation. In this paper, the performance evaluation of an underwater cable burying robot, named URI-T, through the sea trial is addressed. URI-T, the first heavy-duty underwater robot for cable burying tasks developed in South Korea, is designed to perform burying tasks and maintenance tasks for underwater cables and small-size pipes at the sea bed of 2,500m water depth. URI-T includes water-jetting systems and cable detection sensors for cable burying tasks, and employes mainpulators and tools for cable maintenance tasks. The sea trial at the East Sea having 500m water depth was focused to verify the key performance indices: operation water depth, cable burying depth, cable burying speed, and forward speed. The cable maintenance ability was also examined by carrying out the cable cutting test and the cable gripping test. Moreover, applicability of URI-T is also evaluated by two times of cable burying experiments more than 100m distance. As a result, it was verified not only that URI-T satisfies the target performance indicies, but also that URI-T is applicable for the cable burying construction.
Paper VI143-07.15
PDF · Video · Design and Experimental Verification of Two-Dimensional Rate Limiters in Trajectory Generation for Differential Drive Robots
Lauer, Anja Patricia Regina	University of Stuttgart
Uchiyama, Naoki	TUT
Sawodny, Oliver	Univ of Stuttgart
Keywords: Mobile robots Abstract: In order for robots to follow a desired path, velocity trajectories along the path are required. Two-dimensional rate limiters generate smooth velocity trajectories for differential drive mobile robots. First-order two-dimensional rate limiters satisfy the velocity constraints of the right and left wheel, while second-order two-dimensional rate limiters fulfill both velocity and acceleration constraints. This paper proves the global asymptotic stability of first-order two-dimensional rate limiters. It further shows the feasibility of second-order two-dimensional rate limiters by evaluating their performance through experiments with different sample paths and by comparison with a turn-on-the-spot solution.
Paper VI143-07.16
PDF · Video · Curve-Based Approach for Optimal Trajectory Planning with Optimal Energy Consumption: Application to Wheeled Mobile Robots
Singh, Inderjeet	Polytech Lille, University of Lille 1
Singh, Manarshhjot	University of Lille
Bensekrane, Ismail	University of Lille
Lakhal, Othman	University Lille 1, CRIStAL, CNRS-UMR 9189,
Merzouki, Rochdi	Polytech'Lille
Keywords: Mobile robots, Autonomous robotic systems Abstract: Wheeled transportation systems have been used since the dawn of civilization. The great amount of experience we have with wheeled transportation systems gives the Wheeled Mobile Robots (WMRs) an edge over other types of robots. This has allowed WMRs to be the prime candidates for many applications including, but not limited to, military and space applications. Sometimes these vehicles have to work in complex environments with complicated constraints to finish their assigned tasks. This paper presents a methodology to generate a smooth feasible trajectory for WMR using Pythagorean Hodograph (PH) curves. Generated trajectory not only avoids the static obstacles but also conforms to minimum energy consumption and travel time possible within the kinematic constraints of the WMR. Simulations are presented to check the performance of the proposed approach. The proposed method is experimentally validated using a WMR 'Robotino'.
Paper VI143-07.17
PDF · Video · Multi-Robot Energy-Aware Coverage Control in the Presence of Time-Varying Importance Regions
Duca, Rachael N.	University of Malta
Bugeja, Marvin K.	University of Malta
Keywords: Mobile robots, Autonomous robotic systems, Guidance navigation and control Abstract: Multi-robot systems are becoming widely popular in applications where a rapid response is required or where various different robotic capabilities are required. Applications such as surveillance, or search and rescue, would require an efficient team that can be deployed and optimally dispersed over the environment. This is known as the coverage control problem. The solution to this research optimization problem is affected by several external aspects, such as characteristics of the environment as well as factors that pertain to the robotic team. This work proposes a novel solution to the complete coverage problem where the team of robots is restricted with energy limitations, and must cover an environment that has time-varying regions of importance. Our results show that in a realistic scenario, where the robots have limited energy for the task in question, the proposed solution performs significantly better than a typical coverage algorithm which disregards the energy considerations of the robotic team.
Paper VI143-07.18
PDF · Video · Decentralized Strategy for Cooperative Multi-Robot Exploration and Mapping
Batinović, Ana	University of Zagreb
OrŠulić, Juraj	University of Zagreb
Petrovic, Tamara	University of Zagreb
Bogdan, Stjepan	University of Zagreb
Keywords: Mobile robots, Autonomous robotic systems, Intelligent robotics Abstract: This work presents a novel approach to autonomous decentralized multi-robot frontier exploration and mapping of an unknown area. A mobile robot team simultaneously explores the environment, discovers frontier points (points on the border between explored and unexplored space), and shares information in order to become dispersed throughout the environment. During the exploration, information exchanged between the mobile robots is limited to data containing mobile robot positions and current mobile robot target points. The main goal of the approach is to allocate the mobile robots to target frontier points in a way which minimizes the overall exploration time. Moreover, a mobile robot team at the same time creates a common map of the environment. The proposed strategy has been implemented in a simulation environment and compared with a state-of-the-art exploration strategy. Simulation results demonstrate the advantages of the proposed decentralized multi-robot strategy.
Paper VI143-07.19
PDF · Video · Deep Reinforcement Learning for Snake Robot Locomotion
Shi, Junyao	Columbia University
Dear, Tony	Columbia University
Kelly, Scott David	University of North Carolina at Charlotte
Keywords: Mobile robots, Autonomous robotic systems, Intelligent robotics Abstract: The design of gaits for underactuated robots is often unintuitive, with many results derived from either trial and error or simplification of system structure. Recent advances in deep reinforcement learning have yielded results for systems continuous in either states or actions, which may extend to a variety of locomoting robots. In this work we employ reinforcement learning to derive efficient and novel gaits for both terrestrial and aquatic multi-link snake robots. Although such systems operate in different environments, we show that their shared geometric structure allows us to utilize the same learning techniques in both cases to find gaits without any human input. We present results learned and rolled out in simulation, and we describe preliminary efforts to implement the entire learning process on a physical system.
Paper VI143-07.20
PDF · Video · Continuous Reachability Task Transition Using Control Barrier Functions
Srinivasan, Mohit	Georgia Institute of Technology
Santoyo, Cesar	Georgia Tech
Coogan, Samuel	Georgia Tech
Keywords: Mobile robots, Autonomous robotic systems, Robotics technology Abstract: In this paper, a method to achieve smooth transitions between sequential reachability tasks for a continuous time mobile robotic system is presented. Control barrier functions provide formal guarantees of forward invariance of safe sets and finite-time reachability and are able to enforce task execution. Barrier functions used in quadratic programs result in implementation of controllers with real-time performance guarantees. Existing approaches for multi-objective task execution using control barrier functions leverage discretely switched, sequential quadratic programs to achieve successive tasks. However, discrete switching can lead to control input discontinuities which can affect a robot's performance. Hence, we propose a method which ensures continuous transitions between sequential quadratic programs. In particular, a time varying component to the barrier function constraint is introduced which allows for a smooth transition between objectives. Robotic implementation results are also provided.
Paper VI143-07.21
PDF · Video · Economic Model Predictive Control for Obstacle-Aided Snake Robot Locomotion
Müller, Evan	University of Stuttgart
Köhler, Philipp N.	University of Stuttgart
Pettersen, Kristin Y.	Norwegian Univ. of Science and Tech
Allgower, Frank	University of Stuttgart
Keywords: Mobile robots, Design methodologies, Identification and control methods Abstract: This paper studies the application of economic model predictive control (MPC) to snake robot locomotion. The proposed MPC algorithm integrates the gait pattern creation into the closed loop by maximizing the forward snake velocity. We consider both purely planar locomotion as well as obstacle-aided locomotion. A compliant obstacle-snake contact model is introduced, rendering the interaction dynamics considered in the optimal control problem smooth. We illustrate the efficacy of the scheme by numerical simulations. The emerging gait patterns are undulatory and can make simultaneous use of anisotropic ground friction and obstacles.
Paper VI143-07.22
PDF · Video · Improved Visual-Inertial Localization for Low-Cost Rescue Robots
Long, Xiaoling	ShanghaiTech University
Xu, Qingwen	ShanghaiTech University
Yuan, Yijun	ShanghaiTech University
He, Zhenpeng	ShanghaiTech University
Schwertfeger, Sören	ShanghaiTech University
Keywords: Mobile robots, Perception and sensing, Work in real and virtual environments Abstract: This paper improves visual-inertial systems to boost the localization accuracy for low-cost rescue robots. When robots traverse on rugged terrain, the performance of pose estimation suffers from big noise on the measurements of the inertial sensors due to ground contact forces, especially for low-cost sensors. Therefore, we propose Threshold-based and Dynamic Time Warping-based methods to detect abnormal measurements and mitigate such faults. The two methods are embedded into the popular VINS-Mono system to evaluate their performance. Experiments are performed on simulation and real robot data, which show that both methods increase the pose estimation accuracy. Moreover, the Threshold-based method performs better when the noise is small and the Dynamic Time Warping-based one shows greater potential on large noise.
Paper VI143-07.23
PDF · Video · Binary GAN Based Approach for Unsupervised Loop Closure Detection in Autonomous Unmanned Systems
Jin, Sheng	Soochow University
Yang, Hui	Soochow University
Chen, Liang	Soochow University
Gao, Yu	Soochow University
Sun, Rongchuan	Soochow University
McLoone, Seán Francis	Queen's University Belfast
Keywords: Perception and sensing, Intelligent robotics, Mobile robots Abstract: Inspired by generative adversarial network (GAN), we propose a novel unsupervised approach for loop closure detection in autonomous unmanned systems. A binary GAN model dedicated to mobile application scenarios is designed to obtain binary feature descriptors, which are further incorporated into the most commonly used Bag of Visual Words (BoVW) model for loop closure detection. Compared with those hand-crafted features like SIFT and ORB, the performance of loop closure detection in complex environments with strong viewpoint and condition changes can be greatly improved. Compared with existing supervised approach based on convolutional neural network like AlexNet and AMOSNet, the cost-expensive task of supervised data annotation is totally avoided, which make the proposed approach more practical.
Paper VI143-07.24
PDF · Video · Deep-Learning-Based Relocalization in Large-Scale Outdoor Environment
Yu, Shikuan	Dalian University of Technology
Yan, Fei	Dalian University of Technology
Yang, Wenzhe	Dalian University of Technology
Li, Xiaoli	Beijing University of Technology
Zhuang, Yan	Dalian University of Technology
Keywords: Robotics technology, Mobile robots, Autonomous robotic systems Abstract: For the issue of relocalization, this paper proposed a deep-learning-based method for outdoor large-scale environment. In the first step, we projected a 3D Light Detection and Ranging (LiDAR) scan onto three 2D images from top to bottom. Then a densenet-based neural network structure was designed to regress a 4-DOF robot pose. These images are then stacked together, fed into the proposed DCNN architecture, and the output is the predicted robot pose. Extensive experiments have been conducted in practice with a real mobile robot, verifying the effectiveness of the proposed strategy. Our network can obtain approximately 3.5m and 4 degrees accuracy outdoors.
Paper VI143-07.25
PDF · Video · Mobile Robot Navigation Based on Regionalized Spatial Knowledge Representation and Reasoning
Zhong, Chaoliang	Hangzhou Dianzi University
Liu, Shirong	Hangzhou Dianzi University
Lu, Qiang	Hangzhou Dianzi University
Zhang, Botao	Hangzhou Dianzi University
Wang, Jian	Hangzhou Dianzi University
Wu, Qiuxuan	Hangzhou Dianzi Univesity
Gao, Farong	Hangzhou Dianzi University
Keywords: Autonomous robotic systems, Guidance navigation and control, Knowledge modelling and knowledge based systems Abstract: A regionalized environmental knowledge model (REKModel) is presented to describe the environment in the paper. The REKModel is a hierarchical structure in which small regions are grouped together to form superordinate regions. The REKModel is intrinsically hierarchical iterative and nested. Thus an extended nested-graph(ENG) is proposed to construct REKModel. An biomimetic navigation system for mobile robots is presented that is inspired by the fine-to-coarse planning heuristic, a human wayfinding strategy. A online fine-to-coarse pathfinding algorithm designed here allows robots to derives the route with decreasing the level of detail along the route. By using spatial information at different levels of detail for close and coarseness for distance, the memory load and plan complexity are all reduced. The simulation on MobileSim platform verifies the effectiveness and feasibility of the navigation system.
Paper VI143-07.26
PDF · Video · ICS-Zooids - an Experimental Testbed for Cooperative Control Strategies
Rathakrishnan, Nirmal	Hamburg University of Technology
Göttsch, Patrick	Hamburg University of Technology
Werner, Herbert	Hamburg Univ of Technology
Keywords: Networked robotic system modeling and control, Autonomous robotic systems, Embedded robotics Abstract: In this paper, we present an experimental test bench to implement various cooperative control strategies for multi-agent systems, and illustrate its use with experimental results for a source-seeking problem, where a group of small wheeled robots termed as Zooids should locate a source of a given spatial scalar field. This algorithm is implemented as a validation to demonstrate the capabilities of the test bench. We propose to achieve this by utilising an internal target-based position controller, under the assumptions of convexity of the scalar, continuous/discrete field and availability of local measurements of the field, so that agents can calculate its gradient and its Hessian. We then show in experiments, that using estimated gradients and Hessians (with data communicated from neighbours) in the presence of noisy measurements of the field strength provides satisfactory results for convex fields, under various algorithms such as Steepest Descent, Gauss-Newton, Levenberg Marquardt. These algorithms are analysed, and experimental results are discussed.
Paper VI143-07.27
PDF · Video · Effectiveness of Embedded Topology Controllers in a Multi-Robot Network
Rocha, Israel Cordeiro dos Santos	Aeronautics Institute of Technology (ITA)
Ribeiro, Carlos Henrique Costa	Technological Institute of Aeronautics
Ghedini, Cinara	ITA - Aeronautics Institute of Technology
Keywords: Networked robotic system modeling and control, Autonomous robotic systems, Guidance navigation and control Abstract: This paper presents analysis and results for several experiments performed to verify the effectiveness of topology control algorithms running on a multiagent network (e-puck robots), in a multi-objective realistic hardware-based scenario. The main goal of such a network can be, for instance, to provide communication in a disaster zone. In doing so, the agents should be controlled in such a way that they have to ensure connectivity maintenance and robustness to failures while improving the coverage area. These issues were addressed and proved to work in simulated scenarios. However, it lacked the validation on a hardware-based domain, accomplished by this work. By running several experiments from different initial topologies, it was possible to analyze and verify the effectiveness of the developed topology controllers. The hardware-based experiments shown results compatible with the simulated ones.
Paper VI143-07.28
PDF · Video · Why Does Symmetry Cause Deadlocks ?
Grover, Jaskaran Singh	Carnegie Mellon University
Liu, Changliu	Carnegie Mellon University
Sycara, Katia	Carnegie Mellon
Keywords: Networked robotic system modeling and control, Mobile robots, Autonomous robotic systems Abstract: Collision avoidance for multirobot systems has been studied thoroughly. Recently, control barrier functions (CBFs) have been proposed to mediate between collision avoidance and goal achievement for multiple robots. However, it has been noted that reactive controllers (such as CBFs) are prone to deadlock, an equilibrium that causes the robots to stall before reaching their goals. In this paper, we formally analyze two and three robot systems and discover circumstances under which CBFs cause deadlocks using duality theory. For the two robot system, we consider mutually heterogeneous robots (such as one more vigorous or closer to its goal than the other) and prove that this heterogeneity does not help in preventing deadlock. We then consider three robots, and conclude from these two scenarios that the geometric symmetry resulting from robots' initial positions and goals constrains CBFs to generate velocities that render deadlock stable. Thus, conferring skewness to the system can help evade deadlock.
Paper VI143-07.29
PDF · Video · Dynamical Modeling and Gait Optimization of a 2-D Modular Snake Robot in a Confined Space
Classens, Koen Hendrik Johan	Eindhoven University of Technology
Javaheri Koopaee, Mohammadali	University of Canterbury
Pretty, Christopher	University of Canterbury
Weiland, Siep	Eindhoven Univ. of Tech
Chen, Xiaoqi	University of Canterbury
Keywords: Mobile robots, Mechatronic systems, Modeling Abstract: A model-based optimal gait is obtained for the 2-D locomotion of a modular snake robot in a duct. Optimality is considered in the sense of traveling as fast as possible or traveling with minimal energy consumption. The novelty of the work lies in the development of a framework to cast the full dynamic behavior, including contact constraints with simple objects, into an optimization problem which allows for gait parameter, control parameter and/or physical parameter optimization. Optimal gait and control parameters are found via a surrogate optimization procedure which reveals optimal locomotion strategies depending on the duct width and optimization criteria. The framework is tested and illustrated with a number of optimizations of 2-D locomotion of a snake robot where either traveling time or energy consumption is minimized.
Paper VI143-07.30
PDF · Video · Reconfiguration Strategy for a Heavy Mobile Robot with Multiple Steering Configurations
Kumar, Pushpendra	Graphic Era Deemed to Be University
Bensekrane, Ismail	University of Lille
Lakhal, Othman	University Lille 1, CRIStAL, CNRS-UMR 9189,
Merzouki, Rochdi	Polytech'Lille
Keywords: Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Autonomous Mobile Robots, Vehicle dynamic systems Abstract: A redundant robot can complete a given task even in a faulty situation using its alternative configurations. This paper presents a reconfiguration strategy for a redundant heavy mobile robot called Robutainer. It is a four wheeled mobile robot, which is used to transport 40 feet container in port terminals. Robutainer has redundant steering actuations for the front and rear sides, due to this redundancy, it shows four steering configurations namely, dual, front, rear, and skid. Thus, Robutainer can reconfigure between its four steering configurations when subjected to a fault in the steering system. But, it is necessary to detect and isolate a fault in the steering system; subsequently, the robot can be reconfigured according to the available steering configurations. The steering system of Robutainer is a complex multi-domain system with hybrid dynamics. In this work, a graphical modeling approach Bond Graph (BG) is used to develop the fault detection and isolation (FDI) model of the steering system considering its multi-domain components including electric motor, pump, accumulator, hydraulic motor, and transmission; moreover, discrete dynamics of distributor valves are included. Finally, a reconfiguration strategy is developed in order to reconfigure the system according to faults in the components of the steering system. The developed algorithm is verified through simulation in Matlab/Simulink with different components faults, and the experimental data of the robot tracking with four steering configurations is used to develop the reconfiguration strategy.

VI143-08
Robot Manipulators and Control	Regular Session
Chair: Muradore, Riccardo	University of Verona
Co-Chair: Sawodny, Oliver	Univ of Stuttgart
Paper VI143-08.1
PDF · Video · Trajectory Planning for Autonomous Wheeled Mobile Robots with Trailer
Bouzar Essaidi, Ahmed	Ecole Militaire Polytechnique, Laboratoire Mécanique Des Structu
Lakhal, Othman	University Lille 1, CRIStAL, CNRS-UMR 9189,
Coelen, Vincent	Polytech Lille
Belarouci, Abdelkader	Université De Lille, CRIStAL, CNRS-UMR 9189
Haddad, Moussa	Ecole Militaire Polytechnique, Laboratoire Mécanique Des Structu
Merzouki, Rochdi	Ecole Polytechnique Universitaire De Lille
Keywords: Autonomous robotic systems, Mobile robots, Mechatronic systems Abstract: This paper presents a dynamic optimization scheme for generating trajectory planning for autonomous wheeled mobile robots with tractor designed to accomplish missions in indoor environments. Such an optimization criterion problem requires a method that can yield a fast execution time and minimum traveling distance that contains geometrics, kinematics, and physical/environment constraints. The main goal is to develop optimal trajectories planning approach of an autonomous wheeled mobile robots with trailer for the execution of predefined tasks in structures environment. The developed approach can be considered as an extension of the Random Profiles Approach used for wheeled mobile robots. The results also illustrate that thanks to its time optimal trajectories planning, our scheme is well adapted to complex tasks as it can get shorter execution time for the autonomous holonomic tractor with a nonholonomic trailer.
Paper VI143-08.2
PDF · Video · End-Effector Stabilization of a 10-DOF Mobile Manipulator Using Nonlinear Model Predictive Control
Osman, Mostafa Elsaid Abdelaziz	University of Waterloo
Mehrez, Mohamed W.	Memorial University of Newfoundland
Yang, Shiyi	University of Waterloo
Jeon, Soo	University of Waterloo
Melek, William	University of Waterloo
Keywords: Autonomous robotic systems, Robots manipulators, Motion Control Systems Abstract: Motion control of mobile manipulators (a robotic arm mounted on a mobile base) can be challenging for complex tasks such as material and package handling. In this paper, a task-space stabilization controller based on Nonlinear Model Predictive Control (NMPC) is designed and implemented to a 10 Degrees of Freedom (DOF) mobile manipulator which consists of a 7-DOF robotic arm and a 3-DOF mobile base. The system model is based on kinematic models where the end-effector orientation is parameterized directly by a rotation matrix. The state and control constraints as well as singularity constraints are explicitly included in the NMPC formulation. The controller is tested using real-time simulations, which demonstrate high positioning accuracy with tractable computational cost.
Paper VI143-08.3
PDF · Video · An Extension of Barbalat’s Lemma with Its Application to Synchronization of a Class of Switched Networked Nonlinear Systems
Lu, Maobin	City University of Hong Kong
Deng, Fang	Beijing Institute of Technology
Liu, Lu	City University of Hong Kong
Keywords: Autonomous robotic systems, Robots manipulators, Shared control, cooperation and degree of automation Abstract: This paper investigates the leader-following synchronization problem of uncertain Euler-Lagrange multi-agent systems subject to communication delays, disturbances and uniformly connected switching networks. The current settings cause great challenges to the solvability of the problem. To tackle these technical challenges, we make an extension to Barbalat's lemma. Based on the certainty equivalence principle, we propose a novel adaptive distributed control law and apply the generalized Barbalat's lemma to the synchronization problem. The effectiveness of the main result is demonstrated by an application to synchronization control of practical multiple mechanical systems.
Paper VI143-08.4
PDF · Video · Multi-Inputs and Multi-Outputs Equivalent Model Based on Data Driven Controller for a Robotic System
Gomez Casas, Josué	CINVESTAV-Saltillo
Treesatayapun, Chidentree	CINVESTAV-Saltillo
Morales, America	CINVESTAV-Saltillo
Keywords: field robotics, Robots manipulators, Robotics technology Abstract: This paper proposes the control of a data driven model for an experimental robotic system. The components of the robotic system are a redundant robot and a motion capture system considered them as a Multi-Inputs and Mulit-Outputs system. The Pseudo Jacobian Matrix computes the equivalent model of the robotic system taking into account the input and output signals. Besides, we design the adaptive gains for a proportional controller using an artificial neuro-fuzzy network for the robot’s end-effector control. The experimental results validate the proposed control scheme for a regulation control. We provided a Lyapunov analysis to guarantee convergence parameters of the controller.
Paper VI143-08.5
PDF · Video · IOC Based Trajectory Generation to Increase Human Acceptance of Robot Motions in Collaborative Tasks
Hoogerwerf, Eert	Delft University of Technology
Bharatheesha, Mukunda	Delft University of Technology
Clever, Debora	ABB AG
Keywords: Intelligent robotics, Robots manipulators, Design, modelling and analysis of HMS Abstract: Collaboration between humans and robots is an important aspect of Industry 4.0. It can be improved by incorporating human-like characteristics into robot motion planning. It is assumed that humans move optimal with respect to a certain objective or cost function. To find this function, also for a robot, we use an inverse optimal control approach identifying what linear weighted combination of physically interpretable cost functions best mimics human point-to-point motions. A bi-level optimization is used, where the upper level compares the optimal robot result of the lower level with human reference motions. Two depth cameras are combined in a setup to record these reference motions. The resulting weighted cost functions are then used to generate new motions for a seven degrees of freedom robot arm. The resulting optimized motions are compared to standard robot motions based on linear interpolation in joint or task space. The comparison is performed by means of a small experiment where preliminary observations show that humans experience these motions as more anthropomorphic and feel at least equally comfortable and safe compared to existing motion planning strategies.
Paper VI143-08.6
PDF · Video · Dynamic In-Hand Regrasping Using a High-Speed Robot Hand and High-Speed Vision
Higo, Ryosuke	The University of Tokyo
Senoo, Taku	Hiroshima University
Ishikawa, Masatoshi	Univ. of Tokyo
Keywords: Intelligent robotics, Robots manipulators, Robotics technology Abstract: This paper presents a robust and high-speed in-hand regrasping strategy on a two-dimensional plane. The proposed strategy features dynamic motion using a non-contact state with fingers. We used a pair of two-degrees-of-freedom fingers of a high-speed multi-fingered hand and a high-speed vision system. The proposed regrasping strategy consists of three phases: rotating, releasing, and catching. In all phases, visual information captured using a high-speed camera was used. The target state is the state in which the object is rotated 90° from the initial state. Experiments were conducted with different initial grasp positions for three cubes with different diameters and masses. In the experiments, 60 regraspings were performed. We achieved a 100% success rate (60/60). Each regrasping was completed in less than 0.2 s, and the results confirmed that the proposed approach represents a robust and high-speed regrasping strategy.
Paper VI143-08.7
PDF · Video · Online Noise-Estimation-Based Neighbor Selection for Multi-Manipulator Systems
Shen, Henghua	Dalhousie University
Pan, Ya-Jun	Dalhousie University
Bauer, Georgeta	Dalhousie University
Keywords: Networked robotic system modeling and control, Robots manipulators, Motion Control Systems Abstract: In this paper, a novel online neighbor selection policy is proposed in the control of nonlinear networked multi-manipulator systems where manipulators' joints' signals are subject to varying noise levels. By addressing the issue in many conventional control methods of multiagent systems (MASs) where all available neighbor signals are used without evaluating the quality of the information, efforts of this paper seek to improve the overall tracking performance by actively selecting neighbor feedback signals in the robust non-singular terminal sliding mode (NTSM) control. A fast neighbor selection scheme is presented by incorporating an online noise covariance estimation into a nonlinear continuous-discrete unscented Kalman filter (CD-UKF). A selection index vector is recursively updated by the estimated noise covariance matrix for the control design. Simulation results of a group of six degrees of freedom (with three actuated joints) Phantom Omni models demonstrate the effectiveness of the online neighbor selection approach and compare it to previous work which does not actively select neighbor candidates.
Paper VI143-08.8
PDF · Video · Disturbance Observer Based Control for Quasi Continuum Manipulators
Müller, Daniel	University of Stuttgart
Veil, Carina	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Robotics technology Abstract: Nowadays, robots are an essential part of modern production lines, usually working in a designated area since they can pose a threat to human workers. The so-called soft robots constitute a human-friendly alternative to classic industrial robots, even allowing for human-machine collaboration. This is possible due to their soft and therefore inherent safe structure. In this paper we consider quasi continuum manipulators (QCMs), a special kind of soft robots. Their dynamic behavior is affected by friction as well as their soft materials. Dynamical models are thus hard to identify, suffering from imperfections and uncertainties. To overcome these flaws we propose a disturbance observer (DOB) based controller using an extended Kalman filter (EKF). We show superior performance on a real robot compared to an existing benchmark concept based on a PID-like controller. The generalization of this approach is demonstrated by implementing our method on two QCMs with different kinematics.
Paper VI143-08.9
PDF · Video · Towards an Open Toolchain for Fast Nonlinear MPC for Serial Robots
Astudillo, Alejandro	KU Leuven
Gillis, Joris	KU Leuven
Decré, Wilm	Katholieke Universiteit Leuven
Pipeleers, Goele	Katholieke Universiteit Leuven
Swevers, Jan	K. U. Leuven
Keywords: Robotics technology, Autonomous robotic systems, Robots manipulators Abstract: This paper presents an open toolchain tailored for deployment of nonlinear model predictive control for serial robots. The toolchain provides a direct workflow from problem definition to solution deployment on a serial robot based on open-source software. Thus, we provide an insightful selection of modules for rigid body dynamics, numerical optimization, and robot control, and a strategy to make them cooperate in a way that is efficient in terms of computation and engineering time. A detailed numerical study is presented for path-following MPC on a 7-degrees-of-freedom robot, showing the efficiency and ease of use of the presented toolchain while comparing its modules with other tools.
Paper VI143-08.10
PDF · Video · Spline-RRT*: Coordinated Motion Planning of Dual-Arm Space Robot
Yu, Min	Northwestern Polytechnical University
Luo, Jianjun	Northwestern Polytechnical University
Wang, Mingming	Northwestern Polytechnical University
Gao, Dengwei	Northwestern Polytechnical University
Keywords: Robotics technology, Guidance navigation and control, Robots manipulators Abstract: This paper addresses the coordinated motion planning issue for a dual-arm free-floating space robot. Based on the sampling-based planning method, a novel coordinated RRT*-based path planning framework is proposed for a dual-arm manipulation. First, an asymptotically optimal sampling-based method, RRT*, is employed to generate the initial rough path for each end-effector in the task-space. To avoid self-collision, we present a coordinated strategy which samples from separated inertial spaces when performing RRT* algorithm. Second, quartic splines are used to smooth the generated RRT* path so that the robot can execute smoothly. Physical constraints including the end-effectors' limit, joint limit and boundary conditions are all controlled within the design of the quartic splines. The effectiveness of the proposed path planning framework is illustrated and demonstrated via a kinematically redundant dual-arm space robot.
Paper VI143-08.11
PDF · Video · Motion Planning with Cartesian Workspace Information
Liu, Bangshang	Faculty of Electrical and Computer Engineering, Technische Unive
Scheurer, Christian	KUKA Deutschland GmbH
Janschek, Klaus	Technische Universität Dresden
Keywords: Robotics technology, Guidance navigation and control, Robots manipulators Abstract: We propose three extensions to the known sampling-based Exploring/Exploiting Tree (EET) Robot Motion Planner with following considerations: a) robot joint motion bounds, b) additional constraints on robot end-effector pose and c) parallelization of planning procedures to get alternative solutions. We also tackle the gap between global and local motion planning by combining sampling-based motion planning and reactive control approaches. These modifications complement the EET algorithm, which enables our planners to be more beneficial for practical applications. The experimental results demonstrate that our extended EET planners outperform other state-of-the-art sampling-based motion planners for some planning problems according to criteria such as planning time and path length.
Paper VI143-08.12
PDF · Video · Variable-Impedance and Force Control for Robust Learning of Contact-Rich Manipulation Tasks from User Demonstration
Enayati, Nima	ABB AG
Mariani, Stefano	Politecnico Di Milano
Wahrburg, Arne	ABB Corporate Research
Zanchettin, Andrea Maria	Politecnico Di Milano
Keywords: Robotics technology, Intelligent robotics, Co-Learning and self-learning Abstract: This paper proposes a Cartesian variable-impedance and force controller that enables manipulators to accurately track position and force references demonstrated by a user through kinesthetic teaching. The proposed approach deploys the variability of user demonstrations to adapt the compliance profile of the manipulator to uncertainties and utilizes interaction force measurements during task reproduction to enhance force tracking performance. A passivity analysis is provided to demonstrate the stability of the system and a simulation exemplifies how passivity is achieved in the presence of variable impedance and force feedback. Furthermore, using a 7-DOF manipulator equipped with a force sensor, two experiments were conducted to highlight the ability of the proposed approach in successfully reproducing tasks with disturbances, where the state-of-the-art methods fall short.
Paper VI143-08.13
PDF · Video · Comparison of KVP and RSI for Controlling KUKA Robots Over ROS
Arbo, Mathias Hauan	Norwegian University of Science and Technology
Eriksen, Ivar	Norwegian University of Science and Technology
Sanfilippo, Filippo	NTNU
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Keywords: Robotics technology, Motion Control Systems, Robots manipulators Abstract: In this work, an open-source ROS interface based on KUKAVARPROXY for control of KUKA robots is compared to the commercial closed-source Robot Sensor Interface available from KUKA. This comparison looks at the difference in how these two approaches communicate with the KUKA robot controller, the response time and tracking delay one can expect with the different interfaces, and the difference in use cases for the two interfaces. The investigations showed that the KR16 with KRC2 has a 50 ms response time, and RSI has a 120 ms tracking delay, with negligible delay caused by the ROS communication stack. The results highlight that the commercial inferface is more reliable for feedback control tasks, but the proposed interface gives read and write access to variables on the controller during execution, and can be used for simple motion and tooling control.
Paper VI143-08.14
PDF · Video · Position Control of Soft Manipulators with Dynamic and Kinematic Uncertainties
Franco, Enrico	Imperial College London
Tang, Jacky	Imperial College London
Garriga-Casanovas, Arnau	Imperial College London
Rodriguez y Baena, Ferdinando	Imperial College London
Astolfi, Alessandro	Imperial Col. London & Univ. of Rome Tor Vergata
Keywords: Robotics technology, Robots manipulators, Motion Control Systems Abstract: This work investigates the position control problem for a soft continuum manipulator in Cartesian space intended for minimally invasive surgery. Soft continuum manipulators have a large number of degrees-of-freedom and are particularly susceptible to external forces because of their compliance. This, in conjunction with the limited number of sensors typically available, results in uncertain kinematics, which further complicates the control problem. We have designed a partial state feedback that compensates the effects of external forces employing a rigid-link model and a port-Hamiltonian approach and we have investigated in detail the use of integral action to achieve position regulation in Cartesian space. Local stability conditions are discussed with a Lyapunov approach. The performance of the controller is compared with that achieved with a radial-basis-functions neural network by means of simulations and experiments on two prototypes.
Paper VI143-08.15
PDF · Video · Manipulability Optimization for Coordinated Motion Control of Multi-Arm Space Robots
Xu, Ruonan	Northwestern Polytechnical University
Luo, Jianjun	Northwestern Polytechnical University
Wang, Mingming	Northwestern Polytechnical University
Keywords: Robotics technology, Robots manipulators, Motion Control Systems Abstract: By maximizing manipulability, the coordination of multi-arm can be enhanced. In this paper, a method to optimize the manipulability index of cooperative manipulation for a free-floating multi-arm space robot is proposed. Firstly, the manipulability optimization is formulated as a nonlinear optimize problem at position level which is hard to solve online. By redefining constraint equation and manipulability index, it is transformed to a constrained quadratic program problem at velocity level incorporating joint velocity physical limits, which generates joint velocity commands to control the multi-arm to complete predefined tasks. Owing to dynamic coupling effects and closed chain constraints formed by cooperative manipulation, the manipulability index is more complex than that of fixed-base or mobile-base manipulators. Hence, the gradient of the index is approximated by numerical algorithms. Simulations based on a dual-arm space robot model are conducted and the results prove that the proposed method is efficient to optimize the manipulability index.
Paper VI143-08.16
PDF · Video · An Optimisation-Based Distributed Cooperative Control for Multi-Robot Manipulation with Obstacle Avoidance
He, Yanhao	University of Kaiserslautern
Wu, Min	University of Kaiserslautern
Liu, Steven	University of Kaiserslautern
Keywords: Robotics technology, Robots manipulators, Networked robotic system modeling and control Abstract: Multi-robot manipulation systems are usually high-dimensional, kinematically complex and the internal forces are sensitive to robot motion errors due to the physical coupling, especially when the manipulated object is rigid. In this work, a distributed cooperative controller is designed for this scenario. Besides transporting the object, obstacle avoidance and manipulability enhancement are also achieved online by a novel optimisation-based approach. Since the local controller does not require the other robots to send the model or joint-space data, the system is flexible and the communication cost is minimal. Experiments show that no internal force is generated when the robots are changing their poses for the additional tasks and the online computation is fast.
Paper VI143-08.17
PDF · Video · Passivity-Based Variable Impedance Control for Redundant Manipulators
Michel, Youssef	Technical University of Munich
Ott, Christian	German Aerospace Center (DLR)
Lee, Dongheui	Technical University of Munich
Keywords: Robots manipulators Abstract: Kinematic redundancy significantly improves the dexterity and flexibility of robotic manipulators. The redundant degrees of freedom can be exploited to fulfill additional tasks that can be executed without disturbing the primary task. In this work, we investigate how a time varying impedance behavior can be embedded into redundant manipulators where it is desired to achieve such a behavior both for the primary and null space tasks. A passivity based controller is developed, relying on the concept of energy tanks which are filled by the dissipated power in the system, and compensate for non-passive control actions. This guarantees that the system remains passive, which ensures stable interactions with any passive environment. The method is validated in simulations where the interactive behavior of the main and null space tasks is specified by a time varying stiffness profile
Paper VI143-08.18
PDF · Video · Trajectory Planning with Obstacle Avoidance for a Concrete Pump Using Harmonic Potentials
Wanner, Julian	University of Stuttgart
Brändle, Felix	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Robots manipulators, Human operator support, Mechatronics Abstract: The operation of concrete pumps is increasingly supported by assistance systems. They facilitate the complex control task and reduce the risk of accidents. In this paper a trajectory planner for point-to-point motion of a concrete pump is presented. The method is based on harmonic artificial potentials to plan the tool center point motion in the task space and constrained quadratic optimization to convert the task space motion into the configuration space. The algorithm is validated by simulation for a five-link concrete pump.
Paper VI143-08.19
PDF · Video · Method of Identification of Kinematic and Elastostatic Parameters of Multilink Manipulators without External Measuring Devices
Yukhimets, Dmitry	Institute of Automation and Conrtol Processes FEB RAS, Far Easte
Gubankov, Anton	Far Eastern Federal University
Keywords: Robots manipulators, Identification and control methods, Mechatronics Abstract: The paper deals with a method of identification of kinematic and elastostatic parameters of multilink industrial manipulators. This method does not require complex and expensive equipment for high-precision external measurements of position and orientation of the working tool in the Cartesian coordinate system. The method allows simple and cheap means to significantly increase the dynamic accuracy of the movement of working tools of serial manipulators along spatial trajectories during the performance of various technological operations of real production. The simulation is considered.
Paper VI143-08.20
PDF · Video · Real Time Inverse Kinematics Using Dual Particle Swarm Optimization DPSO of 6-DOF Robot for Nuclear Plant Dismantling
Khan, Muhammad Hamza	Pusan National University
Kim, Hyun-Hee	Pusan National University
Abbasi, Saad Jamshed	Pusan National University
Lee, Min Cheol	Pusan National Univ
Keywords: Robots manipulators, Intelligent robotics, Decision making support Abstract: Robotic manipulator inverse kinematics (IK) solution has a significant role in robotics. In this paper, a new paradigm of particle swarm optimization (PSO) called dual particle swarm optimization (DPSO) for the inverse kinematics problem of a robotic manipulator used in the nuclear plant decommissioning process is proposed. The introduced approach of particle swarm optimization relies on the approach of dividing one particle swarm optimization algorithm into two such that each algorithm optimizes separately the problem for position and orientation, in this way the system will achieve faster convergence toward desired results with fewer iterations. The proposed algorithm is designed and implemented in MATLAB/Simulink to solve the inverse kinematics problem for a 6 degree of freedom selective compliance articulated robot arm (SCARA) type robot with joint space constraints. For a real-time experiment, a pair of the joysticks was integrated with MATLAB/Simulink. Using a dual joystick, the position and orientation for the robot were set. Furthermore, the experimental results demonstrate the effectiveness of DPSO on real-time within given constraints.
Paper VI143-08.21
PDF · Video · Model Predictive Interaction Control for Industrial Robots
Gold, Tobias	Friedrich-Alexander-University Erlangen-Nuremberg
Völz, Andreas	Friedrich-Alexander-Universität Erlangen-Nürnberg
Graichen, Knut	Friedrich-Alexander-University Erlangen-Nuremberg
Keywords: Robots manipulators, Intelligent robotics, Identification and control methods Abstract: This paper discusses the use of model predictive control MPC) for industrial robot applications with physical robot- nvironmental interaction. A model predictive interaction control (MPIC) scheme is introduced that deals both with the prediction of the robot motion and the forces between robot and environment. With regard to the robot motion, either the rigid body dynamics, a simplified model, or a cascaded control structure can be employed. The external forces or torques are treated as additional state variables whose dynamics are based on the elastic behavior of the contact surface. Since the force prediction depends on the knowledge of the environmental stiffness, a method for online estimation is discussed. The approach allows to realize different tasks as motion control, compliance control, direct force control as well as hybrid force/motion control by adjusting the weighting factors in the cost function. The implementation is based on the nonlinear MPC software Grampc and the library Pinocchio for computation of rigid body dynamics. Besides comparing the different robot dynamics models, the approach is demonstrated for a hand-guiding and a table wiping task.
Paper VI143-08.22
PDF · Video · Learning-Based Approaches for Forward Kinematic Modeling of Continuum Manipulators
Mahamat Loutfi, Imrane	University of Yaounde I
Bouyom Boutchouang, Audrey Hyacinthe	University of Yaounde I
Melingui, Achille	University of Lille1
Lakhal, Othman	University Lille 1, CRIStAL, CNRS-UMR 9189
Biya Motto, Fredéric	Department of Physics, Faculty of Science, University of Yaounde
Merzouki, Rochdi	Ecole Polytechnique Universitaire De Lille
Keywords: Robots manipulators, Modeling Abstract: Forward kinematic model (FKM) is an essential module in the control law design of manipulator robots. Unlike rigid manipulators where it can be easily established, it remains a real challenge for their continuum counterparts. Model-based and learning-based approaches are commonly used for the forward kinematic modeling of continuum manipulators. Model-based approaches generally lead to imprecise FKM models due to several modeling assumptions, while learning-based approaches generally yield acceptable performance. However, the choice of an appropriate learning model remains a challenging task. In the framework of the forward kinematic modeling of continuum manipulators, this paper proposes an experimental and structural comparative study of the commonly used learning models, namely the multilayer perceptron (MLP), radial based functions (RBF), support vector regression (SVR), and Co-Active adaptive neuro-fuzzy inference system (CANFIS). The Compact Bionic Handling Assistant (CBHA) robot is used as an experimental platform and the predictions of the different learning models are compared respectively to a high precision motion capture system. According to the comparative study, we noted better accuracy for SVRs, rapid convergence for RBFs, and a good compromise between learning time and accuracy for MLPs. CANFIS offers accuracy close to that of SVRs but with much shorter learning time.
Paper VI143-08.23
PDF · Video · Influence of the Object Stiffness on the Grasp Stability with Compliant Hand Based on Energetic Approach
Vollhardt, Ugo	CEA
Makarov, Maria	CentraleSupélec
Caldas, Alex	ESME Sudria
Grossard, Mathieu	CEA LIST
Rodriguez-Ayerbe, Pedro	Supelec
Keywords: Robots manipulators, Modeling Abstract: This article presents a stability analysis of object grasping with a compliant multi-fingered robot hand considering the influence of the flexibility of the grasped object on this stability.In this stability analysis we aimed to compute the maximum disturbance that can be withstood by a compliant hand-object system before being destabilized. Here, the case of objects with a compliant behavior that can be represented by a stiffness matrix is addressed.The specific example of beam objects and cylindrical grasps is investigated, a computation of the local stiffness matrix of the beam object is proposed using Euler-Bernoulli theory for beam deflection and the influence of the Young modulus of the beam on the stability is evaluated.
Paper VI143-08.24
PDF · Video · A Learning Framework to Inverse Kinematics of Redundant Manipulators
Jiokou, Gino	University of Yaoundé 1
Melingui, Achille	University of LIlle1
Lakhal, Othman	University Lille 1, CRIStAL, CNRS-UMR 9189,
Kom, Martin	University of Yaoundé 1
Merzouki, Rochdi	Ecole Polytechnique Universitaire De Lille
Keywords: Robots manipulators, Modeling, Mechatronic systems Abstract: This paper proposes a learning framework for solving the inverse kinematics (IK) problem of high DOF redundant manipulators. The latter possess more DOFs than those required to obtain the end effector (EE) pose. Therefore, for a given EE pose, several joint angle vectors can be associated. However, for a given EE pose, if a set of joint angles is parameterized, the IK problem of redundant manipulators can be reduced to that of non-redundant ones, such that the closed-form analytical methods developed for non-redundant manipulators can be applied to obtain the IK solution. In this paper, some redundant manipulator's joints are parameterized through workspace clustering and configuration space clustering of the redundant manipulator. The growing neural gas network (GNG) is used for workspace clustering while a neighborhood function (NF) is introduced in configuration space clustering. The results obtained by performing a series of simulations on a 7 DOFs redundant manipulator demonstrate the effectiveness of the proposed approach.
Paper VI143-08.25
PDF · Video · Sectorial Fuzzy Controller Plus Feedforward Applied to the Trajectory Tracking of Robot Manipulators
Pizarro-Lerma, Andrés Othón	Instituto Tecnológico De Sonora
Santibanez, Victor	Instituto Tecnologico De La Laguna
Garcia, Ramon	Instituto Tecnológico De La Laguna
Villalobos Chin, Jorge Alberto	Tenológico Nacional De México/Instituto Tecnológico De La Laguna
Keywords: Robots manipulators, Motion Control Systems Abstract: In this paper, we propose a novel sectorial fuzzy controller plus feedforward for the trajectory tracking control of robot manipulators. An outline of the stability proof via Lyapunov criterion of the proposed controller is given. Experimental results are presented in comparison to its classical counterpart: The Proportional-Derivative (PD) plus feedforward controller, from which this new proposal is based. The results obtained using the proposed controller indicate a better performance in terms of joint position error and tolerance to parametric variations.
Paper VI143-08.26
PDF · Video · Adaptive Artificial Potential Fields with Orientation Control Applied to Robotic Manipulators
Viturino, Caio	Universidade Federal Da Bahia
de Melo Pinto Junior, Ubiratan	Universidade Federal Da Bahia
Conceicao, Andre Gustavo Scolari	Federal University of Bahia
Schnitman, Leizer	Federal University of Bahia
Keywords: Robots manipulators, Motion Control Systems, Guidance navigation and control Abstract: This paper proposes the integration of an Adaptive Artificial Potential Fields algorithm with an end effector orientation control technique for real-time robot path planning. The development of autonomous robotic systems has undergone several advances in path planning algorithms. These systems generate object collision free paths in the robot’s workspace. In this context, the Artificial Potential Fields technique has been the focus of improvements in recent years due to its simplicity of application and efficiency in real-time systems, since it does not require a global mapping of the robot’s workspace. In spite of its efficiency, this technique is susceptible to local minimum problems of different natures, such as Goals Non-Reachable with Obstacles Nearby. To solve this problem, an improvement called Adaptive Artificial Potential Fields is used in conjunction with a proposed end effector orientation control technique, which allows to reach a desired orientation of the end effector. The resulting force, generated from the Adaptive Artificial Potential Field, guides the robot end effector to the goal. The Robot Operating System (ROS) framework and a collaborative robot manipulator UR5 are used to validate the proposed method on an approach task for an object on a 3D printer tray.
Paper VI143-08.27
PDF · Video · Globally Asymptotic Output Feedback Tracking of Robot Manipulators with Actuator Constraints
Su, Y. X.	Xidian Univ
Zheng, Chunhong	Xidian Univ
Mercorelli, Paolo	Leuphana University of Lueneburg
Keywords: Robots manipulators, Motion Control Systems, Identification and control methods Abstract: This paper revisits the problem of asymptotic tracking for robot manipulators with actuator constraints and position measurements only. A new dynamic nonlinear filter is first proposed and then a saturated output feedback proportional-derivative (PD) control is constructed. Lyapunov's direct method is employed to show global asymptotic stability (GAS). Explicit conditions on control gains ensuring GAS and avoidance of actuator constraints are obtained. This is accomplished by selecting control gains a priori. Advantage of the proposed approach is that it can assure GAS and satisfy actuator constraints. Numerical simulations are presented to demonstrate the improved performance of the proposed approach.
Paper VI143-08.28
PDF · Video · A New Control Scheme of Cable-Driven Parallel Robot Balancing between Sliding Mode and Linear Feedback
Picard, Etienne	IRT Jules Verne
Tahoumi, Elias	Ecole Centrale Nantes
Plestan, Franck	Ecole Centrale De Nantes-LS2N
Caro, Stéphane	CNRS, LS2N
Claveau, Fabien	Ecole Des Mines De Nantes
Keywords: Robots manipulators, Motion Control Systems, Modeling Abstract: This paper deals with the design of a robust control scheme for a suspended Cable-Driven Parallel Robot (CDPR), composed of eight cables and a moving-platform (MP), for a pick-and-place application of metal plates of various shapes, sizes and masses. The set composed of the MP and a metal plate can have a mass of up to 700 kg. In order to achieve good accuracy and repeatability of the MP pose despite the variability of the transported mass, a robust control scheme must be implemented on the robot. A recently developed controller balancing between sliding mode and linear algorithms (SML) is considered for the application. The performances of the SML controller are analyzed on a CDPR prototype located at IRT Jules Verne, Nantes, France, along a test trajectory for several payloads. The results obtained without any information on the platform or metal plate mass are compared to those of standard proportional-derivative (PD) based control schemes.
Paper VI143-08.29
PDF · Video · Synchronising H-Infinity Robust Distributed Controller for Multi-Robotic Manipulators
Farnam, Arash	Ghent University
Crevecoeur, Guillaume	Ghent University
Keywords: Robots manipulators, Networked robotic system modeling and control, Shared control, cooperation and degree of automation Abstract: In this paper the problem of synchronisation of multiple robotic manipulators using H-infinity robust distributed control systems with respect to the parameter uncertainties and disturbance inputs acting on the manipulators is addressed. Robust synchronising controllers only use the information of outputs of the manipulators, and the corresponding parameters of these output-feedback controllers are designed by computing a series of linear matrix inequalities instead of solving the complex differential (e.g. Hamilton-Jacobi) (in)equalities. The proposed controller can guarantee H-infinity robust performance with respect to the external disturbance inputs and parameters uncertainties, asymptotic stability and synchronisation in the networked manipulators. Using an illustrative example we compare the results extracted in this paper to other works existing in the literature.
Paper VI143-08.30
PDF · Video · Control of Sliding Velocity in Robotic Object Pivoting Based on Tactile Sensing
Costanzo, Marco	Università Degli Studi Della Campania Luigi Vanvitelli
De Maria, Giuseppe	Università Degli Studi Della Campania L. Vanvitelli
Natale, Ciro	Università Degli Studi Della Campania "Luigi Vanvitelli"
Keywords: Robots manipulators, Perception and sensing, Autonomous robotic systems Abstract: Control of robots manipulating objects using only the sense of touch is a challenge. In-hand motion of the manipulated object highly depends on the friction forces acting at the contact surfaces. Soft contacts allow torsional frictions as well as friction forces, therefore robots can perform more complex manipulation abilities like object pivoting. Control of the pivoting sliding motion is very difficult, especially without any visual feedback. The paper proposes a novel method to control the sliding velocity of the object by using a simple parallel gripper endowed with force/tactile sensors only. The strategy is based on a nonlinear observer that estimates the sliding velocity from force/torque measurements and a model of the sliding dynamics.
Paper VI143-08.31
PDF · Video · Heuristic Path Planning Approach for a Granular-Fill Insulation Distributing Robot
Gsellmann, Peter	TU Wien
Melik-Merkumians, Martin	Technische Universität Wien
Hurban, Milan	TU Wien
Schitter, Georg	Vienna University of Technology
Keywords: Robots manipulators, Perception and sensing, field robotics Abstract: In this paper, a heuristic path planning approach for the robotic distribution of granular-fill insulation material is presented. The initial coarse manual distribution of the material leads to an uneven surface with areas of excessive or insufficient material. In order to distribute the granular-fill insulation uniformly with a robot, first the worked area is captured as point cloud with an RGB-D camera, and afterwards these irregularities are located via agglomerative hierarchical clustering. Subsequently, their volumes are estimated providing weights for the path calculation. A path planning method, inspired by the usual working method of human construction workers, is developed and applied. In a test scenario, the total path length and the processing sequence are analysed, varying the blade size and the weight of the distance-to-goal parameter. This analysis yields, that the presented path planning algorithm is well suited for the described application, showing the best results with a larger blade size and a quadratic distance-to-goal behavior.
Paper VI143-08.32
PDF · Video · Pose Estimation and Tracking Control of a Pneumatic Soft Robotic Hand
Gastinger, Julia	University of Stuttgart
Müller, Daniel	University of Stuttgart
Hildebrandt, Alexander	Universitaet Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Robots manipulators, Robotics technology, Autonomous robotic systems Abstract: The use of soft robotics offers opportunities which cannot be achieved with conventional rigid robots, including adaptive interactions with humans (Kim et al. (2013)). This article presents the state estimation and tracking control for a soft robotic hand with 12 degrees of freedom (DOF). In the work we achieve orientation estimation of phalanges and palm using a Multiplicative Extended Kalman-Filter (MEKF) yielding an average mean absolute error of less than 3.5°. Additionally we use the estimatied orientations for a tracking control for the finger poses. Experiments show that we are able to control the position of the fingers with sufficient accuracy and speed.
Paper VI143-08.33
PDF · Video · A 3D Path Following Control Scheme for Robot Manipulators
Wen, Yalun	Texas A&M University
Pagilla, Prabhakar R.	Texas A&M University
Keywords: Robots manipulators, Robotics technology, Mechatronics Abstract: In this paper we describe a novel path following control scheme for robot manipulators where constant tool velocity of travel on a surface is desirable. The path following scheme is applicable to general situations where the surface geometry is typically given in terms of measured data from a sensor. Considering the measured data points as control points, we utilize a cubic spline interpolation to generate a closed-form geometric description for the 3D path. Since joint velocity control is quite common in many industrial robots and most surface finishing tasks require travel with constant velocity along the path, we consider a 3D kinematic model for the end-effector with control inputs as rate of change of orientation and translational velocity that is locally tangent to the surface along the path. By utilizing a path variable and the tangent vector along the path, we formulate a converging path as the path that is traversed from a given robot end-effector position to the desired path and subsequent travel on the desired path on the surface. To evaluate the performance of the scheme, we have conducted a number of real-time experiments on a six degree-of-freedom industrial robot for several example paths which can be employed for sanding of structures, such as aircraft blades and cabin structures, and deburring of large industrial cast parts and gears.
Paper VI143-08.34
PDF · Video · Safe Tracking Control of Euler-Lagrangian Systems Based on a Novel Adaptive Super-Twisting Algorithm
Zhang, Zengjie	Technical University of Munich
Wang, Yongchao	Technical University of Munich
Wollherr, Dirk	Technical University of Munich
Keywords: Robots manipulators, Security and safety of HMS, Mechatronics Abstract: In this paper, a novel adaptive second-order sliding mode controller is designed for Euler-Lagrangian systems with hard safety constraints. Different from the conventional sliding mode controllers, the proposed method provides adaptive controller parameters, such that the robustness of the controller is ensured without bringing up chattering. The controller also guarantees strict compliance to hard state-dependent inequality constraints. The asymptotic convergence of the tracking errors of the proposed controller is proven by a direct Lyapunov method. Finally, the proposed controller is validated by numerical simulation on a three-degree-of-freedom robot platform. The results confirm that the controller ensures strict constraint compliance and precise trajectory tracking, which reveals its potential applicability to the safe control of mechatronic systems.
Paper VI143-08.35
PDF · Video · Elasticity-Aware Online Motion Optimization for Link-Elastic Manipulators
Krämer, Maximilian	TU Dortmund University
Muster, Freia Irina	TU Dortmund University
Rösmann, Christoph	TU Dortmund University
Bertram, Torsten	Technische Universität Dortmund
Keywords: Robots manipulators, Vibration control, Motion Control Systems Abstract: The field of human-robot interaction is a typical application of elastic robots, as they reduce the risk of injuries and physical damage in case of a collision. Elasticities, however, also impose high demands on underlying joint controllers to guarantee minimal vibration during regular operation. Numerous control concepts assume a sufficiently high ability to control vibrations, by e.g., dedicated actuators or special kinematic structures. This work presents an online, optimization-based trajectory planning approach that concentrates on maximizing this ability for elastic manipulators without additional damping actuators or certain kinematic structures. The planning algorithm utilizes a modified quadratic objective function to incorporate the controllability of vibrations as a secondary goal. The effectiveness of the approach is demonstrated on a real 3-DOF, link-elastic robot for different set-points subject to disturbances. The results show that the approach successfully generates elasticity-aware motions and improves the vibration damping capabilities of the underlying controllers. Especially for critical configurations in which the controllers usually have little or no influence on the vibrations, vibration damping is improved or even made possible.
Paper VI143-08.36
PDF · Video · A Variable Stochastic Admittance Control Framework with Energy Tank
Cordoni, Francesco Giuseppe	University of Verona
Di Persio, Luca	University of Verona
Muradore, Riccardo	University of Verona
Keywords: Autonomous robotic systems, Guidance navigation and control, Robots manipulators Abstract: In this paper we address the problem of implementing a stochastic variable admittance control. Both the variable part of the admittance control and the noise affecting the system may concur to the instability of the system. We propose an energy tank approach, based on the theory of stochastic port--Hamiltonian systems and weak passivity, where the energy dissipated by the stochastic system, if any, is stored into the tank to implement the desired actions. As we consider a non--vanishing noise, we need to consider weaker notion of passivity and convergence. We will show how the notion of weak passivity can be properly defined so that equipping a stochastic system with a suitable energy tank, variable admittance control can be efficiently implemented. We prove that the overall system is weakly passive and it converges toward an invariant measure. Simulation results show the effectiveness of the derived theoretical framework.
Paper VI143-08.37
PDF · Video · Kinematic Control of Serial Manipulators Using Clifford Algebra
Shahidi, Amirreza	RWTH Aachen University
Hüsing, Mathias	Institut Für Getriebetechnik, Maschinendynamik Und Robotik, RWTH
Corves, Burkhard	Rwth Aachen University
Keywords: Robots manipulators, Autonomous robotic systems, Mechatronic systems Abstract: We exploit the potentials of Clifford algebra to present a singularity free, compact, and computationally efficient scheme for kinematic control of serial manipulators. We introduce and implement the new special proportional-derivative control scheme. The introduced control scheme facilitates a fast motion control for the manipulators and enables them to react to the changes in their set points quickly. Such conditions are common in the context of dynamic working environments and collaborative manipulation scenarios. We describe the kinematics of the manipulators with unit dual quaternions using screw theory. The Lie-group properties of quaternions and dual quaternions are presented and discussed. By means of Lyapunov theory, it will be shown that the controller is globally exponentially stable.

VI143-09
Robotic Technology	Regular Session
Chair: Melchiorri, Claudio	University of Bologna
Co-Chair: Becker, Leandro	Federal University of Santa Catarina
Paper VI143-09.1
PDF · Video · Embedded Architecture Composed of Cognitive Agents and ROS for Programming Intelligent Robots
Silva, Gustavo Rezende	Universidade Federal De Santa Catarina
Becker, Leandro	Federal University of Santa Catarina
Hübner, Jomi	Universidade Federal De Santa Catarina
Keywords: Intelligent robotics, Flying robots, Hardware-in-the-loop simulation Abstract: This paper proposes and evaluates an embedded architecture aimed to promote the utilization of cognitive agents in cooperation with the Robotic Operating System (ROS), serving as an alternative for programming intelligent robots. It promotes the programming abstraction level in two directions. The first direction regards using cognitive agents facilities for programming the robots intelligence, consisting of its perceptions and related actions. The second direction exploits the facilities of using ROS layers for programming the robot interaction with its sensors and actuators. The paper reports experiments of using agents to command simulated UAVs while measuring performance metrics that allowed us to evaluate the benefits of the proposed architecture.
Paper VI143-09.2
PDF · Video · A Hybrid Genetic Algorithm for Pallet Loading in Real-World Applications
Ancora, Gabriele	University of Bologna
Palli, Gianluca	University of Bologna
Melchiorri, Claudio	University of Bologna
Keywords: Robotics technology, Decision making support, Modeling Abstract: This paper addresses the so called "Distributor's Pallet Packing Problem" in a real industrial scenario. The main goal is to develop an algorithm for loading heterogeneous rectangular boxes on a bin, minimizing some objective functions and also satisfying geometric, stability and fragility constraints. The algorithm must be able to provide, in a reasonable time, the spatial coordinates of the vertices of the placed boxes and also the optimal boxes input sequence. Since this type of combinatorial problem is classified as NP-hard, classical optimization techniques are not suitable. For these reasons, a metaheuristic approach has been developed in order to reduce burden complexity. In particular, a genetic algorithm hybridized with an innovative heuristic technique has been used. The validity and the performance of this algorithm have been tested on several packing instances (orders) provided by an industrial company. The paper is intended as a preliminary study for future developments in the area of industrial container loading problems.
Paper VI143-09.3
PDF · Video · Fast and Intuitive Kinematics Mapping for Human-Robot Motion Imitating: A Virtual-Joint-Based Approach
Wang, Ziwei	Tsinghua University
Liang, Rongjian	Texas A&M University
Chen, Zhang	Tsinghua University
Liang, Bin	Tsinghua University
Keywords: Robotics technology, Human operator support, Human-centred automation and design Abstract: It is quite difficult to imitate the motion of human arms using non-humanoid robots due to their dissimilar embodiments (degree-of-freedom, body morphology, and constraints). However, in most cases of the robotic imitation, the human operator and the robot would not share the same kinematic configuration. This paper addresses the motion imitation problem between the human arm and an industrial robot, where a commonly-used UR5 robot is considered. The motion of the human arm is obtained by an inertial motion capture system, and then the captured motion is reproduced using the UR5 embodiment. A virtual-joint-based approach is proposed to facilitate the fast and intuitive kinematics mapping between the human arm and the UR5 robot, leading to a robotic imitation system that can imitate the tip location and configuration of the human arm simultaneously. The proposed approach is verified experimentally on a real UR5 robot and compared with classic Cartesian-space-based mapping approach and joint-space-based approach.
Paper VI143-09.4
PDF · Video · Towards Thruster-Assisted Bipedal Locomotion for Enhanced Efficiency and Robustness
Dangol, Pravin	Northeastern University
Ramezani, Alireza	University of Illinois at Urbana-Champaig
Keywords: Robotics technology, Mobile robots Abstract: In this paper, we will report our efforts in designing closed-loop feedback for the thruster-assisted walking of bipedal robots. We will assume for well-tuned supervisory controllers and will focus on fine-tuning the joints desired trajectories to satisfy the performance being sought. In doing this, we will devise an intermediary filter based on reference governors that guarantees the satisfaction of performance-related constraints. Since these modifications and impact events lead to deviations from the desired periodic orbits, we will guarantee hybrid invariance in a robust way by applying predictive schemes withing a very short time envelope during the gait cycle. To achieving the hybrid invariance, we will leverage the unique features in our model, that is, the thrusters. The merit of our approach is that unlike existing optimization-based nonlinear control methods, satisfying performance-related constraints during the single support phase does not rely on expensive numeric approaches. In addition, the overall structure of the proposed thruster-assisted gait control allows for exploiting performance and robustness enhancing capabilities during specific parts of the gait cycle, which is unusual and not reported before.
Paper VI143-09.5
PDF · Video · Control of Wall Mounting Robot: Practical Implementation and Experiments
Damgaard, Malte Rørmose	Aalborg University
Pedersen, Rasmus	Aalborg University
Hansen, Karl Damkjær	Aalborg University
Bak, Thomas	Aalborg University
Keywords: Robotics technology, Motion Control Systems, Robots manipulators Abstract: Robots are gaining traction in all industries, not only to replace manual labour but also to collaborate and enhance both human and robot skills and abilities. In this paper, we revisit the trajectory following control design for the WallMo Robot, which is a collaborative wall mounting robot used in the construction industry. The theoretical foundation for a model-free control strategy, handling actuator constraints was presented by Sloth and Pedersen (2017) and verified through simulations. In this paper, the research is extended to also include practical implementation considerations and experimental testing on a real WallMo robot. The implemented control strategy differs from what was presented earlier, but still exhibits tight trajectory tracking - solving the control problem in a practical setting.
Paper VI143-09.6
PDF · Video · ROSI: A Mobile Robot for Inspection of Belt Conveyor
Faria, Henrique	Federal University of Rio De Janeiro
Lizarralde, Fernando	Federal Univ. of Rio De Janeiro
Costa, Ramon R.	COPPE - Federal Univ of Rio De Janeiro
Andrade, Ricardo H. R.	Federal University of Rio De Janeiro
Henriques da Silva, Thales	Federal University of Rio De Janeiro
Pereira, Raphael F. S.	Federal University of Rio De Janeiro
Soares, Evelyn B.	Federal University of Rio De Janeiro
Rocha, Filipe Augusto Santos	Vale Institute of Technology
Franca, Andre	Vale S.A
Medeiros Freitas, Gustavo	Vale Institute of Technology (ITV)
Pessin, Gustavo	ITV
Keywords: Mechatronics, field robotics, Mobile robots Abstract: ROSI is a mobile robot designed to inspect belt conveyor machinery in the mining industry. The proposed system is a wheeled and tracked mobile platform equipped with a robotic manipulator and several sensors to allow execution of a scheduled tasks. The detailed mechatronics design is presented including software architecture.
Paper VI143-09.7
PDF · Video · Additive Manufacturing Path Generation for Robot Manipulators Based on CAD Models
Onstein, Ingrid Fjordheim	Norwegian University of Science and Technology
Evjemo, Linn Danielsen	Norwegian University of Science and Technology
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Keywords: Mechatronic systems, Mechatronics, Robots manipulators Abstract: Traditional extrusion based additive manufacturing (AM) is realized using a 3 degrees of freedom (DOF), translation only, 3D printer. It then follows that the printer must be larger than the printed part. One way of enabling AM on a larger scale is to combine AM with robotics. By using a 6 DOF robot manipulator to extrude a fast-curing material, the workspace of the build would be greatly expanded. In addition, since the structures would no longer have to be built with the bottom-up or top-down approach which is necessary for most existing forms of AM, the flexibility of the building process would also increase. This could possibly reduce the need for support structures to the point of only relying of anchoring and stabilizing. In this paper, a method for generating a path for AM using robot manipulators that takes advantage of the robot's DOF is presented. The path is generated based on simple surfaces in CAD models. First, the surface is sampled and the samples are gathered in a point cloud. Then, a path is generated based on the point cloud. Three different approaches for generating a path are tested where the weighted greedy choice algorithm gave the most promising result. With this algorithm, printing along curved surfaces and in nonlinear paths are enabled.
Paper VI143-09.8
PDF · Video · Robotised Wire Arc Additive Manufacturing Using Set-Based Control: Experimental Results
Evjemo, Linn Danielsen	Norwegian University of Science and Technology
Moe, Signe	Norwegian University of Science and Technology
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Keywords: Mechatronic systems, Mechatronics, Robots manipulators Abstract: Additive manufacturing (AM) is a term that covers a variety of techniques for building custom-made, three dimensional structures. Such methods have moved from initially being used for creating simplified models to enable visualising of a product in a developing process, to creating structures that are suitable as end-products (Gibson et al., 2010). This has made prototyping and the production of custom made parts more accessible to small companies and developers, and AM technologies are still gaining momentum. However, traditional methods for AM are limited to building structures that are smaller than the AM apparatus itself, and bound to building structures layer by layer. The motivation for combining AM with a robot manipulator is to increase the workspace of the build, making it possible to build much larger structures, and to deposit material in any direction. The focus of this research is large-scale AM in metal, so the work presented in this paper focuses on a set-based control method for wire-arc additive manufacturing (WAAM) of a cylindrical, thin-walled structure. The set-based control method used to control the robot manipulator allows for some freedom in the orientation of the tool, so that the material is not necessarily deposited strictly vertically. Evaluating how this impacts the structure helps map how feasible this solution is for building more complex structures in future work.

VI143-10
Telerobotics	Regular Session
Chair: Polushin, Ilia G.	Western University
Co-Chair: Melchiorri, Claudio	University of Bologna
Paper VI143-10.1
PDF · Video · Combined Joint-Cartesian Mapping for Simultaneous Shape and Precision Teleoperation of Anthropomorphic Robotic Hands
Meattini, Roberto	University of Bologna
Chiaravalli, Davide	Alma Mater Studiorum, University of Bologna
Biagiotti, Luigi	University of Modena and Reggio Emilia
Palli, Gianluca	University of Bologna
Melchiorri, Claudio	University of Bologna
Keywords: Robots manipulators, Telerobotics, Motion Control Systems Abstract: There are many applications involving robotic hands in which teleoperation-based approaches are preferred to autonomous solutions. The main reason is that cognitive skills of human operators are desirable in some task scenarios, in order to overcome limitations of robotic hands abilities in dealing with unstructured environments and/or unpredetermined requirements. In particular, in this work we focus on the use of anthropomorphic grasping devices and, specifically, on their teleoperation based on movements of the human operator's hand (the master hand.) Indeed, the mapping of human hand configurations to an anthropomorphic robotic hand (the slave device) is still an open problem, because of the presence of dissimilar kinematics between master and slave that produce shape and/or Cartesian errors - as addressed within our study. In this work, we propose a novel algorithm that combines joint and Cartesian mappings in order to enhance the preservation of both finger shapes and fingertip positions during the teleoperation of the robotic hand. In particular, a transition between the joint and Cartesian mappings is realized on the basis of the distance between the fingertip of the master hands' thumb and the opposite fingers, in which the mapping of the thumb fingertip is specifically addressed. The result of the testing of the algorithm with a ROS-based simulator of a commercially available robotic hand is reported, showing the effectiveness of the proposed mapping.
Paper VI143-10.2
PDF · Video · Control of a Telepresence Robot Using Force Data
Yokoyama, Takuya	Tokyo University of Agriculture and Technology
Hernandez, Vincent	GVLAB - Tokyo University of Agriculture and Technology
Rincon, Liz	Tokyo University of Agriculture and Technology
Venture, Gentiane	Tokyo University of Agriculture and Technology
Keywords: telepresence, Identification and control methods, Human operator support Abstract: Telepresence robots are robots intended to compensate for non-verbal information during telecommunication. However, current telepresence robots don't have subcient functionality to send gesture information, within non-verbal information. This research aims to develop a communication system that recognizes the motion of the human and supplements the lack of gesture information by transmitting it to humanoid robots. The method proposed involves motion data acquisition using force data, gesture recognition with CNN (Convolutional Neural Network) and control of a humanoid robot with the transmission of gesture by on-line control. Finally, the proposal is evaluated by the TDMS (Two-Dimensional Mood Scale) to verify the difference from using the current telepresence robot. As a result, we recognized 6 motions with an automatic motion recognition accuracy of 77.8%. Telepresence using a humanoid robot was confirmed to improve comfortable feeling by transmitting a gesture, although a significant difference from existing telepresence robot was not confirmed.
Paper VI143-10.3
PDF · Video · A Generalized Scattering Framework for Teleoperation with Communication Delays
Polushin, Ilia G.	Western University
Keywords: Telerobotics Abstract: The scattering (wave) based teleoperation is currently one of the most popular approaches to bilateral teleoperation with communication delays. Limitations of the conventional scattering-based teleoperation are mostly related to the underlying passivity requirements imposed on the master-human and slave-environment subsystems. In this paper, a generalized scattering framework for bilateral teleoperation with communication delays is outlined, and basic stability results for generalized scattering-based teleoperator systems with delays are established. The proposed framework removes many limitations of the existing scattering-based teleoperation, and allows for much higher flexibility in the control design for the master and slave subsystems.
Paper VI143-10.4
PDF · Video · A Novel Multilateral Control Design for Delayed Nonlinear Teleoperation System with RBFNN-Based Environments (I)
Huang, Fanghao	Zhejiang University
Chen, Zheng	Zhejiang University
Zhu, Shiqiang	Zhejiang University
Gu, Jason	Dalhousie University
Keywords: Telerobotics, Robots manipulators, Motion Control Systems Abstract: In this paper, a novel multilateral control design for nonlinear teleoperation system is proposed to improve the capability of multiple robots to coordinate efficiently and precisely in the remote environments under time-varying delays and various uncertainties. The environment is modeled with a general form of force under radial basis function neural network(RBFNN)-based identification and reconstruction to avoid the passivity issue in the traditional teleoperation control and provide the human operators with good sensing of environments. The desired trajectory producers and RBFNN-based sliding mode controllers are designed separately to achieve the good tracking of master/slave robots, and the coordinated distribution algorithm is designed to obtain the control input u_{s,i} for each slave robot. Therefore, the global stability, good transparency performance with both position tracking and force feedback, and good cooperative performance can be achieved simultaneously for delayed nonlinear teleoperation system. The real platform experiment is carried out on a 2-master-2-slave teleoperation system to verify the effectiveness of proposed control design.
Paper VI143-10.5
PDF · Video · Bilateral Telemanipulation of Unknown Objects Using Remote Dexterous In-Hand Manipulation Strategies
Montaño, Andres	Universitat Politècnica De Catalunya
Suarez, Raul	Universitat Politecnica De Catalunya (UPC)
Aldana, Carlos I.	University of Guadalajara
Nuño, Emmanuel	University of Guadalajara
Keywords: Telerobotics, Robots manipulators, Networked robotic system modeling and control Abstract: This paper presents an approach to perform bilateral in-hand (dexterous) telemanipulation of unknown objects. The proposed approach addresses three of the main problems in telemanipulation: kinematic issues due to the physical differences between the robotic and the human hands; obtaining coherent haptic feedback to provide information about the manipulation at any time; and time-delays that can affect the stability of the overall closed-loop system. The novelty of the approach lays on the shared control scheme, where the robotic hand uses the tactile and the kinematic information to manipulate an unknown object while the operator commands a desired orientation of the object without caring about the relation between her/his commands and the actual hand movements. The viability of the proposed approach has been tested through transatlantic telemanipulation experiments between Mexico and Spain.

VI145
Mechatronics, Robotics and Components - Human Machine Systems
VI145-01 Cognitive Human-Machine Cooperative Systems: Challenges, Opportunities and Advances   Invited Session, 6 papers
VI145-02 Assistive Technology and Rehabilitation Engineering   Regular Session, 7 papers
VI145-03 Human-Robot Collaboration   Regular Session, 9 papers
VI145-04 Multi-Modal Human-Machine Interaction   Regular Session, 4 papers

VI145-01
Cognitive Human-Machine Cooperative Systems: Challenges, Opportunities and Advances	Invited Session
Chair: Vanderhaegen, Frédéric	Université Polytechnique Hauts-De-France
Co-Chair: Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Organizer: Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Organizer: Vanderhaegen, Frédéric	Université Polytechnique Hauts-De-France
Organizer: Sawaragi, Tetsuo	Kyoto Univ
Organizer: Xue, Jianru	Xi'an Jiaotong University
Paper VI145-01.1
PDF · Video · Operator Performance Prediction Based on Fuzzy Modeling Approach (I)
Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Yin, Zhong	University of Shanghai for Science and Technology
Keywords: Modeling of human performance, Cognitive systems engineering, Brain-machine interaction Abstract: In this paper, physiological signals were measured from five participants, each participating in two sessions of experiment with identical experimental procedure. A simulation platform, AutoCAMS (Automation-enhanced Cabin Air Management System), was used to simulate a complex task environment of human-machine shared process control. Fuzzy models were constructed to quantitatively predict the human operator performance based on three EEG input features. The incremental-PID-controlled particle swarm optimization (IPID-PSO) algorithm was utilized to optimize the parameters of fuzzy models. The IPID-PSO algorithm incorporated incremental-PID-controlled search strategy to speed up the convergence of standard PSO algorithm. The operator performance modeling results are given to show the effectiveness of the IPID-PSO-tuned fuzzy modeling approach proposed to momentary operator performance assessment problem under consideration.
Paper VI145-01.2
PDF · Video · Concepts and Models about Smart Urban Transport Control Systems for City Resilience (I)
Enjalbert, Simon	University Polytechnique Hauts-De-France
Kahn-Ribeiro, Suzana	Federal University of Rio De Janeiro
Vanderhaegen, Frédéric	Université Polytechnique Hauts-De-France
Keywords: Design, modelling and analysis of HMS, Resilience of HMS Abstract: The work presented in this paper concerns the control and the efficient assessment of transport systems of a city by studying the impact of climate change, energy supply or human behaviour on different modalities of mobility. Concepts from Human Machine Systems and from green, eco, sustainable, and smart cities, aggregated on resilient city concept, should be an inspiration to develop model for urban transport control systems. A state-of-the-art is proposed to discuss about these concepts and try to determine criteria which should be selected in such process. A first framework based on cooperation and learning concepts is then presented and still must be improved.
Paper VI145-01.3
PDF · Video · A Survey of Gamified Augmented Reality Systems for Procedural Tasks in Industrial Settings (I)
Nguyen, Diep Vinh Ngoc	Heilbronn University
Meixner, Gerrit	Heilbronn University
Keywords: Human-centred automation and design, Design, modelling and analysis of HMS, Human-centred computing Abstract: Gamification is the adoption of game design elements and mechanisms into non-game contexts. As gamification has been a growing approach to increase people's performance in multiple disciplines such as education, service and marketing, it is necessary to question if gamification is also applicable in the industrial setting. In this paper, we discuss the specific requirements of a gamifed Augmented Reality system in an industrial production setting, its applications as well as challenges.
Paper VI145-01.4
PDF · Video · Design of Productive Socio-Technical Systems by Human-System Co-Creation for Super Smart Society (I)
Sawaragi, Tetsuo	Kyoto Univ
Horiguchi, Yukio	Kyoto University
Hirose, Takayuki	Kyoto University
Keywords: Resilience of HMS, Work in real and virtual environments, Modeling of human performance Abstract: The realization of the 'super-smart society' of "Society 5.0" is being promulgated as the 5th Science and Technology Basic Plan by the Japanese Government. This article summarizes what is needed to promote new science and technology for achieving a super-smart society. Especially, to accelerate the development of "control for societal issues," three aspects of "Feedback," "Ring" and "Harmony," each of which corresponds to the means, the object and the goal of the future control-related science and technology, respectively, are to be stressed. That is, the object of science and technology is to target society or community, not single persons and individuals, and we have to understand complex feedback structures made up of many interactions as essential means to attain the goal of harmonizing technology, human and environment. For this purpose, innovations will necessitate elaborating the SoS (System of Systems), mutually connected systems, including human-in-the-loop systems. It would be significant to model and understand the dynamical complexity of such an SoS and to develop a technique for guaranteeing their resilience. This article presents overviews of some of the author group's works that are related to the above three aspects.
Paper VI145-01.5
PDF · Video · Robotic Society -- Main Features for Base Design of Human-Similar AI Robots (I)
Mau, Jochen	Heinrich Heine University Duesseldorf
Keywords: Design, modelling and analysis of HMS, Human-centred automation and design, Cognitive systems engineering Abstract: In the design process of cognitive human-machine systems, focus is on novel engineered components while the human component is generally considered as known, at least at large: as the cognitive ability of a person expresses in communication, verbal and behavioral, within his or her life-sphere surroundings, whether kindergarten, school, neighborhood, work place, leisure activities, or elderly home, its characteristics are persistent patterns that emerge with biological and cognitive development during childhood and adolescence, are shaped by social interaction in adult life, and finally modified by shrinking vitality in biological aging. However, such phenomenalistic categorization is certainly inadequate as communication is actually an expression of in-system functional dynamics and their controls. It is then their high degree of interweavement across several scale levels, that also interlaces the controls of reproductive subsystems with all other functional subsystems within the human body and thus mandates a fundamental distinction between male and female cognition beyond pregnancy and maternity. As the structure of physiological couplings of functional dynamics within the human body is not understood, impact from outside on within-dynamics is analytically unforeseeable for the machine component. A recent axiomatic theory of multi-scale holistic functional biodynamics for human-body system suggests a concept for functionally equivalent virtual machines, ``human-similar AI robots'', that ``live'' through a human life-cycle from childhood to old age, as appropriate for each sex. Concepts of co-existence and co-habitation can then be formalized in a virtual robotic society of human-similar AI robots.
Paper VI145-01.6
PDF · Video · A Gesture Cognition Strategy for High-Speed Train Drivers on Reconstructed Multiple Views
Mu, Yueyue	Central South University
Zhang, Xiaoyong	Central South University
Wang, Chenglong	Central South University
Li, Shuo	Changsha University of Science & Technology
Yang, Yingze	Central South University
Liu, Weirong	Central South University
Peng, Jun	Central South University
Keywords: Human-centred computing, Cognitive systems engineering, Modeling of human performance Abstract: The driver of high-speed trains usually is required to perform certain gestures to confirm the signals before implementing some operations, which is an essential validation for driving safety. However, the accuracy of gesture recognition is difficult to guarantee due to the jamming background and limited perspective. In this paper, the features of the side view and vertical view are integrated to assist classification decisions. Firstly, point clouds of the gesture are generated with RGB-D data and then projected onto two orthogonal planes to reconstruct the side and vertical view of the gesture. Secondly, multiple-view 3D Convolution Neural Network architecture is proposed with three branches of Convolution Neural Network. Combined with the front view obtained by frame difference, the model learns convolution features from three aspects of the gesture. Further, multiple-view classification results are adaptively fused to acquire the final decision. Experiments show that our approach is superior to the state-of-the-art gesture recognition methods on challenging dataset.

VI145-02
Assistive Technology and Rehabilitation Engineering	Regular Session
Chair: Chu, Bing	University of Southampton
Co-Chair: Seel, Thomas	Technische Universitaet Berlin
Paper VI145-02.1
PDF · Video · Robust Cadence Tracking for Switched FES-Cycling with an Unknown Time-Varying Input Delay Using a Time-Varying Estimate
Allen, Brendon C.	University of Florida
Stubbs, Kimberly J.	University of Florida
Dixon, Warren E.	Univ of Florida
Keywords: Assitive technology and rehabilitation engineering, Design, modelling and analysis of HMS, Human-centred automation and design Abstract: For an individual affected by a lower limb movement disorder, motorized functional electrical stimulation (FES) induced cycling provides a means of functional restoration and therapeutic exercise. However, there exists a potentially destabilizing input delay between the application (and removal) of the stimulation and the production of muscle force. Exacerbating the problem, fatigue results in decreased force production and a time-varying input delay. Moreover, switching between FES and motor control can be destabilizing. This paper implements a time-varying estimate of the delay and develops a control method and switching conditions to account for the time-varying input delayed response of muscle. The controller is shown to yield semi-global uniformly ultimately bounded tracking for the uncertain switched nonlinear dynamic system with input delays.
Paper VI145-02.2
PDF · Video · Implementation of LPV H-Infinity Loop-Shaping Control for a Variable Stiffness Actuator
Bergmann, Lukas	RWTH Aachen University
Liu, Lin	RWTH Aachen University
Pham, The	RWTH Aachen
Misgeld, Berno	RWTH Aachen University
Leonhardt, Steffen	RWTH Aachen
Ngo, Chuong	RWTH Aachen
Keywords: Assitive technology and rehabilitation engineering, Hardware-in-the-loop simulation, Identification and control methods Abstract: Compliant actuators have been increasingly used for active joints in lower-limb exoskeletons or orthoses because they help to guarantee a safe human interaction. One example of such compliant motors is the variable stiffness actuator (VSA). The design of a torque controller for such an actuator is a crucial task in order to provide patients with physical gait assistance and overcome the mechanical limitations of the VSA. Our goal is to implement a torque controller for our mechanical-rotary variable impedance actuator (MeRIA) used in future lower-limb exoskeletons. In the torque control design, we derive a gain-scheduled controller for the polytopic linear parameter-varying (LPV) model of the actuator. This controller is based on the classical H-infinity loop-shaping approach. Measurements on the hardware-in-the-loop system in time and frequency domain show that the designed controller provides adequate performance over the whole varying stiffness range. Additionally, the controller provides H-infinity robustness with respect to coprime factor uncertainty for the polytopic system. Thus, the torque controller fulfills major safety requirements, and can further be used for human-in-the-loop tests and applications with a lower-limb exoskeleton.
Paper VI145-02.3
PDF · Video · FES Based Wrist Tremor Suppression Using Multi-Periodic Repetitive Control
Zhang, Zan	Zhengzhou Univeristy
Chu, Bing	University of Southampton
Liu, Yanhong	Zhengzhou University
Owens, David H.	The Univ of Sheffield
Keywords: Assitive technology and rehabilitation engineering, Identification and control methods Abstract: Tremor is a very common motor disorder, mainly manifested as involuntary, periodic and rhythmic movement in any part of the body, especially in hands and upper-limbs, which seriously affects the life quality of patients. Functional electrical stimulation (FES) has been shown a promising technique to suppress tremor. Most existing FES based design methods assume tremor is a single frequency signal which however is a highly idealized simplification of the real case which contains multiple-frequency or even a frequency band, therefore limiting their practical performance. To address this problem, this paper proposes a controller design method based on multi-periodic repetitive control that is capable of suppressing tremor signal with multiple frequencies. Simulation and experimental results verify the effectiveness of the proposed method.
Paper VI145-02.4
PDF · Video · Robust Markovian Impedance Control Applied to a Modular Knee-Exoskeleton
Escalante, Felix M	University of São Paulo
Perez Ibarra, Juan Carlos	University of São Paulo
Campo, Jonathan	University of São Paulo
Siqueira, Adriano A G	Univ. of Sao Paulo
Terra, Marco Henrique	University of Sao Paulo
Keywords: Assitive technology and rehabilitation engineering, Identification and control methods, Security and safety of HMS Abstract: Lower limb exoskeletons have improved mobility and safety during gait rehabilitation. Joint actuators can be programmed to produce sufficient joint torque to promote human movement. However, the mechanical impedance of the human joints changes constantly to maintain a stable interaction with the environment during walking. These continuous changes introduce nonlinearities and uncertainties that alter abruptly the dynamics of the human-robot interaction, which can destabilize the control system. In this paper, an impedance control approach under explicit Markovian torque control architecture is developed, considering the variable human impedance parameters as parametric uncertainties. As the time-varying human dynamics during walking depends on the quasi-cyclic gait phase transitions, we defined five Markovian operation modes to describe the human-robot interaction during walking. Additionally, impedance parameters of the human knee joint were estimated using an ensemble-based method. Experimental results of the proposed control scheme on a knee-exoskeleton driven by a series elastic actuator show that our proposal guarantees stability and high performance despite the stochastic uncertain human impedance behavior throughout the gait cycle.
Paper VI145-02.5
PDF · Video · A Stochastic Control Strategy for Safely Driving a Powered Wheelchair
Teodorescu, Catalin Stefan	UCL
Zhang, Bingqing	University College London
Carlson, Tom	University College London
Keywords: Assitive technology and rehabilitation engineering, Shared control, cooperation and degree of automation, Motion Control Systems Abstract: In this paper we deal with model-based control design in the presence of uncertainties. We use Stochastic Dynamic Programming to solve two problems, called longitudinal and lateral vehicle control. The goal is to allow safe driving (navigation) of a moving vehicle in an environment with static obstacles. We show how to define the optimization problems given the stochastic driver behavior and environment. The vehicle dynamics model is deterministic (obeys physical laws) and is explicitly integrated into the optimization problem. In terms of results, the numerically computed control policies provide best-on-average performance (according to the expected value operator). In simulation, it is shown that the vehicle effectively avoids obstacles, thus ensuring a safe drive experience.
Paper VI145-02.6
PDF · Video · Control of a Smart Walker for Training Using Interaction-Energy and Personalized Parameters
Stogl, Denis	Karlsruhe Institute of Technology (KIT)
Zumkeller, Daniel	Karlsruhe Institute of Technology (KIT)
Muth, Manuel	Karlsruhe Institute of Technology (KIT)
Hein, Björn	Karlsruhe University of Applied Science
Keywords: Human-centred automation and design, Shared control, cooperation and degree of automation, Assitive technology and rehabilitation engineering Abstract: Smart walkers with admittance controller usually have limited dynamics and low maximal velocity to provide stable and safe behavior. To enable physically challenging training with smart walker control strategies enabling faster dynamics is needed. However, in certain situations, this can lead to instabilities, which further complicates the finding of suitable parameters for the envisioned training functionalities. To overcome these issues, we have introduced an interaction-energy limiter and developed a strategy to automatically determine individual user parameters for an adaptive admittance controller. The energy limiter bounds the controller and training elements to avoid uncomfortable and dangerous situations. These training elements are placed on a 2D map of a training environment. If the user passes these training elements with our smart walker -- RoboTrainer -- they are triggered. Therefore we call them spatial control actions. We can show that interaction-energy limiter successfully avoids instabilities and dangerous situations when spatial control actions are triggered. The evaluation with 22 users, which used RoboTrainer with and without individualized parameters, successfully demonstrate the benefits of the parameterization method. The presented method could be generally valuable for the implementation of smart walkers in everyday life since it provides a solution for dealing with users with different skills and a solution for safe interaction with smart walkers using high-dynamic control.
Paper VI145-02.7
PDF · Video · On the Influence of the Moment of Inertia on the Mechatronic Drive Control Quality within the Exoskeleton
Stebulyanin, Mikhail	Moscow State Technological University STANKIN
Ermolov, Ivan	Ishlinsky Institute for Problems in Mechanics of Russian Academy
Sukhanov, Artem	Ishlinsky Institute for Problems in Mechanics RAS
Keywords: Design, modelling and analysis of HMS, Mechatronic systems, Human operator support Abstract: The paper considers the interaction between human arm and electromechanical system of the exoskeleton device. Authors proposed the mathematical model of human-exoskeleton interaction on the example of an EMG controlled mechatronic DC-motor. Features of the torque generation with the mechatronic drive of the exoskeleton under the conditions of desynchronization of the speeds of the operator's arm and the exoskeleton link are shown. The exoskeleton motion simulation results with different moments of inertia of the drive system are presented.

VI145-03
Human-Robot Collaboration	Regular Session
Chair: Engelbrecht, Jacobus Adriaan Albertus	Stellenbosch University
Co-Chair: Selma, Music	Technische Universität München
Paper VI145-03.1
PDF · Video · Situational Awareness Oriented Interfaces on Human-Robot Interaction for Industrial Welding Processes
Waschburger dos Santos, Caroline	Universidade Federal Do Rio Grande
Duarte Filho, Nelson	Universidade Federal Do Rio Grande
Espindola, Danubia	Federal University of Rio Grande - FURG
Botelho, Silvia	Universidade Federal Do Rio Grande
Keywords: Decision making support, Intelligent interfaces, Human operator support Abstract: Safety, efficiency and effectiveness are important characteristics for human-robot interaction in a factory. So, workers and operators are exposed to challenges of interacting with these systems, in particular with welding robots. Considering the complexity of the industrial context and of the welding process itself, an important factor for the operator is "to understand what is happening" or to obtain situational awareness (SA). The SA increases decision-making capacity, reduces errors, and adds features to improve the human-robot interface (HRI). In order to integrate SA into interfaces for human-robot interaction, this work proposes the mapping of important aspects of SA for the welding process, based on a literature review and a case study to identify SA on interfaces for HRI. Finally, comments which aspects should be included in situational awareness oriented interfaces in order to provide more intelligent interfaces.
Paper VI145-03.2
PDF · Video · Adaptive Negotiation Model for Human-Machine Interaction on Decision Level
Rothfuss, Simon	Karlsruhe Institute of Technology (KIT)
Ayllon, Catarina	Karlsruhe Institute of Technology (KIT)
Flad, Michael	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Decision making support, Shared control, cooperation and degree of automation, Modeling of human performance Abstract: Our work is a contribution to automation design for human-machine cooperation with explicit emancipated cooperative decision making. We propose an adaptive negotiation framework as a model for human-machine interaction on decision level. This expands modeling of human-machine cooperation, starting at the stabilization and trajectory level with approaches such as shared control, towards higher levels of interaction as guidance and navigation. In essence, the framework extends the well-known basic negotiation model of multi-agent systems by an explicit adaptation of the agent's negotiation behavior. The adaptation is based on an opponent model using a Bayesian learning approach. An exemplary implementation for the application of human-automation interaction in autonomous driving is introduced. First results prove the high flexibility of the framework to model human negotiation behavior.
Paper VI145-03.3
PDF · Video · Group Synchronization in Coordination Tasks Via Network Control Methods
Givigi, Sidney	Queen's University
Cabral, Kleber	Royal Military College
Jardine, Peter Travis	Royal Military College of Canada
Keywords: Human operator support, Ajustable or adaptive autonomy, Modeling of human performance Abstract: This paper deals with the coordination problem among robots and between robots and humans using network control methods. In several applications, robots need to collaborate with humans in order to perform tasks, such as in collaborative transportation of objects, cooperative assembly of structures, or production line activities. In all these cases, the robot needs to observe the environment and take actions according to one of more other agents; human or robotic. When only one more agent is involved (dyadic interactions), the problem is relatively well studied. However, this paper focuses on when more than one other agent is involved in the collaboration. All agents are represented as part of a graph that determines their communication architecture. Network controllers are proposed for this environment and simulations show that synchronization of all agents is achieved. Furthermore, experiments show that a virtual agent is able to efficiently interact with humans and synchronize itself to their motion. To our knowledge this is the first time network control was explicitly applied to this problem.
Paper VI145-03.4
PDF · Video · A Novel Approach to Integrate Human-In-The-Loop Testing in the Development Chain of Automated Driving: The Example of Automated Lane Change
Rogic, Branko	MAGNA Steyr
Nalic, Demin	Graz University of Technology
Eichberger, Arno	Graz University of Technology
Bernsteiner, Stefan	MAGNA Steyr
Keywords: Human operator support, Design, modelling and analysis of HMS, Modeling of human performance Abstract: For market introduction of advanced driver assistant (ADAS) and automated driving (AD) systems on full vehicle level, testing and validation is one of the biggest challenges. The present study describes a novel approach that integrates a driving simulator in a virtual development process aiming to reduce time and effort for system development. The approach is demonstrated on a specific automated lane change assist (LCA) system. To this end, the LCA function and the corresponding human machine interface (HMI) are developed and implemented in the driving simulator. The core of the approach is a driving simulator-based testing method which proposes a novel two stage testing concept and involves multiple test drivers. The method provides better insight into the overall system performance and, moreover, detects potentials for improvements dedicated for the ADAS functionalities as well as for the design of the HMI system. Using this method, a driving simulator study with 20 volunteer drivers is conducted to evaluate the LCA system with respect to driver acceptance and user friendliness. The results of the study will be used for the parametrization and fine tuning of the LCA function as well as for the HMI improvement.
Paper VI145-03.5
PDF · Video · A Roadmap for the Future Design of Human-Robot Collaboration
Buxbaum, Hans-Jürgen	Niederrhein University of Applied Sciences
Sen, Sumona	Niederrhein University of Applied Sciences
Häusler, Ruth	Human Factors Solutions
Keywords: Human-centred automation and design, Security and safety of HMS, Robotics technology Abstract: Human-robot collaboration systems are a new and interesting approach in the science of robotics. Collaborative robot systems can be used without protective fences in direct interaction with humans. For ongoing developments in human-robot collaboration, further improvements in a multitude of disciplines and research areas are necessary. The scope of interdisciplinary research work in this context is enormous and the scientific field is, due to the high level of interdisciplinarity, quite complex. In the debates within the Ladenburg Discourse* on human-robot collaboration, it was agreed that guidelines for future research and development work would be very useful and would enable researchers to structure and position their work in this wide field. Duplications and redundancies could be avoided, and synergies and cooperations could be promoted. For those reasons, an extended set of thirteen theses is formulated. This paper describes these theses, as a summary of the Ladenburg Discourse, with the intention to provide a roadmap for human-robot collaboration.
Paper VI145-03.6
PDF · Video · Human Decision-Making Behavior Modeling for Human Multi-Robot Interaction System
Wu, Wenhua	Fuzhou University
Huang, Jie	Fuzhou University
Zhang, Zhenyi	Fuzhou University
Keywords: Modeling of human performance, Autonomous robotic systems Abstract: In this paper, the composition of human decision-making process in human-robot interaction is analyzed and the human decision-making behavior is modeled. The human decision-making process is divided into data-processing station and human cognitive system. By combining with the null-space-based control (NSBC) method, the traditional drift diffusion model (DDM) is applied for for human decision-making behavior modeling in human-robot interaction (HRI). In addition, HRI is studied for a platoon of autonomous robots in an unknown environment with multiple obstacles. Moreover, the human intervention task is designed to help robots achieve tasks successfully. Finally, simulation examples are given to demonstrate the satisfactory performance of the proposed method.
Paper VI145-03.7
PDF · Video · Co-Operative Collision Avoidance for Unmanned Aerial Vehicles Using Both Centralised and Decoupled Approaches
Palmer, Lauren	Stellenbosch University
Engelbrecht, Jacobus Adriaan Albertus	Stellenbosch University
Keywords: Shared control, cooperation and degree of automation, Guidance navigation and control, Flying robots Abstract: This paper presents the design of co-operative collision avoidance algorithms for Unmanned Aerial Vehicles (UAVs) using vertical avoidance manoeuvres. The co-operative collision avoidance problem is formulated as an optimal control problem and solved using an A* search algorithm. Two different approaches are developed and compared: a centralised approach where the collision avoidance trajectories for all UAVs are planned simultaneously, and a decoupled approach where the individual collision avoidance trajectories for each UAV is planned sequentially, with the planning sequence determined by a UAV priority order. The UAVs co-operate by sharing their state and intent information with one another and with a central node, if present. The co-operative collision avoidance algorithms are verified and evaluated using illustrative simulations. These simulations support the expected behaviour of the algorithms. The centralised approach finds the most optimal solution to the problem while the solution found by the decoupled approach depends on the priority allocation of the UAVs. The decoupled approach can find either the most optimal or a sub-optimal solution to the problem, with the priority allocation occasionally resulting in the decoupled approach being unable to find a solution. This suggests that the centralised approach will, on average, find solutions more often and find more optimal solutions than the decoupled approach.
Paper VI145-03.8
PDF · Video · Shared Control for Human-Robot Collaboration: A Game-Theoretical Approach
Selma, Music	Technische Universität München
Hirche, Sandra	Technical University of Munich
Keywords: Shared control, cooperation and degree of automation, Human operator support, Human-centred computing Abstract: Complementing human and robot capabilities is essential for many tasks, e.g. rehabilitation and collaborative manufacturing. However, it is still not clear how control between humans and robots should be shared in order to ensure efficient task execution and intuitive interaction. Game theory seems as a promising mathematical framework that allows: i) posing this challenge as a dynamic negotiation (game) among human and robot (players) and ii) solving it to obtain optimal solution. In this work, we propose a differential game-theoretic shared control approach for human-robot haptic collaboration with Nash equilibrium optimal solution. We validate the proposed approach experimentally in a scenario where human is physically coupled with a haptic device and interacts with a virtual reality to perform a trajectory tracking task.
Paper VI145-03.9
PDF · Video · Human Robot Interaction for Future Remote Manipulations in Industry 4.0
Ghosh, Ayan	University of Sheffield
Paredes, Daniel	The University of Sheffield
Veres, Sandor M	University of Sheffield
Rossiter, J. Anthony	Univ of Sheffield
Keywords: Tele-robotics, Tele-presence, Telecommunication-based automation systems Abstract: In the nuclear industry it is still common to rely on tele-operated robots. Tele- operation however can be strenuous and demanding on operating personnel and productivity can be low without advanced HRI interfaces. Today, the world is moving towards Industry 4.0. With that vision, this paper introduces the concept of Remotely Instructed Robots (RIRs), which are reliable but still rely on human intelligence. RIRs can accept high and low level instructions from the operator and execute tasks based on operators’ descriptions and at a variety of complexity levels. The paper outlines an agent model of RIRs and furthermore, presents how it could be implemented inside nuclear glove boxes to achieve novel human robot interaction.

VI145-04
Multi-Modal Human-Machine Interaction	Regular Session
Chair: Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Co-Chair: Chen, Luefeng	China University of Geosciences
Paper VI145-04.1
PDF · Video · Selection of Optimal EEG Electrodes for Human Emotion Recognition
Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Chen, Peng	East China University of Science and Technology, School of Infor
Keywords: Brain-machine interaction, Multi-modal interaction, Human-centred computing Abstract: In recent years, emotion recognition has attracted increasing interest from researchers from diverse fields. Because of their intrinsic correlation with emotions, physiological signals based emotion recognition method is not susceptible to the so-called social masking and thus more objective than traditional visual, audio or text data based methods. In particular, EEG signals are more responsive to emotion fluctuations than other peripheral physiological signals. In this paper, a 4-class EEG-based emotion classification problem is considered. Firstly the subjective data clustering is performed to identify the optimal number of emotional states. Then wavelet and nonlinear dynamics analyses are used to extract EEG features of emotions. Finally, we consider the brain areas for emotion generation and show that the use of only a small number of EEG electrodes placed on the frontal area of scalp can achieve a 4-class emotion classification accuracy of higher than 90%.
Paper VI145-04.2
PDF · Video · CNN-Based Broad Learning with Efficient Incremental Reconstruction Model for Facial Emotion Recognition
Chen, Luefeng	China University of Geosciences
Li, Min	China University of Geosciences (wuhan)
Lai, Xuzhi	China University of Geosciences
Hirota, Kaoru	Tokyo Institute of Technology
Pedrycz, Witold	University of Alberta
Keywords: Intelligent interfaces, Knowledge modelling and knowledge based systems, Human-centred computing Abstract: The convolutional neural network-based broad learning with efficient incremental reconstruction model (CNNBL) is proposed to recognize emotions in human-robot interaction. It aims to extract deep and abstract features from facial emotional images, and reduce the influence of the complex structure and slow network updates on facial emotion recognition in deep learning. Feature extraction is carried out by convolution and maximum pooling, and then the ridge regression algorithm is used for emotion recognition. When the network needs to expand, the network is dynamically updated by incremental learning algorithm. We verified the experimental performance through k-fold cross validation. According to the recognition results, the accuracy on JAFFE database of our proposal is greater than that of the state of the art, such as the Local Binary Patterns with Softmax and Deep Attentive Multi-path convolutional neural network.
Paper VI145-04.3
PDF · Video · Classifying Mental Workload Levels Using Semi-Supervised Learning Technique
Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Li, Jianrong	East China University of Science and Technology, School of Infor
Keywords: Modeling of human performance, Cognitive systems engineering, Brain-machine interaction Abstract: Real-time monitoring and analysis of human operator's mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although data-driven machine learning (ML) approach has shown promise in MWL recognition, it is usually difficult to acquire sufficient labeled data to train the ML model. This paper proposes semi-supervised extreme learning machines (SS-ELM) for MWL pattern classification using solely a small number of labeled data. The experimental data analysis results are presented to show the effectiveness of the proposed SS-ELM paradigm to effectively exploit a large number of unlabeled data for the real-world 3- or 4-class MWL classification problem.
Paper VI145-04.4
PDF · Video · K-Means Clustering-Based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition
Chen, Luefeng	China University of Geosciences
Wang, Kuanlin	China University of Geosciences
Wu, Min	China University of Geosciences
Pedrycz, Witold	University of Alberta
Hirota, Kaoru	Tokyo Institute of Technology
Keywords: Multi-modal interaction, Intelligent interfaces, Knowledge modelling and knowledge based systems Abstract: Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognition rate. However, in the multimodal feature fusion at the feature level, most of the methods do not consider the intrinsic relationship between different modes. Only the fusion of analysis and transformation of the feature matrices of different modes does not make better use of modal differences to improve the recognition rate. This problem led us to propose feature fusion method based on K-Means clustering and kernel canonical correlation analysis (KCCA). Clustering makes the classification of features not classified by mode, but by the degree of influence on emotional labels, thus positively affecting the results of KCCA. The experimental results obtained on the Savee database show that the proposed K-Means based KCCA improves overall classification performance and produces higher recognition rate than that of the state of art methods, such as the Informed Segmentation and Labeling Approach.

VI151
Manufacturing and Logistics Systems - Manufacturing Plant Control
VI151-01 Smart, Advanced and Robust Assembly: Toward "Assembly System 4.0"   Invited Session, 7 papers
VI151-02 Prognostics and Health Management in Manufacturing: New Challenges and Perspectives in the Era of Industry 4.0   Open Invited Session, 10 papers
VI151-03 Quality and Process Control in Modern Manufacturing   Open Invited Session, 6 papers
VI151-04 Intelligent Manufacturing Systems   Regular Session, 18 papers

VI151-01
Smart, Advanced and Robust Assembly: Toward "Assembly System 4.0"	Invited Session
Chair: Cohen, Yuval	Afeka Tel Aviv College of Engineering
Co-Chair: Faccio, Maurizio	University of Padova
Organizer: Cohen, Yuval	Afeka Tel Aviv College of Engineering
Organizer: Pilati, Francesco	Department of Industrial Engineering, University of Bologna
Organizer: Faccio, Maurizio	University of Padova
Organizer: Limère, Veronique	Ghent University
Paper VI151-01.1
PDF · Video · Smart and Efficient: Learning Curves in Manual and Human-Robot Order Picking Systems (I)
Loske, Dominic	FOM, Ild, Essen
Klumpp, Matthias	Georg-August-University of Göttingen
Keywords: Device integration technologies, Intelligent system techniques and applications, Methodologies and tools for analysis of complexity Abstract: Order picking has been identified as the most labour-intensive, as well as costly activity within warehouse logistics and is experiencing significant changes due to new technologies in the forms of artificial intelligence (AI) and automation. One fundamental question concerns the employees learning progress in human-robot picking systems compared to existing manual technologies. Therefore, this paper presents an empirical analysis of learning curves in manual pick-by-voice (n=30 pickers) and semi-automated (n=20 pickers) order picking. Aspiring to measure the individual learning progress without a priori assumptions, this publication is the first to apply Data Envelopment Analysis and examine order pickers learning curves in real application scenarios. The findings indicate that automating human work accelerates the individual learning progress in human-robot picking systems.
Paper VI151-01.2
PDF · Video · Assembly Line Balancing for Personalized Production (I)
Pilati, Francesco	University of Trento
Lelli, Giovanni	Department of Industrial Engineering - University of Bologna
Faccio, Maurizio	University of Padova
Gamberi, Mauro	University of Bologna, Department of Industrial Engineering
Regattieri, Alberto	University of Bologna
Keywords: Assembly and disassembly, Modeling of assembly units, Job and activity scheduling Abstract: Assembly line balancing problems aim to an efficient and effective assignment of all the required tasks to workstations in a flow oriented production system. Nowadays, assembly lines have to face the manufacturing of extremely personalized products (e.g. cars) as requested by an increasingly higher portion of the market demand. Several literature contributions focus on different balancing problems affected by the wide variety of the final product, e.g. mixed and multi model assembly lines. However, no contribution seems to tackle the personalized production of goods. Such products require to assemble a certain number of tasks whatever the final product personalization is, and a variable number of optional of different type determined by the specifications of every single costumer. This paper faces the generalized assembly of personalized goods proposing an innovative two step methodology to optimize the workload balancing between the assembly line stations, considering traditional tasks and the optional required by the product personalization, which could occur with different frequencies and pairings. The first phase of the developed methodology executes a clustering of product options required by the costumers based on a similarity index. This phase leads to the definition of several sets of optional typically requested together by the customer and with similar mounting time. The methodology second phase leverages the defined clusters of optional. Indeed, optional of the same cluster shouldn’t be assigned to the same workstation to reduce the overload or underload of the assembly operators. An integer programming model is proposed to assign both traditional tasks and optional to stations, to maximize the assembly line balancing considering the order frequency and assembly time of the clusterized optional. An industrial case study is adopted to test and validate the proposed two steps methodology. The obtained results highlight a consistent time balancing between assembly line workstations and a significant limitation of the operator overloads.
Paper VI151-01.3
PDF · Video · Implementing Large-Scale Aerospace Assembly 4.0 Demonstration Systems (I)
Sanderson, David	University of Nottingham
Turner, Alison	University of Nottingham
Shires, Emma	University of Nottingham
Chaplin, Jack Christopher	University of Nottingham
Ratchev, Svetan	University of Nottingham
Keywords: Intelligent manufacturing systems, e-Manufacturing technologies and facilities, Flexible and reconfigurable manufacturing systems Abstract: The Future Automated Aerospace Assembly phase 1 technology Demonstrator (FA3D) was commissioned at the University of Nottingham and used to demonstrate concepts from the EPSRC Evolvable Assembly Systems project in specific industrial use cases. A number of lessons were learned from the specification, procurement, commissioning, and use of the cell. These lessons have been applied to the specification of Phase 2 of the Future Automated Aerospace Assembly Demonstrator (FA3D2) - currently in development - that will translate the Evolvable Assembly Systems research to a higher technology readiness level and address the challenges of scalable and transformable manufacturing systems. The FA3D2 will act as a showcase national experimental testbed and technology demonstrator in digital- and informatics-enabled aerospace manufacturing technologies, and the project itself will generate knowledge, skills, and experience in the delivery of such systems for academia and industry. After summarising the Evolvable Assembly Systems project, this paper presents details of the technologies demonstrated through the FA3D, and how this experience has been used to develop a novel approach to specifying the FA3D2.
Paper VI151-01.4
PDF · Video · A New Cobot Deployment Strategy in Manual Assembly Stations: Countering the Impact of Absenteeism (I)
Cohen, Yuval	Afeka Tel Aviv College of Engineering
Shoval, Shraga	Ariel University
Keywords: Device integration technologies, Assembly and disassembly, Production activity control Abstract: This paper discusses a new strategy for deploying cobots in assembly lines having manual stations. The paper first presents the contribution of absenteeism to the temporary appearance of bottle-neck stations and the resulted lost throughput. It then delineates some barriers and obstacles of cobots’ deployment in these stations. Finally, it discusses the advantages of employing a cobot-specialist for a defined segment of the assembly line. The suggested role of the cobot-specialist is to quickly find ways in which a cobot will alleviate the work of a temporary workers filling positions of absentees. Such replacement workers are in their early stages of their learning curve, and are considerably slow, with high chances of becoming a bottleneck. A bottleneck station dictates the pace of the whole line and reducing its cycle-time, increases the throughput of the whole line. Thus, the suggested approach prevents throughput losses due to absenteeism. Having a line-segment specialist that is familiar with the various stations in his/her segment ensures both having some pre-prepared schemes of cobot deployment for each station, and the ability of rapid installation of the cobot. Moreover, replacement workers typically are too busy to deal with the cobot’s installation or operation. The approach is validated using ARENA simulation scenarios for various line segments.
Paper VI151-01.5
PDF · Video · "Station-Sequence" Parts Feeding in Mixed Models Assembly: Impact of Variations and Industry 4.0 Possible Solutions (I)
Bortolini, Marco	Alma Mater Studiorum - University of Bologna
Faccio, Maurizio	University of Padova
Gamberi, Mauro	University of Bologna, Department of Industrial Engineering
Pilati, Francesco	University of Trento
Keywords: Logistics in manufacturing, Assembly and disassembly, Production activity control Abstract: Parts feeding is a complex logistic problem, stressed by the increasing product variety that forces the assembly systems to manage a great number of models with a mixed model approach. In this context a possible parts feeding policy is the "station-sequence", sequences of parts supplied to the assembly stations as function of the production models. This parts feeding policy can reduce stocks at the assembly stations, but offers potential production stops due to its low robustness. Different external elements can perturb the parts sequences (i.e. changing in production schedule, tasks times variation, variable supply lead times, etc.). The aim of this paper is to study, through a simulation study and a statistical analysis, the station-sequence part feeding policy considering its dynamic time-dependence the impact of the model mix and time perturbations on the system performance. Authors discuss the possible application of the real time events traceability, achievable through the I4.0 application, in order to mitigate the variability influence on the system performances.
Paper VI151-01.6
PDF · Video · Low-Cost Automation – Changing the Traditional View on Automation Strategies Using Collaborative Applications (I)
Fast-Berglund, Aasa	Chalmers University of Technology
Salunkhe, Omkar	Chalmers University of Technology
Åkerman, Magnus	Chalmers
Keywords: Assembly and disassembly, Flexible and reconfigurable manufacturing systems, Intelligent system techniques and applications Abstract: Abstract: The labor cost has been one of the main reasons for industry to move some of the production to so called low-cost countries. Research has shown that this issue is more complex than just calculate labor cost as main driver. Organization culture, research and development and technical competence is also important drivers for a successful automation strategy. Another important factor when it comes to automation strategies is what production parameters to consider choosing the right automation. Traditionally five parameters have been considered i.e. Volume, batch sizes, variants, investment cost and labor cost. With new and cheaper solutions for automation these two views on automation and low-cost production need to be considered and changed. This paper will describe three demonstrators using low-cost automation solutions to automate simple tasks in final assembly systems. The stations’ investment cost is all below 50,000 euro. The first demonstrators have been set up and tested in a lab environment. The results show a high precision, easiness in programming and high quality. The aim is to test this further in real industrial environment to stress the system and to put it into a tougher environment.
Paper VI151-01.7
PDF · Video · Automating Nut Tightening Using Machine Learning (I)
Wedin, Kevin	Chalmers
Johnsson, Christoffer	Chalmers
Åkerman, Magnus	Chalmers
Fast-Berglund, Aasa	Chalmers University of Technology
Bengtsson, Viktor	Chalmers
Alveflo, Per-Anders	AB Volvo
Keywords: Flexible and reconfigurable manufacturing systems, Intelligent system techniques and applications, Intelligent decision support systems in manufacturing Abstract: Mass customization of products results in a high variance of products. At the final assembly at Volvo trucks each frame has around 200 nuts that should be fasten on the frame along with different components. The frame is slowly moving, and the two operators have around five minutes to determine what nuts that should be fastened at their station. In order to distinguish this some of the nuts are inverted which means that they should be left for another station. This paper aims to investigate and demonstrate how machine learning and object recognition can be used in order to determine what nuts to fasten in the assembly station in order to save time for the operator and possible also be handled with help of a robot in the future. The experiment is done together with Volvo trucks on one of the truck frames. Two different algorithms have been tested and evaluated and the results shows a best hit rate of over 95 percent.

VI151-02
Prognostics and Health Management in Manufacturing: New Challenges and Perspectives in the Era of Industry 4.0	Open Invited Session
Chair: Nguyen, Thi Phuong Khanh	Tarbes National Engineering School (INPT-ENIT)
Co-Chair: Choi, Joo Ho	Korea Aerospace University
Organizer: Nguyen, Thi Phuong Khanh	Tarbes National Engineering School (INPT-ENIT)
Organizer: Medjaher, Kamal	Tarbes National Engineering Institute (INPT-ENIT)
Organizer: Choi, Joo Ho	Korea Aerospace University
Paper VI151-02.1
PDF · Video · Bootstrap Confidence Interval on IOHMM Parameters for System Health Diagnostic under Multiple Operating Conditions (I)
Shahin, Kamrul	Universite De Lorraine
Simon, Christophe	University of Lorraine
Weber, Philippe	Université De Lorraine, CNRS, (CRAN UMR 7039)
Keywords: Intelligent maintenance systems, Intelligent manufacturing systems, Maintenance models and services Abstract: The operating conditions have an important impact on system degradation. This paper uses the Input-Output Hidden Markov Model to represent the system degradation having multiple operating conditions. In this paper the bootstrap method is applied to estimate the model parameters and applied to diagnostic the system health. Parameters of the model are computed with 95% confidence intervals. The uncertainty about multiple data sequences and degradation speed is handled in the proposed model. A numerical application is given to explain the methodologies used to estimate the model parameters and diagnostic the system health.
Paper VI151-02.2
PDF · Video · Diagnosing Intermittent Faults through Non-Linear Analysis (I)
Khan, Samir	University of Tokyo
Yairi, Takehisa	Department of Aeronautics and Astronautics, the University of To
Keywords: Maintenance models and services, Model-driven systems engineering, Intelligent system techniques and applications Abstract: To cope with certain exogenous stimuli, there have been inexorable advances of technology, with an increased focus and fascination with the accuracy of diagnostic equipment. This can become a difficult problem to solve as it warrants real-time monitoring whilst taking up unnecessary measures to improve overall system reliability and maintainability. Intermittent faults may be benign and their overall impact on a system varies with mission objectives and operating conditions. Major failures can often be averted if these problems can be detected sufficiently in advance by observing them in dynamical behaviour. The phase space trajectory reconstructed from a time series is known to elucidate such behaviours however it is seldom applied for fault analysis. This article makes use of dynamic system theory and investigates its application for fault estimation by analysing non-stationarities which arise due to the changing dynamics under intermittent conditions. Intermittent fault detection presents a challenge for traditional fault diagnostic equipment as they do not manifest themselves all the time. The idea is to move away from the traditional approaches and investigate the use of non-linear analysis by building a reference trajectory using the phase space reconstruction. This is used as an objective measure for any deviations caused by intermittent phenomena. The method is validated using simulated data and shows promise. The implications of the study are to identify new fault isolation bounds necessary to improve diagnostic success rates and potentially lead to early diagnosis of intermittent faults in electrical equipment.
Paper VI151-02.3
PDF · Video · Prognosis and Health Management Using Energy Activity (I)
Singh, Manarshhjot	University of Lille
Gehin, Anne-Lise	University of Lille
Ould Bouamama, Belkacem	Ecole Polytechnique De Lille
Keywords: Process supervision, Quality assurance and maintenance, Model-driven systems engineering Abstract: Accurate detection of faults in a dynamic system is very beneficial as this information can be used in a wide variety of ways by the machine operators or designers. This advantage becomes many folds when regarding the future condition i.e. time to failure, named remaining useful life, is available in addition to that of the present condition. Thus, prognosis is one of the most useful tools to improve the working of a machine as many critical decisions can be made. Prognosis can be critical for applications that risk loss of life and property. In this paper, a hybrid method, utilizing bond graph and artificial intelligence, is proposed for system health estimation (SHE) and prognosis. The Bond Graph model is used to calculate Energy Activity, which is used as a common metric for both SHE and prognosis. The proposed method is checked by simulation on a spring mass damper system undergoing a fault.
Paper VI151-02.4
PDF · Video · Planetary Gear Fault Detection in Wind Turbine Gearboxes Based on a Ten-Year Historical Data from Three Wind Farms (I)
Kordestani, Mojtaba	University of Windsor
Rezamand, Milad	University of Windsor
Orchard, Marcos	Universidad De Chile
Carriveau, Rupp	University of Windsor
Ting, David	Univ of Windsor
Saif, Mehrdad	University of Windsor
Keywords: Intelligent maintenance systems, Konwledge discover (data mining), Integrated monitoring, control and security for critical infrastructure systems Abstract: Gear faults contribute to a significant portion of failures in wind turbine systems. As such, condition monitoring and fault detection of these components assist in maintenance scheduling; hence, preventing catastrophic failures of the gearbox. This paper introduces a new integrated fault detection approach to detect gear faults in wind turbines. To accomplish this task, vibration signals are collected and used to extract various time-domain features. Next, a Dynamic Principle Component Analysis (DPCA) is adaptively employed to identify failure dynamics by reducing the time-domain feature dimension. Following that, a Support Vector Machine (SVM) is implemented to detect and isolate gear faults. Experimental test studies with ten-year historical data of three wind farms in Canada are conducted. Test results indicate that the proposed hybrid approach performs superior compared to DPCA using Multilayer Perceptron (MLP) Neural Networks (NNs).
Paper VI151-02.5
PDF · Video · Gear Grinding Monitoring Based on Deep Convolutional Neural Networks (I)
Liu, Chenyu	KU Leuven
Mauricio, Alexandre	Department of Mechanical Engineering, KU Leuven, Dynamics of Mec
Chen, Zhuyun	School of Mechanical and Automotive Engineering, South China Uni
Declercq, Katrien	VCST Industrial Products, Sint-Truiden, Belgium
Meerten, Yannick	VCST Industrial Products, Sint-Truiden, Belgium
Yann, Vonderscher	VCST Industrial Products, Sint-Truiden, Belgium
Gryllias, Konstantinos	KU Leuven
Keywords: Process supervision, Quality assurance and maintenance, Monitoring and control of spatially distributed systems Abstract: Grinding plays a vital role in modern gear manufacturing industry while the need for high quality products is continuously increasing. A methodology for gear grinding monitoring, exploiting the power of Deep Learning architectures and 2D representations, is presented in this paper. Vibration signals, measured during the grinding process under healthy and faulty conditions, are classified with high accuracy. Three types of faults i.e., a high profile form error, a high lead error, and a high profile slope variation, have been emulated. The Short-Time Fourier Transform (STFT) of each vibration signal is calculated, and the 2D time-frequency representations are input to a Deep Convolutional Neural Network (DCNN) for classification. Different filter sizes are tested, and the classification accuracy of 95.0% has been achieved, demonstrating the efficiency of the methodology for gear grinding monitoring.
Paper VI151-02.6
PDF · Video · Data-Driven Diagnostics of Positioning Deviations in Multi-Axis Robots for Smart Manufacturing (I)
Soualhi, Moncef	Tarbes National Engineering Institute (INPT-ENIT)
Nguyen, Thi Phuong Khanh	Tarbes National Engineering School (INPT-ENIT)
Medjaher, Kamal	Tarbes National Engineering Institute (INPT-ENIT)
Lebel, Denis	METALLICADOUR
Cazaban, David	METALLICADOUR
Keywords: Intelligent manufacturing systems, Intelligent maintenance systems Abstract: Nowadays, advanced industrial robots are increasingly used and gradually replacing human activities in smart manufacturing that requires high precision and high performance. During this process, a small deviation of a robot axis can lead to other axes drifts, and then significantly affects the product quality. Hence, this paper aims to present an effective approach to monitor and diagnose the origin position deviations of multi-axis robots. The proposed method uses the encoder measurements of each axis to extract features and build appropriate health indicators. These obtained health indicators are then injected into a Machine Learning classifier to localize the origin of the deviation, i.e which axis causes these drifts. Furthermore, the performance of this method is verified through a real industrial test bench, used for machining, that investigates various deviation severities in different axes of the robot.
Paper VI151-02.7
PDF · Video · Comparison of Different Models of Future Operating Condition in Particle-Filter-Based Prognostic Algorithms (I)
Rozas, Heraldo	University of Chile
Tamssaouet, Ferhat	LGP, ENIT-INP, Université De Toulouse
Jaramillo Montoya, Francisco	Universidad De Chile
Nguyen, Thi Phuong Khanh	Tarbes National Engineering School (INPT-ENIT)
Medjaher, Kamal	Tarbes National Engineering Institute (INPT-ENIT)
Orchard, Marcos	Universidad De Chile
Keywords: Internet-of-Things and Sensing Enterprise, Systems interoperability Abstract: In literature, a major part of the prognostic studies considers the mission profile as a static parameter when evaluating the system RUL. However, in practice, the way in which a system operates significantly impacts the future evolution of its degradation. Therefore, this paper aims at evaluating the impact associated with the utilization of three different methods to characterize future operating conditions within the implementation of probability-based prognostic algorithms, namely LSTM, Markov Chain and Constant (or time-invariant) usage. These three methods are compared together in terms of both prognostic accuracy and essential update times when investigating the blue ToD of an electric bicycle Li-Ion battery.
Paper VI151-02.8
PDF · Video · Low Cost Monitoring on a Shoestring: Solutions for Digital Manufacturing (I)
Tlegenov, Yedige	University of Cambridge
Hawkridge, Gregory	University of Cambridge
McFarlane, Duncan Campbell	University of Cambridge
Parlikad, Ajith Kumar	University of Cambridge
Reyner, Nicholas	University of Cambridge
Thorne, Alan	University of Cambridge
Keywords: Intelligent maintenance systems, Manufacturing plant control, Intelligent manufacturing systems Abstract: Digital manufacturing is focussed on leveraging the availability of digital information to improve the effectiveness of manufacturing activities. One of the digitalisation pathways for manufacturing is monitoring, which can be challenging due to the high costs of industrial monitoring solutions and the difficulty in justifying their return on investment. This study examines whether the introduction of low cost technologies can address the monitoring needs of digital manufacturing. In particular, we consider the role non-industrial, "off-the-shelf" technologies can play. The main aim of this paper is to present blueprints for low cost monitoring of industrial operations and identify candidate low cost technologies which can contribute effectively to the implementation of these systems. Related work on low cost monitoring and commercially available technologies are analysed and evaluated. Low-cost monitoring blueprints and candidate technologies are proposed based on the results of the analysis. An example implementation of a presented blueprint indicates the potential of integrating non-industrial, off-the-shelf technologies into low cost monitoring solutions.
Paper VI151-02.9
PDF · Video · Health-Aware Model Predictive Control of Wind Turbines Using Stifness Degradation Approach (I)
Sanchez, Hector	SAC, UPC
Escobet, Teresa	Univ. Politecnica De Catalunya
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Keywords: Process supervision, Maintenance models and services Abstract: Wind turbine blades are under significant gravitational, inertial, and aero-dynamic loads, which cause their fatigue and degradation during the wind turbine operational life. The present work proposes a Model Predictive Control scheme that integrates remaining useful life predictions of the blade based on a stiffness degradation model embedded in a prognostics algorithm. The flapwise blade root bending loads are used as inputs to the damage model which describes the propagation of damage from a microscopical scale manifesting in a macroscopical scale as stiffness loss. The proposed control scheme integrates prognostics information in the MPC formulation in order to optimize the trade-off that exists between the conflictive objectives of producing power and extend the remaining useful life of the blades. The proposed control scheme has been tested using the sensor information from the well known high fidelity wind turbine simulator FAST (Fatigue, Aerodynamics, Structures and Turbulence).
Paper VI151-02.10
PDF · Video · Ensemble Learning-Based Fault Detection in Nuclear Power Plant Screen Cleaners (I)
Deleplace, Antoine	Assystem Energy & Infrastructure
Atamuradov, Vepa	Assystem Energy & Infrastructure
Allali, Ahmed	Assystem Energy & Infrastructure
Pellé, Juliette	Assystem Energy & Infrastructure
Plana, Robert	Assystem Energy & Infrastructure
Alleaume, Guillaume	Assystem Energy & Infrastructure
Keywords: Intelligent maintenance systems, Life-cycle control, Intelligent manufacturing systems Abstract: This paper presents a fault detection approach based on feature selection and ensemble machine learning technique for nuclear power plant (NPP) screen cleaner condition monitoring. Firstly, comprehensive set of statistical features are extracted from in-field raw accelerometer data. Then, a seperability based feature selection metric is utilized to select relevant features in order to enhance accuracy of fault detection algorithm. Afterwards, Extreme Gradient Boosting (XGBoost), which is a decision-tree-based ensemble Machine Learning algorithm, is trained using the selected features for fault detection. The comparative analysis on fault detection is also conducted in this study using different classifiers next to XGBoost. The approach is validated on different fault types of screen cleaners. The results show that the ensemble learning outperforms other classifiers in terms of accuracy and can be effectively used for NPP screen cleaners condition monitoring.

VI151-03
Quality and Process Control in Modern Manufacturing	Open Invited Session
Chair: Abel, Dirk	RWTH-Aachen University
Co-Chair: Stemmler, Sebastian	RWTH Aachen University
Organizer: Abel, Dirk	RWTH-Aachen University
Organizer: Stemmler, Sebastian	RWTH Aachen University
Paper VI151-03.1
PDF · Video · Grey-Box Approach for the Prediction of Variable Residence Time Distribution in Continuous Pharmaceutical Manufacturing (I)
Elkhashap, Ahmed	RWTH Aachen University
Meier, Robin	L.B. Bohle Maschinen + Verfahren GmbH
Stenger, David	RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Manufacturing plant control, Modeling of manufacturing operations Abstract: Axial dispersion models are used for the prediction of residence time distribution (RTD) of the flow occurring in various processes. Such models are essential for the understanding of the flow dynamics allowing monitoring, control and material tracing specially in the scope of continuous pharmaceutical manufacturing. However, RTDs are most usually dependent on the process variables (PVs), indicating that a single constant parameter dispersion model would not be capable of capturing this variability. In this contribution a variable parameter axial dispersion model is proposed, where the dependency on the process variables are captured from experimental data using Gaussian Process Regression (GPR) models. The method is illustrated with an example of a Vibrated Fluidized Bed Dryer (VFBD), in which a number of tracer experiments are performed at different values of the drying process air flow rate and vibration acceleration. The axial dispersion model parameter values are identified for each experiment. Manifolds for the axial dispersion model parameters are then constructed by the regression of the GP models on the identified values. Comparison between the experiments and model predictions for an example validation case are shown, insight about the advantages of the method in model based controller design is given.
Paper VI151-03.2
PDF · Video · Part Mass Estimation Strategy for Injection Molding Machines (I)
Maderthaner, Jakob	TU Wien
Kugi, Andreas	Vienna University of Technology
Kemmetmueller, Wolfgang	TU Wien, Automation and Control Institute
Keywords: Process supervision, Manufacturing plant control, Quality assurance and maintenance Abstract: In injection molding, it is crucial to ensure high part quality over a long time period because typically these parts are produced in large numbers. Process variations influence the production and the resulting part quality. The part mass is frequently used as a quality measure as it can be easily measured by a scale after the part is finished. On the other hand, it is not possible to directly measure the part mass during the injection phase. This paper proposes a method to estimate the part mass by means of sensors, which are typically available in an injection molding machine. Compared to the state of the art, the proposed strategy also allows to estimate the time evolution of the part mass during the injection process. The accuracy of 0.25% and the robustness, with respect to process parameter variations, of the proposed part mass estimation is demonstrated by measurements.
Paper VI151-03.3
PDF · Video · Online Model Adaptation in Cold Rolling for Improvement of Thickness Precision (I)
Wehr, Matthias	RWTH Aachen University
Stenger, David	RWTH Aachen University
Schaetzler, Sven	RWTH Aachen University
Beyer, Ralf	RWTH Aachen, Institute of Automatic Control
Abel, Dirk	RWTH-Aachen University
Hirt, Gerhard	RWTH Aachen University
Keywords: Manufacturing plant control, Intelligent manufacturing systems, Modeling of manufacturing operations Abstract: Cold rolling is a process that finishes the production of flat steel and must therefore guarantee high strip precision. However, the strip thickness produced in the roll gap cannot be measured directly which makes its observation in the roll gap challenging. In this paper, the model of both the mill frame as well as the cold rolled strip are optimized online using measured process data. A Recursive Least Squares parameter estimator is used to determine mill modulus and offset of the roll stand, while the rolling model of the steel strip is adapted using Gaussian Process Regression. The adapted models are then used in a model based controller which adjusts the roll gap accordingly. Experimental results show that the precision of the models is enhanced using online measurements. As a result the desired strip thickness is achieved despite initial model uncertainties.
Paper VI151-03.4
PDF · Video · Quality Control in Injection Molding Based on Norm-Optimal Iterative Learning Cavity Pressure Control (I)
Stemmler, Sebastian	RWTH Aachen University
Vukovic, Marko	RWTH Aachen University
Ay, Muzaffer	RWTH Aachen University
Heinisch, Julian	RWTH Aachen University
Lockner, Yannik	RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Hopmann, Christian	Institute of Plastics Processing (IKV) at RWTH Aachen University
Keywords: Manufacturing plant control, Intelligent manufacturing systems, Quality assurance and maintenance Abstract: Plastic injection molding is characterized by high design flexibility of the manufactured parts. Consequently, it is one of the most important processes for mass production of plastic parts. The setup of the manufacturing process is very complex due to numerous impact factors. In addition, material fluctuations or changing ambient conditions require the adaption of the setup during manufacturing to guarantee a constant product quality. In order to reduce the setup effort and to control the quality, the concept of model-based self-optimization is applied to injection molding. Therefore, a model-based Norm-Optimal Iterative Learning Controller (NOILC) is used to track a desired reference for the cavity pressure during the entire cycle. This reference is determined by the so-called pvT-optimization which considers the cooling behavior of the melt within the cavity. It is shown by experiments that the cavity pressure can be controlled with high accuracy using the presented NOILC. Furthermore, the accuracy of the quality, especially the part weight is improved by combining the NOILC with an additional pvT-optimization.
Paper VI151-03.5
PDF · Video · Robust Parametrization of a Model Predictive Controller for a CNC Machining Center Using Bayesian Optimization (I)
Stenger, David	RWTH Aachen University
Ay, Muzaffer	RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Manufacturing plant control, Quality assurance and maintenance Abstract: Control algorithms such as model predictive control (MPC) and state estimators rely on a number of different parameters. The performance of the closed loop usually depends on the correct setting of these parameters. Tuning is often done manually by experts based on a simulation model of the system. Two problems arise with this procedure. Firstly, experts need to be skilled and still may not be able to find the optimal parametrization. Secondly, the performance of the simulation model might not be able to be carried over to the real world application due to model inaccuracies within the simulation. With this contribution, we demonstrate on an industrial milling process how Bayesian optimization can automate the tuning process and help to solve the mentioned problems. Robust parametrization is ensured by perturbing the simulation with arbitrarily distributed model plant mismatches. The objective is to minimize the expected integral reference tracking error, guaranteeing acceptable worst case behavior while maintaining real-time capability. These verbal requirements are translated into a constrained stochastic mixed-integer black-box optimization problem. A two stage min-max-type Bayesian optimization procedure is developed and compared to benchmark algorithms in a simulation study of a CNC machining center. It is showcased how the empirical performance model obtained through Bayesian optimization can be used to analyze and visualize the results. Results indicate superior performance over the case where only the nominal model is used for controller synthesis. The optimized parametrization improves the initial hand-tuned parametrization notably.
Paper VI151-03.6
PDF · Video · Development of a UI Submodel for the Industry 4.0 Component
Baron, Lukas	Technische Universität Dresden
Braune, Annerose	Technische Universität Dresden, Electrical Engineering
Keywords: Design, modelling and analysis of HMS, Knowledge modelling and knowledge based systems, Intelligent interfaces Abstract: A provision of user interfaces (UI) by use of the Industry 4.0 component and its asset administration shell (AAS) requires the development of a new UI submodel. Depending on the intended use case and the planned context of use, the submodel needs to be able to store and characterize multiple UI fragments (Variants of the UI) that shall be included in UI solutions. For that, appropriate properties need to be identified and a submodel structure has to be designed. In order to apply the newly designed UI submodel in a plug and produce scenario, the properties need to be formally specified, thus, being interpretable by automatic tools. This contribution presents a UI submodel, a catalogue of UI fragment properties, and a first case study applying these properties to UI fragments of existing industrial systems.

VI151-04
Intelligent Manufacturing Systems	Regular Session
Chair: Dolgui, Alexandre	IMT Atlantique
Co-Chair: Jumar, Ulrich	Ifak - Institut F. Automation U. Kommunikation
Paper VI151-04.1
PDF · Video · Case Study Analysis of Laser-Assisted Low-Cost Automation Assembly
Müller-Polyzou, Ralf	Leuphana University of Lüneburg
Meier, Nicolas	Leuphana University of Lüneburg
Georgiadis, Anthimos	Leuphana University of Lüneburg
Keywords: Assembly and disassembly, Flexible and reconfigurable manufacturing systems Abstract: Highly connected Cyber-Physical Systems (CPS) are central elements for the Digital Factory of Industry 4.0. The integration of existing automation infrastructure with cost-efficient laser systems for worker guidance creates Low-Cost Automation (LCA) CPS that enable quality workplaces. Such human centric LCA CPS must be usability optimized. This paper presents the findings of three case studies focusing on the perceived efficiency, effectiveness and system usability of an LCA CPS laser-assisted assembly station in a shop-floor scenario. By using an inductive approach, design principles are derived that enable usability optimized LCA CPS to support acceptance and productivity.
Paper VI151-04.2
PDF · Video · Line Balancing and Sequencing for Peak Power Minimization
Lamy, Damien	Mines Saint-Etienne
Delorme, Xavier	Mines Saint-Etienne
Gianessi, Paolo	Mines Saint Etienne
Keywords: Assembly and disassembly, Job and activity scheduling, Flexible and reconfigurable manufacturing systems Abstract: In the past years, environmental awareness started to bring new production paradigms based on energy efficiency. If it is possible to improve energy efficiency of existing production systems, it should be even more profitable to consider this objective at the design stage. In the context of Paced Production Lines, and given power requirements for operations, it becomes possible to assign more efficiently these operations to stations while respecting other constraints such as maximum takt time and number of workstations. The repetitive nature of paced lines implies that misconceptions implying a high peak power consumption will see this peak power repeated over and over without having large possibilities to correct it. In order to tackle peak power minimization objectives, this implies to consider sequencing of operations in addition to their assignment to workstation which is not classical in line balancing. In this paper, the problem under study is presented with a new specific feature that allows to consider semi-active sequence of operations at each station. In order to address large scale instances, a first metaheuristic approach is implemented and evaluated on an extended dataset from the literature. Results show that it is possible to improve energy efficiency at the design stage of production systems.
Paper VI151-04.3
PDF · Video · LSTM Water Prediction for Feedforward Control of Moulding Sand Compressibility
Rose, Alexander	Hochschule Hannover
Seel, Alexander	IAV GmbH
Luck, Bennet	IAV GmbH
Grotjahn, Martin	Hannover University of Applied Science and Arts
Keywords: Discrete event systems in manufacturing, Manufacturing plant control Abstract: This paper presents a databased approach for improving the precision of the moulding sand compressibility in the moulding sand mixer of a foundry. In this approach, the deviation between the measured and the target compressibility is reduced by controlling the water addition. The complex dynamic behaviour of the process variables and their influence on the water addition is modelled with a long short-term memory (LSTM) network. Another LSTM network as control path simulates the impact of the water addition on the compressibility. Simulation and experimental results with the applied model for water prediction in a feedforward control yield relevant improvements of the moulding sand compressibility.
Paper VI151-04.4
PDF · Video · Cooperative Control of a Flexible Manufacturing System
Zgorzelski, Markus	Ruhr-Universität Bochum
Lunze, Jan	Ruhr-Universität Bochum
Keywords: Discrete event systems in manufacturing, Modelling and control of hybrid and discrete event systems, Manufacturing automation over networks Abstract: This paper considers networked discrete-event systems. Local state-feedback controllers enable each subsystem to reach local target states. Due to the physical restrictions between the subsystems, the local target states might not be reachable autonomously, but cooperatively with the help of other subsystems. Therefore, each subsystem is extended by a network unit, which detects and resolves possible physical restrictions. If cooperation is necessary, the network units temporarily modify their local target states while applying situation-dependent communication. The proposed method is applied to the flexible manufacturing system HANS and its applicability to real-life systems is demonstrated by experimental results.
Paper VI151-04.5
PDF · Video · Cost and Quality Assessment of a Disruptive Reconfigurable Manufacturing System Based on MOPSO Metaheuristic
Khan, Abdul Salam	LCFC, ENSAM, Metz
Homri, Lazhar	Arts Et Métiers ParisTech
Dantan, Jean-yves	Arts Et Métiers ParisTech
Siadat, Ali	Arts Et Métiers ParisTech
Keywords: Flexible and reconfigurable manufacturing systems Abstract: Reconfigurable manufacturing system is an active field of research for more than two decades, due to its enhanced efficiency and high throughput. An important aspect of such systems is process planning which assigns reconfigurable machines to different operations. This study examines the process planning problem subject to different defects and considers novel optimization criteria based on scrap cost, re-work cost, number of failed and conforming units produced by a process plan. A multi-objective model has been developed to optimize the total cost and the quality decay index of the process plan. Due to NP hard nature of the problem, a heuristic called multi-objective particle swarm optimization has been implemented and a numerical example has been analyzed. The results will help decision maker in understanding the impact of quality on process plan selection and a trade-off between different components of the proposed model.
Paper VI151-04.6
PDF · Video · Minimizing Task Reassignments in the Design of Reconfigurable Manufacturing Lines with Space Restrictions
Yelles-Chaouche, Abdelkrim R.	IRT Jules Verne
Gurevsky, Evgeny	Université De Nantes
Brahimi, Nadjib	Rennes School of Business
Dolgui, Alexandre	IMT Atlantique
Keywords: Flexible and reconfigurable manufacturing systems Abstract: This paper deals with the design of a reconfigurable manufacturing line able to produce multiple products belonging to a same family. The aim is to generate for each product an appropriate line configuration subject to a given set of constraints so as to minimize the number of reassigned tasks when switching from one configuration to another. For this purpose, a mixed-integer linear programming (MILP) model is developed and tested on two categories of instances with 20 and 50 tasks respectively using a commercial solver. The obtained results show the efficiency (in terms of CPU and GAP) of the proposed MILP model to handle the first category of instances. However, it finds its limits to tackle the second category of instances.
Paper VI151-04.7
PDF · Video · Toward Scheduling for Reconfigurable Manufacturing Systems
Lamy, Damien	Mines Saint-Etienne
Delorme, Xavier	Mines Saint-Etienne
Lacomme, Philippe	Univ Blaise Pascale
Fleury, Gérard	Université Blaise Pascal Laboratoire d’Informatique (LIMOS) UMR
Keywords: Flexible and reconfigurable manufacturing systems, Job and activity scheduling Abstract: Reconfigurable Manufacturing Systems have been introduced in the mid 1990s as an alternative to classical dedicated or flexibles production systems. They are supposed to be more reactive and capable of evolving depending on unpredictable and high-frequency market changes induced by global market competition. While this concept has received a lot of attention in the literature, mainly at the design and conception phase of the production system, only few works are addressing the operational management of such production systems. One of the key features of reconfigurable manufacturing system is the possibility to use different configurations. The objective is to schedule operations efficiently while considering the different configurations of the system that are available. Switching from one configuration to another requires setup times. However, contrary to classical setup times that can be found in literature on scheduling problems, switching from a configuration i to j may require that some machines are stopped. This paper intends to formalise such a problem in the context of Flow-shop and Job-shop production systems. First results on small case instances are introduced.
Paper VI151-04.8
PDF · Video · Prediction of Pulsed Heat Loads in Manufacturing Plants
Fuhrmann, Florian	Technische Universität Wien
Schirrer, Alexander	Vienna University of Technology
Kozek, Martin	Vienna University of Technology
Jakubek, Stefan M.	Technical Univ. of Vienna/Austria
Keywords: Manufacturing plant control Abstract: Predictive control is beneficial for effective energy demand management. Precise disturbance pre-diction is a decisive factor for the performance of predictive control. This paper focuses on the accu-rate prediction of pulsed heat loads caused by heat treatment in manufacturing industry processes. An application-oriented method to predict heat load peaks is developed utilizing basic laws of thermo-dynamics, validated with process data from an industrial use case, and tested with a model predictive controller. Two core characteristics of the method enable a straightforward application in industry: 1. Historic data from few measurement points are sufficient. 2. Robustness against measurement noise.
Paper VI151-04.9
PDF · Video · Mathematical Model for a Cutting Path Avoiding Intersections
Makarovskikh, Tatiana	South Ural State University
Panyukov, Anatoly	South Ural State University
Keywords: Manufacturing plant control, Modeling of manufacturing operations, Procedures for process planning Abstract: During the technological preparation of the cutting process, it is necessary to determine the path of the cutter when there are no self-intersections of the cutting path and the part cut off from the sheet does not require any cuts, then arise the problems: first, representation of the cutting plan as a planar graph which is the homeomorphic image of the cutting plan; second, algorithms to find the cutter routes in this graph. The paper is devoted to a polynomial-time algorithm for constructing a non-intersecting ordered enclosing chain (NOE-chain) for a plane Eulerian graph. The proposed approach consists in splitting of all original graph vertices with degree higher than 4 by introducing fictive vertices and edges and, thus, reducing the considered earlier problem to the problem of finding an A-chain with ordered enclosing in a plane connected 4-regular graph. A test example of constructing NOE-chain with ordered enclosing is considered.
Paper VI151-04.10
PDF · Video · Optimal Production Planning for Flexible Manufacturing Systems: An Energy-Based Approach
Diaz, Jenny	Universitat Politècnica De Catalunya
Ocampo-Martinez, Carlos	Universitat Politecnica De Catalunya (UPC)
Keywords: Manufacturing plant control, Production planning and control, Flexible and reconfigurable manufacturing systems Abstract: Production programming in a manufacturing industry is usually performed based on off-line optimisations of the processing times or plant productivity. However, most of these approaches do not consider the energy market and its fluctuations. Therefore, it is not possible to take advantage of these fluctuations to also minimise the energy costs and to increase the plant profit. In this regard, a control strategy based on the Economic Model Predictive Control approach is proposed to reduce energy costs during the operation of a manufacturing plant. The proposed controller determines the instants in which the production programs should be executed to satisfy the daily demand while minimising the energy costs through regular updates of the energy prices according to the current energy market. Besides, by implementing a control strategy in real time, changes in the demand of parts according to the customer requirements could also be considered, adding more flexibility to the plant operation. The proposed control strategy has been tested in simulation, and the obtained results show that energy costs can be reduced without affecting the plant productivity.
Paper VI151-04.11
PDF · Video · A Sustainable Development Evaluation Card for a Manufacturing Company (I)
Patalas-Maliszewska, Justyna	University of Zielona Góra
Łosyk, Hanna	University of Zielona Góra
Jasiulewicz-Kaczmarek, Malgorzata	Poznan University of Technology
Keywords: Modeling of manufacturing operations, Production activity control, Life-cycle control Abstract: Sustainable development (SD), in production, is possible when the company's management has access to data and information, the analysis of which allows the level of SD to be assessed. The use of information technologies enables enterprises to effectively manage resources through comprehensive and integrated solutions, matched to the specific needs of the enterprise. The article proposes a Sustainable Development Evaluation Card for a manufacturing company, which consists of the following elements: (1) SD goals, (2) SD indicators, (3) Analytic Hierarchy Process method, (4) ERP system functionality, (5) reference values of SD indicators, (6) level of SD, (7) recommended actions for SD. The usability of the proposed solution is shown, using as an example a real-life, production company as a case study.
Paper VI151-04.12
PDF · Video · Synchronism Recovery of Discrete Event Systems
Alves, Lucas Vinícius Ribeiro	Universidade Federal De Minas Gerais
Pena, Patricia Nascimento	Universidade Federal De Minas Gerais
Keywords: Discrete event systems in manufacturing, Intelligent maintenance systems, Quality assurance and maintenance Abstract: Most of the systems are build of components that should stay synchronized for the system to work properly. Usually, the synchronism of these subsystems is maintained through communication and this communication is subject to failures, leading the system to a undesirable state, where the states of the components do not match. In this sense, this paper deals with the problem of resynchronizing components of a system, leading to a global state where the individual states of the subsystems match with each other. In order to do so, an algorithm, using ideas of synchronizing automata, automata that reach a specific state when a synchronizing word is executed, regardless the origin state, is presented.
Paper VI151-04.13
PDF · Video · GPU Accelerated Acoustic Field Determination for a Continuously Excited Circular Ultrasonic Transducer
Lemos Duran, Alberto	EPUSP
Sato, Andre Kubagawa	Escola Politecnica Da Universidade De Sao Paulo
Silva Jr, Agesinaldo M.	EPUSP
Franco, Ediguer E.	Universidad Autonoma De Occidente
Buiochi, Flavio	University of Sao Paulo
Martins, Thiago de Castro	University of Sao Paulo
Adamowski, Julio Cezar	University of Sao Paulo
Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Keywords: Intelligent manufacturing systems, Device integration technologies Abstract: This work presents a GPU algorithm to calculate the acoustic field generated by a circular ultrasonic transducer radiating in water a continuous wave. The acoustic pressure in a space point in front of the transducer is calculated by Rayleigh integral, which uses the Huygens principle to compose the field as the sum of contributions from an infinite number of point sources. Because the pressure at each spatial point can be calculated independently, the solution algorithm can run in parallel, taking advantage of the GPU cores. Some experiments were performed in a frequency range from 0.25 to 5.0 MHz. The radiating surface was discretized in order to have a fixed number of elemental areas per wavelength. Results showed the validity of the acoustic fields simulated. In addition, a performance analysis showed that the GPU was 50 times faster than CPU for the most demanding problems.
Paper VI151-04.14
PDF · Video · Alarm Correlation to Improve Industrial Fault Management
Benatia Mohamed Amin, Amin	LINEACT-CESI
Baudry, David	CESI
Louis, Anne	CESI
Keywords: Intelligent manufacturing systems, Konwledge discover (data mining), RFId and ubiquitous manufacturing Abstract: Maintenance management is one of the key component to assess product quality and decrease production cost in several manufacturing enterprises. Nowadays, impressive progress & level of integration has been made in monitoring technologies and industrial data analysis (i.e., Industrial Articial Intelligence (AI)) thus allowing new Condition-Based Maintenance (CBM) capabilities. However, data-driven CBM algorithms, especially black-box models, need labeled data which is often unavailable. In addition, they are generally dicult to interpret making it hard to integrate them in a real industrial system. In this paper, we investigate the use of Frequent Pattern Mining algorithm, an enumeration-tree based approach, for extracting relationships between industrial alarm events. Due to the time indexation of the alarm events, we adapt the algorithm in order to take into account the duration between alarm events when extracting the itemsets. Filtered rules where evaluated according to the Minimmum support & Condence framework with lift consideration. Obtained results show that FPM algorithm can derive very useful knowledge on system behaviour allowing the identication of alarm subsequence with the corresponding root cause.
Paper VI151-04.15
PDF · Video · Reinforcement Learning for Resource Constrained Project Scheduling Problem with Activity Iterations and Crashing (I)
Sung, Inkyung	Aalborg University
Choi, Bongjun	Aalborg University
Nielsen, Peter	Aalborg University
Keywords: Job and activity scheduling, Intelligent decision support systems in manufacturing Abstract: Resource allocation is a key decision-making process in project management that assigns resources to activities of a project and determines the timing of the allocation in a cost and time effective manner. In this research, we address the resource allocation for a project, where iterations between activities of the project exist and the crashing, a method to shorten the duration of an activity by incorporating additional resources, is available. Considering the stochastic nature of project execution, we formulate the resource allocation as a Markov decision process and seek the best resource allocation policy using a deep reinforcement learning algorithm. The feasibility and performance of applying the algorithm to the resource allocation is then investigated by comparison with heuristic rules.
Paper VI151-04.16
PDF · Video · Gated Recurrent Unit Networks for Remaining Useful Life Prediction
Li, Li	College of Electronic and Information Engineering, Tongji Univer
Zhao, Zhen	Tongji University
Zhao, Xiaoxiao	Tongji University
Lin, Kuo-Yi	College of Electronic and Information Engineering, Tongji Univer
Keywords: Maintenance models and services, Intelligent maintenance systems, Intelligent manufacturing systems Abstract: Remaining useful life prediction is a key procedure for prognostics and health management. However, traditional data-driven methods rely on handcrafted feature selection from the whole range of time series data, which may not obtain the temporal information for complex systems. This study proposes a gated recurrent unit networks based approach to predict remaining useful life. First, time window approach is applied on sample preparation for multiple sensor data. In particular, unsupervised stacked sparse autoencoder is utilized to automatically extract nonlinear features, then the selected features are fed into gated recurrent unit based recurrent neural networks to predict remaining useful life. The effectiveness of the proposed method is demonstrated on the commercial modular aero-propulsion system simulation data from NASA. Experimental results validate that the proposed approach achieves better prediction performance than other methods.
Paper VI151-04.17
PDF · Video · Profit Optimization for Zero Ending Inventories Dynamic Pricing Model under Stochastic Demand and Fixed Lifetime Product
Kitaeva, Anna	National Reseach Tomsk State University
Stepanova, Natalia	V. A. Trapeznikov Institute of Control Sciences of Russian Acade
Zhukovskaya, Alexandra	Tomsk State Pedagogical University
Keywords: Adaptive control, Parametric optimization Abstract: We consider a single perishable product under a compound Poisson demand with a price sensitive intensity and a continuous batch size distribution. A model of a dynamic retail price control with an adjustable coefficient is proposed providing almost surely zero ending inventories at the end of the product’s lifetime. To obtain probabilistic characteristics of the selling process and the expected profit a diffusion approximation of the demand process is used. The task of the expected profit optimization with respect to the coefficient and lot size for a linear intensity-of-price dependence is solved.
Paper VI151-04.18
PDF · Video · A Knowledge Based System for Managing Heterogeneous Sources of Engineering Information
Ocker, Felix	Technical University of Munich
Vogel-Heuser, Birgit	Technical University of Munich
Seitz, Matthias	Technical University of Munich
Paredis, Christiaan Jos Jan	Georgia Institute of Technology
Keywords: Knowledge modelling and knowledge based systems, Mechatronic systems, Modeling Abstract: As ever increasing amounts of engineering information become available, engineers require novel ways to manage this information. Especially in mechatronic engineering, e.g., the engineering of Cyber-Physical Production Systems, engineers from various disciplines are involved, and they represent their knowledge in heterogeneous ways. To be able to efficiently gain an overview of the available information and find the information required, engineers need support. Additionally, awareness regarding interdisciplinary dependencies should be increased to reduce late changes. Such dependency analyses allow engineers to better identify and thus manage potential inconsistencies, which can be expected to reduce development time. The Knowledge Based System presented supports engineers during the design process of production systems by providing an overview of available engineering knowledge, its representation, and associated stakeholders. Additionally, engineers can leverage the underlying holistic information model to create and manage digital twins.

VI152
Manufacturing and Logistics Systems - Manufacturing Modeling for Management and Control
VI152-01 AI–driven Methods for Multimodal Logistic Systems Modeling and Performance Analysis   Invited Session, 5 papers
VI152-02 Digital Twins in CPS-Based Manufacturing Plant Control   Invited Session, 7 papers
VI152-03 Human Factors in Production and Logistics Systems of the Future   Invited Session, 10 papers
VI152-04 Intelligent Methods and Tools Supporting Decision Making in Manufacturing Systems and Supply Chains   Invited Session, 5 papers
VI152-05 Operations Research Techniques for Complex Systems Scheduling   Invited Session, 5 papers
VI152-06 System Identification for Manufacturing Control Applications   Open Invited Session, 5 papers
VI152-07 Intelligent Services for Manufacturing and Maintenance   Regular Session, 5 papers
VI152-08 Scheduling for Manufacturing   Regular Session, 7 papers
VI152-09 Production Planning and Control   Regular Session, 11 papers

VI152-01
AI–driven Methods for Multimodal Logistic Systems Modeling and Performance Analysis	Invited Session
Chair: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Co-Chair: Sarmah, S P	IIT Kharagpur
Organizer: Banaszak, Zbigniew	Koszalin University of Technology
Organizer: Bocewicz, Grzegorz	Koszalin University of Technology
Organizer: Robertas, DamaŠevičius	Kaunas University of Technology
Organizer: Gola, Arkadiusz	Faculty of Mechanical Engineering, Lublin University of Technolo
Organizer: Nielsen, Izabela	Aalborg University
Organizer: Smutnicki, Czeslaw Adam	Wroclaw University of Technology
Organizer: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Organizer: Sarmah, S P	IIT Kharagpur
Organizer: Wójcik, Robert	Wrocław University of Science and Technology
Paper VI152-01.1
PDF · Video · UAVs Fleet Mission Planning Robust to Changing Weather Conditions (I)
Bocewicz, Grzegorz	Koszalin University of Technology
Radzki, Grzegorz	Koszalin University of Technology
Nielsen, Izabela	Aalborg University
Witczak, Marcin	University of Zielona Gora
Banaszak, Zbigniew	Koszalin University of Technology
Keywords: Job and activity scheduling, Distributed nagigation and control of unmmanned autonomous vehicles, Logistics in manufacturing Abstract: A fleet of homogeneous UAVs fly in a 2D plane matching a distribution network to service customers in a collision-free manner. Limited UAVs’ battery capacity and UAVs’ weight reduction during they traveling along planned routes and goods delivery as well as changing weather conditions are also taken into account. The goal is to determine a set of routings covering all delivery points so that the total distance traveled by the UAVs fleet is constrained by a battery capacity limit. All customers’ demands are realized within a given time horizon and take into account forecasted weather constraints, focusing on changes in a wind speed and direction. In this context, the main objective is to propose a declarative model allowing one to prototype proactive routings of UAVs fleet mission. Computational experiments assessing alternative strategies of UAVs fleet mission robust to forecast weather conditions are discussed.
Paper VI152-01.2
PDF · Video · Declarative Modelling Approach for New Product Development (I)
Relich, Marcin	University of Zielona Gora
Nielsen, Izabela	Aalborg University
Bocewicz, Grzegorz	Koszalin University of Technology
Smutnicki, Czeslaw Adam	Wroclaw University of Technology
Banaszak, Zbigniew	Koszalin University of Technology
Keywords: Intelligent system techniques and applications, Business process management systems, Intelligent decision support systems in manufacturing Abstract: The paper is concerned with using constraint programming for simulating an alternative project completion of new product development (NPD). All possible variants of project completion are sought within the company’s resources and requirements for an NPD project. A company and its projects can be considered in terms of variables and constraints that constitute the systems approach for a project prototyping problem. This problem is described in the form of a constraint satisfaction problem and implemented with the use of constraint programming techniques. The paper also presents a method for estimating the NPD cost and unit production cost, and simulating variants that ensure the desirable level of costs, including the impact of granularity on the number of solutions. An example shows the applicability of the proposed approach in the context of NPD projects.
Paper VI152-01.3
PDF · Video · Detection of Defected Zone Using 3D Scanning Data to Repair Worn Turbine Blades (I)
Ueda, Edson Kenji	Escola Politecnica Da Universidade De Sao Paulo
Barari, Ahmad	University of Ontario Institute of Technology
Sato, Andre Kubagawa	Escola Politecnica Da Universidade De Sao Paulo
Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Keywords: Intelligent manufacturing systems, Manufacturing plant control Abstract: This work will present a method to determine the curve that approximates the worn perimeter in a turbine blade. A CAD model is used as reference and it is searched for points of a measured point cloud that shows a worn in a blade. A threshold is used to filter measured and fabrication errors, resulting in a point cloud that just indicates the worn region. The alpha complex algorithm is used to triangulate the determined points. The resulting triangulation eliminates long edges making possible to a triangulation with concave regions. The boundary points of this triangulation is determined by the search for edges that belongs to just one triangle. A simulated annealing is used to optimize a cost function to determine the piecewise cubic Bézier curve that approximates these boundary points.
Paper VI152-01.4
PDF · Video · Manufacturability Assessment in Assembly Processes (I)
Matuszek, Józef	University of Bielsko-Biala
Seneta, Tomasz	University of Bielsko-Biala
Plinta, Dariusz	University of Bielsko-Biala
Więcek, Dariusz	University of Bielsko-Biala
Keywords: Methodologies and tools for analysis of complexity, Procedures for process planning, Assembly and disassembly Abstract: In this paper, there is presented the problem of assessing the manufacturability of complex products at the design stage of the manufacturing process considering the criterion of execution of assembly operations processes and production costs. Assessment of manufacturability was given on the example of the Boothroyd & Dewhurst method. This paper describes how to estimate the times and costs of assembly operations according to the mentioned above criteria with the use of the expert system. The presented example illustrates its practical application. The method of analysis presented in this article, developed by the authors, will be the subject of further research aimed at creation of an advanced expert system supporting the design of assembly systems.
Paper VI152-01.5
PDF · Video · Structural Decomposition Approach to Design of No-Wait Cyclic Schedules for Repeatedly Operating Transport System Dedicated to Supply Loops (I)
Wójcik, Robert	Wrocław University of Science and Technology
Gola, Arkadiusz	Faculty of Mechanical Engineering, Lublin University of Technolo
Pempera, Jaroslaw	Wroclaw University of Science and Technology
Patalas-Maliszewska, Justyna	University of Zielona Góra
Keywords: Job and activity scheduling, Production planning and control, Procedures for process planning Abstract: The paper presents a method allowing to construct no-wait cyclical schedules for repetitive transport systems (e.g. the milk-run) servicing cyclic material supply loops in the production system using selected means of transport (e.g. AGVs). The transport means are following established routes and given arrival times. The routes are composed of sectors linking workstations. Transport trolleys may share specific sectors of the route in mutual exclusion mode and must wait in a given sector to enter the next sector of the route when another trolley occupies it. The job-shop repetitive transportation system is a system of cyclic processes with a fixed structure that are executing sequences of operations (routes) using shared resources (sectors). The work aims to find a no-wait cyclic schedule that guarantees the required delivery dates or establish that such a schedule does not exist. It considers cyclic process systems for which each resource can be used by at most two operations, and the deadlock state cannot occur as a result of waiting processes on shared resources. For specified initial operations of cyclic processes and their start times (the initial system state), the problem of determining no-wait cyclical schedules decomposes into subproblems. Each subproblem consists of the verification of necessary and sufficient conditions for the existence of solutions for each of 2-process subsystems composed of one shared resource and two processes using this resource. The method aims of prototyping various variants of process starting times for which the conditions guaranteeing no-wait property of the system hold simultaneously for each of the 2-process subsystems. It allows designing cyclic schedules for complex systems composed of 2-process subsystems that are structurally deadlock-free. The class of cyclical processes considered in this article is broader than the class of cascade-like (chain-like, sequential) process systems analysed so far in the literature. In this context, the results obtained are an extension of the existing ones.

VI152-02
Digital Twins in CPS-Based Manufacturing Plant Control	Invited Session
Chair: Lee, Jay	University of Cincinnati
Co-Chair: Negri, Elisa	Politecnico Di Milano
Organizer: Iung, Benoît	Lorraine University
Organizer: Lee, Jay	University of Cincinnati
Organizer: Macchi, Marco	Politecnico Di Milano
Organizer: Negri, Elisa	Politecnico Di Milano
Organizer: Weichhart, Georg	Profactor GmbH
Paper VI152-02.1
PDF · Video · Human-Computer-Machine Interaction for the Supervision of Flexible Manufacturing Systems: A Case Study (I)
Hernandez Rodriguez, Jose Daniel	Universidad De Los Andes
Cespedes Sabogal, Edgar Schneider	Universidad De Los Andes
Gutierrez, David Andres	Universidad De Los Andes
Sanchez-Londono, David	Los Andes University
Barbieri, Giacomo	Universidad De Los Andes
Abolghasem, Sepideh	University of Los Andes
Romero, David	Tecnológico De Monterrey
Fumagalli, Luca	Politecnico Di Milano
Keywords: Process supervision, Modeling of manufacturing operations, Production planning and control Abstract: Production is moving from mass-production to ‘mass-customization’ and ‘personalization’ (lot-size-one). Accordingly, modern manufacturing systems must become more agile and responsive to changing global markets and closer to customers. Industry 4.0 technologies have the premises to face these changes in the production paradigm. However, technologies must be supported by methodological approaches focused on the process to be optimized, digitalized, and made more flexible. In this paper, we propose a seamless Human-Computer-Machine Interaction (HCMI) architecture for supporting the supervision activity of the operator in the context of flexible manufacturing systems. The suggested interaction is implemented and validated using a lab case study where we demonstrate how the proposed HCMI architecture, in line with the Industry 4.0 architectural design principles, enables ‘close-to-real-time’ supervision of the manufacturing system in its self-adaptation to production changes.
Paper VI152-02.2
PDF · Video · The Role of Dynamics in Digital Twins and Its Problem-Tailored Representation (I)
Cimino, Chiara	Politecnico Di Milano
Ferretti, Gianni	Politecnico Di Milano
Leva, Alberto	Politecnico Di Milano
Keywords: Model-driven systems engineering, Modeling of manufacturing operations, Manufacturing plant control Abstract: In Smart Manufacturing, the Internet of Things technology brings about new possibilities as for the interaction of Cyber-Physical Systems with their virtual models - in Industry 4.0 jargon, Digital Twins. Besides traditional roles in engineering and control design, Digital Twins cab play innovative ones by evolving together with their cyber-physical counterpart: predictive maintenance, fault detection, or fast training of data-based decision aid tools. In this paper we focus on the relevance of dynamic models in this scenario, particularly as for the co-existence of continuous-time and discrete-event models wherever control and planning are involved. We argue that in such cases, models with analysis-specific levels of detail have to co-exist, interact and maintain mutual consistency. We propose a modelling approach to address the problem, and present a supporting example based on an object-oriented modelling language.
Paper VI152-02.3
PDF · Video · A Framework for Operator Assist Apps of Automated Systems (I)
Wehrstedt, Jan Christoph	Siemens AG
Sohr, Annelie	Siemens AG
Schenk, Tim	Siemens AG
Rosen, Roland	Siemens AG
Zhou, Yayun	Siemens AG
Keywords: Production planning and control, Modeling of manufacturing operations, Job and activity scheduling Abstract: The role of assist functions for complex production systems is increasing. This paper introduces a framework for the developing simulation-based assist functions by using reusable microservices, a common data format and a low coding HMI. This approach is illustrated for an online bottleneck detection for a production system.
Paper VI152-02.4
PDF · Video · Local Decision Making Based on Distributed Digital Twin Framework (I)
Villalonga, Alberto	Center for Automation and Robotic (CSIC-UPM)
Negri, Elisa	Politecnico Di Milano
Fumagalli, Luca	Politecnico Di Milano
Macchi, Marco	Politecnico Di Milano
Castaño Romero, Fernando	Centre for Automation and Robotics (UPM-CSIC)
Haber, Rodolfo	Center for Automation and Robotics (UPM-CSIC)
Keywords: Intelligent decision support systems in manufacturing, Intelligent system techniques and applications, Intelligent manufacturing systems Abstract: In recent years under the fourth industrial revolution, digitalization has taken an important role in the manufacturing industry. Digital twins (DT) are one of the key enabling technologies that are leading the digital transformation. Integrating DT with IoT and artificial intelligence enable the developing of more accurate models of the real world to improve scheduling tasks, production performances optimization and decision making. This work proposes a distributed digital twin framework to improve decision making at local level in manufacturing. A decision making module based on an adaptive threshold algorithm is implemented. Finally, the proposed framework is evaluated on a pilot line, highlighting the decision making module detection of possible faults, alerting the operator and notifying to the MES to trigger actions of reconfiguration and scheduling
Paper VI152-02.5
PDF · Video · The Role of Digital Twins in the Fulfilment Logistics Chain (I)
Piancastelli, Cosimo	Universita´ Degli Studi Di Firenze
Tucci, Mario	Florence University
Keywords: Complex logistic systems, Digital enterprise, Enterprise integration Abstract: Although Digital Twins has gained great momentum in the last few years, even being developed in the scenario of manufacturing systems, scarce attention has been devoted till now to the Logistics Digital Twin (LDT). In this paper we describe the first efforts to define the requirements, and derive from them the architecture and framework for LDT for fulfilment centres. The analysis stems from actual logistics platforms, for internet orders fulfilment and will use them as verification, validation and accreditation (VV&A) testbed.
Paper VI152-02.6
PDF · Video · A Digital Shadow Cloud-Based Application to Enhance Quality Control in Manufacturing (I)
Santolamazza, Annalisa	University of Rome Tor Vergata
Groth, Corrado	University of Rome Tor Vergata
Introna, Vito	Università Di Roma
Porziani, Stefano	University of Rome Tor Vergata
Scarpitta, Francesco	University of Rome Tor Vergata
Urso, Giorgio	University of Rome Tor Vergata
Valentini, Pier Paolo	University of Rome Tor Vergata
Costa, Emiliano	RINA Consulting S.p.A
Ferrante, Edoardo	RINA Consulting S.p.A
Sorrentino, Stefano	RINA Consulting S.p.A
Capacchione, Biagio	CMS Spa
Rochette, Michel	ANSYS France
Bergweiler, Simon	DFKI GmbH
Poser, Valerie	DFKI GmbH
Biancolini, Marco E.	University of Rome Tor Vergata
Keywords: Quality assurance and maintenance, Intelligent manufacturing systems, Life-cycle control Abstract: In Industry 4.0 era, rapid changes to the global landscape of manufacturing are transforming industrial plants in increasingly more complex digital systems. One of the most impactful innovations generated in this context is the "Digital Twin", a digital copy of a physical asset, which is used to perform simulations, health predictions and life cycle management through the use of a synchronized data flow in the manufacturing plant. In this paper, an innovative approach is proposed in order to contribute to the current collection of applications of Digital Twin in manufacturing: a Digital Shadow cloud-based application to enhance quality control in the manufacturing process. In particular, the proposal comprises a Digital Shadow updated on high performance computing cloud infrastructure in order to recompute the performance prediction adopting a variation of the computer-aided engineering model shaped like the actual manufactured part. Thus, this methodology could make possible the qualification of even not compliant parts, and so shift the focus from the compliance to tolerance requirements to the compliance to usage requirements. The process is demonstrated adopting two examples: the structural assessment of the geometry of a shaft and the one of a simplified turbine blade. Moreover, the paper presents a discussion about the implications of the use of such a technology in the manufacturing context in terms of real-time implementation in a manufacturing line and lifecycle management.
Paper VI152-02.7
PDF · Video · Reconfigurable Manufacturing Systems Characteristics in Digital Twin Context (I)
Tang, Jiecheng	Cranfield University
Emmanouilidis, Christos	Cranfield Univeristy
Salonitis, Konstantinos	Cranfield University
Keywords: Flexible and reconfigurable manufacturing systems, Digital enterprise, Modeling of manufacturing operations Abstract: The concept of a reconfigurable manufacturing system (RMS) has been introduced to enable production systems to continuously evolve and respond rapidly to unpredicted and fluctuating market environments. To achieve this goal, RMS needs to exhibit six core characteristics: modularity, integrability, scalability, diagnosability, convertibility and customisation. These characteristics are required to ensure manufacturing systems’ resilience while maintaining productivity and quality. Assessing these characteristics at both the design and operating phase can be aided by the digital twinning (DT) of physical systems. To this end, the DT-RMS concept is introduced in this paper as a dynamic cyber-replica of the physical production environment, enabling a high-level of transparency about data, performance, and relevant reconfiguration decisions. As a result, DT-RMS responds to the need to integrate requirements and performance targets for the RMS characteristics at design and operating-time

VI152-03
Human Factors in Production and Logistics Systems of the Future	Invited Session
Chair: Grosse, Eric	Saarland University
Co-Chair: Sgarbossa, Fabio	Norwegian University of Science and Technology - NTNU
Organizer: Grosse, Eric	Saarland University
Organizer: Sgarbossa, Fabio	Norwegian University of Science and Technology - NTNU
Organizer: Glock, Christoph	Technische Universität Darmstadt
Organizer: Battini, Daria	University of Padua
Organizer: Neumann, W. Patrick	Human Factors Engineering Lab, Department of Mechanical and Indu
Paper VI152-03.1
PDF · Video · Effects of Human Communication on a Web-Based Information System (I)
Seki, Norihito	Hokkai-Gakuen University
Keywords: Collaborative networked organizations principles, Internet of Services and Service Science, Business process management systems Abstract: Objectives: This study investigates how human communication helps promote the use of information systems that intermediate businesses; it does so by studying a load-matching system used in the transportation industry. Load-matching systems are designed to increase the transportation efficiency of trucking companies. Most load-matching systems in Japan are inactive; the Japan Local Network System (JL) is one of the few successful load-matching services. Materials and Method:　A questionnaire survey was administered to 663 member corporations of the JL. A total of 145 responses were received (response rate: 21.9%); of these, 38 were excluded due to missing values, leaving a final sample of 107. The respondents provided appropriate values for each of the seven variables, that is, human communication, meta-information, access to the system, entry load information, matching load, entry truck information, and matching truck. Results: We constructed several structural equation models via covariance structure analysis. In the model adopted in this study, all paths were significant at the 1% level. Furthermore, the conformity indices were satisfactory (χ2 = 15.43, GFI = .961, AGFI = .909, CFI = .991, RMSEA = .051, AIC = 47.243). Conclusions: This study examined the effect of human communication on the use of an information system. We investigated the key factors that promote trade in a web-based load-matching service by undertaking a positive analysis of the results of a questionnaire survey administered to members of the JL, a successful web-based load-matching service that encourages members to exchange and distribute information via face-to-face communication. The results of covariance structure analysis revealed that increased information distribution promotes the intermediary service and that metadata sharing helps increase the number of transactions. Metadata were also found to be acquired via face-to-face communication. Keywords: Small- and Medium-sized Truck Carrier, Load-matching system, Human communication, Information sharing, Covariance structure analysis, Logistics in Japan
Paper VI152-03.2
PDF · Video · Age Management in the Context of Industry 4.0 and Beyond (I)
Grah, Barbara	Faculty of Economics, University of Ljubljana
Colnar, Simon	Faculty of Economics, University of Ljubljana
Dimovski, Vlado	Faculty of Economics, University of Ljubljana
Penger, Sandra	School of Economics and Business, University of Ljubljana
Keywords: Modelling and decision making in complex systems, Quality assurance and maintenance, Process supervision Abstract: Keeping workers active and productive for a longer time is one of the key societal challenges of developed economies. Older workers have accumulated experiences and knowledge during their working lifetime, but due to declining functional capacities, many of them will not be able to work until the increased retirement age. Contemporary technological solutions supporting human-machine interactions such as smart working environment, production cells, exoskeletons, and others, in the context of Industry 4.0 technologies enable workers to stay productive longer. In the present study, we use a multiple decrement model. In the numerical example, we apply the model to the European industrial workforce. We modeled transitions among different productivity states of industrial workers, ranging from a potential employee to workforce exit, through retirement or death. The presented study shows the importance of appropriate age management practice applications that have the potential to substantially prolong the work-life of industrial workers in the European Union. The demographic model presented, allows measuring the influence that technological solutions in the context of Industry 4.0 have on the workers' entrance and exits. The model shows how leveraging the accumulated workers' knowledge and experience of older workers and automation of physically demanding tasks can not only improve the productivity of industrial systems but also decrease the costs of ill-health related expenditures.
Paper VI152-03.3
PDF · Video · Robot Picker Solution in Order Picking Systems: An Ergo-Zoning Approach (I)
Sgarbossa, Fabio	Norwegian University of Science and Technology - NTNU
Romsdal, Anita	Norwegian University of Science and Technology
Johannson, Finn Hartvig	Norwegian University of Science and Technology
Krogen, Torbjørn	Currence Robotics
Keywords: Logistics in manufacturing, Production planning and control, Modeling of manufacturing operations Abstract: Manual order picking is the most labour-intensive activity in warehouses. As an alternative, robot pickers that can work alongside manual order pickers have emerged. This paper presents such a robot picker and develops a method for assigning products to two warehouse zones; one for robot pickers and one for human pickers. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to develop the zoning method, minimizing human workload and maximizing the similarity of product categories in each zone. The method was verified in a case study.
Paper VI152-03.4
PDF · Video · Design of AGV Systems in Working Environments Shared with Humans: A Multi Case Study (I)
Zuin, Silvia	University of Padua
Hanson, Robin	Chalmers University of Technology
Battini, Daria	University of Padua
Persona, Alessandro	University of Padua
Keywords: Logistics in manufacturing, Multi-agent systems applied to industrial systems, Process supervision Abstract: To meet the challenges and needs of an ever-changing market and as part of the fourth industrial revolution, factories are transforming into increasingly automated environments. A widely used and well-established solution today is Automated Guided Vehicles (AGVs), which often work closely with humans in crowded environments. Thus, in addition to flexibility, another important criterion associated with automatic handling systems is safety. The purpose of this work is to show how the involvement of three different but equally important roles in the design of an AGV system can benefit the whole project. The advantage of considering three different perspectives is the possibility of obtaining a more complete vision from the earliest stages of implementation, avoiding, as far as possible, the need to make changes in the next stages, which would generate higher costs than necessary. The article is based on two case studies, each one set in a major European manufacturing company: the first one is an Italian automotive manufacturer and the second one is a Swedish manufacturer of mechanical components. Both case companies apply AGVs in their material handling processes and, accordingly, have experience of both implementing and operating AGV systems. The article applies semi-structured interviews to study the three key roles, highlighting the key points for each role and showing the common issues that emerged from the interviews.
Paper VI152-03.5
PDF · Video · Work Characteristics in Logistics 4.0: Conceptualization of a Qualitative Assessment in Order Picking (I)
Winkelhaus, Sven	TU Darmstadt
Grosse, Eric	Saarland University
Keywords: Logistics in manufacturing, Job and activity scheduling, Production planning and control Abstract: Logistics 4.0 is an emerging phenomenon, where new digital technologies are used to fulfill increasing demands of delivering individualized products against high cost pressure and fast delivery. Within this development, human factors should not be neglected, since they will remain an important aspect of process efficiency and business success. One logistics process that has undergone a major transformation within Logistics 4.0 with regard to manual human work is warehouse order picking. However, the implications of increasing digitalization on human workers in order picking is not yet fully understood. Hence, this contribution grounds on a qualitative assessment of work characteristics in order picking and conceptualizes possible influences of the digital transformation on order pickers. These conceptual interrelations enable to design future workplaces that allow higher job satisfaction, motivation, quality and performance of work as well as lower turnover intentions.
Paper VI152-03.6
PDF · Video · Smart Logistics and the Logistics Operator 4.0 (I)
Cimini, Chiara	University of Bergamo
Lagorio, Alexandra	University of Bergamo
Romero, David	Tecnológico De Monterrey
Cavalieri, Sergio	University of Bergamo
Stahre, Johan	Chalmers University of Technology
Keywords: Device integration technologies, e-Manufacturing technologies and facilities, Intelligent manufacturing systems Abstract: The advent of the Fourth Industrial Revolution is expected to deeply change several aspects of the manufacturing industry. Among them, the logistics and supply chain activities will be affected by these changes both at operational and managerial level to face the market drivers of flexibility and masscustomisation. In this context, the work of operators in internal and external logistics will be affected by these changes and increase the interaction between humans and machines. The evolution of the roles of humans in Logistics 4.0 will give birth to "The Logistics Operator 4.0" paradigm. The aim of this paper is to investigate the impacts of Industry 4.0 technologies on the different roles of logistics operators that work in the main logistics domains and areas.
Paper VI152-03.7
PDF · Video · Reducing Fatigue Level through Tasks and Breaks Assignment in Order Picking System (I)
Sgarbossa, Fabio	Norwegian University of Science and Technology - NTNU
Vijayakumar, Vivek	Norwegian University of Science and Technology
Keywords: Modeling of manufacturing operations, Production activity control, Procedures for process planning Abstract: At the present scenario in production and logistics systems, some activities are still carried out manually by the operators such as lifting, lowering pushing/ holding, or carrying of objects (Napolitano, 2012). Thus, it is necessary to highlight the conditions of the operator such as fatigue, stress, safety, and errors while designing such systems particularly, in cases where the whole body is used intensively, such as order picking (OP) process (Battini, Delorme, Dolgui, Persona, & Sgarbossa, 2016). The order picking process is the retrieval of items from the warehouse to fulfill customer and production requirements, which is the most time consuming and labor-intensive activity in warehousing. Moreover, order picking could demand a great deal of physical effort because of frequent handling of items, gradually resulting in increased physical fatigue level due to the demand of high energy expenditure by the pickers. Thus, energy expenditure depends on some attributes of OP such as item characteristics, order profiles, and storage assignments (Battini, Glock, Grosse, Persona, & Sgarbossa, 2016). Consequently, there has been a need for reducing the fatigue level of the order pickers to improve their performance in picking by providing recovery to the operators during their work. To reduce the accumulated fatigue, adequate recovery time has been found out through Rest Allowance (RA), which is based on energy expenditure rate of the working period and the resting period (Price, 1990), as well as on the maximum acceptable work level or maximum energy expenditure rate. This is even more important when considering the ageing workforce because the maximum energy expenditures tend to decrease with an increase in age i.e. lower acceptable work level for an ageing workforce. Hence the age of order picker plays an important factor in determining the fatigue and recovery trend (Achten & Jeukendrup, 2003).
Paper VI152-03.8
PDF · Video · Considering Workers' Features in Manufacturing Systems: A New Job-Rotation Scheduling Model (I)
Finco, Serena	Università Degli Studi Di Padova
Zennaro, Ilenia	University of Padova
Battini, Daria	University of Padua
Persona, Alessandro	University of Padua
Keywords: Job and activity scheduling, Assembly and disassembly, Production planning and control Abstract: The European manufacturing industry is entering a new era in which working populations are ageing. The E.U. had set itself strategy objectives to increase the labour market participation of older workers. However, practical limits arise, and a complete re-thinking of operation management strategies and manufacturing systems design and management is needed. As underlined in several works, older workers have not the same physical capacity as the younger ones. Consequently, they are more subjected to develop work-related musculoskeletal disorders despite younger colleagues. On the other hand, they might present higher skill levels in doing some specific tasks due to their considerable experience. Thus, they can be employed in teaching or training younger or unskilled workers. Starting from these initial considerations, in this paper, we develop a new age-oriented job rotation scheduling model. Both physical capacity and experience level aspects are included in the mathematical model aiming to maximize daily productivity. We quantify physical fatigue by using the energy expenditure rate and the maximum acceptable energy expenditure. Then, the rest allowance concept is evaluated according to the workers’ age and the shift work duration. Variable execution times of each job according to the workers’ experience level and mandatory training activities for unskilled workers are also taken into consideration. Finally, a numerical case derived by a real application is proposed to validate the model and demonstrate benefits we can achieve by applying it.
Paper VI152-03.9
PDF · Video · Human Decision Making in Systems with Limited Capacity (I)
Haeussler, Stefan	University of Innsbruck
Ilmer, Quirin	University of Innsbruck
Stefan, Matthias	University of Innsbruck
Keywords: Modelling and decision making in complex systems, Production planning and control, Intelligent decision support systems in manufacturing Abstract: Humans are a crucial component of operational decision making and, thus, largely influence the performance of companies and supply chains. Behavioral decision making, including risk and loss averse behavior, limited cognitive abilities and behavioral biases can be expected to result in different outcomes compared to supply chains including only rational profit-maximizing agents. The aim of this paper is to shed some light on the potential human influence on systems (e.g., supply chains) with limited capacities – which prevail in industrial practice where people compete for scarce resources. Based on insights from state-of-the-art (behavioral) operations management literature we identify potential environmental factors and human causes that lead to a better understanding of human decision making in systems with limited capacity.
Paper VI152-03.10
PDF · Video · Dual Robot Kit Preparation in Batch Preparation of Component Kits for Mixed Model Assembly (I)
Fager, Patrik	Chalmers University of Technology
Hanson, Robin	Chalmers University of Technology
Fast-Berglund, Aasa	Chalmers University of Technology
Keywords: Logistics in manufacturing, Modeling of manufacturing operations, Modeling of assembly units Abstract: Kitting is a materials supply principle that plays a vital role for performance in mixed model assembly systems. The kit preparation process, whereby component kits are created, is central when kitting is applied. Kit preparation is a form of materials handling and is associated with several ergonomic and quality related issues. Robotics holds a great potential for decreasing the need for human labour, but literature on the topic is scarce. The purpose of this paper is to identify the time efficiency potential of a dual robot application for kit preparation. To address the purpose, a mathematical model is developed that allows dual robot kit preparation to be analysed and compared with manual kit preparation. Furthermore, the model supports identification of a suitable batch size given a lead time requirement from the assembly system. A numerical example shows dual robot kit preparation to be slightly more efficient than its manual ditto for preparation of 2, 3 and 4 kit batch sizes. The paper makes a theoretical contribution in terms of the time efficiency model of dual robot kit preparation. This model is also useful for practitioners when evaluating the potential of dual robot arm kit preparation in their own processes.

VI152-04
Intelligent Methods and Tools Supporting Decision Making in Manufacturing Systems and Supply Chains	Invited Session
Chair: Freitag, Michael	University of Bremen
Co-Chair: Frazzon, Enzo Morosini	Federal University of Santa Catarina
Organizer: Freitag, Michael	University of Bremen
Organizer: Frazzon, Enzo Morosini	Federal University of Santa Catarina
Organizer: Pereira, Carlos Eduardo	Federal Univ. of Rio Grande Do Sul - UFRGS
Paper VI152-04.1
PDF · Video · Industry 4.0 Influences on Maintenance Operation: A Bibliometric Analysis (I)
Reis, Thiago Augusto Silva	Universidade Metodista De Piracicaba
Campos, Fernando Celso	UNIMEP/PPGEP
Keywords: Maintenance models and services, Intelligent maintenance systems, e-Manufacturing technologies and facilities Abstract: The paper describes the Industry 4.0 influences on maintenance operation through a bibliometric analysis. The current trend is the introduction of 4.0 concepts allied with basic maintenance practices. It has been considered as an important tool to improve the machine availability and equipment reliability. New modern techniques are been used to predict and optimize maintenance processes, in fact it is understood as a strategical activity and a profit contributor to ensure productivity and efficiency in manufacturing systems. With the bibliometric analysis, it is possible to analyze the main trends and the 4.0 tools most related to maintenance operation optimization.
Paper VI152-04.2
PDF · Video · Simulation-Based Optimization for the Integrated Control of Production and Logistics: A Performance Comparison (I)
Pires, Matheus Cardoso	Federal University of Santa Catarina
Frazzon, Enzo Morosini	Federal University of Santa Catarina
Quadras, Djonathan L. O.	Federal University of Santa Catarina
Broda, Eike	University of Bremen
Freitag, Michael	University of Bremen
Keywords: Production planning and control, Logistics in manufacturing, Job and activity scheduling Abstract: Manufacturing systems’ efficiency depends on the proper assignment of orders to resources. Due to existing interdependencies, the integrated consideration of production, inventory and delivery processes can improve the overall manufacturing performance. However, the integration can result in high complexity and stochasticity. Thus, the three areas are rarely addressed together. Thereof, this paper proposes an integrated simulation-based optimization method to cope with uncertainty and complexity. The proposed approach was compared to a benchmark approach and the obtained results show that the first is able to handle the complexity and stochasticity of real-world manufacturing systems, surpassing the performance of the latter.
Paper VI152-04.3
PDF · Video · Deep Learning-Based Object Recognition for Counting Car Components to Support Handling and Packing Processes in Automotive Supply Chains (I)
Börold, Axel	BIBA – Bremer Institut Für Produktion Und Logistik at the Univer
Teucke, Michael	BIBA - Bremer Institut Für Produktion Und Logistik at the Univer
Rust, Johannes	BIBA – Bremer Institut Für Produktion Und Logistik at the Univer
Freitag, Michael	University of Bremen
Keywords: Intelligent decision support systems in manufacturing, Logistics in manufacturing, Quality assurance and maintenance Abstract: Complex distributed supply chains, e.g., in the automotive industry, need to cope with high product variety. Digital image processing can use specific geometric and optical properties of parts and components for determining their type and thus needs no external markers. It is thus well applicable to supply chain processes that involve direct handling of many different product components and need no individual identification of items. An example of such a process is counting items of different product types during packing. In this paper, we use deep learning-based digital image processing methods in order to distinguish and count the number of objects of two different types of automotive components in standardized transport bins, detected by time-of-flight (ToF) depth sensors. Classical watershed object counting methods are adapted to depth data and support the fast generation of training data for the deep learning-based classification methods. The proposed method is applied to an automotive supply chain, and it is demonstrated that car components can be counted with good reliability during packing into transport bins. Thus, digital image processing can be useful to supplement auto-identification and sensor technologies and complete digital end-to-end monitoring of supply chains.
Paper VI152-04.4
PDF · Video · Supervised Machine Learning for Knowledge-Based Analysis of Maintenance Impact on Profitability (I)
Schenkelberg, Kai	University of Siegen
Seidenberg, Ulrich	University of Siegen
Ansari, Fazel	Vienna University of Technology (TU Wien)
Keywords: Manufacturing plant control Abstract: Recent empirical studies reveal that predictive maintenance is essential for accomplishing business objectives of manufacturing enterprises. Knowledge-based maintenance strategies for optimal operation of industrial machines and physical assets reasonably require explaining and predicting long term ecconomic impacts, based on exploring historical data. This paper examines how supervised machine learning (ML) techniques may enhance anticipating the economic impact of maintenance on profitability (IMP). Planning and monitoring of maintenance activities supported by various statistical learning and supervised ML algorithms have been investigated in the literature of production management. However, data-driven prediction of IMP has not been largely adressed. A novel data-driven framework is proposed comprising cause-and-effect dependencies between maintenance and profitability, which constructs a set of appropriate features as independent variables.
Paper VI152-04.5
PDF · Video · Dynamic Production Order Allocation for Distributed Additive Manufacturing (I)
Agostino, Icaro	Federal University of Santa Catarina
Frazzon, Enzo Morosini	Federal University of Santa Catarina
Gomes Soares Alcalá, Symone	Federal University of Goiás
Basto, João	INESC TEC
Taboada Rodriguez, Carlos Manuel	Federal University of Santa Catarina
Keywords: Decentralized and distributed control, Job and activity scheduling, Internet-of-Things and Sensing Enterprise Abstract: Distributed manufacturing systems represent a new paradigm in the industrial context, supported by new technologies provided by industry 4.0. In this paper, a model for dynamic allocation of Production Orders (PO) in the context of distributed additive manufacturing systems is proposed. The scheduling model performs a local optimization of PO allocation considering a production times forecasting model, fed by system state data obtained by means of an IoT platform, and transportation real-time data. A simulation-based experiment was conducted in a test case with real and simulated data collected from an elevator spare parts provider in Brazil. A significant reduction of 77.94% of the Average Waiting Time (AWT) was obtained, allowing for an increased efficiency of the additive manufacturing system, which supports the forthcoming pilot application.

VI152-05
Operations Research Techniques for Complex Systems Scheduling	Invited Session
Chair: Yalaoui, Farouk	University of Technology of Troyes, Institue of Services and Industries of Future of Troyes,
Co-Chair: Ouazene, Yassine	Université De Technologie De Troyes
Organizer: Ouazene, Yassine	Université De Technologie De Troyes
Organizer: Yalaoui, Farouk	University of Technology of Troyes, Institue of Services and Ind
Paper VI152-05.1
PDF · Video · A Dedicated Lot Sizing Problem in Tire Industry (I)
Koch, Cyril	University of Technology of Troyes
Ouazene, Yassine	Université De Technologie De Troyes
Arbaoui, Taha	ICD-LOSI, University of Technology of Troyes
Yalaoui, Farouk	University of Technology of Troyes, Institue of Services and Ind
Jaunet, Nicolas	Manufacture Française Des Pneumatiques Michelin
De Wulf, Antoine	Manufacture Française Des Pneumatiques Michelin
Keywords: Production planning and control, Production activity control, Modeling of manufacturing operations Abstract: In this paper, we consider a dedicated lot sizing and scheduling problem inspired from a real-world application in tire industry. This problem consists in scheduling several products on parallel machines with eligibility constraints within a finite planning horizon. We consider several specific constraints such as the number of simultaneous scheduled products, the number of setup per period and minimum quantities to produce. A mathematical model that determines a production schedule minimizing backlogging, low and high inventory surplus is proposed and tested on real data with up to 210 products, 70 machines and 7 periods. The obtained results show the effectiveness of the proposed model which improve significantly the industrial solution.
Paper VI152-05.2
PDF · Video · Mathematical Model for Scheduling Food Production in Hospital Catering (I)
Abderrabi, Fatima	University of Technology of Troyes
Godichaud, Matthieu	University of Technology of Troyes
Yalaoui, Alice	University of Technology of Troyes
Yalaoui, Farouk	University of Technology of Troyes, Institue of Services and Ind
Amodeo, Lionel	University of Technology of Troyes
Qerimi, Ardian	Hospital Center of Troyes
Thivet, Eric	Hospital Center of Troyes
Keywords: Production planning and control, Logistics in manufacturing, Job and activity scheduling Abstract: The problem addressed in this paper was motivated by a real optimization problem of the supply chain of the hospital center of Troyes (HCT). The HCT is currently seeking to review and improve its logistics processes. The implementation of techniques and methods of operational research must provide solutions that improve the efficiency of logistics activities. In this work, we are interested in the problem of scheduling food production in the central kitchen of HCT. A novel mathematical model for the production scheduling of multi-products and multi-stages food processes in hospital catering is proposed. This mathematical model has been implemented in commercial solver CPLEX and it has been tested on real instances of HCT and from the literature. The implementation results of the mathematical model proposed have proved its efficiency for the scheduling of the food production process.
Paper VI152-05.3
PDF · Video · New Heuristic for Single Machine Semi-Online Total Completion Time Minimization (I)
Nouinou, Hajar	Université De Technologies De Troyes (UTT)
Arbaoui, Taha	ICD-LOSI, University of Technology of Troyes
Yalaoui, Alice	University of Technology of Troyes
Keywords: Job and activity scheduling, Production planning and control, Intelligent decision support systems in manufacturing Abstract: This paper addresses a semi-online setting of the minimization of the total completion time scheduling problem on a single machine, where jobs arrive over-time, i.e, each job has a corresponding release date at which it becomes available for processing. In this study, the case where the release dates of the jobs are known at the beginning of the decision process is considered while processing times remain unknown. A semi-online algorithm that makes use of the available information in order to produce better schedules compared to its online peers is presented. A numerical analysis is established, showing the impact of having this information about release dates.
Paper VI152-05.4
PDF · Video · Disassembly Lot Sizing Problem with Disposal Decisions for Multiple Product Types with Parts Commonality (I)
Pour Massahian Tafti, Meisam	UTT-LOSI
Godichaud, Matthieu	University of Technology of Troyes
Amodeo, Lionel	University of Technology of Troyes
Keywords: Assembly and disassembly, Modelling and decision making in complex systems, Optimization and control of large-scale network systems Abstract: Disassembly lot sizing problem is one of the important operational problems in disassembly systems. It can be defined as the problem of determining the disassembly quantity and timing of the used-products to fulfill the demand of their parts over a finite planning horizon. This paper considers the case of multiple product types with parts commonality and the objective is to minimize the sum of setup, disassembly operation, and inventory holding costs. High inventory holding cost can be generated: because of disparity between independent and unbalanced demands, and the disassembly of one unit of used-product generates all the parts with different ratios. Aggregate formulation (AGG) can be used to model this problem by considering disposal decisions. Linear-Programming (LP) relaxation of this model doesn't give very good lower bound, especially for the large-sized instances. We aim to improve lower bound of the problem. Facility Location-Based formulation (FAL) is developed which can obtain optimal or near optimal solution by using LP relaxation approach. A two-phase heuristic is proposed which constructs an initial solution by using LP relaxation approach, and then improves by a dynamic programming based heuristic. Computational experiments are conducted on randomly generated test problems which show that the models and methods can give optimal or near-optimal solutions in very short computational times.
Paper VI152-05.5
PDF · Video · A Case for Symbolic Limited Optimal Discrete Control: Energy Management in Reactive Data-Flow Circuits
özbaltan, Mete	University of Liverpool
Berthier, Nicolas	University of Liverpool
Keywords: Control problems under conflict and/or uncertainties Abstract: We present a framework for achieving efficient dynamic management of configurable reactive data-flow circuits subject to global design objectives such as mutual exclusion on shared resources and minimization of energy consumption. We propose a new symbolic controller synthesis algorithm that targets the optimization of a cost function summed over a sliding window of a given number of reactions of the system. We then present a technique for constructing symbolic models of configurable data-flow circuits that lends itself to the automatic computation of dynamic configuration controllers. We use these models to experimentally evaluate our control algorithm, and make the case for symbolic optimal discrete controller synthesis on such designs.

VI152-06
System Identification for Manufacturing Control Applications	Open Invited Session
Chair: Bakhtadze, Natalia	V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences
Co-Chair: Jharko, Elena	V.A. Trapeznikov Institute of Control Sciences
Organizer: Lototsky, Vladimir	V.A. Trapeznikov Institute of Control Sciences
Organizer: Bakhtadze, Natalia	V.A. Trapeznikov Institute of Control Sciences, Russian Academy
Organizer: Chernyshov, Kirill	V.A. Trapeznikov Institute of Control Sciences
Organizer: Jharko, Elena	V.A. Trapeznikov Institute of Control Sciences
Paper VI152-06.1
PDF · Video · Parameter Identification of Block-Oriented Nonlinear Systems in the Frequency Domain (I)
Shanshiashvili, Besarion	Georgian Technical University
Rigishvili, Temur	LTD Scientific-Enterprise Company ’’SOVBI’’
Keywords: Modeling of manufacturing operations, Identification and model reduction, Modelling and decision making in complex systems Abstract: A problem of parameter identification of nonlinear dynamic systems of manufacturing processes on the set of block-oriented models in the frequency domain is considered. Method of parameter identification in steady state at the input sinusoidal influences is proposed. The solution of the problem of parameter identification is reduced to the solution of the systems of algebraic equations by using the Fourier approximation. The parameters estimations are received by the least squares method. The identification method is investigated by theoretical analysis and computer modelling.
Paper VI152-06.2
PDF · Video · Relay Feedback Identification with Shifting Filter for PID Control (I)
Hofreiter, Milan	Czech Technical University in Prague, Fac. of Mechanical Eng
Keywords: Identification for control, Modeling of manufacturing operations, Production activity control Abstract: The paper describes a recently introduced relay shifting method for process identification using a single relay feedback test. The aim is to obtain a process model for automatic tuning of PID controllers. This method is applicable for open-loop stable, unstable and integrating systems if there is sustained oscillation in a biased-relay feedback test. For this purpose the identification method uses a filter called a "shifting filter" which enables to estimate the next point on a process frequency characteristic. Furthermore, this additional point can be used to estimate the parameters of the process transfer function with multiple parameters, including static gain, even under a static load disturbance. In the paper, a new more robust algorithm for fitting a second-order time delayed model is introduced. It can be used for the PID controller design of the most processes describable by linear models. For the first time the shifting filter is also applied for the relay feedback identification of unstable systems. The method is demonstrated on examples of stable, unstable and integrating systems.
Paper VI152-06.3
PDF · Video · Consistent Measures of Dependence in the Identification of Multi-input/Multi-Output Systems and Applications (I)
Chernyshov, Kirill	V.A. Trapeznikov Institute of Control Sciences
Jharko, Elena	V.A. Trapeznikov Institute of Control Sciences
Sakrutina, Ekaterina	V.A. Trapeznikov Institute of Control Sciences
Keywords: Nonlinear system identification, Stochastic system identification, Identification and model reduction, Manufacturing plant control Abstract: An approach to constructing linearized input/output mappings of multi-input/multi-output stochastic systems is presented. The approach is based on involving an information-theoretic measure of dependence of random vectors as a criterion of selection of input variables of the model. An application of the mathematical technique developed to a task of advanced automated process control system functions regarding nuclear power plants efficiency monitoring is considered.
Paper VI152-06.4
PDF · Video · On the Modelling of a Decentralised Production Control System in the Industry 4.0 Environment (I)
Grassi, Andrea	Universita' Degli Studi Di Napoli "Federico II"
Guizzi, Guido	University of Naples Federico II
Santillo, Liberatina Carmela	Università Degli Studi Di Napoli "Federico II"
Vespoli, Silvestro	Università Degli Studi Di Napoli "Federico II"
Keywords: Production planning and control, Production activity control, Flexible and reconfigurable manufacturing systems Abstract: The paper deals with a decentralized production control in an Industry 4.0 environment. In such a kind of systems, the capability to deliver a high level of product customization together with reduced response time is crucial to maintain competitiveness and to increase profit. A semi-heterarchical architecture, formed by three levels, in which the first is responsible for meeting business objectives, the second to maintain target system general performances, and the third to tackle operative scheduling problems, is first discussed as a framework for the future implementation in an Industry 4.0 environment. Successively, the problem to model the system form a dynamic point of view is addressed directly at the second architectural level. This paper, in particular, contributes to the semi-heterarchical architecture development, by proposing a first mathematical model of the shop-floor of a such a system, involving the use of the population dynamic modelling. Finally, the results of the first implementation in a simulated environment are reported.
Paper VI152-06.5
PDF · Video · Forecasting of Key Indicators of the Manufacturing System in Changing External Environment (I)
Avdeeva, Zinaida	V.A. Trapeznikov Institute of Control Sciences of RAS; National
Grebenuk, Helen	Institute of Control Sciences
Kovriga, Svetlana	V.A. Trapeznikov Institute of Control Sciences of the Russian Ac
Keywords: Modelling and decision making in complex systems, Intelligent system techniques and applications, Konwledge discover (data mining) Abstract: The management of a manufacturing system faces with the problem of long-term and medium-term forecasting of the system-forming factors of the stable functioning of the system(raw material prices, expected demand, the volume of orders, cost of products), changing due to dynamics of the markets for raw materials and end-products, high competition, as well as other political, economic and global factors. The expected improvement of the forecasting quality has not been achieved even with a large amount of qualitative and quantitative information about the system. The events accompanied by cumulative influences from many factors often lead to rapid changes in prices (structural shifts, changes in trends and price relationships) that are reflected in the quantitative data with a delay. Analysis of the strength and direction of cumulative influences of many factors on prices improves the quality of forecasting. This paper proposes the general scheme of the forecasting algorithm based on a system of models that includes a situation cognitive map and a set of the quantitative forecasting models of changes in the key indicators of a manufacturing system.

VI152-07
Intelligent Services for Manufacturing and Maintenance	Regular Session
Chair: Cordoni, Francesco Giuseppe	University of Verona
Co-Chair: Benyoucef, Lyes	Aix-Marseille University
Paper VI152-07.1
PDF · Video · Modularity and Integrability-Based Energy Minimization in a Reconfigurable Manufacturing Environment: A Non-Linear Mixed Integer Formulation (I)
Massimi, Elisa	Department of Industrial Engineering, Alma Mater Studiorum - Uni
Haddou Benderbal, Hichem	IMT Atlantique, LS2N-CNRS, Nantes, France
Benyoucef, Lyes	Aix-Marseille University
Bortolini, Marco	Alma Mater Studiorum - University of Bologna
Keywords: Flexible and reconfigurable manufacturing systems, Procedures for process planning, Modeling of manufacturing operations Abstract: Nowadays, manufacturing environment is characterized by the necessity of customized flexibility as well as responding rapidly and cost-effectively to changing market demands while minimizing impacts on environment and society. To reach these goals, a key paradigm called sustainable manufacturing can be coupled with reconfigurable manufacturing systems (RMSs). The coupling of RMS characteristics and sustainability concerns is a basis to develop a new generation of sustainable production systems. This paper outlines sustainability in a reconfigurable environment from an energy consumption point of view. A non-linear mathematical model is developed to optimize the energy consumption of a RMS through a redefinition of its core characteristics—modularity and integrability. The objective is to minimize the energy consumption of the system by selecting the most suitable modular machines from a set of candidate machines. The optimization problem is addressed using an exhaustive search heuristic. Finally, the applicability of the proposed approach is illustrated through a simple numerical example and the discussion of the obtained results
Paper VI152-07.2
PDF · Video · Quality Management and Blockchain Adoption in a Supply Chain (I)
Liu, Yang	Donghua University
Shen, Bin	Donghua University
Keywords: Intelligent manufacturing systems, Modeling of manufacturing operations, Business process management systems Abstract: In the past, it was difficult to check, identify, and trace product quality. Quality violation regularly takes place when consumers know product quality is overstated. In this paper, we examine the motivation for and implication of a supply chain that adopts blockchain technology to improve product quality in supply chains. We build up a stylish model in which a two-echelon supply chain consisting of one manufacturer and one retailer. The manufacturer decides whether or not to adopt blockchain and the retailer sells products to consumers. Our results imply that the manufacturer always provides a low-quality product without blockchain but when the quality-cost ratio is sufficiently high with the affordable blockchain adoption cost, blockchain technology could encourage the manufacturer to produce high-quality products.
Paper VI152-07.3
PDF · Video · Deep Learning Based Silicon Content Estimation in Ironmaking Process
Zhou, Heng	Zhejiang University
Zhang, Haifeng	Guangxi Liuzhou Iron and Steel Group Co. Ltd
Yang, ChunJie	Zhejiang University
Sun, Youxian	Zhejiang Univ
Keywords: Modeling of manufacturing operations, Quality assurance and maintenance, Intelligent system techniques and applications Abstract: Given the complexity and isolation of the blast furnace (BF), field engineers generally operate the system upon their former experience and the operating manual. Harsh environment and equipment shortage have made the testing of silicon content a prevailing method for the detection of temperature within BF. As the silicon content is a comprehensive performance of internal thermal state, knowing the exact value in advance can be very helpful for operators to keep the furnace temperature at a reasonable extent. Thus, an improved gated recurrent unit recurrent neural network (GRU-RNN) is proposed to predict the silicon content of hot metal, indicating a competitive performance at 92.4% hit rate among several deep learning methods.
Paper VI152-07.4
PDF · Video · Fault Prediction As a Service in the Smart Factory: Addressing Common Challenges for an Effective Implementation
Assad Neto, Anis	Pontifícia Universidade Católica Do Paraná
Ribeiro da Silva, Elias	University of Southern Denmark
Souza, André	Pontifícia Universidade Católica Do Paraná
Deschamps, Fernando	Pontifical Catholic University of Parana
Pinheiro de Lima, Edson	Pontifical Catholic University of Parana
Gouvea da Costa, Sergio	Pontifícia Universidade Católica Do Paraná
Keywords: Production activity control, Intelligent maintenance systems, Maintenance models and services Abstract: Fault prediction in manufacturing systems has consistently been an important theme in engineering research. Data-driven methods to deliver this service are gaining momentum due to developments regarding information and communication technologies. Particularly, fault prediction may be interpreted as a supervised learning classification problem, in which algorithms trained by operational data gathered from the shop-floor are capable of informing managers whether a machine might enter in a failure state or not. Despite the relevance of this approach, implementations are hindered by several challenges. In this work, we review approaches aimed to deal with four of these challenges, namely: limited amount of training data, unbalanced training data sets, uncertainty regarding which variables should be monitored, and uncertainty regarding how exactly historical data should be employed in the algorithm’s training. To deal with training sets with limited size, learning procedures observed to perform well with a lower volume of training data can be used, such as the Random Forests technique. Alternatively, transfer learning techniques can be utilized to adapt models trained in a virtual domain with abundant synthetic data to the real manufacturing system domain. To deal with unbalance among classification classes, cost-sensitive learning methods can be employed to alter the penalties incurred when misclassifications occurs in the minority class. Alternatively, resampling methods can be applied before learning occurs. Lastly, both the decisions regarding which variables to track, and to what extent historical data should be included in the training process, can be addressed through the use of specific feature selection methods.
Paper VI152-07.5
PDF · Video · A Deep Learning Unsupervised Approach for Fault Diagnosis of Household Appliances
Cordoni, Francesco Giuseppe	University of Verona
Bacchiega, Gianluca	I.R.S. Srl
Bondani, Giulio	IRS Srl
Radu, Robert	FirsT Srl
Muradore, Riccardo	University of Verona
Keywords: Quality assurance and maintenance, Process supervision, Intelligent manufacturing systems Abstract: Fault detection and fault diagnosis are crucial subsystems to be integrated within the control architecture of modern industrial processes to ensure high quality standards. In this paper we present a two-stage unsupervised approach for fault detection and diagnosis in household appliances. In particular a suitable testing procedure has been implemented on a real industrial production line in order to extract the most meaningful features that allow to efficiently classify different types of fault by consecutively exploiting deep autoencoder neural network and k-means or hierarchical clustering techniques.

VI152-08
Scheduling for Manufacturing	Regular Session
Chair: Takai, Shigemasa	Osaka University
Co-Chair: de Prada, Cesar	Univ. of Valladolid
Paper VI152-08.1
PDF · Video · A New Process Quality-Based Multi-Objective Multi-Part Approach for the Integrated Process Planning and Scheduling (IPPS) Problem in Reconfigurable Manufacturing Environment (I)
Morganti, Luca	Department of Industrial Engineering, Alma Mater Studiorum - Uni
Haddou Benderbal, Hichem	IMT Atlantique, LS2N-CNRS, Nantes, France
Benyoucef, Lyes	Aix-Marseille University
Bortolini, Marco	Alma Mater Studiorum - University of Bologna
Galizia, Francesco Gabriele	University of Padova
Keywords: Flexible and reconfigurable manufacturing systems, Procedures for process planning, Job and activity scheduling Abstract: This paper addresses the so calledintegrated process planning and scheduling (IPPS) problemin a reconfigurable manufacturing environment. Process planning and scheduling are two important and complex functions in manufacturing. To reduce the problem complexity, theyare considered sequentially by traditional approaches. In this paper, we consider the simultaneous integration of both functions by developing a heuristicapproach to solve the IPPS problem in a reconfigurable environment. Reconfigurable manufacturing systems (RMSs)compriseof a set of machines distinguished by multiple working configurations and tools. Each machine can perform a certain number of operations based on its configurationsand their availability.The purpose of the proposed heuristic approach is to find the best assignment of operations to machines while considering process-quality. Finally, to demonstrate the approach applicability, an illustrative numerical example is presented and the results discussed
Paper VI152-08.2
PDF · Video · Collaborative Supply Chain Planning and Scheduling of Construction Projects
Elmughrabie, Walid	école De Technologie Supérieure éTS
Ben Sassi, Oumaima	école De Technologie Supérieure
Dao, Thien-My	ETS/University of Québec
Chaabane, Amin	école De Technologie Supérieure
Keywords: Job and activity scheduling, Logistics in manufacturing, Modelling and decision making in complex systems Abstract: In this study, we propose an integrated model for collaborative Construction Supply Chain (CSC) planning that deals with the joint project scheduling and material ordering decisions. The main objective is to achieve more coordination and, therefore, to reduce the total CSC cost. More specifically, we consider a two-echelon Supply Chain (SC) composed of a manufacturer, a warehouse, and multiple construction sites where multiple independent construction projects are planned. The projects require different materials that are provided by the same manufacturer with a limited production capacity. The starting time of each activity is subject to materials availability in construction sites. A mixed-integer linear programming (MILP) model is developed to reduce the total costs while collaboration between contractors is possible. The model is implemented using the IBM ILOG® CPLEX® Optimization Studio and used to analyze the collaboration process through a numerical study to demonstrate the benefits of collaborative planning in construction project management. The decision model help also in finding practical construction projects’ sequences as well as suitable materials ordering, manufacturing, and inventories plans for SC participants.
Paper VI152-08.3
PDF · Video · Retail Order Picking Scheduling with Missing Operations and Limited Buffer
Souiden, Sawssen	MINES Saint-étienne
Cerqueus, Audrey	Mines Saint Etienne
Delorme, Xavier	Mines Saint-Etienne
Rascle, Jean-Lucien	Boa Concept
Keywords: Job and activity scheduling, Modelling and decision making in complex systems Abstract: Order picking is one of the most critical activities in the warehousing process. In order to obtain high profits, e-commerce retailers have focused on dedicated and accurate order picking methods. Zone picking is a picking approach commonly used for retail order picking where small-sized items have to be collected. Nevertheless, to become more efficient, it requires a scheduling policy for managing the bins flow which avoids blocking and mitigates order pickers unproductive times. This paper studies a specific variant of the Non-Permutation Flow-Shop (NPFS) scheduling problem with missing operations, transportation times, and limited capacity constraints. A mathematical formulation of this new problem is proposed to minimize the total elapsed time for all machines. We study an illustrative example to analyze the differences between the optimal solution of the proposed model and a naive solution.
Paper VI152-08.4
PDF · Video · A Home Health Care Planning Problem with Continuity of Care and Flexible Departing Way for Caregivers
Liu, Wenheng	Université De Technologie De Belfort-Montbéliard
Dridi, Mahjoub	UTBM
Fei, Hongying	Shanghai University
Hajjam El Hassani, Amir	University of Technology of Belfort-Montbéliard
Keywords: Job and activity scheduling, Procedures for process planning, Production planning and control Abstract: This paper formulates a mixed-integer programming model for a mid-term home health care routing and scheduling problem with considering several real-life constraints, such as continuity of care, time window, qualification of caregivers, and a flexible departing way for caregivers. Three sub-objectives: operational cost, the satisfaction of patients, and workload balancing of caregivers are merged with the weights as the objective function. The model is addressed by a commercial solver Gurobi through the randomly generated instances inspired by Periodic Vehicle Routing Problem with Time Windows (PVRPTW) benchmark. Computational results present that this problem can be solved efficiently. Furthermore, the relationship between sub-objectives and optimal results is discussed by changing weight allocation. This work offers HHC managements a proper method to respect practical constraints, achieve optimal objectives as well as find the optimal solution efficiency.
Paper VI152-08.5
PDF · Video · A Two-Stage Simulated Annealing-Based Scheduling Algorithm for a Make-And-Pack Production Plant
Yfantis, Vassilios	University of Kaiserslautern
Büscher, Sven	DEAMOS E.K
Klanke, Christian	TU Dortmund University
Corominas, Francesc	Procter & Gamble
Engell, Sebastian	TU Dortmund
Keywords: Job and activity scheduling, Production planning and control, Manufacturing plant control Abstract: Industrial scheduling problems are characterized by their highly combinatorial nature due to the large number of alternative solutions. The presence of discrete and continuous decisions in scheduling models usually lead to discrete optimization problems. Although powerful solvers and algorithms exist for this class of problems, real-life applications may still require prohibitively long computation times, severely hindering their practical deployability. An alternative way to solve hard discrete optimization problems is the use of metaheuristic algorithms, which provide approximate solutions in short computation times. In this contribution a scheduling algorithm based on simulated annealing is developed and applied to a make-and-pack process from the consumer goods industry. The algorithm consists of two stages, the first of which determines the allocation of the orders to the production lines, while the second refines the schedule by optimizing the sequence within each line. Two different layouts of the plant are examined, one where the make-and-pack stages are directly coupled and another where a finite intermediate buffer is used to decouple the two production stages. The generated production schedules are compared to nominal ones provided by the plant's planners, underlining the potential of the proposed approach, both in terms of solution quality and necessary computation time.
Paper VI152-08.6
PDF · Video · Distributed Job Shop Scheduling Using Consensus Alternating Direction Method of Multipliers
Miyamoto, Toshiyuki	Osaka University
Umeda, Toyohiro	Kobe Steel LTD
Takai, Shigemasa	Osaka University
Keywords: Job and activity scheduling, Production planning and control, Procedures for process planning Abstract: Scheduling problems belong to NP-hard and are not easily solved in large systems. In recent years, the development of optimization methods in multi-agent systems has been remarkable. In this paper, we consider a large-scale system as a multi-agent system and discuss a method of solving a scheduling problem using consensus among agents. We propose a distributed method using the alternating direction method of multipliers and evaluate the method using a small-scale instance of the scheduling problem.
Paper VI152-08.7
PDF · Video · Closed-Loop Scheduling in a Canned Food Factory
Gómez Palacín, Carlos	Universidad De Valladolid
Vilas, Carlos	Instituto De Investigacions Mariñas
Alonso, Antonio A.	IIM-CSIC
Pitarch, Jose Luis	Universidad De Valladolid
de Prada, Cesar	Univ. of Valladolid
Keywords: Job and activity scheduling, Production planning and control, Production activity control Abstract: This paper addresses the problem of closed-loop operation of scheduling, together with the interaction of control and scheduling, for a class of processes that appear very often in industry: those that combine continuous production lines with parallel batch units that share some resources. The paper presents a novel approach to this problem, including batching and a new type of precedence in the assignment problem. It also considers the effect of shared resources on the duration of the cycle time of the batch units. The approach is illustrated with a real-life example of a canned tuna factory

VI152-09
Production Planning and Control	Regular Session
Chair: Dolgui, Alexandre	IMT Atlantique
Co-Chair: Fatahi Valilai, Omid	Jacobs University Bremen GGmbH
Paper VI152-09.1
PDF · Video · Internal Supply Chain Digital Twin of a Pharmaceutical Company
Santos, João A. M.	Hovione FarmaCiencia
Lopes, Miguel	Hovione FarmaCiencia
Viegas, Joaquim	IDMEC, Instituto Superior Técnico, Universidade De Lisboa, Portu
Vieira, Susana M.	Technical University of Lisbon, Instituto SuperiorT´ecnico, CIS/I
Sousa, Joao M. C.	Technical Univ of Lisbon, Instituto Superior Tecnico
Keywords: Production planning and control, Digital enterprise, Monitoring and control of spatially distributed systems Abstract: A digital twin of a pharmaceutical company's internal supply chain is presented, along with a simulation-based rough cut capacity planning tool capable of giving estimates of the required monthly capacity for the different areas of the organization on the long-term. The work was a case study performed at a pharmaceutical company. The digital twin is delivered through a graphical user interface containing both its visualization and simulation tools. The proposed digital twin supplies accurate estimates of capacity needs to supply chain managers, giving the ability to easily visualize the resources required from different involved areas in the following 24 months.
Paper VI152-09.2
PDF · Video · The Digital Twin As a Core Component for Industry 4.0 Smart Production Planning
Novak, Petr	Czech Technical University in Prague - CIIRC
Vyskocil, Jiri	Czech Technical University in Prague - CIIRC
Wally, Bernhard	JKU Linz
Keywords: Production planning and control, Intelligent manufacturing systems, Flexible and reconfigurable manufacturing systems Abstract: Production systems that adhere the Industry 4.0 vision require new ways of control and integration of individual components, such as robots, transportation system shuttles or mobile platforms. This paper proposes a new production system control concept based on closing a feedback loop between a production planning system and a digital twin of the physical production system. The digital twin keeps up-to-date information about the current state of the physical production system and it is combined with the production planner utilizing artificial intelligence methods. Production recipes and concrete process instantiations are planned for each production order on-the-fly, based on the production system state retrieved form the digital twin. This approach provides a high flexibility in terms of ability to add and to remove products as well as production resources. It also enables error recovery by re-planning the production if some failure happens. The proposed approach is tested and evaluated on an internally hosted Industry 4.0 testbed, which confirms its efficiency and flexibility.
Paper VI152-09.3
PDF · Video · Reinforcement Learning for Dual-Resource Constrained Scheduling
Martins, Miguel S. E.	IDMEC – Instituto De Engenharia Mecânica
Viegas, Joaquim	IDMEC, Instituto Superior Técnico, Universidade De Lisboa, Portu
Coito, Tiago	Instituto Superior Técnico, Universidade De Lisboa
Firme, Bernardo	Instituto Superior Técnico
Sousa, Joao M. C.	Technical Univ of Lisbon, Instituto Superior Tecnico
Figueiredo, Joao Manuel	Universidade Evora
Vieira, Susana M.	Technical University of Lisbon, Instituto SuperiorT´ecnico, CIS/I
Keywords: Production planning and control, Job and activity scheduling, Intelligent manufacturing systems Abstract: This paper proposes using reinforcement learning to solve scheduling problems where two types of resources of limited availability must be allocated. The goal is to minimize the makespan of a dual-resource constrained flexible job shop scheduling problem. Efficient practical implementation is very valuable to industry, yet it is often only solved combining heuristics and expert knowledge. A framework for training a reinforcement learning agent to schedule diverse dual-resource constrained job shops is presented. Comparison with other state-of-the-art approaches is done on both simpler and more complex instances that the ones used for training. Results show the agent produces competitive solutions for small instances that can outperform the implemented heuristic if given enough time. Other extensions are needed before real-world deployment, such as deadlines and constraining resources to work shifts.
Paper VI152-09.4
PDF · Video · A Newsboy Formulae to Optimize Planned Lead Times for Two-Level Disassembly Systems (I)
Slama, Ilhem	IMT Atlantique, Nantes, France
Ben-Ammar, Oussama	école Des Mines De Saint-étienne, CMP Georges Charpak
Dolgui, Alexandre	IMT Atlantique
Masmoudi, Faouzi	Ecole Nationale Des Ingénieurs
Keywords: Production planning and control, Logistics in manufacturing, Assembly and disassembly Abstract: Disassembly planning and inventory management are important for businesses to provide customers with used components at competitive prices. To achieve this objective, one of the planners' priorities is to reduce the expected level of inventory in an uncertain environment. This study deals with a single-period disassembly to-order problem with known and fixed demand for components. The disassembly lead time for each component is an independent discrete random variable whose probability distributions are known and bounded. A mathematical model is suggested to determine the disassembly order for the end-of-life product and to calculate the expected total cost. Newsboy formulae for optimal disassembly order determination that minimizes the expected total cost is developed.
Paper VI152-09.5
PDF · Video · The Storage Space Allocation Problem in a Dry Bulk Terminal: A Heuristic Solution
Ait Ouahaman, Assia	Mohammadia School of Engineers/ Mohammed VI Polytechnic Universi
Benjelloun, Khalid	Mohammadia School of Engineers,
Kenné, Jean-Pierre	école De Technologie Supérieure
Najid, Najib. M.	IRRCyN/Université De Nantes
Keywords: Production planning and control, Logistics in manufacturing, Job and activity scheduling Abstract: The bulk port operations are given a growing attention for their important role in the global supply chain in different industries (mining, energy ...). To guarantee their competitiveness, the efficient management of port logistics, including yard side management is crucial. In this paper, we consider a real-word storage space allocation problem at an export bulk terminal. We formulate the problem as a mixed integer linear program and we propose a heuristic method to solve large scale data sets. Both the model and the heuristic can help the yard planner to test different scenarios and provide better stock yard plan, which is a first step toward improving the management of operations in the bulk terminal under study.
Paper VI152-09.6
PDF · Video · Chance-Constrained LQG Production Planning Problem under Partially Observed Forward-Backward Inventory Systems
Salviano, Oscar	Pontifícia Universidade Católica De Campinas - PUCCAMP
Andres, Frederic Henri Nicolas	National Institute for Informatics
Keywords: Production planning and control, Logistics in manufacturing, Modeling of manufacturing operations Abstract: The target system of our research is a reverse logistics system with imperfect information of inventory variables. This system is affected by two independents and uncorrelated random variables that represent demand and return fluctuations. A Discrete-time, chance-constrained, Linear Quadratic Gaussian Problem under imperfect information of inventory systems (DCLQG) is formulated in order to develop an aggregate manufacturing and remanufacturing plan. Technically, an optimal closed-loop solution for this stochastic problem is possible, but it is not easy to get it, particularly for large size problems. Thus, an open-loop updating approach that provides a quasi-optimal solution is investigated here. This approach considers an equivalent deterministic problem to the DCLQG problem. It is based on the conditional mean value and on variances of inventory variables, which are estimated from a Kalman filter procedure. Such an approach allows managers to build an aggregated production plan, periodically revised, that helps them to make decisions. An open-loop updating approach is compared to a no-updating approach, which depends only on the initial condition of states of the system. An example shows the importance of information gathering to provide sub-optimal solutions for stochastic problems with imperfect information of states. It is also shown that sub-optimal production policies can improve the company’s profitability.
Paper VI152-09.7
PDF · Video · An Analysis of the BWE-Associated Costs: The Issue of Demand Forecasting Accuracy
Mirab Samiee, Zahra	Sharif University of Technology
Rostamzadeh, Mehrdad	Sharif University of Technology
Fatahi Valilai, Omid	Jacobs University Bremen GGmbH
Keywords: Production planning and control, Modeling of manufacturing operations, Production activity control Abstract: The bullwhip effect (BWE) has a significant impact on increasing the total cost of a supply chain. Among the factors contributing to this effect, demand forecasting plays a vital role. This paper explores the role of demand forecasting accuracy on the amount of the BWE-related cost, taking an intervened demand process with stochastic perturbations into account. In this regard, a simulation study on a two-echelon supply chain is conducted to investigate the association between forecasting accuracy and the BWE-related costs. Subsequently, a new replenishment policy based on the classic order up to a target (OUT) policy is introduced to determine order values that mitigate the BWE-related costs in comparison to the classic OUT policy.
Paper VI152-09.8
PDF · Video · Analysis of the Impact of Demand Volatility and Return Policies on a Price-Setting Newsvendor
Hedayatinia, Pooya	University
Lemoine, David	Ecole Des Mines De Nantes
Massonnet, Guillaume	LS2N, IMT Atlantique
Viviani, Jean-Laurent	IGR-IAE De Rennes, Université Rennes 1
Keywords: Production planning and control, Modelling and decision making in complex systems Abstract: This paper studies a newsvendor problem in which the retailer can set both the selling price and the quantity ordered. The demand is stochastic and price-dependent and the retailer has the possibility to sell his unsold units at the end of the sales season. We present an analytical model of the retailer optimization process and show the conditions that the retailer can find optimal quantity and price simultaneously, then we use numerical methods to reveal the properties of retailer's behavior. The existing results of price-setting newsvendor do not include buyback and our work brings a new condition on the lost sales rate elasticity for the computation of an optimal solution. Our results show that return policies can improve the profit of retailer and that this effect increases with the volatility of the demand. This observation reveals a crucial point for the supplier to design their contract according to demand uncertainty, allowing them to influence the retailer's decision on price and order quantity by offering buy-back for unsold products.
Paper VI152-09.9
PDF · Video · Inventory Model for Disassembly Systems with Price Dependant Return Rate
Godichaud, Matthieu	University of Technology of Troyes
Amodeo, Lionel	University of Technology of Troyes
Keywords: Production planning and control, Procedures for process planning, Assembly and disassembly Abstract: In this paper, we are proposing a new Economic Order Quantity (EOQ) model for return-driven disassembly systems. End-of-life (EoL) products arrive in the system to be disassembled into parts or material fractions that can be sold in different secondary market or disposed of in an environmental conscious way. The return are considered here controllable with respect to a buyback price. The model can determine if the system is profitable by finding an equilibrium between revenues obtained from the components and buyback, disassembly and inventory costs. The properties of the model are analyzed to derive an efficient solution approach to find the optimal return price and the reorder interval. A sensibility analysis performed on an illustrative example shows the effect of the model parameters.
Paper VI152-09.10
PDF · Video · Inventory Control Based on Dynamic Programming with State Probability Distribution
Qiao, Xue	Southeast University
Wang, Zheng	Southeast University
Keywords: Logistics in manufacturing, Production & logistics over manufacturing networking, Production planning and control Abstract: In this abstract, we model the inventory control problem under inaccurate inventory record over a finite horizon by a dynamic programming with state probability distribution. To solve the problem, an approximated algorithm by considering the backward optimization and the interpolation of state probability distribution is developed. Numerical experiments verify the effectiveness of the proposed dynamic programming model and the approximation algorithm.
Paper VI152-09.11
PDF · Video · Effective Continuous-Flow Supply Chains Using Centralized Model Predictive Control
Hipólito, Tomás	IDMEC, Instituto Superior Técnico, Universidade De Lisboa
Nabais, João Lemos	Escola Superior De Tecnologia De Setúbal, InstitutoPolitécnico De
Botto, Miguel Ayala	Technical Univ. of Lisbon
Negenborn, Rudy	Delft University of Technology
Keywords: Logistics in manufacturing, Modeling of manufacturing operations, Production planning and control Abstract: This paper proposes three different formulations of a centralized Model Predictive Control framework to manage the logistics of continuous-flow Supply Chains subject to fluctuating demand. The Supply Chain is modelled as a dynamical system composed of several players handling commodities from the production phase to the retail phase. Additionally, commodities are categorized according to their characteristics. An external control agent continuously gathers information regarding Supply Chain operation. Using that information, the control agent monitors the inventory of the retailer and assigns the commodity quantity to replenish it, adopting a Model Predictive Control algorithm. Three different formulations of the Model Predictive Control algorithm are designed based on the inventory of the retailer: i) constant inventory, ii) dynamical heuristic inventory, and iii) dynamical control inventory. These formulations are simulated for a Supply Chain operating under a "just-in-time" management policy.

VI153
Manufacturing and Logistics Systems - Enterprise Integration and Networking
VI153-01 Bio-Inspired, Autonomous Future Enterprise   Invited Session, 5 papers
VI153-02 Interoperability in the Cyber-Physical Enterprise   Open Invited Session, 10 papers

VI153-01
Bio-Inspired, Autonomous Future Enterprise	Invited Session
Chair: Caramihai, Simona Iuliana	University "Politehnica"of Bucharest
Co-Chair: Dumitrache, Ioan	University
Organizer: Dumitrache, Ioan	University
Organizer: Caramihai, Simona Iuliana	University
Paper VI153-01.1
PDF · Video · Bio-Inspired Coordination and Control of Autonomous Vehicles in Future Manufacturing and Goods Transportation (I)
Caruntu, Constantin - Florin	Technical University "Gheorghe Asachi" of Iasi
Pascal, Carlos	"Gheorghe Asachi" Technical University of Iasi
Maxim, Anca	"Gheorghe Asachi" Technical University of Iasi
Pauca, Ovidiu	Gheorghe Asachi Technical University of Iasi
Keywords: Distributed nagigation and control of unmmanned autonomous vehicles, Bio-inspired manufacturing systems and self-organization, Multi-agent systems applied to industrial systems Abstract: The will to apply bio-inspired techniques to coordinate and control autonomous X vehicles (AXVs) has increased tremendously during the last decade due to their advantages in the face of complexity in today's demanding applications. Thus, several bio-inspired approaches for multiple-entities optimization have been proposed in the literature for various limited applications, e.g., drone coordination, mobile robot formation maintenance. In all these strategies, the entities must plan their path and control their movements while coordinating their behavior w.r.t. the other members, and they must avoid collisions, so the task could be very difficult in the unstructured environments present in future manufacturing plants and goods transportation. Future applications of these bio-inspired techniques for coordination and control of AXVs include large warehouses, manufacturing, logistics, last-mile delivery, etc. The AXVs could be grouped to carry larger goods or they can act as swarm members when they do not have a common goal, but they must interact while they move to complete the allocated tasks and intersect their paths with the paths of other entities. As such, this paper illustrates the concept of applying such bio-inspired coordination and control techniques for the development of future manufacturing and goods transportation, a discussion being carried out regarding the advantages and disadvantages of several techniques for their use in specific applications.
Paper VI153-01.2
PDF · Video · Robot Digital Twin towards Industry 4.0 (I)
Vladareanu, Luige	Romanian Academy, Institute of Solid Mechanics
Gal, Alexandru	Institute of Solid Mechanics of the Romanian Academy
Melinte, Octavian	Institute of Solid Mechanics of the Romanian Academy
Vladareanu, Victor	"Politehnica" University of Bucharest
Iliescu, Mihaiela	Institute of Solid Mechanics of the Romanian Academy
Bruja, Adrian	Technical University of Civil Engineering of Bucharest
Feng, Yongfei	Ningbo University, Ningbo 315211
Ciocirlan, Alexandra-Catalina	Institute of Solid Mechanics of the Romanian Academy
Keywords: Intelligent system techniques and applications, Digital enterprise, Decentralized and distributed control Abstract: The paper presents the development of a digital twin for a high frequency hardening robot and connected hardware and software modules. The paper describes the virtual environment model, the robot emulation and optimisation model, and the reference generation model, as well as their respective visual interfaces, used for controlling both the physical and digital robots. The application is integrated into the multi-purpose Virtual Intelligent Portable Robot Platform (VIPRO).
Paper VI153-01.3
PDF · Video · Future Enterprise As an Intelligent Cyber-Physical System (I)
Dumitrache, Ioan	University Politehnica Bucharest
Caramihai, Simona Iuliana	University Politehnica Bucharest
Sacala, Ioan Stefan	University Politehnica Bucharest
Moisescu, Mihnea Alexandru	University Politehnica Bucharest
Popescu, Dragos Constantin	University Politehnica of Bucharest
Keywords: Enterprise integration, Enterprise modelling and BPM, Model-driven systems engineering Abstract: The appearance of new paradigms such as Cyber-Physical Systems paradigm has led to the appearance of the next industrial revolution. A Cyber- Physical System based Enterprise involves the usage of physical objects, knowledge structured based on workflows, control systems, human integration, systemic data representation and communication processes. The authors propose the concept of Intelligent Cyber Enterprise (ICE) in order to provide a generic architecture enabling the design of complex enterprise systems enhanced with social and technical capabilities. Components of the architecture have to be independent, facilitating the selection of context-oriented behaviors. In order to facilitate the design of ICE components, the authors have proposed a platform for modeling and evaluation.
Paper VI153-01.4
PDF · Video · Bio-Inspired Autonomous Enterprise Systems (I)
Caramihai, Simona Iuliana	University "Politehnica"of Bucharest
Dumitrache, Ioan	University
Moisescu, Mihnea Alexandru	University Politehnica Bucharest
Sacala, Ioan Stefan	University Politehnica Bucharest
Keywords: Enterprise integration, Bio-inspired manufacturing systems and self-organization, Enterprise modelling and BPM Abstract: The socio-economical context of this century has faced enterprises with various challenges, thus resulting in a wide variety of enterprise control and management approaches. This paper underlines the correlation between specific functional requirements of different enterprise systems and the behavioral characteristics they should display. Bio-inspired models are analysed in correlation to enterprise systems. Evolving paradigms have focused on the importance of contextualized sensing in problem solving and the paper advocates the utility of the human brain inspired perception-behavior generation-learning approach in autonomous enterprise control.
Paper VI153-01.5
PDF · Video · Digital Twin in 5G Digital Era Developed through Cyber Physical Systems (I)
Vladareanu, Luige	Romanian Academy, Institute of Solid Mechanics
Vladareanu, Victor	"Politehnica" University of Bucharest
Gal, Alexandru	Institute of Solid Mechanics of the Romanian Academy
Melinte, Octavian	Institute of Solid Mechanics of the Romanian Academy
Pandelea, Marius	Institute of Solid Mechanics of the Romanian Academy
Radulescu, Mihai	Institute of Solid Mechanics of the Romanian Academy
Ciocirlan, Alexandra-Catalina	Institute of Solid Mechanics of the Romanian Academy
Keywords: Integrated monitoring, control and security for critical infrastructure systems, Distributed nagigation and control of unmmanned autonomous vehicles, Modelling and decision making in complex systems Abstract: The paper Cyber Physical Systems integrated in VIPRO- Platform through intelligent control interfaces and genetic algorithms to build "digital-twins" robots vectors tools for cyber-physical manufacturing presents. Intelligent control interfaces are useful for simulating robots vectors’ capabilities in a safe and cost-effective way, but it is challenging to accurately emulate the behavior of the physical tools. When an unmanned autonomous vehicles breaks down or malfunctions, engineers can always go back to check the digital traces using the "digital-twins" VIPRO- Platform for diagnosis and prognosis. This paper presents an integration of Cyber Physical Systems using intelligent control interfaces and genetic algorithms into developing "digital-twins" VIPRO- Platform in 5G Digital Era to improve their accountability and capabilities for cyber-physical manufacturing. The intelligent control interfaces data are used to extract the machining characteristics profiles of a digital-twins machine tool, with which the tool can better reflect the actual status of its physical counterpart in its various applications. The modelling techniques and decision making in complex systems for controlling the position of a unmanned autonomous vehicles engaged in a mission are discussed, and analytical techniques of data and genetic algorithms are presented for modeling and developing "digital-twins "VIPRO- Platform. Copy-right © 2019 IFAC

VI153-02
Interoperability in the Cyber-Physical Enterprise	Open Invited Session
Chair: Panetto, Hervé	CRAN, University of Lorraine, CNRS
Co-Chair: Emmanouilidis, Christos	Cranfield Univeristy
Organizer: Panetto, Hervé	CRAN, University of Lorraine, CNRS
Organizer: Weichhart, Georg	Profactor GmbH
Organizer: Molina, Arturo	Tecnologico De Monterrey
Paper VI153-02.1
PDF · Video · BPMN+I to Support Decision Making in Innovation Management for Automated Production Systems Including Technological, Multi Team and Organizational Aspects (I)
Vogel-Heuser, Birgit	Technical University of Munich
Brodbeck, Felix Claus	Ludwig-Maximilians-Universitaet Muenchen
Kugler, Katharina Gabriele	Ludwig-Maximilians-Universitaet Muenchen
Passoth, Jan-Hendrik	TUM
Maasen, Sabine	TUM
Reif, Julia A. M.	Ludwig-Maximilians-Universität, Munich
Keywords: Enterprise networks design and implementation, Enterprise modelling and BPM, Model-driven systems engineering Abstract: A joined interdisciplinary approach from systems engineering, organizational sociology and psychology is introduced using an enriched Business Process Model and Notation (BPMN+I) based modeling approach to support decision making on a management level for both mid-term decisions such as in-/outsourcing and short-term decisions such as fixing a weakness on site during start-up of a plant abroad or involving the design offices. This approach focusses on the actual collaboration between interdisciplinary teams within an organizational context by enriching BPMN with checklists applicable to all interfaces along the projects’ workflow. Our contribution aims at supporting innovation management for automated Production Systems which depends on successful interdisciplinary collaboration.
Paper VI153-02.2
PDF · Video · A Generic Product and Resource Description to Enable Capability Matchmaking for Production As a Service (I)
Hermann, Jesko	Deutsches Forschungszentrum Für Künstliche Intelligenz GmbH (DFK
Rübel, Pascal	Deutsches Forschungszentrum Für Künstliche Intelligenz GmbH
Wagner, Achim	German Research Centre for Artificial Intelligence
Ruskowski, Martin	German Research Center for Artificial Intelligence
Keywords: Procedures for process planning, Production planning and control, Internet of Services and Service Science Abstract: The shift from mass production to mass customization and product personalization has a strong impact on the manufacturing industry. The production of small lot sizes or completely individualized products on large scale remains a challenge for the manufacturing companies. Concepts such as "Production as a Service" promise a more efficient manufacturing of small lot-sizes while making better use of existing production resources. In a world where different products will compete for the same resources alternative process chains gain in importance to achieve a global optimum in manufacturing. This paper reviews existing approaches for a generic description of products and the matching of product and manufacturing resources allowing for the generation of alternative process chains. Based on the findings product and resource are described and a matching approach is outlined.
Paper VI153-02.3
PDF · Video · Integration of Existing Cyber-Physical Manufacturing Systems into a Common Information Model (I)
Schmied, Sebastian	Technische Hochschule Ingolstadt
Mathias, Selvine George	Technische Hochschule Ingolstadt
Großmann, Daniel	Technische Hochschule Ingolstadt
Jumar, Ulrich	Ifak - Institut F. Automation U. Kommunikation
Keywords: Flexible and reconfigurable manufacturing systems, Device integration technologies, Intelligent manufacturing systems Abstract: In order to be able to serve constantly new customer requirements, manufacturing systems must be able to adapt to frequent changes. In addition, repeatedly objects are removed or added to the network. To control and monitor such a constantly changing system a mapping of existing manufacturing systems into a common information model is necessary. This model describes information that is produced and stored in different entities of the complete system. To create a common address space and expose the relations between the devices an aggregation of every element in the system is needed. This paper describes a methodology for the creation of an information model for a complete manufacturing environment, followed by an approach for the aggregation of the singular system entities. The concept of this paper is illustrated with a demonstrator. The results of this approach have been discussed in the following sections along with the proposal for further directions.
Paper VI153-02.4
PDF · Video · Towards a Cyber-Physical PLM Environment: The Role of Digital Product Models, Intelligent Products, Digital Twins, Product Avatars and Digital Shadows (I)
Romero, David	Tecnológico De Monterrey
Wuest, Thorsten	West Virginia University
Harik, Ramy	University of South Carolina
Thoben, Klaus-Dieter	Bremer Institut Für Produktion Und Logistik GmbH
Keywords: Life-cycle control, Intelligent manufacturing systems, Internet-of-Things and Sensing Enterprise Abstract: Over the last year, there was rarely a day without industry announcing a new project involving Digital Twins or a scholarly publication with Digital Twin in the title. However, given the novelty of the concept and the pace of these developments, there are several fundamental open questions yet to be answered. In this paper, we take a step back and holistically discuss the Digital Twin and its related concepts. We aim to explore the "engineering requirements" for developing a Cyber-Physical Product Lifecycle Management (PLM) Environment to support the cyber-physical product lifecycle – the foundation of functional and effective Digital Twins. Furthermore, we provide definitions for a digital product model, an intelligent product, a cyber-physical product, a product avatar, a digital shadow, and a digital thread, and discuss their interrelations as the main building blocks for developing a Cyber-Physical PLM Environment.
Paper VI153-02.5
PDF · Video · Triple V Product Development Framework and Its Interoperability between Product, Model and Data Lifecycles (I)
Li, Qing	Tsinghua University
Wei, Hailong	Tsinghua University
Yu, Chao	Department of Automation, Tsinghua University
Wang, Shuangshuang	Tsinghua University
Xiao, Linlin	China Industrial Control Systems Cyber Emergency Response Team
Keywords: Model-driven systems engineering, Digital enterprise, Enterprise Reference Models and Their Verification, Validation, and Accreditation Abstract: In order to reduce the time and cost of verification, validation and accreditation (VV&A), increase the probability that design will succeed at one time, the traditional product development framework and methodology, which is usually described as the V framework, is extended through the double V framework to the model and data based triple V framework. The new framework provides an opportunity to converge data lifecycle, model lifecycle and product (development) lifecycle together. The paper analyses the interoperability of proposed triple V framework and implements it in a ship damage control system development project.
Paper VI153-02.6
PDF · Video · Context Ontology Development for Connected Maintenance Services (I)
Emmanouilidis, Christos	Cranfield Univeristy
Gregori, Matteo	Cranfield University
Al-Shdifat, Ali	Cranfield University
Keywords: Internet of Services and Service Science, Intelligent maintenance systems, Systems interoperability Abstract: The opportunity to shift from corrective and preventive to data-driven Predictive Maintenance has received a significant boost with the deeper penetration of Internet of Things (IoT) technologies in industrial environments. Processing IoT generated data nonetheless creates challenges for data management and actionable data processing. One way to handle such complexity is to introduce context information modelling and management, wherein data and service delivery are determined upon resolving the apparent context of a service or data request. In this paper, context information management is considered on the basis of a valid knowledge construct for reliability-oriented maintenance management. The aim is to produce a viable semantic organization of data for maintenance services. It is applied on an industrial case linked to maintenance of a distributed fleet of connected production grade industrial printers. The complexity of translating the data generated by such production assets to actionable information is significant, as the status of a single asset is characterised by several hundreds of failure modes and a multitude of event codes. To assess the viability of the ontology for the targeted application, a qualitative usability evaluation study of the ontology is performed.
Paper VI153-02.7
PDF · Video · A Multi-Facets Ontology Matching Approach for Generating PLC Domain Knowledge Graphs
An, Yameng	Hangzhou Dianzi University
Qin, Feiwei	Hangzhou Dianzi University
Sun, Danfeng	Institut Für Automation Und Kommunikation
Wu, Huifeng	Hangzhou Dianzi University
Keywords: Systems interoperability, Intelligent system techniques and applications, Model-driven systems engineering Abstract: Programmable Logic Controller (PLC) has been playing an important role in industrial automation. Users want to improve programming efficiency by implementing code reuse and more intelligent code retrieval. Due to the heterogeneity of different PLC development environments, it is then necessary to design a computable knowledge model to semantically represent, organize, and utilize these diversified resources. Using the ontology technique is a common way to achieve the interoperability of heterogeneous systems. Aim at this, we propose an ontology matching approach in this paper. Knowledge extraction and alignment are difficult for most of the knowledge graphs construction tasks, however, we are able to build the PLC domain knowledge graph with high accuracy and completeness by considering PLC domain characteristics, designing layered ontology, and implementing the matching process primarily on schema level instead of instance level.
Paper VI153-02.8
PDF · Video · Comparison of Communication Technologies for Industrial Middlewares and DDS-Based Realization
Trunzer, Emanuel	Technical University of Munich
Schilling, Thomas	Technical University of Munich
Müller, Micha	Technical University of Munich
Vogel-Heuser, Birgit	Technical University of Munich
Keywords: Internet-of-Things and Sensing Enterprise, Systems interoperability, Protocols and information communication Abstract: The automation industry is currently in the process of transforming towards Industrie 4.0. To fully leverage the new possibilities, e.g., predictive maintenance, systems from all levels of the AT-pyramid are required to be fully connected. For this purpose there exist abstract models as well as concrete implementations of middleware-based interconnection platforms. This paper aims to close the gap between abstract concepts and concrete implementations by comparing technological concepts for a middleware implementation. At first, requirements are determined, which should be fulfilled by middleware to be comprehensible and competitive. Based on these requirements, six different middleware technologies are presented and evaluated. The evaluation yields that both OPC UA Pub/Sub with AMQP/MQTT as transport and DDS suit the requirements best. However, there are no complete implementations of OPC UA Pub/Sub with AMQP/MQTT as transport available yet. Therefore DDS is chosen for a prototypical middleware implementation. The prototype is tested and shows to fulfill all except one requirement, namely real-time constraints. In conclusion, it is recorded that for future middleware implementations, OPC UA Pub/Sub (as soon as complete implementations are available) and DDS are the most appropriate technologies.
Paper VI153-02.9
PDF · Video · Towards a Conceptual Framework for Smart Assessment in Organisations
Romero, Marcelo	University of Lorraine, Luxembourg Institute of Science and Tech
Guédria, Wided	Luxembourg Institute of Science and Technology, Luxembourg
Panetto, Hervé	CRAN, University of Lorraine, CNRS
Barafort, Béatrix	Luxembourg Institute of Science and Technology
Keywords: Abstract: Enterprises are constantly in motion, aiming to evolve through transformations that could allow them to face various challenges. In order to carry out these transformations, there is a need for an objective view of different organisational aspects. Assessments allow to provide this view by covering diverse aspects such as performance, quality, compliance, readiness, etc. However, the assessment process could be expensive since it is often based on a sequence of complex activities that must be carried out by experts or complex systems. On the other hand, the assessment results must reflect the current state of the assessed entity. Hence, there is a need for methods to autonomously adapt the results to significant changes of the entity, and that are be able to use embedded knowledge to provide relevant assessment results. To tackle these issues, this work proposes a Smart Assessment Framework (SAF), a conceptual framework devised to guide the development of smarter assessment approaches based on the integration of capabilities from smart systems to carry out the assessment process.
Paper VI153-02.10
PDF · Video · A New Paradigm and Meta-Model for Cyber-Physical-Social Systems
Yilma, Bereket	Luxembourg Institute of Science and Technology (LIST)
Naudet, Yannick	Luxembourg Institute of Science and Technology (LIST)
Panetto, Hervé	CRAN, University of Lorraine, CNRS
Keywords: Abstract: The notion of Cyber-Physical-Social System (CPSS) and similar concepts using different acronyms emerged as a major paradigm shift to facilitate the interaction between human and Cyber-Physical System (CPS). However, human interaction and behaviour is the result of multiple social dimensions governed by complex environmental, cultural and contextual factors which are not yet fully understood. Additionally, works in this direction still lack a well established systemic foundation. Thus, handling properly the social factor in HumanCPS interaction remains an open challenge. In this paper, we present a new perspective and a formalisation for the CPSS paradigm, which is grounded on the theory of systems. The aim of this is to provide a general framework to handle social dimensions in Human-CPS interactions. We propose a meta-model, which provides a conceptual ground to design CPSS spaces where CPSs are enhanced with social capabilities.

VI154
Manufacturing and Logistics Systems - Large Scale Complex Systems
VI154-01 Distributed Control and Optimization on Complex Networks   Invited Session, 5 papers
VI154-02 Large-Scale Complex Networked Systems: Analysis and Control   Open Invited Session, 16 papers
VI154-03 Security of Large-Scale Complex Systems   Open Invited Session, 7 papers
VI154-04 Modelling, Monitoring and Decision Making in Complex Systems   Regular Session, 20 papers

VI154-01
Distributed Control and Optimization on Complex Networks	Invited Session
Chair: Ye, Mengbin	Curtin University
Co-Chair: Anderson, Brian D.O.	Australian National Univ/NICTA
Organizer: Ye, Mengbin	Curtin University
Organizer: Liu, Ji	Stony Brook University
Organizer: Cao, Ming	University of Groningen
Paper VI154-01.1
PDF · Video · Distributed Feedback Control on the SIS Network Model: An Impossibility Result (I)
Ye, Mengbin	Curtin University
Liu, Ji	Stony Brook University
Anderson, Brian D. O.	Australian National Univ/NICTA
Cao, Ming	University of Groningen
Keywords: Decentralized and distributed control, Optimization and control of large-scale network systems, Multiagent systems Abstract: This paper considers the deterministic Susceptible-Infected-Susceptible (SIS) epidemic network model, over strongly connected networks. It is well known that there exists an endemic equilibrium (the disease persists in all nodes of the network) if and only if the effective reproduction number of the network is greater than 1. In fact, the endemic equilibrium is unique and is asymptotically stable for all feasible nonzero initial conditions. We consider the recovery rate of each node as a control input. Using results from differential topology and monotone systems, we establish that it is impossible for a large class of distributed feedback controllers to drive the network to the healthy equilibrium (where every node is disease free) if the uncontrolled network has a reproduction number greater than 1. In fact, a unique endemic equilibrium exists in the controlled network, and it is exponentially stable for all feasible nonzero initial conditions. We illustrate our impossibility result using simulations, and discuss the implications on the problem of control over epidemic networks.
Paper VI154-01.2
PDF · Video · Multi-Agent Infinite Horizon Persistent Monitoring of Targets with Uncertain States in Multi-Dimensional Environments (I)
Cerqueira Pinto, Samuel	Boston University
Andersson, Sean	Boston University
Hendrickx, Julien M.	UCLouvain
Cassandras, Christos G.	Boston Univ
Keywords: Monitoring and control of spatially distributed systems, Multiagent systems, Distributed nagigation and control of unmmanned autonomous vehicles Abstract: This paper investigates the problem of persistent monitoring, where a finite set of mobile agents persistently visits a finite set of targets in a multi-dimensional environment. The agents must estimate the targets' internal states and the goal is to minimize the mean squared estimation error over time. The internal states of the targets evolve with linear stochastic dynamics and thus the optimal estimator is a Kalman-Bucy Filter. We constrain the trajectories of the agents to be periodic and represented by a truncated Fourier series. Taking advantage of the periodic nature of this solution, we define the infinite horizon version of the problem and explore the property that the mean estimation squared error converges to a limit cycle. We present a technique to compute online the gradient of the steady state mean estimation error of the targets' states with respect to the parameters defining the trajectories and use a gradient descent scheme to obtain locally optimal movement schedules. This scheme allows us to address the infinite horizon problem with only a small number of parameters to be optimized.
Paper VI154-01.3
PDF · Video · On the Impact of Edge Modifications for Networked Control Systems (I)
Lindmark, Gustav	Linköping University
Altafini, Claudio	Linkoping University
Keywords: Optimization and control of large-scale network systems Abstract: This paper investigates the impact of addition/removal of edges in complex networks. Growing a network by the addition of edges has for instance been suggested as a way to improve network robustness to external disturbances. Moreover, when network controllability is considered, designing edge additions is a promising alternative to add more actuation capabilities in order to improve different performance metrics. We quantify the impact of an edge modification with the H-2 and H-infinity norms. For networks with positive edge weights we show how the H-infinity norm can be computed exactly for each possible single edge modification, while for the H-2 norm we instead obtain a lower bound. This bound is linked to the trace of the controllability Gramian, hence it can be used for instance to reduce the energy needed for control.
Paper VI154-01.4
PDF · Video · On Games with Coordinating and Anti-Coordinating Agents (I)
Vanelli, Martina	Politecnico Di Torino
Arditti, Laura	Politecnico Di Torino
Como, Giacomo	Politecnico Di Torino
Fagnani, Fabio	Politecnico Di Torino
Keywords: Multiagent systems, Modelling and decision making in complex systems, Efficient strategies for large scale complex systems Abstract: This work studies Nash equilibria for games where a mixture of coordinating and anti-coordinating agents, with possibly heterogeneous thresholds, coexist and interact through an all-to-all network. Whilst games with only coordinating or only anti-coordinating agents are potential, also in the presence of heterogeneities, this does not hold when both type of agents are simultaneously present. This makes their analysis more difficult and existence of Nash equilibria not guaranteed. Our main result is a checkable condition on the threshold distributions that characterizes the existence of Nash equilibria in such mixed games. When this condition is satisfied an explicit algorithm allows to determine the complete set of such equilibria. Moreover, for the special case when only one type of agents is present (either coordinating or anti-coordinating), our results allow an explicit computation of the cardinality of Nash equilibria.
Paper VI154-01.5
PDF · Video · Controlling a Networked SIS Model Via a Single Input Over Undirected Graphs (I)
Wang, Dan	The Hong Kong University of Science and Technology
Liu, Ji	Stony Brook University
Pare, Philip E.	KTH Royal Institute of Technology
Chen, Wei	Peking University
Qiu, Li	Hong Kong Univ. of Sci. & Tech
Beck, Carolyn L.	Univ. of Illinois at Urbana-Champaign
Basar, Tamer	Univ. of Illinois at Urbana-Champaign
Keywords: Optimization and control of large-scale network systems, Decentralized and distributed control Abstract: This paper formulates and studies the problem of controlling a networked SIS model using a single input in which the network structure is described by a connected undirected graph. A necessary and sufficient condition on the values of curing and infection rates for the healthy state to be exponentially stable is obtained via the analysis of signed Laplacians when the control input is the curing budget of a single agent. In the case when the healthy state is stabilizable, an explicit expression for the minimum curing budget is provided. The utility of the algorithm is demonstrated using a simulation over a network of cities in the northeastern United States.

VI154-02
Large-Scale Complex Networked Systems: Analysis and Control	Open Invited Session
Chair: Wang, Xiaofan	Shanghai JiaoTong Univ
Co-Chair: Sakurama, Kazunori	Kyoto University
Organizer: Wang, Xiaofan	Shanghai JiaoTong Univ
Organizer: Cao, Ming	University of Groningen
Organizer: Ren, Wei	University of California, Riverside
Paper VI154-02.1
PDF · Video · Characterizing Network Controllability and Observability for Abstractions and Realizations of Dynamic Networks (I)
Johnson, Charles	Brigham Young University
Warnick, Sean	Brigham Young Univ
Keywords: Identification and model reduction, Modelling and decision making in complex systems Abstract: One method for managing the complexity of a complex network is by abstracting that complexity away with a simpler, yet behaviorally equivalent, mathematical model. A theory for such abstractions is currently under development cf. Kivits and Van den Hof (2018) as well as Woodbury and Warnick (2019). While recent work has considered concepts of controllability and observability for networked dynamic systems (cf. Xiang et al. (2019) and Liuand Barabási (2016)), this paper analyzes these concepts for abstractions of dynamic networks. In particular, we present the notion of a complete abstraction and an extraneous realization of a dynamic network and show that these concepts characterize the controllability and observability properties of a class of abstractions of such dynamic networks.
Paper VI154-02.2
PDF · Video · Neighborhood Interval Observer Based Coordination Control for Multi-Agent Systems with Disturbances (I)
Wang, Xiaoling	Nanjing University of Posts and Telecommunications
Jiang, Guo-Ping	Nanjing Univ of Posts & Telecommunications
Yang, Wen	East China University of Science and Techonology
Su, Housheng	Huazhong University of Science and Technology
Wang, Xiao Fan	Shanghai Jiao Tong Univ
Keywords: Decentralized and distributed control, Multiagent systems Abstract: This paper focuses on multi-agent systems with uncertain disturbances, in which only the bounding functions on the disturbances and the bounds on the initial state of each agent are known. By designing a neighborhood interval observer for this kind of multi-agent system, the estimation of the sum of the relative state of each agent associated with itself and its neighbors is firstly realized. Then, on the basis of these estimated information, local control algorithm is designed to drive the system to achieve bounded consensus. Finally, numerical simulations are provided to verify the theoretical results.
Paper VI154-02.3
PDF · Video · Self-Organized Polygon Formation Control of Swarm Robots under Cyclic Topologies (I)
Zhou, Bo	Beijing Institute of Technology
Yang, Qingkai	Beijing Institute of Technology
Dou, Lihua	Beijing Institute of Technology
Fang, Hao	Beijing Institute of Technology
Chen, Jie	Beijing Institue of Technology
Keywords: Multiagent systems, Decentralized and distributed control Abstract: In this paper, we consider the problem of controlling a swarm of mobile robots to formulate a prescribed formation shape under cyclic topologies. By mimicking the shape transformation of elastic strings, we design a distributed control strategy using local sensing quantities. To implement this control algorithm, only a small number of robots need to be regulated to achieve the desired formation shape. It is shown that the desired polygon formation can be globally asymptotically stabilized under the proposed control strategy. Furthermore, in order to adapt to the situations where external influence is not exerted on the ``right" robots, we propose a new self-organized control strategy that is capable of transferring the external influence through interacting with their nearest neighboring robots. Simulations are carried out to demonstrate the effectiveness of the proposed control strategies.
Paper VI154-02.4
PDF · Video · Formation Control of Non-Holonomic Multi-Agent Systems under Relative Measurements (I)
Sakurama, Kazunori	Kyoto University
Keywords: Multiagent systems, Decentralized and distributed control, Optimization and control of large-scale network systems Abstract: This paper addresses a formation control problem for multi-agent systems with non-holonomic constraints under relative measurements. To overcome the issue of non-holonomic constraints, we design a feedback controller deriving rotational and translational motions according to formation error. A special form of formation error is employed here, which depends only on relative positions in a local frame. Hence, the designed controller is distributed and relative, meaning that only relative measurements of neighbors are used. Because a clique-based function is used, not an edge-based one, the best performance is yielded of all distributed, relative, gradient-based controllers. Moreover, we derive a necessary and sufficient condition of graphs under which a desired formation is achieved by such controllers. The proposed method is valid regardless of the dimension of the space, and thus it is applicable to not only unmanned ground vehicles (UGVs) but also unmanned aerial vehicles (UAVs). The effectiveness of the proposed method is demonstrated by simulations.
Paper VI154-02.5
PDF · Video · Evolution of Opinion Dynamics with Eccentric Agents (I)
Zhang, Qi	Shanghai Jiao Tong University
Wang, Lin	Shanghai Jiao Tong University
Wang, Xiaofan	Shanghai JiaoTong Univ
Keywords: Modelling and decision making in complex systems, Decentralized and distributed control, Multiagent systems Abstract: More recently, there has been a surge of studies that seek mechanisms of the opinion evolution. While many studies have been dedicated to this field, much less attention has been paid to the joint influence of diverse agents on the opinion evolution. In this paper, we proposed an opinion dynamic model based on the Deffuant Weisbuch(DW) model with the existence of eccentric agents. The eccentric agent will change its opinion if the eccentric agent is selected and the opinion difference between two selected agents is beyond the bounded confidence. Previous studies have demonstrated that consensus usually cannot be achieved in the DW model. However, our study suggests that the existence of a single eccentric agent is able to promote consensus in numerical simulations, regardless of any bounded confidence and initial opinion distribution. We further proved that the DW model with the single eccentric agent achieves quasi-consensus. The equilibrium of the system was also proposed. Lastly, we analyzed the final opinion distribution and convergence time with varying bounded confidence and convergence parameters.
Paper VI154-02.6
PDF · Video · A Fundamental Performance Limit of Cloud-Based Control in Terms of Differential Privacy Level (I)
Kawano, Yu	Hiroshima University
Kashima, Kenji	Kyoto University
Cao, Ming	University of Groningen
Keywords: Decentralized and distributed control, Integrated monitoring, control and security for critical infrastructure systems Abstract: In this paper, we address a privacy issue raised by cloud based control. In a cloud based control framework, a plant typically has no access to the models of the cloud system and other plants connected via the cloud system. Under restricted information, the plant is required to design its local controller for achieving control objectives. As a control objective, we consider a tracking problem, and for constant reference signals, a class of tracking controllers is identified based on Youla parametrization. More importantly, as local tracking controllers are implemented, there is a possibility that the cloud system or other plants connected via the cloud system may be able to identify private information of the plant by using the collected signal from the plant; for example, the reference signal (say, the target production amount) of the plant can be viewed as a piece of private information. In order to evaluate the privacy level of the reference signal, we employ the concept of differential privacy. For the Laplace mechanism induced by the entire system, we show that the differential privacy level cannot be further improved from a ceiling value for any parameters of the local controller. In other words, there is a performance limit in terms of differential privacy level, which is determined by the plant and cloud system only.
Paper VI154-02.7
PDF · Video · From Sensor to Processing Networks: Optimal Estimation with Computation and Communication Latency (I)
Ballotta, Luca	University of Padova
Schenato, Luca	Univ of Padova
Carlone, Luca	MIT
Keywords: Optimization and control of large-scale network systems, Decentralized and distributed control, Efficient strategies for large scale complex systems Abstract: This paper investigates the use of a networked system (e.g., swarm of robots, smart grid, sensor network) to monitor a time-varying phenomenon of interest in the presence of communication and computation latency. Recent advances in edge computing have enabled processing to be spread across the network, hence we investigate the fundamental communication-computation trade-off, arising when a sensor has to decide whether to transmit raw data (incurring communication delay) or preprocess them (incurring computational delay) in order to compute an accurate estimate of the state of the phenomenon of interest. We propose two key contributions. First, we formalize the notion of processing network. Contrarily to sensor and communication networks, where the designer is concerned with the design of a suitable communication policy, in a processing network one can also control when and where the computation occurs in the network. The second contribution is to provide analytical results on the optimal preprocessing delay (i.e., the optimal time spent on computations at each sensor) for the case with a single sensor and multiple homogeneous sensors. Numerical results substantiate our claims that accounting for computation latencies (both at sensor and estimator side) and communication delays can largely impact the estimation accuracy.
Paper VI154-02.9
PDF · Video · Suboptimal Distributed LQR Design for Physically Coupled Systems (I)
Xu, Liang	Swiss Federal Institute of Technology Lausanne
Guo, Baiwei	EPFL
Galimberti, Clara Lucía	école Polytechnique Fédérale De Lausanne
Farina, Marcello	Politecnico Di Milano
Carli, Ruggero	Univ of Padova
Ferrari-Trecate, Giancarlo	Ecole Polytechnique Fédérale De Lausanne
Keywords: Optimization and control of large-scale network systems, Decentralized and distributed control, Efficient strategies for large scale complex systems Abstract: In this paper, we propose a suboptimal distributed LQR control method, applicable to systems coupled through both physical interconnections and the quadratic cost to be minimized. Thanks to a novel suboptimal but distributed cost-to-go matrix update that enforces block-diagonality, the suboptimal LQR gain matrix is structured, making the overall control scheme distributed. Moreover, the proposed control design algorithm is scalable. Theoretical properties of the method, including the stability of the closed-loop system, are investigated. A case study is shown to illustrate the features of the approach.
Paper VI154-02.10
PDF · Video · Dynamic Pricing for Power Control in Remote State Estimation (I)
Ding, Kemi	Nanyang Technological University
Ren, Xiaoqiang	Shanghai University
Qi, Hongsheng	Chinese Academy of Sciences
Shi, Guodong	The Australian National University/The University of Sydney
Wang, Xiaofan	Shanghai JiaoTong Univ
Shi, Ling	Hong Kong University of Science and Technology
Keywords: Efficient strategies for large scale complex systems, Decentralized and distributed control, Optimization and control of large-scale network systems Abstract: This paper considers the remote state estimation with multiple sensors. Each sensor transmits its sensing data to a remote estimator over a shared channel, where simultaneous transmissions are allowed. Regrading the transmission of other sensors as interference signals, the system designer should coordinate the sensors appropriately in order to maximize the overall estimation performance. Motivated by microeconomics, we treat sensors as self-interested power buyers under different unit prices announced by the system designer. Accordingly, the strategic interactions among sensors are formulated in a non-cooperative game, upon which the existence and uniqueness of a pure equilibrium solution are proved. Even if the game admits a conflict of interests among sensors, under well-designed prices, the game outcome aligns with the global optimal solution. We also devise an algorithm to compute these prices with simple iterations, which is given in explicit forms for ease of implementation.
Paper VI154-02.11
PDF · Video · Bearing-Based Formation Control of Multi-Agent System without Leader's Velocity Information (I)
Ji, Hongyu	Fudan University
Yuan, Quan	Fudan University
Li, Cong	Fudan University
Li, Xiang	Fudan University
Keywords: Multiagent systems, Decentralized and distributed control Abstract: This paper studies formation control of multi-agent systems with an underlying network constructed by defined the follower Henneberg construction. We propose a bearing-only formation control law of multi-agent systems, where a leader moves at a constant velocity, and the followers are unaware of the leader's velocity. We prove that the system can asymptotically reach its desired position and form the target formation. The proposed control law scales the formation to avoid obstacles, where the formation robustness is also analysed. Numerical simulations are provided to further support our findings.
Paper VI154-02.12
PDF · Video · Consensus of Nonlinear Systems with Data-Rate Constraints (I)
Voortman, Quentin	Eindhoven University of Technology
Pogromsky, A. Yu.	Eindhoven Univ of Technology
Matveev, Alexey S.	St.Petersburg Univ
Nijmeijer, Hendrik	Eindhoven Univ of Technology
Keywords: Efficient strategies for large scale complex systems, Decentralized and distributed control, Multiagent systems Abstract: In this paper, consensus for a network of dynamical systems which communicate over datarate constrained communication channels is considered. Each system in the network is equipped with a sensor and an actuator which are at locations remote from one another. In order to transmit the state of any system to any of the actuators, the sensors use data-rate constrained communication channels. Based on the messages each actuator receives from the sensors, it applies an appropriate control input to its system such that all systems achieve a particular type of consensus. Sensor/actuator pairs that achieve that particular type of consensus are called consensus protocols. In this contribution, an efficient in terms of required data-rates consensus protocol is presented. For the protocol a theorem proving conditions on the sufficient minimal data-rates to implement it is provided. The sufficient data-rate is proven to depend on the larger-than-one singular values of the linear part of the mapping of the systems in the network. Finally, an example is provided in the form of consensus for a network of harmonically forced bouncing ball systems, for which an analytical bound is provided on the sufficient outgoing channel rates.
Paper VI154-02.13
PDF · Video · Opinion Dynamics of Social Networks with Stubborn Agents Via Group Gossiping with Random Participants (I)
Aguilar, Emerico	Osaka University
Fujisaki, Yasumasa	Osaka Univ
Keywords: Multiagent systems, Decentralized and distributed control Abstract: Several recent models of opinion dynamics utilize gossip-based methods as an alternative to deterministic classical models. This approach is meant to be a more realistic representation of real-world communications by using random pairwise interactions. Our previous work extended the process of gossip-based models by enabling agents to communicate with a random subset of their neighbors. In this paper, we apply this idea to networks with stubborn agents. While the opinions in this model tend to oscillate, its expected dynamics is convergent, and the expected opinions and time-averaged opinions coincide over time.
Paper VI154-02.14
PDF · Video · Comparing Agent-Based Control Architectures for Next Generation Telecommunication Network Infrastructures (I)
Perez Hernandez, Marco	University of Cambridge
McFarlane, Duncan Campbell	University of Cambridge
Herrera, Manuel	University of Cambridge
Jain, Amit Kumar	University of Cambridge
Parlikad, Ajith Kumar	University of Cambridge
Keywords: Multiagent systems, Optimization and control of large-scale network systems, Monitoring and control of spatially distributed systems Abstract: Multi-agent systems have been an effective choice for designing control systems that are flexible and agile. However, few attention has been given to the evaluation of the architectures of such systems. This becomes critical with the emerging requirements in complex domains such as digital network infrastructures. In this paper, we propose an approach for the evaluation of agent-based control architectures and introduce three multi-agent based architectures for the supervisory control of network service operations of the next generation of digital infrastructures. With the proposed approach, we evaluated the architectures and the implemented control systems prototypes under a realistic network infrastructure environment. Our approach has been effective to evaluate the candidate architectures. The results of communication overhead and reaction time, have shown that agent-based hierarchical and heterarchical-ring architectures have outperformed the heterarchical-complete network architecture.
Paper VI154-02.15
PDF · Video · Switchable PID Controller Tuning Based on Golden Section Reduction Rule (I)
Sun, Jinggao	East China University of Science and Technology
Su, Guanghao	East China University of Science and Technology
Chen, Xianfeng	Ecust
Yang, Wen	East China University of Science and Techonology
Keywords: Optimization and control of large-scale network systems, Methodologies and tools for analysis of complexity, Efficient strategies for large scale complex systems Abstract: Resulting from the complexity and sensitivity instinct, high-order control system design is always a challenge faced by engineers from process industry. To solve this challenging task, a switchable control scheme consisted of two sub-controllers tuned based on two complementary simplified models respectively is proposed in this paper, and golden section is introduced into process model reduction to simplify parameter tuning. Inspired by adaptive control strategy, the controller switch mechanism depends on the time domain response similarity between the original high-order model and the simplified model. Besides, PID controller structure and corresponding parameter tuning method, such as Ziegler-Nichols method and SIMC method, are remained to guarantee the facility and efficiency of sub-controller design. The proposed method has been tested on several examples (balanced, lag-dominant, and a delay-dominant process) and the comparison with other tuning method based on step-response data resulting in favorable control performance.
Paper VI154-02.16
PDF · Video · On Consensus and Collective Behavior Over Heterogeneous Temporal Networks (I)
Zino, Lorenzo	University of Groningen
Rizzo, Alessandro	Politecnico Di Torino
Porfiri, Maurizio	New York University Polytechnic School of Engineering
Keywords: Multiagent systems Abstract: We study the problem of self-coordination of a network of dynamical systems toward a common state, which has a wide range of applications, such as studying the emergence of collective behaviors in social, economical, and biological groups. Most of the literature on this topic focuses on static networks, challenging our mathematical understanding of coordination in temporal networks. Here, we expand the state of the art by studying consensus problems over temporal networks, modeled as activity driven networks. Such a modeling framework allows to include heterogeneity in the network, whereby some nodes are more involved in the process of information sharing than others. Through stochastic stability theory and eigenvalue perturbation techniques, we analyze the French-DeGroot consensus protocol over activity driven networks. We derive closed-form expressions for the expected consensus state and the rate of convergence in a mean-square sense, which points at a detrimental effect of moderate levels of heterogeneity for large-scale networks. Finally, we discuss the scenario in which there is a set of leaders that aim at steering the whole network to their state. Here, we demonstrate that heterogeneity may be beneficial to their objective. Simulations are conducted to support and illustrate our analytical findings.

VI154-03
Security of Large-Scale Complex Systems	Open Invited Session
Chair: Promyslov, Vitaly	V.A. Trapeznikov Institute of Control Sciences
Co-Chair: Jharko, Elena	V.A. Trapeznikov Institute of Control Sciences
Organizer: Promyslov, Vitaly	V.A. Trapeznikov Institute of Control Sciences
Organizer: Poletikin, Alexey	Institute of Control Sciences
Organizer: Jharko, Elena	V.A. Trapeznikov Institute of Control Sciences
Organizer: Meshcheryakov, Roman	V. A. Trapeznikov Institute of Control Sciences of Russian Acade
Paper VI154-03.1
PDF · Video · Kill Chain Attack Modelling for Hidden Channel Attack Scenarios in Industrial Control Systems (I)
Neubert, Tom	Brandenburg University of Applied Science
Vielhauer, Claus	Brandenburg University of Applied Sciences
Keywords: Methodologies and tools for analysis of complexity Abstract: The protection against Advanced Persistent Threats (APTs) is an important topic in nuclear and industrial information technology security since the last decade. Nowadays steganography, i.e. information hiding techniques are increasingly used by attackers in order to operate without being detected. The usage of hidden channel communication in APTs creates a novel form of attack scenarios for which the current defense mechanisms are usually ineffective. In order to defend industrial control systems against those attacks, it is necessary to understand and comprehend the attacks. Thus, this paper presents how attack modelling based on the Lockheed Martin Cyber Kill Chain can be used to analyze hidden channel APT attack scenarios and how it can be used to elaborate defense mechanisms and to reveal attack indicators along all phases of those attack scenarios.
Paper VI154-03.2
PDF · Video · Private Weighted Sum Aggregation for Distributed Control Systems (I)
Alexandru, Andreea B.	University of Pennsylvania
Pappas, George J.	Univ of Pennsylvania
Keywords: Decentralized and distributed control, Multiagent systems, Integrated monitoring, control and security for critical infrastructure systems Abstract: Data aggregation in distributed networks is a critical element in Internet of Things applications ranging from smart grids and robot swarms to medical monitoring over multiple devices and data centers. This paper addresses the problem of private weighted sum aggregation, i.e., how to ensure that an untrusted aggregator is able to compute only the weighted sum of the users' private local data, with proprietary weights. We propose a scheme that achieves the confidentiality of both the users' local data and the weights, as long as there are at least two participants that do not collude with the rest. The solution involves two layers of encryption based on the Learning With Errors problem. We discuss how to achieve efficient multi-dimensional data aggregation by using plaintext packing in the homomorphic cryptosystem used, such that the communication between the users and the aggregator is minimized.
Paper VI154-03.3
PDF · Video · Assessment of Deterministic Delay Bounds for a DoS-Attack Prevention Device with a Static Window Flow Control (I)
Promyslov, Vitaly	V.A. Trapeznikov Institute of Control Sciences
Semenkov, Kirill	ICS RAS
Keywords: Integrated monitoring, control and security for critical infrastructure systems, Optimization and control of large-scale network systems, Modelling and control of hybrid and discrete event systems Abstract: This article focuses on the justification of the timing characteristics of devices using a static window flow control mechanism for protection against denial of service (DoS) attacks. The main focus is on a particular type of DoS attack, like flood and hit-and-run attacks. An attack of that kind can be performed using the black-box approach with a minimal piece of knowledge about the internals of the attacked system. The methods of tropical algebra (min-plus algebra) are used to compute the timing characteristics of the device with static window flow control.
Paper VI154-03.4
PDF · Video · Input Design for Active Dectection of Integrity Attacks Using Set-Based Approach (I)
Trapiello, Carlos	UPC
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Keywords: Integrated monitoring, control and security for critical infrastructure systems Abstract: This paper presents the design of an input sequence in order to actively guarantee detectability of integrity attacks. The design of the input sequence is formulated as an optimization problem where the performance degradation imposed in the protected system is minimized while guaranteeing attack detectability by separating the reachable sets of the system in healthy and attacked operation. By considering uncertainties bounded by zonotopes, the design of an optimal open-loop input sequence such that guarantee the separability of the reachable zonotopic sets can be computed by solving a Mixed Integer Quadratic Program (MIQP). Following this approach, attack detection can be guaranteed by: I) forcing a distinct behavior of the system outputs; II) ensuring that residuals under attack will exit the healthy residual set. Furthermore, the present work also considers the imposition of residuals detectability for the specific replay attack scenario affecting an state estimate control system. The effectiveness of the proposals is validated in simulation by means of a numerical example.
Paper VI154-03.5
PDF · Video · Assessment of Hidden Channel Attacks: Targetting Modbus/TCP (I)
Lamshöft, Kevin	Otto-von-Guericke-University Magdeburg
Dittmann, Jana	Otto-von-Guericke-University Magdeburg
Keywords: Integrated monitoring, control and security for critical infrastructure systems Abstract: Recent findings in research on malware threats indicate an increasing use of information hiding techniques as a novel approach for compromising IT-Systems by using covert functions and hidden channels. Especially in the context of covert intrusion and data exfiltration, networks of Industrial Control Systems (ICS) are a valuable target for information hiding based attacks. In this paper we discuss how 18 known patterns of information hiding in networks can be applied to protocols found in ICS networks and demonstrate how information can be covertly embedded and retrieved at the example of Modbus/TCP to achieve an overall protocol-compliance by also studying the embedding capacity. Additionally we provide a first tendency of warden- compliance, if the warden has a suspicion that there is a hidden message (conspicuousness). For a practical analysis we introduce an evaluation framework based on open-source software enabling assessment and quick implementation of hidden channels in common protocols found in ICS networks. In combination with a pattern-based approach for the identification of hidden channels, we show how this framework can be utilized as a systematic approach to identify and evaluate plausible hidden channels in industrial communication protocols. From the 14 identified patterns, in this paper we use the introduced framework to implement and evaluate two exemplary timing and storage channels in Modbus/TCP. Our results show 14 protocol-compliant patterns of information hiding based attacks in the context of Industrial Control Systems as well as the necessity of more research in this particular field, especially in terms of further plausible combination of pattern, warden-compliance, detection and mitigation strategies.
Paper VI154-03.6
PDF · Video · On the Secret Sharing Scheme Based on Supercodes Decoding (I)
Ivanov, Fedor	HSE
Kreschuk, Alexey	National Research University Higher School of Economics
Krouk, Eugenii	National Research University Higher School of Economics
Keywords: Integrated monitoring, control and security for critical infrastructure systems Abstract: Secret sharing schemes have been studied intensively for the last 20 years, and these schemes have a number of real-world applications. There are a number of approaches to the construction of secret sharing schemes. One of them is based on codes of forward error correction (FEC). In fact, every linear code can be used to construct secret sharing schemes. For instance original Shamir secret sharing scheme is based on erasure decoding of Reed-Solomon codes. One of the main drawbacks of secret sharing schemes based on FEC is a dependence between number of users (participants) and field size of FEC. In this paper we propose a new scheme of secret sharing based on iterative decoding of LDPC codes in terms of supercodes decoding concept. In this scheme a field size can be made arbitrary and independent on the number of participants.
Paper VI154-03.7
PDF · Video · Increased IT Security by Model-Based Vulnerability Analysis of IT/I&C Systems and Proof of ISO Conformity (I)
Lange, Mathias	Hochschule Magdeburg-Stendal
Keywords: Modelling and decision making in complex systems, Integrated monitoring, control and security for critical infrastructure systems, Optimization and control of large-scale network systems

VI154-04
Modelling, Monitoring and Decision Making in Complex Systems	Regular Session
Chair: Bernus, Peter	Griffith University
Co-Chair: Pascucci, Federica	Università Degli Studi Roma Tre
Paper VI154-04.1
PDF · Video · A Green Routing and Scheduling Problem in Home Health Care
Luo, Hongyuan	UTBM
Dridi, Mahjoub	UTBM
Grunder, Olivier	Université De Technologie De Belfort-Montbéliard
Keywords: Complex logistic systems, Production & logistics over manufacturing networking, Logistics in manufacturing Abstract: The growing concern about the influences of anthropogenic pollutions has forced researchers and scholars to study the environmental concerns. This paper addresses a green routing and scheduling problem in home health care (HHC) with the constraints of synchronized visits and carbon emissions. In this work, the objective is to design a reasonable logistics route meanwhile reduce the effect on the environment for the HHC company. The formulated mixed-integer programming (MIP) model is solved for a set of small scale instances using Gurobi solver with a time limit of 1 hour. An efficient two-phase heuristic approach through decomposing the studied problem into a routing problem and a speed optimization problem is proposed. The heuristic approach is based on two exact methods using Gurobi solver and dynamic programming (DM) method. The proposed heuristic approach is examined by a total of 19 instances with different scales. The experimental results for the studied problem highlight the effectiveness and efficiency of the proposed heuristic approach.
Paper VI154-04.2
PDF · Video · Temporal Object Tracking in Large-Scale Production Facilities Using Bayesian Estimation
Kortmann, Karl-Philipp	Leibniz University Hannover
Zumsande, Johannes	Leibniz University Hannover
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Efficient strategies for large scale complex systems, Intelligent maintenance systems, Modelling and control of hybrid and discrete event systems Abstract: Moving towards comprehensive digitalization of production facilities, it is critical to know the location of work pieces, charges, or other objects of interest that change location over time during production. For the case of a limited traceability of these objects, we first present a theoretical approach that performs a recursive Bayesian estimation of the object's location over time based on typical passage measurements in production (e. g. light barriers or RFID systems). The probabilistic method is based on a directed acyclic graph modeling the transfer and sojourn of the objects in the production network. Subsequently, the method is validated on simulated data while varying both size and measurement conditions of the process. The results show the benefit of the proposed method against a single estimation and demonstrate its potential for the application in real time scenarios.
Paper VI154-04.3
PDF · Video · Real-Time Prediction of Curing Processes Using Model Order Reduction
Frank, Tobias	Leibniz University Hanover
Zeipel, Henrik	Leibniz University Hanover, Institute of Mechatronic Systems
Wielitzka, Mark	Leibniz University Hanover
Bosselmann, Steffen	Leibniz Universität Hannover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Identification and model reduction, Monitoring and control of spatially distributed systems, Efficient strategies for large scale complex systems Abstract: Manifold engineering applications are directly affected by temperature. For rubber or composite curing processes, temperature distributions over time inside the compounds are crucial for chemical cross-linking reactions. Most of these reactions occur subsequently to a heating process during product cool down. Online prediction of cooling phases is performed during the actual heating process and hence, final cure status can be estimated before the actual process finishes. Therefore, mold temperatures and heating duration can be adapted in regard to current ambient conditions, and hence product quality is increased. In order to achieve longterm thermal predictions for complex product geometries, simulating nonlinear thermal finite element models is unfeasible, due to high computational effort. Hence, a prediction-model is derived from finite element analysis using matrix export, linearization, model order reduction algorithms such as rational Krylov or iterative rational Krylov and correction of operating point deviation. A special remark is given to temperature dependent boundary conditions, choice of time discretization and choice of solving algorithm, to address arising conflicting goals between execution time and simulation accuracy. Eventually, a complete process simulation is performed during the task-cycle time on a PLC control with a sufficiently high accuracy.
Paper VI154-04.4
PDF · Video · Research on Decision Support Method for Batch Planning of Steelmaking-Continuous Casting Charge under Lagrangian Framework
Sun, Liangliang	Shenyang Jianzhu University
Yu, Yaqian	Shenyang Jianzhu University
Li, Congxin	Shenyang Jianzhu University
Cloete, Duncan Stephen	Shenyang JianZhu University
Bai, Song	Shenyang Jianzhu University
Keywords: Intelligent decision support systems in manufacturing Abstract: Charge batch planning is the bottleneck of production management planning in iron and steelmaking enterprises. The optimization of the charge batch planning process will directly influence the iron and steelmaking cost, production and energy consumption. In this paper, an effective mathematical model based on multi-objective weighting method is built up to describe the multi-performance indexes and the multi-constraints; an efficiency adaptive search algorithm based on linear augmented Lagrangian relaxation framework is proposed to alleviate the problem of sawtooth oscillation when the traditional Lagrangian algorithm searches within the feasible domain. The strategy proposed in this paper is verified based on the background of the actual steelmaking and continuous casting management process in China steelmaking plant. The optimization results guarantee the solution quality and speed of charge batch planning of steelmaking-continuous casting.
Paper VI154-04.5
PDF · Video · A New Reinforcement Learning for Multi-Train Marshaling with Time Evaluation
Hirashima, Yoichi	Osaka Institute of Technology
Keywords: Intelligent decision support systems in manufacturing, Logistics in manufacturing, Methodologies and tools for analysis of complexity Abstract: In this paper, a new reinforcement learning method is proposed to solve a train marshaling problem for assembling several outgoing trains simultaneously. In the addressed problem, the order of the incoming freight cars is assumed to be random. Then, the freight cars are classified into several sub-tracks. The cars on sub-tracks are rearranged to the main track by a certain desirable order. In the proposed method, each set of freight cars that have the same destination make a group, and the desirable group layout constitutes the best outgoing trains. When a rearrangement operation is conducted, the best number of sub-tracks used in the operation is obtained by a reinforcement learning system, as well as the best layout of groups in the trains, the best order to rearrange cars by the desirable order, and the best sub-track for the car to be removed. The marshaling plan that consists of series of removal and rearrangement operations are generated based on the processing time of movements of freight cars. The total processing time required to assemble outgoing trains can be minimized by the proposed method.
Paper VI154-04.6
PDF · Video · Energetic and Economic Performance Evaluation of Production Systems: Perspective Analysis
Alaouchiche, Yasmine	University of Technology of Troyes
Ouazene, Yassine	Université De Technologie De Troyes
Yalaoui, Farouk	University of Technology of Troyes, Institue of Services and Ind
Keywords: Intelligent manufacturing systems, Modeling of manufacturing operations Abstract: Improving the economic as well as the energetic performances of manufacturing systems has become a real challenge for both researchers and industrials. Due to the economic, legislative and environmental pressure, enhancing both economic and energetic performances arouses interest and attracts further efforts. The objective of this paper is to discuss current work done on this subject, analyze the results and propose further perspectives for research in this area towards sustainability. Furthermore, an introduction to an economic and energetic evaluation for serial production lines is also presented.
Paper VI154-04.7
PDF · Video · Multi-States Two-Machine Permutation Flow Shop Scheduling Optimisation with Time-Dependent Energy Costs
Aghelinejad, Mohammadmohsen	University of Technology of Troyes
Masmoudi, Oussama	University of Technology of Troyes
Ouazene, Yassine	Université De Technologie De Troyes
Yalaoui, Alice	University of Technology of Troyes
Keywords: Job and activity scheduling, Modeling of manufacturing operations, Procedures for process planning Abstract: This paper studies a multi-states two-machine flowshop scheduling problem with variable electricity tariffs. The main issue is to assign a set of jobs to available time slots with different energy costs to minimise the total energy consumption costs. For this purpose, two different 0-1 linear programs are proposed for the problem. Computational experiments are presented and numerical results are discussed and analyzed in order to evaluate their efficiencies.
Paper VI154-04.8
PDF · Video · Enabling Interactive Visualizations in Industrial Big Data
Bezerra, Aguinaldo	Universidade Federal Do Rio Grande Do Norte
Greati, Vitor	Universidade Federal Do Rio Grande Do Norte
Campos, Vinícius	Universidade Federal Do Rio Grande Do Norte
Silva, Ivanovitch	Universidade Federal Do Rio Grande Do Norte
Guedes, Luiz Affonso	Federal University of Rio Grande Do Norte
Leitão, Gustavo	UFRN
Silva, Diego	Universidade Federal Do Rio Grande Do Norte
Keywords: Konwledge discover (data mining), Discrete event systems in manufacturing, Intelligent decision support systems in manufacturing Abstract: Industries are considered data rich but information poor environments. Mainly due to systems design restrictions, to the lack of adequate processing power and to a sector culture notably focused on collecting, selecting, storing and preserving historical series in on-demand access repositories, massive data generated in industrial operations is traditionally neglected (or simply took aside). This huge amount of unprocessed data resting in these repositories is a latent and rich source of information that could be used to improve industrial processes. This work then proposes an approach in which an elastic processing engine is designed to be plugged-in to currently installed industrial information infrastructure to provide it with the ability of performing visual analytics on massive industrial data. A case study where an interactive visualization application is made possible in real-world industrial data scenario of over 100 million records is presented to attest the effectiveness and potential of the proposed approach in enabling interactive visualizations to Industrial Big Data.
Paper VI154-04.9
PDF · Video · Artificial Intelligence Platform Proposal for Paint Structure Quality Prediction within the Industry 4.0 Concept
Kebisek, Michal	Slovak University of Technology in Bratislava
Tanuska, Pavol	Slovak University of Technology
Spendla, Lukas	Slovak University of Technology in Bratislava
Kotianova, Janette	Slovak University of Technology in Bratislava
Strelec, Peter	Slovak University of Technology in Bratislava
Keywords: Konwledge discover (data mining), Intelligent system techniques and applications Abstract: This article provides an artificial intelligence platform proposal for paint structure quality prediction using Big Data analytics methodologies. The whole proposal fits into the current trends that are outlined in the Industry 4.0 concept. The painting process is very complex, producing huge volumes of data, but the main problem is that the data comes from different data sources, often heterogeneous, and it is necessary to propose a way to collect and integrate them into a common repository. The motivation for this work were the industry requirements to solve specific problems that cannot be solved by standard methods but require a sophisticated and holistic approach. It is the application of artificial intelligence that suggests a solution that is not otherwise visible, and the use of standard methods would not give any satisfactory results. The result is the design of an artificial intelligence platform that has been deployed in a real manufacturing process, and the initial results confirm the correctness and validity of this step. We also present a data collection and integration architecture, which is an integral part of every big data analytics solution, and a principal component analysis that was used to reduce the dimensionality of the large number of production process data.
Paper VI154-04.10
PDF · Video · Top-Down Nested Supervisory Control of State-Tree Structures Based on State Aggregations
Wang, Xi	SEME, Xidian University
Moor, Thomas	Friedrich-Alexander Universität Erlangen-Nürnberg
Li, Zhiwu	Xidian University
Keywords: Modelling and control of hybrid and discrete event systems, Hierarchical multilevel and multilayer control, Modelling and decision making in complex systems Abstract: With a structured state space, state-tree structures (STS) are a powerful framework to model hierarchical finite state machines (HFSM). The boundary consistency property of STS endows them a compact and neatly representation. In this study, by decomposing an STS into a set of STS nests in a top-down nested approach and finding a supervisor for each, the boundary consistency property is extended to the supervisory control of STS. As a consequence, the state spaces for both the system model and optimal supervisor are significantly reduced. Two examples are provided, in which the state space of a large scale HFSM example is reduced from 10^24 to 2*10^18.
Paper VI154-04.11
PDF · Video · Piecewise Linearization for Solving Models to Locate Urban Logistics Facilities
Racedo-Gutierrez, Jelibeth	Universidad Manuela Beltrán
Torres-Delgado, Fidel	Universidad De Los Andes
Keywords: Modelling and decision making in complex systems, Complex logistic systems, Logistics in manufacturing Abstract: Facilities location is a strategic decision in supply chain design since it affects products and information flows through all the echelons. In urban contexts, facilities location is even more important because it shapes both the distribution activities and urban landscapes. In addition, changes in facilities location patterns have caused non-intended externalities such as congestion, emissions, noise, among others. We present a non-linear programming model to establish optimal facilities location in urban areas, modelling the city as a transportation network and considering congestion into the objective function. To solve the model, we use a piecewise linear optimization, which allows to obtain an optimal solution.
Paper VI154-04.12
PDF · Video · Energy Costs of Production and Project Assessment
Enaleev, Anver	V.A.Trapeznikov Institute of Control Sciences
Tsyganov, Vladimir	V.A. Trapeznikov Institute of Control Sciences
Keywords: Modelling and decision making in complex systems, Decentralized and distributed control, Intelligent decision support systems in manufacturing Abstract: Corporation cycle of developing a project and its implementation in the production to minimize energy costs is considered. A hierarchical control system for this cycle is reviewed for harmonizing the interests of its elements taking into account the human factor. A procedure for a comprehensive assessment of project to diminish the energy costs of production is proposed. The key factor of such an assessment is the energy costs rating of existing production. The problem of determination of such a rating is formulated. Conditions for such determination are obtained taking into account the interests of the elements of the corporation responsible for production. These conditions are illustrated by the example of determining the ratings of energy costs of production in large scale corporation Russian Railways. An example of a comprehensive assessment procedure for projects to reduce the cost of energy production in this corporation based on these ratings is given.
Paper VI154-04.13
PDF · Video · Surrogate Modelling and Optimization for Complex Liquefied Natural Gas Refrigeration Cycles
Savage, Thomas	University of Manchester
Almeida-Trasvina, Hector	University of Manchester
del Rio-Chanona, Ehecatl Antonio	Imperial College London
Smith, Robin	University of Manchester
Zhang, Dongda	University of Manchester
Keywords: Modelling and decision making in complex systems, Efficient strategies for large scale complex systems, Modeling of manufacturing operations Abstract: In this paper, surrogate modelling and optimization is investigated for use in large scale chemical processes. A novel CryoMan cascade liquefied natural gas (LNG) refrigeration cycle is selected as the case study which has been highlighted for potential use within industry. Given its high nonlinearity and dimensionality (31 input variables and 20 output variables with a number of physical constraints) and short time horizon for real-time decision-making, an time-efficient optimization scheme must be developed to maximize process performance. Therefore, various supervised and unsupervised learning techniques as well as surrogate model structures are explored in order to accurately capture the behaviour of this highly complex and interrelated process flowsheet. Optimal solutions identified by the surrogate models are validated against the rigorous process model. Following from the challenges encountered by artificial neural network based surrogate models, Gaussian processes were adopted and combined with partial least squares to simultaneously reduce dimensionality and capture the nonlinearity of the underlying chemical process. Through this innovative surrogate modelling strategy, overall time to optimize the LNG production process was reduced by orders of magnitude compared to the rigorous model based optimization methodology, hence significantly facilitating the industrial application of this new process.
Paper VI154-04.14
PDF · Video · Toward a Science of Resilience, Supportability 4.0 and Agility
Bernus, Peter	Griffith University
Noran, Ovidiu	Griffith University
Goranson, Ted	Griffith University
Keywords: Modelling and decision making in complex systems, Intelligent decision support systems in manufacturing, Optimization and control of large-scale network systems Abstract: Large and complex systems have a long-expected life and evolve slower than small systems. As such, they may live through several technological, social, economic and ecological changes in their environment. A fundamental challenge discussed in this paper is how to (re)design and change large-scale systems so that they remain maintainable and evolvable e.g. for the expected duration of their lives. This must also be achieved in view of their legacy and carried out in an affordable, risk-mitigated and timely manner. After defining some important features of large-scale systems and reviewing the state of the art in managing systems evolution, the paper characterizes the problems, solution scope and opportunities in the area and defines basic principles, theory, associated life cycle architecture and methodology approach for long-term systems supportability.
Paper VI154-04.15
PDF · Video · The Smart Extension Approach for Securing Industrial Control Systems
Colelli, Riccardo	University of Roma Tre
Foglietta, Chiara	University ROMA TRE, Dipartimento Di Ingegneria
Panzieri, Stefano	Universitá Di Roma Tre
Pascucci, Federica	Università Degli Studi Roma Tre
Keywords: Integrated monitoring, control and security for critical infrastructure systems, Process supervision, Industrial communication protocols Abstract: Industrial Control Devices are one of the major targets for hackers due to their exposure to threats. The principle of "air gaps" (disconnecting the Industrial Control Network from the operational networks) is not anymore feasible in a connected world. In this paper, a host anomaly detection system for Critical Infrastructures networks is presented. The device, called Smart Extension, also implements a filtering strategy in order to secure a single host reacting to cyber threats. Therefore, it is positioned in the network between PLC (Programmable Logic Controller) and the SCADA (Supervisory Control and Data Acquisition) control centre, more precisely just in front of the PLC. Finally, experimental results are shown in order to explain the internal working procedures in a possible case study.
Paper VI154-04.16
PDF · Video · Model Predictive Control Strategy Based on Improved Trajectory Extension Model for Deviation Correction in Vertical Drilling Process
Zhang, Dian	China University of Geosciences (Wuhan)
Wu, Min	China University of Geosciences
Chen, Luefeng	China University of Geosciences
Lu, Chengda	China University of Geosciences
Cao, Weihua	China University of Geosciences
Wang, Feng	China University of Geosciences
Keywords: Modelling and decision making in complex systems, Modelling and control of hybrid and discrete event systems, Intelligent system techniques and applications Abstract: Vertical drilling system is widely used in deep geological exploration. As only inclination angle is considered in conventional vertical drilling systems, which decreases the quality of drilling trajectory, especially in geological drilling. In this paper, a model predictive control strategy based on improved trajectory extension model is provided, and it aims to reduce the position deviation and inclination angle of the drilling trajectory in vertical drilling process. An improved trajectory extension model is established by considering both attitude dynamic and space movement of bottom hole assembly under ground in vertical drilling process; and then, in order to deal with control constraints directly, a model predictive controller is provided based on the improved trajectory extension model. Simulation results of deviation correction are presented for validating the proposed strategy.
Paper VI154-04.17
PDF · Video · Demand Tracking Control in Manufacturing Systems
Othman, Khaled	Kiel University
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: Monitoring and control of spatially distributed systems, Production planning and control, Optimization and control of large-scale network systems Abstract: The purpose of this research is to design optimal boundary control to solve demand tracking problems for manufacturing systems represented at the factory level in terms of conservation laws coupled with ordinary differential equations. The factory level is modeled as a network with arcs describing specific production policies, e.g., velocity, processing rate, number of machines, and each vertex represents the buffer zone. Different interconnection topologies that correspond to dispersing and merging networks are considered. Numerical solutions are performed using direct and indirect methods.
Paper VI154-04.18
PDF · Video · Planning of Vehicle Routes for the Exam Booklet Distribution: A GIS-Based Solution Approach
özkan, Bariş	Ondokuz Mayis University
özceylan, Eren	Gaziantep University
Mete, Suleyman	Gaziantep University
Keywords: Optimization and control of large-scale network systems, Complex logistic systems, Modelling and decision making in complex systems Abstract: A vehicle routing problem (VRP) motivated by the case of examination booklet distribution is considered in this paper. In this practical and repetitive problem, the boxes include exam booklets that are taken from a depot in the university campus and distributed to the 49 exam buildings (schools) where the exams are held in. For the distribution, there are 18 vehicles with different box capacities. The exam is organized in four different sessions. Visiting the maximum three schools by each vehicle is one of the main constraints of the problem. This rich VRP variant concerns the capacitated heterogonous vehicle fleet, multi-distribution and a limited number of schools visited. Due to the complexity and NP-hardness of the problem, a geographic information system (GIS)-based solution approach, which uses a tabu search heuristic method, is applied to obtain an acceptable solution in a reasonable time. Our numerical results show that total traveled distance, average capacity utilization and the total number of routes are improved by 19.39%, 9.14%, and 9.38%, respectively, in comparison with the current distribution plan.
Paper VI154-04.19
PDF · Video · A Dynamic Method to Solve the Fixed Charge Network Flow Problem
Nie, Zhibin	Tsinghua University
Wang, Shuning	Tsinghua University
Keywords: Optimization and control of large-scale network systems, Complex logistic systems, Water supply and distribution systems Abstract: This paper studies the widely applied fixed charge network flow problem (FCNFP) which is NP-hard. We approximate the FCNFP with a bilinear programming (BP) problem that is determined by a parameter. When this parameter is small enough, the optimal solution to the FCNFP is the same as the optimal solution to the BP problem. Therefore, solving the FCNFP can be transformed into solving a series of BP problems. These BP problems are solved by alternately solving two linear programming problems. A dynamic method is proposed to update the parameter associated with the BP problem after solving one of the linear programming problems rather than solving the whole BP problem. Numerical experiments show the performance of the proposed dynamic method.
Paper VI154-04.20
PDF · Video · The Vulnerability of Securing IoT Production Lines and Their Network Components in the Industry 4.0 Concept
Horak, Tibor	Slovak University of Technology in Bratislava
Cervenanska, Zuzana	Slovak University of Technology in Bratislava
Huraj, Ladislav	University of SS. Cyril and Methodius Trnava
Vazan, Pavel	Slovak University of Technology in Bratislava
JánoŠík, Ján	Slovak University of Technology in Bratislava
Tanuska, Pavol	Slovak University of Technology
Keywords: Integrated monitoring, control and security for critical infrastructure systems, Internet-of-Things and Sensing Enterprise, Discrete event systems in manufacturing Abstract: IoT systems are an integral part of every modern industrial enterprise Industry 4.0. IoT is the term for modern remote devices controlled via the Internet. Internet of Things is the name of technologies that allow cheap wireless connection and communication of various sensors and devices to automate, accelerate and streamline processes. In the interconnected world of Industry 4.0, there are many potential resources existing for infiltration. Cybercriminals could take control of manufacturing industries, manipulate machines, or could do an industrial espionage. This type of attack is called Denial of Service. In the second case, the attack preserves the attacker's anonymity through an IP address by using a potentially innocent third party (a reflector) that is indirectly involved in the attack. Through this attack, the attacker forwards the flow of attacking data to the target victim. The attacker sends the packets with a fake spoof source IP address set to the victim's IP address to the reflector, thus indirectly overloading the target with the packets, or it will intrude into a network device through a faulty WPS implementation. The simulation model of the production line and the IoT security system Fibaro were used to investigate these attacks. The article demonstrates the possibility of attacks on network devices and the misuse of IoT devices in order to compromise production machines which use DRDoS and Brute-force attacks.

VI161
Power and Process System - Chemical Process Control
VI161-01 Advances in Stochastic and Set Based Control and Estimation   Invited Session, 6 papers
VI161-02 Data Science for Systems   Invited Session, 10 papers
VI161-03 Industrial Data Science and Machine Learning Applications   Invited Session, 4 papers
VI161-04 Recent Progress in Explicit MPC Methods   Invited Session, 8 papers
VI161-05 Control and Estimation of Particulate Processes   Open Invited Session, 6 papers
VI161-06 Control and Operability of Intensified and Modular Industrial Manufacturing Systems   Open Invited Session, 6 papers
VI161-07 Processes Control with Tomographic Sensors   Open Invited Session, 6 papers
VI161-08 Thermodynamics and Control   Open Invited Session, 9 papers
VI161-09 Predictive and Optimization-Based Control for Chemical Processes   Regular Session, 11 papers
VI161-10 Modeling and Monitoring for Process Control   Regular Session, 16 papers
VI161-11 Process Control   Regular Session, 22 papers

VI161-01
Advances in Stochastic and Set Based Control and Estimation	Invited Session
Chair: Paulen, Radoslav	Slovak University of Technology in Bratislava
Co-Chair: Mesbah, Ali	University of California, Berkeley
Organizer: Paulen, Radoslav	Slovak University of Technology in Bratislava
Organizer: Houska, Boris	ShanghaiTech University
Organizer: Villanueva, Mario Eduardo	ShanghaiTech University
Organizer: Mesbah, Ali	University of California, Berkeley
Organizer: Engell, Sebastian	TU Dortmund
Paper VI161-01.1
PDF · Video · Dual Multi-Stage NMPC Using Sigma Point Principles (I)
Thangavel, Sakthi	TU Dortmund
Paulen, Radoslav	Slovak University of Technology in Bratislava
Engell, Sebastian	TU Dortmund
Keywords: Model predictive and optimization-based control, Advanced process control, Advanced control technology Abstract: Dual control is a technique that addresses the trade-off between probing (excitation signals) and control actions, which results in a better estimation of the unknown parameters and therefore in a better (tracking or economic) performance. Multi-stage NMPC is a robust-control scheme that represents the uncertainty using a scenario tree that is often built by assuming parametric uncertainty and by taking into account the minimum, nominal and maximum values of the uncertain parameters. If the uncertainty set is not a box, this procedure augments the uncertainty set and results in a loss of performance. Here, we mitigate this problem by tightly approximating the uncertainty set using the so-called sigma points and computing an ellipsoidal over-approximation of the reachable set of the system using the unscented transformation. We also improve the performance by considering the future reduction of the ranges of the uncertainties due to control actions and measurements thereby achieving implicit dual control actions. The advantages of the proposed approach over the standard multi-stage NMPC scheme are demonstrated for a linear and a nonlinear (semi-batch reactor) simulation case study.
Paper VI161-01.2
PDF · Video · Estimation Technique for Offset-Free Economic MPC Based on Modifier Adaptation (I)
Vaccari, Marco	University of Pisa
Pelagagge, Federico	University of Pisa
Bonvin, Dominique	EPFL
Pannocchia, Gabriele	University of Pisa
Keywords: Real time optimization and control, Model predictive and optimization-based control, Advanced process control Abstract: Economic model predictive control formulations that combine online optimizing control with offset-free methodologies such as modifier adaptation have been proposed recently. These new algorithms are able to achieve asymptotic optimal performance despite the presence of plant-model mismatch. However, there is a major requirement stemming from the modifier-adaptation part, namely, the necessity to know the static plant gradients at the sought (and therefore still unknown) steady-state operating point. Hence, for implementation purposes, the algorithms need to be enhanced with plant gradient estimation techniques. This work proposes to estimate modifiers directly, based on steady-state perturbations and using Broyden’s approximation. The proposed economic MPC algorithm has been tested in simulation on the Williams-Otto reactor and provides plant optimality upon convergence.
Paper VI161-01.3
PDF · Video · Stochastic Model Predictive Control with Adaptive Chance Constraints Based on Empirical Cumulative Distributions (I)
Santos, Tito	Federal University of Bahia
Cunha, Victor	Federal University of Bahia
Mesbah, Ali	University of California, Berkeley
Keywords: Model predictive and optimization-based control, Real time optimization and control Abstract: Individual chance constraints can be used to systematically seek trade-offs between control performance and constraint violation for a given disturbance description. This paper presents a Stochastic Model Predictive Control (SMPC) approach with adaptive individual chance constraints that relies on online adaptation of the disturbance description using the empirical cumulative distribution (ECDF). Individual chance constraints are ensured by using a suitable worst-case confidence interval derived from the ECDF. The confidence interval may, however, be excessively conservative due to the empirical nature of the ECDF. To reduce this conservatism, the proposed approach accounts for the updated disturbance information, which is sampled online from the one-step ahead prediction error. Hence, the initial ECDF can be obtained from a reduced number of samples since the conservative handling of the chance constraint is continuously mitigated. This will also allow for using simpler models of the stochastic system disturbances. Convergence and recursive feasibility of the proposed adaptive approach are established. A DC-DC converter benchmark problem is used to illustrate the usefulness of the proposed approach.
Paper VI161-01.4
PDF · Video · Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty (I)
Petsagkourakis, Panagiotis	University College London
Sandoval, Ilya Orson	Instituto De Ciencias Nucleares, Universidad Nacional Autonoma D
Bradford, Eric	Norwegian University of Science and Technology
Zhang, Dongda	University of Manchester
del Rio-Chanona, Ehecatl Antonio	Imperial College London
Keywords: Real time optimization and control, Nonlinear process control, Batch and semi-batch process control Abstract: Dynamic real-time optimization (DRTO) is a challenging task due to the fact that optimal operating conditions must be computed in real time. The main bottleneck in the industrial application of DRTO is the presence of uncertainty. Many stochastic systems present the following obstacles: 1) plant-model mismatch, 2) process disturbances, 3) risks in violation of process constraints. To accommodate these difficulties, we present a constrained reinforcement learning (RL) based approach. RL naturally handles the process uncertainty by computing an optimal feedback policy. However, no state constraints can be introduced intuitively. To address this problem, we present a chance-constrained RL methodology. We use chance constraints to guarantee the probabilistic satisfaction of process constraints, which is accomplished by introducing backoffs, such that the optimal policy and backoffs are computed simultaneously. Backoffs are adjusted using the empirical cumulative distribution function to guarantee the satisfaction of a joint chance constraint. The advantage and performance of this strategy are illustrated through a stochastic dynamic bioprocess optimization problem, to produce sustainable high-valued bioproducts.
Paper VI161-01.5
PDF · Video · A Probabilistic Validation Approach for Penalty Function Design in Stochastic Model Predictive Control (I)
Mammarella, Martina	CNR
Alamo, Teodoro	Universidad De Sevilla
Lucia, Sergio	TU Berlin
Dabbene, Fabrizio	CNR
Keywords: Model predictive and optimization-based control, Advanced control technology, Control system design Abstract: In this paper, we consider a stochastic Model Predictive Control able to account for effects of additive stochastic disturbance with unbounded support, and requiring no restrictive assumption on either independence nor Gaussianity. We revisit the rather classical approach based on penalty functions, with the aim of designing a control scheme that meets some given probabilistic specifications. The main difference with previous approaches is that we do not recur to the notion of probabilistic recursive feasibility, and hence we do not consider separately the unfeasible case. In particular, two probabilistic design problems are envisioned. The first randomization problem aims to design offline the constraint set tightening, following an approach inherited from tube-based MPC. For the second probabilistic scheme, a specific probabilistic validation approach is exploited for tuning the penalty parameter, to be selected offline among a finite-family of possible values. The simple algorithm here proposed allows designing a single controller, always guaranteeing feasibility of the online optimization problem. The proposed method is shown to be more computationally tractable than previous schemes. This is due to the fact that the sample complexity for both probabilistic design problems depends on the prediction horizon in a logarithmic way, unlike scenario-based approaches which exhibit linear dependence. The efficacy of the proposed approach is demonstrated with a numerical example.
Paper VI161-01.6
PDF · Video · Set-Based State Estimation: A Polytopic Approach (I)
Valero, Carlos Eduardo	Slovak University of Technology in Bratislava
Villanueva, Mario Eduardo	ShanghaiTech University
Houska, Boris	ShanghaiTech University
Paulen, Radoslav	Slovak University of Technology in Bratislava
Keywords: Process observation and parameter estimation, Process modeling and identification, Identification and modelling Abstract: This paper is concerned with guaranteed parameter estimation for discrete-time nonlinear systems subject to bounded uncertainties. The proposed approach is based on polytopic set parameterizations. Similar to other estimation and filtering approaches, the presented algorithm is based on two operations, propagation of the polytopic uncertainty through the dynamics and an update operation using the measurement. Both the propagation and the update steps are based on set-operations that use a parameterized lifted outer approximations of the polytopes. The performance of the approach is illustrated by applying it to the double integrator system, where the presented polytopic parameterization approach leads to accurate and rigorous parameter estimates.

VI161-02
Data Science for Systems	Invited Session
Chair: Qin, S. Joe	University of Southern California
Co-Chair: He, Qinghua (Peter)	Auburn University
Organizer: Qin, S. Joe	University of Southern California
Organizer: He, Qinghua (Peter)	Auburn University
Organizer: Flores-Cerrillo, Jesus	Linde
Paper VI161-02.1
PDF · Video · Supervised Block-Aware Factorization Machine for Multi-Block Quality-Relevant Monitoring (I)
Zhu, Qinqin	University of Waterloo
Keywords: Data mining and multivariate statistics, Process performance monitoring/statistical process control, Monitoring of product quality and control performance Abstract: Multi-block multivariate statistical methods have been developed to extract useful information from process and quality data in the era of big data, where process variables are partitioned into several meaningful blocks. However, most of these methods did not consider cross-correlations among divided blocks, which leads to inferior monitoring performance. In this article, a block-aware factorization machine (BAFM) algorithm is proposed to exploit information from process and quality data. In BAFM, quality data are first classified into normal and abnormal labels with principal component analysis based quality monitoring framework. Afterwards, a block number is attached to each process variable, and the interactions among different variables (both within and cross blocks) are learned through latent variables, which is supervised by the classified quality labels. Apart from the variable relation within the same block, BAFM also incorporates the block information; thus, both inner and cross correlations are constructed. The monitoring framework based on BAFM is developed, and its effectiveness and superiority are demonstrated through the Tennessee Eastman process.
Paper VI161-02.2
PDF · Video · Characterizing the Predictive Accuracy of Dynamic Mode Decomposition for Data-Driven Control (I)
Lu, Qiugang	University of Wisconsin - Madison
Shin, Sungho	University of Wisconsin-Madison
Zavala, Victor M.	University of Wisconsin-Madison
Keywords: Identification and modelling, Signal and identification-based methods, Control of large-scale systems Abstract: Dynamic mode decomposition (DMD) is a versatile approach that enables the construction of low-order models from data. Controller design tasks based on such models require estimates and guarantees on predictive accuracy. In this work, we provide a theoretical analysis of DMD model errors that reveals impacts of model order and data availability. The analysis also establishes conditions under which DMD models can be made asymptotically exact. We numerically validate our theoretical results using a 2D diffusion system.
Paper VI161-02.3
PDF · Video · A Phase Segmentation Approach for Applying Reinforcement Learning to Batch Polymerization Process Control (I)
Yoo, Haeun	KAIST
Kim, Boeun	University of Wisconsin – Madison
Lee, Jay H.	KAIST
Keywords: Advanced control technology, Batch and semi-batch process control, Real time optimization and control Abstract: Nonlinear model predictive control (NMPC) or economic NMPC (eNMPC) is a widely studied optimal control method for batch processes with strongly nonlinear dynamics, but its performance can degrade severely in the presence of uncertainties in feedstock quality and other process characteristics. Reinforcement learning (RL) can be a good alternative in such cases since it can address stochastic uncertainties in a near-optimal manner using data samples from simulations or real operation. The downside is a large data requirement and unstable learning behavior, especially when the target system exhibits highly time-varying behavior as most batch processes do. To apply an RL algorithm to batch process control in a more stable and effective way, this study suggests a phase segmentation approach to consider the distinct dynamic characteristics of different phases. The approach designs separate reward functions and actor-critic networks. As a case study, optimal control of a polyol batch polymerization process is simulated to demonstrate the improvement in control policy brought by the phase segmentation approach and to compare its control performance with standard eNMPC.
Paper VI161-02.4
PDF · Video · Non-Dimensional Feature Engineering and Data-Driven Modeling for Microchannel Reactor Control (I)
Tsay, Calvin	The University of Texas at Austin
Baldea, Michael	The University of Texas at Austin
Keywords: Neural networks in process control, Nonlinear model reduction, Process control applications Abstract: Catalytic plate microchannel reactors (CPRs) are a promising means for modular hydrogen/fuels production from distributed natural gas resources. However, the equipment miniaturization presents challenges for process control, including spatially-distributed models, limited availability of measurements, and fast process time constants. In the present paper, we investigate the use of data-driven models-specifically, artificial neural networks (ANNs)-to estimate temperature "hotspots" within CPRs. We prescribe nonlinear transformations of the model inputs in the form of well-known dimensionless quantities (e.g., Reynolds number), and we show that these engineered features can improve the prediction capability of computationally parsimonious ANNs using a first-principles reactor model. Finally, we present a simulation case study that demonstrates the use of a trained ANN for inferential model predictive control.
Paper VI161-02.5
PDF · Video · Feature Based Fault Detection for Pressure Swing Adsorption Processes (I)
Lee, Jangwon	Auburn University
Kumar, Ankur	Linde
Flores-Cerrillo, Jesus	Linde
Wang, Jin	Auburn University
He, Qinghua (Peter)	Auburn University
Keywords: Estimation and fault detection, Monitoring and performance assessment, Industrial applications of process control Abstract: Over the past few decades, there has been widespread development of pressure swing adsorption (PSA) systems, with their applications expanding from traditional bulk gas separation and drying, to CO2 sequestration, trace contaminant removal, and many others. With extensive industrial applications, there is a significant need for effective monitoring methods to detect and diagnose process abnormalities in real-time, as well as to facilitate predictive maintenance for avoiding major production disruptions ahead. Although periodic operations such as PSA have been used widely in chemical and petrochemical industries, the process monitoring of these operations has received limited attention compared to non-periodic continuous or batch processes. A potential reason is that the monitoring of periodic processes is significantly more challenging than that of processes operated at steady-state. In this work, we propose a data-driven feature space monitoring (FSM) approach for PSA processes. We show that the FSM based fault detection naturally addresses the challenges in monitoring periodic processes, such as unequal step and/or cycle time that requires trajectory alignment or synchronization for the traditional statistical process monitoring (SPM) methods. In addition, we demonstrate the superior fault detection performance of the proposed method compared to the conventional SPM methods using both simulated faults and real faults from an industrial PSA process.
Paper VI161-02.6
PDF · Video · Distribution Independent Threshold Setting Based on One-Class Support Vector Machine (I)
Louen, Chris	University of Duisburg-Essen
Ding, Steven X.	Univ of Duisburg-Essen
Keywords: AI methods for FDI, Computational methods for FDI, Data mining and multivariate statistics Abstract: In this paper, threshold setting issues for data-driven fault detection are addressed. It is state of the art that multivariate analysis based threshold setting schemes are widely applied, which generally require detailed knowledge about the distribution of the process data. The often used Hotelling’s T2, SPE threshold setting is based on the assumption of Gaussian distributed process data. In industrial applications, the distribution of data sets is often unknown or non-Gaussian. Alternatively, the fault detection is formulated as classification or outlier detection (one-class) problem which can be solved e.g. by means of machine learning algorithms. The classifier parameter choice is normally done by expert knowledge or using iterative approaches like cross validation. Such a procedure has considerable influence on the fault detection performance. The availability of training and evaluation data collected under faulty conditions is mostly very limited or time and cost consuming and thus often problematic. This paper presents an iterative threshold setting algorithm, which only uses fault-free data for parameter optimization. For this purpose, a one-class support vector machine which is restricted to convex data sets (including non-Gaussian) is used. The effectiveness of the proposed threshold setting scheme is assessed based on false alarm rate, fault detection rate and randomized algorithm evaluation. Additionally, random uniform distributed uncertainties (scaling and rotation) and offset faults (inside an ellipse) are taken into account. Finally, a comparison study with principal component analysis and Hotelling’s T2, SPE threshold setting schemes is demonstrated.
Paper VI161-02.7
PDF · Video · Integrating Dynamic Neural Network Models with Principal Component Analysis for Model Predictive Control (I)
Hassanpour, Hesam	McMaster University
Corbett, Brandon	McMaster University
Mhaskar, Prashant	McMaster Univ
Keywords: Process modeling and identification, Neural networks in process control, Model predictive and optimization-based control Abstract: This work addresses the problem of identifying models and implementing model predictive control (MPC) for industrial data sets with possibly correlated manipulated variables. The key idea is to use principal component analysis (PCA) to reject the redundancy in the input space first and utilize scores to build the dynamical model of the system using recurrent neural networks (RNN). Then, the identified model is embedded in the MPC framework computing the optimized values of scores. The optimized inputs are calculated using the loadings of the PCA model and applied to the system. The efficacy of the proposed approach is evaluated using a chemical reactor example. The results are compared with a base-case scenario where the data is directly utilized to build a dynamic neural network model and used as part of a model predictive control implementation. The simulation results show the superiority of the proposed integrated PCA-RNN models for model predictive control.
Paper VI161-02.8
PDF · Video · Deep Neural Network Approximation of Nonlinear Model Predictive Control (I)
Cao, Yankai	University of British Columbia
Gopaluni, Bhushan	University of British Columbia
Keywords: Model predictive and optimization-based control, Nonlinear process control Abstract: This paper focuses on developing effective computational methods to enable the real-time application of model predictive control (MPC) for nonlinear systems. To achieve this goal, we follow the idea of approximating the MPC control law with a Deep Neural Network (DNN). To train the deep neural network offline, we propose a new "optimize and train" method that combines the steps of data generation and neural network training into a single high-dimensional stochastic optimization problem. This approach directly optimizes the closed-loop performance of the DNN controller over a finite horizon for a number of initial states. The large-scale optimization problem can be solved efficiently using parallel computing techniques. The benefits of this approach over the conventional "optimize then train" protocol is illustrated through numerical results.
Paper VI161-02.9
PDF · Video · Internet-Of-Things Enabled Manufacturing: Challenges to Machine Learning and Deep Learning (I)
He, Qinghua (Peter)	Auburn University
Wang, Jin	Auburn University
Keywords: Monitoring and performance assessment, Estimation and fault detection, Process modeling and identification Abstract: Although many general frameworks have been proposed for IoT enabled systems and their potential in industrial applications, there is limited study on the properties, such as capabilities and limitations, of these industrial IoT devices. In particular, there is little to no study on the characteristics of the data generated from these IoT devices when installed on manufacturing systems, and what challenges the collected IoT process data will present to the conventional machine learning approaches (particularly deep learning) in industrial applications such as process modeling and monitoring. In this work, we will present our study of the data characteristics of two different IoT devices in two IoT-enabled manufacturing testbeds. One is the application of IoT vibration sensors for monitoring a pump-flow process and the other is the application of short-range IoT Wi-Fi for estimating moisture content of woodchips in a chemical pulping process. Our study shows that the data generated from IoT devices are truly messy big data that can be described by the 4V characteristics, namely volume, velocity, variety and veracity. We further demonstrate that the most prominent challenge that IoT data present to machine learning, especially deep learning, is the data veracity or the messiness of the data, which include a variety of components such as significant noises, irregular sampling intervals, missing values and segments. We demonstrate that in both IoT enabled applications, rote application of machine learning methods, including deep learning methods, result in underperforming models that lead to incomplete or misleading conclusions. In contrast, robust feature engineering guided by human learning (e.g., data exploration/visualization, domain knowledge integration, and fundamental relation extraction) plays a key role for improving machine learning performance.
Paper VI161-02.10
PDF · Video · On Data Science for Process Systems Modeling, Control and Operations (I)
Qin, S. Joe	University of Southern California
Dong, Yining	University of Southern California
Keywords: Process modeling and identification, Monitoring and performance assessment, Data mining and multivariate statistics Abstract: Data science is emerging as a multidisciplinary field with tremendous recent development in theoretical foundations and expanded applications in both science and engineering. Engineering applications include industrial data analytics, autonomous systems, energy analytics, environmental applications, economic data modeling, image sequence modeling, and other high dimensional time-series data analytics. This paper is concerned with the integration of data science with dynamic systems, monitoring and control. The development of machine learning is reviewed in both a neural-mimic learning route and a learning control route, which deals with intrinsically uncertain dynamic systems. The paper then reviews the interaction of data with process manufacturing systems modeling and control, involving both data and first principles models with varying proportions. Problems include data reconciliation, state and disturbance estimation, system identification, process monitoring, and inferential property estimation. For time series data in process manufacturing systems, we present latent dynamic variable modeling methods to extract the principal dynamics in a low dimensional subspace of the data. The approaches effectively distill latent dynamic features from the data for easy interpretation, prediction, and visualization. An industrial case study is presented to illustrate how these latent dynamic analytics extract important features for process troubleshooting and monitoring.

VI161-03
Industrial Data Science and Machine Learning Applications	Invited Session
Chair: He, Qinghua (Peter)	Auburn University
Co-Chair: Qin, S. Joe	University of Southern California
Organizer: He, Qinghua (Peter)	Auburn University
Organizer: Qin, S. Joe	University of Southern California
Organizer: Flores-Cerrillo, Jesus	Linde
Paper VI161-03.1
PDF · Video · Platforms for Automatic PAT Soft Sensor Development and Analysis (I)
Seabra dos Reis, Marco P.	University of Coimbra
Rato, Tiago	University of Coimbra
Keywords: Process modeling and identification, Monitoring of product quality and control performance, Data mining and multivariate statistics Abstract: The performance of soft sensors from spectroscopic Process Analytical Technology data is directly related to the type of modelling methodology and preprocessing technique used during model development. However, their selection is often decoupled and based on simple trial and error procedures. Furthermore, the current modelling methodologies focus solely on selecting the most informative wavebands and do not attempt to enhance the prediction capabilities within each waveband. To overcome these limitations, two frameworks have been proposed for (i) optimal feature selection and (ii) systematic comparison of multiple combinations of modelling methodologies and preprocessing techniques: MR-SS and SS-DAC. The Multiresolution Soft Sensor (MR-SS) optimizes the resolution of each waveband by spectral aggregation, generally leading to models with superior performance than their single-resolution counterparts of the same model class. The Soft Sensor Development, Assessment and Comparison (SS-DAC) framework, selects the best combination of modelling methodologies and preprocessing techniques by use of structured randomization and rigorous statistical analysis of the overall prediction merits of the different models. The analytical and predictive merits of these two proposed methodologies are illustrated on a case study of real near infrared (NIR) spectra.
Paper VI161-03.2
PDF · Video · Data Science Challenges in Chemical Manufacturing (I)
Braun, Birgit	Dow
Castillo, Ivan	The Dow Chemical Company
Joswiak, Mark	Dow
Peng, You	Dow
Rendall, Ricardo	Dow
Schmidt, Alix	Dow
Wang, Zhenyu	Tufts University
Chiang, Leo	The Dow Chemical Company
Colegrove, Brenda	Dow
Keywords: Data mining and multivariate statistics Abstract: Industrial processes are ripe with data and offer countless opportunities for applied data science, machine learning and artificial intelligence. While process automation and control are providing more guidance in normal operating states, the need for data analytics is abundant when dealing with deviations from defined states, aiming at consistent transitions, or exploring new operating states to optimize production. This paper provides a brief overview of some examples, and introduces a real-life case study available to educators to challenge engineering students in preparation for roles in the chemical industry.
Paper VI161-03.3
PDF · Video · Improving Featured-Based Soft Sensing through Feature Selection (I)
Lee, Jangwon	Auburn University
Wang, Jin	Auburn University
Flores-Cerrillo, Jesus	Linde
He, Qinghua (Peter)	Auburn University
Keywords: Process modeling and identification, Estimation and fault detection, Industrial applications of process control Abstract: Driven by the expanding applications of spectroscopic technologies, many advancements have been reported for soft sensor modeling, which infers a sample’s properties from its spectroscopic readings. Because the number of wavelengths contained in a sample spectrum is usually much larger than the number of samples, "curse-of-dimensionality" is a common challenge that would affect the predictive power of the soft sensor. This challenge could be alleviated through variable selection. However, there is no guarantee that the truly relevant variables would be selected, and the selected variables are often (very) sensitive to the choice of training and validation data. To help address this challenge, we have developed a feature-based soft sensing approach by adapting the statistics pattern analysis (SPA) framework. In the SPA feature-based soft sensing, the features extracted from different segments of the complete spectrum were utilized to build the model. In this way, the information contained in the whole spectrum is used to build the model, while the number of the variables is significantly reduced. In this work, by integrating a novel variable selection approach we developed recently with the SPA feature-based soft sensor, we not only further improve the soft sensor’s prediction performance, but also identify the key underlying chemical information from spectroscopic data. The performance of the improved feature-based soft sensing approach, termed SPA-CEEVS, is demonstrated using two NIR datasets, and compared with several best performing soft sensing approaches.
Paper VI161-03.4
PDF · Video · Abnormal Condition Prediction Via Adaptive Deep Learning for Fused Magnesium Furnaces (I)
Gaochang, Wu	Northeastern University
Chai, Tianyou	Northeastern Univ
Wu, Zhiwei	Northeastern University
Keywords: Methods based on neural networks and/or fuzzy logic for FDI Abstract: Fused magnesium furnace (FMF) is the main equipment for producing fused magnesia, which heats and melts the powdered raw materials through electrical arc. Caused by the low-grade, complex mineral composition and large variations in the composition, the optimal setting value of the melting current in a FMF will change dynamically with the melting process and the feeding of the raw materials, leading to semi-molten abnormal condition. The main challenge of semi-molten condition prediction lies in the representation of dynamic features, that is, the network is trained and tested in the same operation state. In this paper, we overcome this challenge within a novel deep learning framework for the prediction of semi-molten condition using video data from an in-situ industrial camera. Specifically, an adaptive deep learning framework is developed mimicking the adaptive concept in control theory. Different from the fixed parameters in the commonly-used deep neural network, the proposed framework continuously updates the network parameters with newly collected data that reflects the condition features after the transference. The framework is composed of two sets of neural networks: an upper neural network that learns an initial set of parameters (weight and bias) from scratch by using the existing historical data, and continuously corrects the parameters by using the newly collected data based on the fine-tuning technique; a lower neural network receives the fine-tuned parameters from the upper network to keep the capability of representing dynamic features, and uses the real-time video stream to predict the semi-molten condition. By using image sequences from production processes of a real FMF, the proposed method is evaluated, and compared with other two baseline approaches based on deep learning techniques. The results show that the proposed method is effective and superior in forecasting advance and prediction accuracy.

VI161-04
Recent Progress in Explicit MPC Methods	Invited Session
Chair: Monnigmann, Martin	Ruhr-Universität Bochum
Co-Chair: Kvasnica, Michal	Slovak University of Technology in Bratislava
Organizer: Bhartiya, Sharad	IIT Bombay
Organizer: Kvasnica, Michal	Slovak University of Technology in Bratislava
Organizer: Monnigmann, Martin	Ruhr-Universität Bochum
Paper VI161-04.1
PDF · Video · Reducing the Computational Effort of MPC with Closed-Loop Optimal Sequences of Affine Laws (I)
Monnigmann, Martin	Ruhr-Universität Bochum
Pannocchia, Gabriele	University of Pisa
Keywords: Model predictive and optimization-based control, Real time optimization and control Abstract: We consider the classical infinite-horizon constrained linear-quadratic regulator (CLQR) problem and its receding-horizon variant used in model predictive control (MPC). If the terminal constraints are inactive for the current initial condition, the optimal input signal sequence that results for the open-loop CLQR problem is equal to the closed-loop optimal sequence that results for MPC. Consequently, the closed-loop optimal solution is available from solving only one CLQR problem instead of the usual infinite number of CLQR problems solved on the receding horizon. In the presence of disturbances or because of plant-model mismatch, the system will eventually leave the predicted optimal trajectory. Consequently, the solution of the single open-loop CLQR problem is no longer optimal, and the receding horizon problem must resume. We show, however, that the open-loop solution is also robust. Robustness essentially is given, because the solution of the CLQR problem not only provides the sequence of nominally optimal input signals, but a sequence of optimal affine laws along with their polytopes of validity. We analyze the degree of robustness by computational experiments. The results indicate the degree of robustness is practically relevant.
Paper VI161-04.2
PDF · Video · The Integration of Explicit MPC and ReLU Based Neural Networks (I)
Katz, Justin	Texas A&M University
Pappas, Iosif S.	Texas A&M University
Avraamidou, Styliani	Imperial College London
Pistikopoulos, Efstratios N.	Texas A&M University
Keywords: Neural networks in process control, Model predictive and optimization-based control, Advanced process control Abstract: Using neural networks to capture complex dynamics of highly nonlinear systems is a promising feature for advanced control applications. Recently it has been shown that ReLU based neural networks can be exactly recast in a mixed-integer linear programming formulation. This reformulation enables the incorporation of deep learning models in model predictive control strategies. To alleviate the computational burden of solving the piecewise linear optimization problem online, multiparametric programming is utilized to obtain the full, offline, explicit solution of the optimal control problem. In this work, a strategy is presented for the integration of deep learning models, specifically neural networks with rectified linear units, and explicit model predictive control. The proposed strategy is demonstrated on the advanced control of the ACUREX solar field.
Paper VI161-04.3
PDF · Video · Accelerating Explicit Model Predictive Control by Constraint Sorting (I)
Holaza, Juraj	Slovak University of Technology in Bratislava
Oravec, Juraj	FCFT, STU in Bratislava
Kvasnica, Michal	Slovak University of Technology in Bratislava
Dyrska, Raphael	Ruhr-Universität Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Fikar, Miroslav	Slovak University of Technology in Bratislava
Keywords: Model predictive and optimization-based control, Real time optimization and control, Advanced control technology Abstract: Explicit MPC represents one of the fastest ways of real-time MPC implementation. As the explicit MPC policy is optimization-free in real-time control, its efficiency is determined by solving a point location problem. This paper proposes the novel concept of accelerating explicit MPC that significantly speeds up the real-time evaluation of the point location problem. The introduced strategy has two layers: (i) an offline phase determines a smart order of the regions to be explored, and (ii) an online phase removes further regions to be explored on the fly based on the current value of the value function. The main advantage of layer (i) is that the order is evaluated offline, therefore, it does not increase the real-time implementation of explicit MPC. The implementation of layer (ii) slightly increases the real-time evaluation but leads to further speed-up of the point location problem. As the proposed layers are based just on the evaluation of some appropriate value function, the main benefit is that these layers are fully applicable also for higher-dimensional systems. Although the accelerated explicit MPC variant does not reduce the worst-case time of solving the point location problem, an extensive case study demonstrates the efficiency of the proposed strategy.
Paper VI161-04.4
PDF · Video · A Neural Network Architecture to Learn Explicit MPC Controllers from Data (I)
Maddalena, Emilio Tanowe	école Polytechnique Fédérale De Lausanne
da Silva Moraes, Caio Guilherme	Federal University of Santa Catarina
Waltrich, Gierri	Federal University of Santa Catarina
Jones, Colin N.	Ecole Polytechnique Federale De Lausanne (EPFL)
Keywords: Model predictive and optimization-based control, Methods based on neural networks and/or fuzzy logic for FDI, Application of power electronics Abstract: We present a methodology to learn explicit Model Predictive Control (eMPC) laws from sample data points with tunable complexity. The learning process is cast in a special Neural Network setting where the coefficients of two linear layers and a parametric quadratic program (pQP) implicit layer are optimized to fit the training data. Thanks to this formulation, powerful tools from the machine learning community can be exploited to speed up the off-line computations through high parallelization. The final controller can be deployed via low-complexity eMPC and the resulting closed-loop system can be certified for stability using existing tools available in the literature. A numerical example on the voltage-current regulation of a multicell DC-DC converter is provided, where the storage and on-line computational demands of the initial controller are drastically reduced with negligible performance impact.
Paper VI161-04.5
PDF · Video · Some Necessary and Sufficient Conditions for Correctness of Linear Machine in Presence of Numerical Errors (I)
Sharma, Aditi	Indian Institute of Technology, Bombay
Bhushan, Mani	Indian Institute of Technology Bombay
Keywords: Model predictive and optimization-based control Abstract: Linear machine (LM) has been recently proposed (Airan et al., 2017) for solving the point location problem which arises in explicit model predictive control (e-MPC). LM associates a linear discriminant function with each critical region identified in the offline phase in e-MPC. The solution to the online point location problem in the LM approach then simply corresponds to the region whose discriminant function attains the largest value amongst all the discriminant functions. LM involves two steps: (i) identification of neighbouring critical regions, and (ii) finding the discriminant functions by writing constraints involving discriminant functions of neighbouring pairs of regions. Both these steps involve solving linear programming (LP) problems. Similar to any other optimization problem, the constraints of the LP are satisfied with some tolerances. Even though theoretically sound, the resulting LM may not accurately identify the critical region due to the numerical errors arising from these tolerances. In the current work, we identify some conditions which can be used as an aid by the user to judge the accuracy of LM results. In particular, we give a necessary condition for step (i) whose violation will yield incorrect misclassification for some point location problems. We also propose a sufficient condition whose satisfaction guarantees the accuracy of linear machine solution despite numerical errors which may have crept in during step (ii) of the LM design. This condition needs to be evaluated for each specified point during the point location phase. We illustrate these ideas on the well known quadruple tank system.
Paper VI161-04.6
PDF · Video · Multiparametric Nonlinear MPC: A Region Free Approach (I)
Mate, Sammayak	IIT Bombay
Bhartiya, Sharad	IIT Bombay
Nataraj, P.S.V.	Indian Inst. of Tech
Keywords: Model predictive and optimization-based control, Nonlinear process control, Advanced process control Abstract: Determination of active constraints forms an essential part of the multiparametric MPC approach for linear systems. An analysis of KKT conditions to identify active constraints provides piecewise affine control laws and their corresponding critical regions (CRs). However, an extension of multiparametric MPC for nonlinear systems requires overcoming significant challenges: predictions are nonlinear and so are constraints, in which case the MPC problems takes the form of a nonlinear program (NLP). Application of KKT conditions show that, in general, the MPC control law for nonlinear systems is piecewise, implicit, nonlinear function of the state. Moreover, the CRs have nonlinear boundaries. In this work, we propose an offline combinatorial approach to identify all active sets of constraints for the nonlinear MPC problem a priori. The offline approach uses implicit enumeration of the constraints based on feasibility of KKT conditions and a primal criteria. Thus, the offline step provides all the admissible CRs as well as the corresponding nonlinear system of KKT equations corresponding to each CR. The online MPC implementation uses a region-free approach, wherein the CR corresponding to the current state as well as the control action is determined by solving the nonlinear system of KKT equations online. The method is demonstrated using a numerical example from literature.
Paper VI161-04.7
PDF · Video · A Strategy for the Exact Solution of Multiparametric/Explicit Quadratically Constrained NMPC Problems (I)
Pappas, Iosif S.	Texas A&M University
Diangelakis, Nikolaos A.	Texas A&M University
Pistikopoulos, Efstratios N.	Texas A&M University
Keywords: Model predictive and optimization-based control, Real time optimization and control, Nonlinear process control Abstract: Multiparametric programming has proven to be an efficient strategy to alleviate the computational burden of solving model predictive control problems online. Recently, it has been shown that through a second-order Taylor approximation to the Basic Sensitivity Theorem, the exact solution of multiparametric/explicit quadratically constrained nonlinear model predictive control problems is enabled. As a result, the state space is nonlinearly partitioned, and the optimal control actions are expressed as nonlinear functions of the states of the system. In this work, an algorithm for the complete exploration of the parameter space and the derivation of the parametric solution of the aforementioned problem is provided. The proposed strategy is utilized to implicitly explore the parameter space by identifying the unique and optimal active sets which describe the parametric solution. The applicability of the presented methodology is demonstrated on a regulation problem of a nonisothermal continuously-stirred tank reactor near an unstable steady-state.
Paper VI161-04.8
PDF · Video · An Explicit Model Predictive Controller for Constrained Stochastic Linear Systems
Desimini, Riccardo	Politecnico Di Milano
Prandini, Maria	Politecnico Di Milano
Keywords: Robust control (linear case), Convex optimization, Parametric optimization Abstract: In this paper we introduce an explicit Model Predictive Controller (eMPC) for a linear system subject to an additive stochastic disturbance with bounded support. The finite horizon control problem that is solved to determine the eMPC consists in minimizing an average quadratic cost subject to robust linear constraints involving state and input. By resorting to a control law parametrization that is affine in the disturbance, the finite horizon control problem is reformulated as a convex quadratic optimization program and solved via multiparametric quadratic programming. The resulting eMPC is piecewise affine as a function of the state. The proposed approach is compared with an alternative min-max approach from the literature on a numerical example.

VI161-05
Control and Estimation of Particulate Processes	Open Invited Session
Chair: Palis, Stefan	University Magdeburg
Co-Chair: Kienle, Achim	University Magdeburg
Organizer: Palis, Stefan	University Magdeburg
Organizer: Kienle, Achim	University Magdeburg
Paper VI161-05.1
PDF · Video · Extremum Seeking Control for a Mass Structured Cell Population Balance Model in a Bioreactor (I)
Beniich, Nadia	Département De Mathématique, Faculté Des Sciences, El Jadida
Abouzaid, Bouchra	Département De Mathématique, Faculté Des Sciences, El Jadida
Dochain, Denis	Univ. Catholique De Louvain
Keywords: Control of particulate processes, Estimation and control in biological systems, Real time optimization and control Abstract: This paper is concerned with the design of an adaptive extremum seeking control scheme for a mass structured cell population balance model in a bioreactor. The feed substrate concentration is considered as the manipulated input to drive system states to the desired setpoints that maximize the value of an objective function of the cell density. We assume limited knowledge on the objective function and we use the substrate concentration measurements to estimate this function. We use the Lyapunov's stability theorem and a persistency of excitation condition to show that the proposed adaptive extremum seeking control achieves the exponential convergence to the desired set points. Numerical simulation has been performed to illustrate the performance of the proposed approach.
Paper VI161-05.2
PDF · Video · Lyapunov-Based Online Parameter Estimation for Continuous Fluidized Bed Layering Granulation (I)
Otto, Eric	Otto Von Guericke University Magdeburg
Neugebauer, Christoph	Otto Von Guericke University Magdeburg
Palis, Stefan	Otto Von Guericke University Magdeburg
Kienle, Achim	Otto Von Guericke University Magdeburg
Keywords: Process modeling and identification, Industrial applications of process control, Control of particulate processes Abstract: This paper is concerned with online parameter identification of milling behavior in fluidized bed layering granulation with external sieve-mill-cycle. A mill function is approximated with weighted Gaussian ansatz functions using a Lyapunov-based parameter estimation algorithm with a process model and plant data. The plant data is both generated by simulations and measured in experiments. In addition to previous work the asymptotic convergence of the parameter estimator is proven theoretically. The identified mill function is validated by simulation of the process. It is shown that the plant and the identified model are in good agreement near the desired steady state.
Paper VI161-05.3
PDF · Video · Modelling and Control of Particulate Systems - Three Industrial(ly Based) Case Studies (I)
Dochain, Denis	Univ. Catholique De Louvain
Casenave, Céline	INRA
Henri, Cedric	UCL
Noon, Leslie	UCL
Keywords: Control of particulate processes Abstract: This paper deals with the modelling and control application for three case studies of particulate systems: one agglomeration process (for anti-foam agents in washing machine soap), and two crystallization processes, one related to one ice-cream crystallization, the other related to the pharmaceutical industry.
Paper VI161-05.4
PDF · Video · Inferential Control of Product Properties for Fluidized Bed Spray Granulation Layering (I)
Dürr, Robert	Max Planck Institute for Dynamics of Complex Technical Systems
Neugebauer, Christoph	University of Magdeburg
Palis, Stefan	University Magdeburg
Bück, Andreas	Friedrich-Alexander University Erlangen-Nuremberg
Kienle, Achim	University Magdeburg
Keywords: Control of particulate processes, Estimation and fault detection, Process control applications Abstract: Fluidized bed layering granulation has found application in a wide range of industrial processes, e.g. food, pharmaceutical or fertilizer manufacturing. The quality of the produced granules is a critical factor for subsequent processing steps and depends on individual particle properties like characteristic size, porosity or mechanical stability. Therefore, these properties have to be monitored closely during the process to enable accurately timed intervention by plant operators or the application of suitable feedback control algorithms. In case certain properties are not measurable due to financial or technical limitations, observer techniques can fill the gap and provide reliable estimates for these properties. In this manuscript, observer design is demonstrated and validated for a fluidized bed layering granulation process model represented by a complex set of partial and ordinary differential equations. Furthermore, an inferential integral state feedback controller is designed and applied to the complex nonlinear model.
Paper VI161-05.5
PDF · Video · Numerical Gaussian Process Kalman Filtering (I)
Küper, Armin	KU Leuven
Waldherr, Steffen	KU Leuven
Keywords: Estimation and control in biological systems, Control of particulate processes Abstract: In this manuscript we introduce numerical Gaussian process Kalman filtering (GPKF). Numerical Gaussian processes have recently been developed to simulate spatiotemporal models. The contribution of this paper is to embed numerical Gaussian processes into the recursive Kalman filter equations. This embedding enables us to do Kalman filtering on infinite-dimensional systems using Gaussian processes. This is possible because i) we are obtaining a linear model from numerical Gaussian processes, and ii) the states of this model are by definition Gaussian distributed random variables. Convenient properties of the numerical GPKF are that no spatial discretization of the model is necessary, and manual setting up of the Kalman filter, that is fine-tuning the process and measurement noise levels by hand is not required, as they are learned online from the data stream. We showcase the capability of the numerical GPKF in a simulation study of the advection equation.
Paper VI161-05.6
PDF · Video · Robust Control of Fluidized Bed Layering Granulation (I)
Neugebauer, Christoph	Otto Von Guericke University Magdeburg
Seidel, Carsten	Otto Von Guericke University Magdeburg
Palis, Stefan	University Magdeburg
Kienle, Achim	University Magdeburg
Keywords: Control of particulate processes, Industrial applications of process control, Control of distributed systems Abstract: This contribution is concerned with control of fluidized bed layering granulation with external sieve-mill-cycle. It is well-known that this configuration is sensitive with respect to variations in the operating conditions and supplied material properties. Therefore, control is needed to achieve desired particle properties over a wide range of process conditions. In this contribution H_infty-control is applied in order to control the process. In contrast to preceding works, the coupling between the particle and the fluid phase is taken into account. Furthermore, in addition to the Sauter diameter of the particle size distribution, the apparent particle porosity is controlled, which is of great importance for practical applications.

VI161-06
Control and Operability of Intensified and Modular Industrial Manufacturing Systems	Open Invited Session
Chair: Pistikopoulos, Efstratios N.	Texas A&M University
Co-Chair: Bollas, George M.	University of Connecticut
Organizer: Pistikopoulos, Efstratios N.	Texas A&M University
Organizer: Bollas, George M.	University of Connecticut
Organizer: Baldea, Michael	The University of Texas at Austin
Organizer: Mitsos, Alexander	RWTH Aachen University
Paper VI161-06.1
PDF · Video · Nonlinear Model Predictive Control of the Hydraulic Fracturing Process (I)
Lin, Kuan-Han	Carnegie Mellon University
Eason, John	Carnegie Mellon University
Yu, Zhou (Joyce)	Carnegie Mellon University
Biegler, Lorenz T.	Carnegie Mellon Univ
Keywords: Model predictive and optimization-based control, Industrial applications of process control, Real time optimization and control Abstract: Hydraulic fracturing has drawn significant attention over the past decade, as it can recover crude oil and natural gas from shale deposits previously considered inaccessible, which brings considerable economic benefits. However, hazardous operating conditions of extremely high pressure and environmental concerns require us to control this process carefully. Unfortunately, nonhomogeneous rock properties make this process difficult to control. Therefore, an accurate dynamic model and a well-designed controller are needed. In this work, we use the well-known Perkins-Kern-Nordgren (PKN) model with reformulation to solve the moving boundary problem. Next, the process is controlled by a standard Nonlinear Model Predictive Controller (NMPC) and multistage NMPC. We find that the process performance deteriorates under the influence of uncertainty with standard NMPC. When we control the process with standard NMPC, the pressure violation happens in one of the parameter mismatch cases. Nonetheless, when we apply multistage NMPC and consider the uncertainty evolution with a scenario tree, no constraint violations occur for all cases for both time-invariant and time-varying uncertainties. We also discuss the computational performance of different robust horizons for multistage NMPC. Our results demonstrate that the multistage NMPC is a promising approach to handle uncertainty caused by nonhomogeneous rock properties in the hydraulic fracturing process.
Paper VI161-06.2
PDF · Video · Operability and Safety Considerations in Process Intensification (I)
Tian, Yuhe	Texas A&M University
Pistikopoulos, Efstratios N.	Texas A&M University
Keywords: Interaction between design and control, Model predictive and optimization-based control, Process control applications Abstract: The importance of considering operability, control, and safety criteria in the analysis and design of process intensification configurations is discussed in this paper. We first rigorously analyze the loss of degrees of freedom and role of constraints in intensified systems comparing with their conventional process counterparts. A comparison study on inherent safety metrics in reactive distillation process is then presented to stress the need for new safety metrics at early design stage. To address these operability and safety challenges, we highlight a framework for systematic integration of operability, safety, and control to synthesize operable process intensification systems.
Paper VI161-06.3
PDF · Video · Sensor Network Design for Smart Manufacturing - Application on Precision Machining (I)
Awasthi, Utsav	University of Connecticut
Bollas, George M.	University of Connecticut
Keywords: Condition Monitoring, FDI based on qualitative models, Parameter estimation based methods for FDI Abstract: Energy consumption in a manufacturing facility comprises direct energy used in the manufacturing operations and indirect energy consumed by activities to maintain proper equipment conditions (e.g., heating and cooling). Reducing the energy consumption in a manufacturing facility requires sensors to monitor the energy usage patterns ("energy profiles") and a concomitant data analytics process for correlating them with the activities being performed. This work explores the design and integration of optimal sensor networks for measuring and identifying the context of energy usage in manufacturing processes. This information is useful in production planning and scheduling to optimize energy usage and reduce energy cost. We explore a system-level representation of precision machining for optimal sensor locations and types that allow the monitoring of energy consumption. This is accomplished through maximization of a measure of the information matrix, subject to constraints on the cost of sensors. First, a system-level model is presented for predicting energy consumption in precision machining. A formulation is then presented for the selection of sensors and the operating mode for maintenance tests in manufacturing. The sensor network design is cast as a mixed-integer non-linear program that selects possible sensors based on their contribution to information gain with respect to energy consumption and their impact on equipment cost. For this purpose, we explore the sensitivity of the machining process with respect to admissible inputs at different system fault scenarios.
Paper VI161-06.4
PDF · Video · Symbolic Regression of Uncertainty-Resilient Inferential Sensors for Fault Diagnostics (I)
Hale, William	University of Connecticut
Bollas, George M.	University of Connecticut
Keywords: AI methods for FDI, Active Fault Diagnosis, FDI based on qualitative models Abstract: An algorithm is presented for the design of inferential sensors for fault diagnostics in thermal management systems. The algorithm uses input and output sensed system information to improve the detection and isolation of a fault by generating inferential sensors that augment the measured information to: (i) reduce the evidence of uncertainty in the inferred variables, and thus decrease false alarm and nondetection rates; and (ii) provide distinguishable responses to faults, and thus reduce reduce the rate of misdiagnoses. The novelty of the algorithm is its use of genetic programming to evolve explainable inferential sensors that maximize information criteria specific to fault diagnostics. The chosen criteria: (i) least squares regression; and (ii) Ds-optimality (calculated from the Fisher Information Matrix), leverage symbolic mathematics and automatic differentiation to obtain parametric sensitivities of the measured outputs and inferential sensors. The algorithm is included in a standard work for fault diagnostics, where its effectiveness is assessed through k-NN classification and illustrated in an application to an aircraft cross-flow plate-fin heat exchanger.
Paper VI161-06.5
PDF · Video · Production Scheduling of Supply Chains Comprised of Modular Production Units (I)
Allen, R. Cory	Texas A&M Energy Institute
Avraamidou, Styliani	Texas A&M University
Pistikopoulos, Efstratios N.	Texas A&M University
Keywords: Industrial applications of process control, Control and optimization of supply chains Abstract: In this work, we introduce a mixed-integer linear programming (MILP) formulation to determine the optimal production schedule of a supply chain network with production facilities comprised of transportable modular production units. The problem is solved in a rolling horizon fashion, which allows for rapid changes in raw material availabilities and product demands. The effectiveness of our methodology is illustrated through the use of a circular supply chain case study. The case study is centered in the Permian Basin and focuses on a set of wastewater treatment facilities comprised of modular processing units. The results illustrate the benefits of utilizing production facilities comprised of modular production units operating in parallel, wastewater storage units, and fresh water storage units.
Paper VI161-06.6
PDF · Video · Closed-Loop Real-Time Supply Chain Management for Perishable Products (I)
Lejarza, Fernando	The University of Texas at Austin
Baldea, Michael	The University of Texas at Austin
Keywords: Control and optimization of supply chains, Real time optimization and control, Model predictive and optimization-based control Abstract: Supply chain networks are dynamical systems with particular control challenges that stem from inventory deterioration and external disturbances (i.e., unanticipated consumer demand, time delays, etc.). For industries handling highly perishable inventory (e.g, fresh produce, vaccines, biologics) controlling product quality throughout the multiple echelons of the supply chain is critical to minimize inventory waste and satisfy consumer quality requirements. However, quality, as a function of time and environmental conditions (i.e., temperature, humidity, light, etc.), is difficult to model accurately resulting in unpredicted inventory spoilage. In this paper we demonstrate a novel closed-loop, feedback-based control framework that employs real-time product quality measurements for optimal supply chain management. A moving horizon approach is used to periodically update decisions (i.e., production, transportation, storage, and respective environmental conditions) based on fed-back information. We demonstrate that the postulated feedback controller effectively stabilizes the supply chain dynamics, while minimizing costs. An illustrative case study is provided.

VI161-07
Processes Control with Tomographic Sensors	Open Invited Session
Chair: Hampel, Uwe	Helmholtz-Zentrum Dresden-Rossendorf
Co-Chair: Hlava, Jaroslav	Faculty of Mechatronics, Technical University of Liberec
Organizer: Hampel, Uwe	Helmholtz-Zentrum Dresden-Rossendorf
Organizer: Hlava, Jaroslav	Faculty of Mechatronics, Technical University of Liberec
Paper VI161-07.1
PDF · Video · Two Camera 3D Time Series Reconstruction of a Mesh Subjected to Differential Excitation (I)
Goh, Michael Joon Seng	Monash University Malaysia
Chiew, Yeong Shiong	Monash University
Foo, Ji Jinn	Monash University Malaysia
Keywords: Process control applications, Measurement and instrumentation, Advanced control technology Abstract: The present study proposes a novel bio-inspired scheme for the 3D time series reconstruction of a Mesh. The key motivation of this study is to develop a cost effective and accessible system without compromising capabilities for the fundamental understanding in complicated external stimuli-induced vibration of a Mesh. A bio-inspired algorithm traces along the strands of the mesh to match a known control point to the next keypoint until the entire surface is matched for the critical reconstruction at the first frame/timestep. The match is then disseminated to the subsequent frames steps via digital image correlation and photogrammetric methods applied to effectively recover the time series response of the dynamic surface. This study offers significant and quantitative insight into the vibration and fluctuation of the entire excited surface. A 160mm×160mm mesh fluctuation is successfully re-constructing with a sampling density of approximately 1600 points at 24 frames per second. The proof-of-concept experiment was able to detect the undulation of mesh under an in-phase and an out-of-phase excitation, which result in the reconstruction of the point cloud with a 0.38mm error, as well as the frequency and phase angle accuracy attainments of about 99.1% and 86.0%, respectively. In short, the current reconstruction scheme may provide insights into the control and response of a piezoelectric mesh.
Paper VI161-07.2
PDF · Video · LQR Control of Moisture Distribution in Microwave Drying Process Based on a Finite Element Model of Parabolic PDEs (I)
Hosseini, Marzieh	University of Eastern Finland
Kaasinen, Anna	University of Eastern Finland
Link, Guido	Karlsruhe Institute of Technology
Lähivaara, Timo	University of Eastern Finland
Vauhkonen, Marko	University of Eastern Finland
Keywords: Control of large-scale systems, Advanced process control Abstract: The microwave drying process is a widely used technology in the drying of porous dielectric materials. Designing a controller for moisture distribution in this process can improve product quality and reduce energy consumption and production time. In this paper, a model-based controller for moisture distribution in an industrial microwave drying process is developed. The moisture and temperature in this process are described by a pair of partial differential equations (PDEs) and have both temporal and spatial variations. In this view, using a semi-discrete finite element approximation, the coupled system of PDEs is transformed into a system of ordinary differential equations (ODEs). Based on the discretized ODEs, a linear quadratic regulator (LQR) controller is designed to determine the power levels of multiple microwave sources in this process to reach and maintain the desired moisture level. Numerical simulations are carried out in three different drying scenarios. The results show that the proposed controller achieves a very good performance in tracking the desired moisture level.
Paper VI161-07.3
PDF · Video · Flow Monitoring for Continuous Steel Casting Using Contactless Inductive Flow Tomography (CIFT) (I)
Glavinic, Ivan	Helmholtz-Zentrum Dresden-Rossendorf
Ratajczak, Matthias	Helmholtz-Zentrum Dresden-Rossendorf
Stefani, Frank	Helmholtz-Zentrum Dresden-Rossendorf
Wondrak, Thomas	Helmholtz-Zentrum Dresden Rossendorf
Keywords: Process control applications, Measurement and instrumentation Abstract: The control of the liquid steel flow in the mould of a continuous caster based on real time flow measurements is a challenging task due to the lack of appropriate measurement techniques. The opaqueness, the high temperature of 1500 C and the chemical aggressiveness of the melt require non-optical contactless methods. In order to reconstruct the complex flow structure in the mould the Contactless Inductive Flow Tomography (CIFT) is a promising candidate, since it allows the visualization of the flow structure in the melt by applying a magnetic field to the melt, measuring the flow induced perturbation of that field and solving subsequently a linear inverse problem. The combination of this new measurement technique with typical electromagnetic actuators like electromagnetic brakes used in continuous casting pose a challenge to the CIFT measurement system, because the flow induced magnetic field is in the range of 100 nT and has to be measured robustly on the background of the static magnetic field with the amplitude of 300 mT generated by the brake. In this work we will show recent developments regarding this topic for a small model of a continuous caster in the lab. Furthermore, we will present a new method on how the complex linear inverse problem can be solved in real time providing a time resolution of about 1 Hz.
Paper VI161-07.4
PDF · Video · Control of a Gas-Liquid Inline Swirl Separator Based on Tomographic Measurements (I)
Garcia, Matheus	Delft University of Technology
Sahovic, Benjamin	Helmholtz-Zentrum Dresden-Rossendorf
Sattar, Muhammad Awais	Lodz University of Technology
Atmani, Hanane	Institut De Mecanique Des Fluides De Toulouse (IMFT/INPT)
Schleicher, Eckhard	HZDR
Hampel, Uwe	Helmholtz-Zentrum Dresden-Rossendorf
Babout, Laurent	Lodz University of Technology
Legendre, Dominique	Toulouse INP
Portela, Luis M	Delft University of Technology
Keywords: Process modeling and identification, Real time optimization and control, Model predictive and optimization-based control Abstract: This text structures the application of Wire-Mesh sensors and Electrical Resistance Tomography in the control of an Inline Swirl Separator. It introduces a mechanistic model of the two-phase flow inside the device, which is linearized around an ideal perfect operation, and implemented in a Model Predictive Controller. The whole text is structured aiming at a future real application of the controller, briefly introducing the setup that is going to be used, the sensors and their working principles. The results obtained show a stable controller, able to regulate the process relatively fast in relation to the time resolution of the sensors. The positive response of the approach stimulates further improvements in the model developed, and the implementation of more sophisticated techniques to handle the non-linearities of the process.
Paper VI161-07.5
PDF · Video · Switched MPC Based on Clogging Detection in Continuous Casting Process (I)
Abouelazayem, Shereen	Technical University of Liberec
Glavinic, Ivan	Helmholtz-Zentrum Dresden-Rossendorf
Wondrak, Thomas	Helmholtz-Zentrum Dresden Rossendorf
Hlava, Jaroslav	Faculty of Mechatronics, Technical University of Liberec
Keywords: Industrial applications of process control, Process modeling and identification, Model predictive and optimization-based control Abstract: Nozzle clogging contributes heavily to quality issues seen during the process of continuous casting. The presence of clogging in the Submerged Entry Nozzle (SEN) can significantly change the flow patterns in the mould and therefore impact the quality of the steel product. Also, there is a high risk of inclusions due to parts of the clogging material breaking off and entering the mould. In this paper, we propose a new sensor setup that allows us to detect clogging in the SEN by monitoring the angle of the exiting jet. Based on this clog detection setup, a switched MPC controller is used to keep the angle of the exiting jet between the optimum ranges using an Electromagnetic Brake. This allows the controller to keep the angle of the jet in the optimum range even when clogging occurs in the nozzle. Experimental data from a laboratory scale continuous caster is used to derive the models for the controller.
Paper VI161-07.6
PDF · Video · Image Reconstruction in Electrical Impedance Tomography Via Artificial Neural Network in Two-Phase Flow (I)
Tanaka, Koji	Chiba University
Takakura, Yuya	Chiba University
Sejati, Prima Asmara	Chiba University
Kawashima, Daisuke	Chiba University
Takei, Masahiro	Chiba University
Keywords: Process control applications, Measurement and instrumentation, Advanced process control Abstract: Electrical impedance tomography (EIT) technology is an image reconstruction technique based on the difference of electrical characteristics inside the measurement domain. The EIT is used in industrial applications such as gas distribution detection and mean gas void fraction estimation of two-phase flow in pipes. The most challenging in EIT is to solve nonlinear and ill-posed inverse problems. In the present study, the inverse problem is solved using an artificial neural network (ANN). ANN is trained using the current vector measured by the voltage-current (VC) system. As a result, the proposed ANN shows a highly accurate image reconstruction as compared with the conventional method such as linear approximation and versatile applicability.

VI161-08
Thermodynamics and Control	Open Invited Session
Chair: Hudon, Nicolas	Queen's University
Co-Chair: Ramirez, Hector	Universidad Federico Santa Maria
Organizer: Hudon, Nicolas	Queen's University
Organizer: Ramirez, Hector	Universidad Federico Santa Maria
Organizer: Dochain, Denis	Univ. Catholique De Louvain
Organizer: Maschke, Bernhard	Univ Claude Bernard of Lyon
Organizer: van der Schaft, Arjan J.	Univ. of Groningen
Paper VI161-08.1
PDF · Video · Disturbance Attenuation Via Nonlinear Feedback for Chemical Reaction Networks (I)
Marton, Lorinc	Sapientia University
Hangos, Katalin M.	Computer and Automation Research Institute HAS
Szederkenyi, Gabor	Computer and Automation Research Institute, Hungarian
Keywords: Nonlinear process control, Advanced control technology, Process control applications Abstract: This paper deals with the setpoint control of Chemical Reaction Networks (CRNs) in the presence of disturbances. The addressed control problem is traced back to the output feedback-based stabilization of passive systems. First, the passivity properties of complex balanced CRNs are discussed. Second, it is shown that, by combining the kinetic feedback based control with the passivity theory-based output feedback approach, arbitrary disturbance attenuation in controlled CRNs can be achieved. A case study is provided to demonstrate the applicability of the proposed control design approach.
Paper VI161-08.2
PDF · Video · Modelling the 1D Piston Problem As Interconnected Port-Hamiltonian Systems (I)
Treton, Anne-Sophie	ISAE-SUPAERO
Haine, Ghislain	Institut Superieur De l’Aeronautique Et De L’Espace
Matignon, Denis	ISAE
Keywords: Control of distributed systems, Identification and modelling Abstract: In this study, the modelling of the boundary-controlled 1D piston problem as the interconnection of simpler port-Hamiltonian systems (pHs) is addressed. More precisely, two viscous compressible fluids are separated by a moving rigid body on a bounded domain (0, L). Thermodynamics is taken into account, leading to two pHs for each physical domain: one associated to the kinetic energy and the other one to the internal energy. No chemical reaction is being considered in the system. A control by mass injection/rejection and heating is then applied at the left end of the first fluid.
Paper VI161-08.3
PDF · Video · Lyapunov Function Partial Differential Equations for Stability Analysis of a Class of Chemical Reaction Networks (I)
Wu, Shan	Zhejiang University
Lu, Yafei	Zhejiang University
Gao, Chuanhou	Zhejiang University
Keywords: Nonlinear process control, Process modeling and identification Abstract: We investigate a broad family of chemical reaction networks (CRNs) assigned with mass action kinetics, called complex-balanced-produced-CRNs (CBP-CRNs), which are generated by any given complex balanced mass action system (MAS) and whose structures depend on the selection of producing matrices. Unluckily, the generally applied pseudoHelmholtz free energy function may fail to act as a Lyapunov function for the CBP-CRNs. Inspired by the method of Lyapunov function partial differential equations (PDEs), we construct one solution of their corresponding Lyapunov function PDEs, termed as the generalized pseudoHelmholtz free energy function, and further show that solution can behave as a Lyapunov function to render the asymptotic stability for the CBP-CRNs. This work can be taken as an argument of the conjecture that Lyapunov function PDEs approach can serve for any MAS.
Paper VI161-08.4
PDF · Video · Reducing Dynamics (I)
Grmela, Miroslav	Ecole Polytechnique De Montreal
Pavelka, Michal	Charles University
Keywords: Nonlinear model reduction, Control of multi-scale systems Abstract: Reduction of a dynamical theory consists of two steps: (i) finding its phase portrait (collection of all trajectories), and (ii) recognizing in it a pattern that is then identified with the phase portrait of the reduced dynamical theory. The original dynamical system becomes split in the reduction into the reduced dynamics representing the recognized pattern and the reducing dynamics representing the process of its emergence. From the experimental point of view, the reducing dynamics represents the process of preparing macroscopic systems for using the reduced description.
Paper VI161-08.5
PDF · Video · Robust Control of a Class of Bilinear Systems by Forwarding: Application to Counter Current Heat Exchanger (I)
Zitte, Bertrand David	Université Claude Bernard Lyon 1, LAGEP UMR 5007
Hamroun, Boussad	Univ Lyon, Université Claude Bernard Lyon 1, CNRS, LAGEP UMR 500
Astolfi, Daniele	CNRS - Univ Lyon 1
Couenne, Francoise	Univ Lyon, Université Claude Bernard Lyon 1
Keywords: Nonlinear process control, Process control applications, Control system design Abstract: In this paper we propose a control for the counter-current heat exchanger. By using energy balance equations, we propose a model in structured bilinear system that allows to capture the heat transfer and convection phenomena. We study the problem of regulating the output temperature of the cold (or hot) fluid by controlling the flowing velocity of the hot (or cold) fluid. Using an integral action and a forwarding based control method, we derive a non linear control which achieve output regulation, robustly with respect to model parameter uncertainties. Numerical simulations confirms the effectiveness of the proposed control.
Paper VI161-08.6
PDF · Video · About Dissipative and Pseudo Port-Hamiltonian Formulations of Irreversible Newtonian Compressible Flows (I)
Mora, Luis A.	Universidad Técnica Federico Santa María
Le Gorrec, Yann	FEMTO-ST, ENSMM
Matignon, Denis	ISAE
Ramirez, Hector	Universidad Federico Santa Maria
Yuz, Juan I.	Universidad Técnica Federico Santa María
Keywords: Process modeling and identification, Modeling and simulation of power systems Abstract: In this paper we consider the physical-based modeling of 3D and 2D Newtonian fluids including thermal effects in order to cope with the first and second principles of thermodynamics. To describe the energy fluxes of non-isentropic fluids we propose a pseudo port-Hamiltonian formulation, which includes the rate of irreversible entropy creation by heat flux. For isentropic fluids, the conversion of kinetic energy into heat by viscous friction is considered as an energy dissipation associated with the rotation and compression of the fluid. Then, a dissipative port-Hamiltonian formulation is derived for this class of fluids. In the 2D case we modify the vorticity operators in order to preserve the structure of the proposed models. Moreover, we show that a description for inviscid or irrotational fluids can be derived from the proposed models under the corresponding assumptions leading to a pseudo or dissipative port-Hamiltonian structures.
Paper VI161-08.7
PDF · Video · Control of Reaction Systems Using Decoupled Dynamics Via Perturbed Hamiltonian Formulation (I)
Nguyen, Thanh Sang	University Malaya
Tan, Chee Keong	University of Malaya
Hoang, Ngoc Ha	Univ. of Technology (VNU-HCM) and Univ. Cath. De Louvain (Belgiu
Azlan Hussain, Mohd	University of Malaya
Keywords: Nonlinear process control, Advanced control technology, Process control applications Abstract: This work proposes a novel control strategy to stabilize the dynamics of a homogenous reactor, described by the extents of reaction and inlet streams with the inclusion of heat balance. Specifically, we formulate this transformed model into a perturbed Port-Hamiltonian (PH) structure, where the vector of reaction rates is expressed as a matched/unmatched and time-varying disturbance. Then, together with the tracking-error-based control method for the stabilization, two different configurations to compensate such disturbance, including a feed-forward law and a dynamic feedback one, are designed such that the error system asymptotically converges to the setpoint and preserves the PH representation by assigning an appropriate damping injection. A complex reaction system is used to illustrate the approach.
Paper VI161-08.8
PDF · Video · Stability Analysis of Thermodynamic Systems: Heat Conduction in Solids (I)
Lou, Daming	Eindhoven University of Technology
Weiland, Siep	Eindhoven Univ. of Tech
Keywords: Interaction between design and control, Nonlinear process control, Process control applications Abstract: This paper addresses the fundamental difference between equilibria of thermodynamic systems and equilibria of autonomous state space systems. The notion of stability of thermodynamic equilibria is analyzed in terms of an entropy generating function that classifies as a Lyapunov function to prove asymptotic stability of thermal equilibria. The stability analysis is performed for both finite and infinite dimensional systems. It is shown how the proposed Lyapunov function naturally extends to assess stability of interconnected thermal systems. A number of examples is given to demonstrate the time evolution of the Lyapunov function.
Paper VI161-08.9
PDF · Video · Energy Shaping Plus Damping Injection of Irreversible Port Hamiltonian Systems (I)
Villalobos, Ignacio	Universidad Técnica Federico Santa María
Ramirez, Hector	Universidad Federico Santa Maria
Le Gorrec, Yann	FEMTO-ST, ENSMM
Keywords: Nonlinear process control, Process control applications Abstract: Irreversible port-Hamiltonian systems (IPHS) are an extension of port-Hamiltonian systems (PHS) for irreversible thermodynamics which encompass a large class of thermodynamic systems that may contain reversible and irreversible phenomena. Energy shaping and damping injection are standard structure preserving passivity based control approaches which have proven to be very successful for the stabilization of PHS. However in the case of irreversible thermodynamics, the non-linear nature of the systems makes it non-trivial to apply these approaches for stabilization. In this paper we propose a systematic procedure to perform, in a first control loop, energy shaping by control by state modulated interconnection with a controller in IPHS form. Then, a second control loop guarantees asymptotic stability by the feedback of a new closed-loop passive output. The approach allows to stabilize IPHS while preserving the IPHS structure in closed-loop, allowing to interpret the closed-loop system as a desired thermodynamic system. The example of the continuous stirred tank reactor is used to illustrate the approach.

VI161-09
Predictive and Optimization-Based Control for Chemical Processes	Regular Session
Chair: Pannocchia, Gabriele	University of Pisa
Co-Chair: Streif, Stefan	Technische Universität Chemnitz
Paper VI161-09.1
PDF · Video · Implementation of an Industry 4.0 System to Optimally Manage Chemical Plant Operation
Vaccari, Marco	University of Pisa
Bacci di Capaci, Riccardo	University of Pisa
Brunazzi, Elisabetta	Department of Industrial and Civil Engineering (DICI), Universit
Tognotti, Leonardo	University of Pisa
Pierno, Paolo	Altair Chimica SpA
Vagheggi, Roberto	Altair Chimica Spa
Pannocchia, Gabriele	University of Pisa
Keywords: Control and optimization of supply chains, Process optimisation, Model predictive and optimization-based control Abstract: The evolution of the process industry in the direction of automation and digitalization is nowadays a consolidated phenomenon. In this direction, Industry 4.0 paradigms are leading many industrial companies to significantly update their facilities. This paper presents a scheduling algorithm that takes the role of a real-time optimization (RTO) element in a larger project framework where the various network components are aimed to be all highly interconnected. The proposed methodology is applied to an Italian chemical industrial site, in order to best manage the production rates of the various products and the sales plan for the different clients. Numerous plants and processes are considered into the model: batch and continuous production lines, saleable and non-storable products. Concepts of linear optimization and batch operation scheduling are used in the algorithm construction. This whole structure lays the foundation for a full integration between different elements of the facility, that is, the control systems and the selling department.
Paper VI161-09.2
PDF · Video · On the Implementation of Nonlinear Model Predictive Control for Simultaneous Design and Control Using a Back-Off Approach
Palma-Flores, Oscar	University of Waterloo
Rafiei, Mina	University of Waterloo
Ricardez-Sandoval, Luis	University of Waterloo
Keywords: Interaction between design and control, Model predictive and optimization-based control, Process optimisation Abstract: In the present work, we investigate the challenges and limitations of the incorporation of nonlinear model predictive control (NMPC) for the integration of design and control of chemical processes. To tackle this problem, we implemented a simultaneous methodology based on a back-off approach, in which the process design moves away from the optimal steady-state to a new dynamically feasible operating condition under process disturbances. The procedure is formulated as a series of bounded optimization problems in a sequential manner to identify the optimal design of the process with optimal control performance. Power series expansion (PSE) is used to represent constraints and cost functions in the bounded optimization problems. The approach has been implemented on a wastewater treatment plant. Results indicate that the proposed methodology leads to considerable improvement in the process economics and performance compared to a decentralized PI control strategy.
Paper VI161-09.3
PDF · Video · A Hierarchical Architecture for the Coordination of an Ensemble of Steam Generators
Spinelli, Stefano	CNR, Politecnico Di Milano
Longoni, Elia	Politecnico Di Milano
Farina, Marcello	Politecnico Di Milano
Petzke, Felix	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Ballarino, Andrea	Consiglio Nazionale Delle Ricerche - Istituto Di Sistemi E Tecno
Keywords: Model predictive and optimization-based control, Control of large-scale systems, Control of multi-scale systems Abstract: This work presents a hierarchical architecture for the optimal management of an ensemble of steam generators, which needs to jointly sustain a common load. The coordination of independent subsystems is provided by a multi-layer control scheme. A high-level optimizer computes the optimal shares of production to be allocated to single generators. At medium level, a robust tube-based model predictive control (MPC) is proposed to track the time-varying demand of the ensemble using a centralized, but aggregated model, whose order does not scale with the number of subsystems. At low level, decentralized controllers are in place to stabilize the internal boiler pressure. The control architecture enables the dynamic modification of the ensemble configuration and plug and play operations. Simulation results are reported to demonstrate the potentialities of the proposed approach.
Paper VI161-09.4
PDF · Video · A Simplified Implementation of Tube-Enhanced Multi-Stage NMPC
Abdelsalam, Yehia	Technical University of Dortmund (TU Dortmund)
Subramanian, Sankaranarayanan	TU Dortmund
Engell, Sebastian	TU Dortmund
Keywords: Model predictive and optimization-based control, Nonlinear process control, Real time optimization and control Abstract: In a previous work, multi-stage NMPC and tube-based NMPC schemes were combined into a single framework called tube-enhanced multi-stage NMPC with the goal of achieving an improved trade-off between simplicity and performance. In tube-enhanced multi-stage NMPC, the large uncertainties are handled using a multi-stage primary controller and the small uncertainties are handled using a multi-stage ancillary controller that tracks the predictions of the primary controller. In this work, we propose the replacement of the multi-stage ancillary controller by a single scenario NMPC that tracks the predicted trajectories of one of the scenarios of the multi-stage primary controller. The scenario that will be tracked by the ancillary controller as well as the ancillary controller model are time varying and are adapted to the current plant dynamics. The benefits of the new formulation are demonstrated on the benchmark Williams-Otto Continuous Stirred Tank Reactor (CSTR) example.
Paper VI161-09.5
PDF · Video · A Comparison of Low-Complexity Charging and Balancing Protocols with Degradation-Awareness for a String of Li-Ion Cells
Goldar Davila, Alejandro	Université Libre De Bruxelles
Kinnaert, Michel	Université Libre De Bruxelles
Garone, Emanuele	Université Libre De Bruxelles
Keywords: Model predictive and optimization-based control, Optimal operation and control of power systems, Smart grids Abstract: This work introduces and compares low-computational cost MPC-based algorithms based on a reduced-order electrochemical model, the Equivalent Hydraulic Model (EHM), for the fast charge and balance of a string of battery cells accounting for degradation-related phenomena. The balance is carried out through a fully shunting grid. The shunting scenarios are described in two different approaches, namely: binary variables and pulse with modulation (PWM). Due to the complexity of solving nonlinear and non-convex constrained optimal problems, we approximate the balancing grid configurations of the string as subsystems to solve an optimization problem that follows the maximization over current and configuration of the string, while minimizing the charging current of each subsystem. Numerical results show that a PWM-based approach outperforms a mixed-integer approach, showing a charging time three times lower.
Paper VI161-09.6
PDF · Video · Iterative Learning Stochastic MPC with Adaptive Constraint Tightening for Building HVAC Systems
Long, Yushen	Nanyang Technological University
Xie, Lihua	Nanyang Technological University
Keywords: Model predictive and optimization-based control, Real time optimization and control Abstract: Most of the existing stochastic model predictive control (SMPC) algorithms for systems subject to random disturbance are designed offline using the distribution information of the uncertainties. In this paper, we propose an iterative learning based MPC for systems subject to time varying stochastic constraints on states. Different from those existing offline design approaches, except for the boundedness, this algorithm does not require to know the distributions or statistics such as the covariances of the uncertainties and the parameters of the controllers are adjusted online using the observations of past state trajectories. By making use of the iterative nature of the process, pointwise in time stochastic constraints are enforced so that it can handle time-varying constraints. Under some proper assumptions, this iterative procedure is shown to be equivalent to a root-searching problem and stochastic approximation theory is applied to show that the empirical average converges to the prescribed expectation in probability. The proposed algorithm is applied to an HVAC control problem to show its effectiveness.
Paper VI161-09.7
PDF · Video · Testing Minimum Cost Strategies of Pumping Systems with Scheduled Electric Tariffs in a Lab Scale Plant
Sanchis, Roberto	Universitat Jaume I
Lorenzo, Johnata	University Jaume I
Peñarrocha-Alós, Ignacio	Universitat Jaume I De Castelló
Keywords: Model predictive and optimization-based control, Real time optimization and control, Process control applications Abstract: This paper describes the development and testing of a lab plant that emulates a water supply pumping system with the objective of testing optimal pumping strategies based on standard solvers. The emulated system consists of two tanks that supply the water to two districts in a town. There are two pumps, that can fill the tanks through a reconfigurable hydraulic system with several valves. The automatic controller determines the valves and pumps that are active at each instant of time in order to minimize the operation cost, taking into account the electric tariff periods. Some aspects on the development of the lab plant are first discussed, including hydraulic aspects and real time control implementation issues. Then, a mathematical model is proposed to be able to formulate, in matrix form, the cost index and the constraints, such that, standard solvers as Mosek or CBC can be used. The full optimization proposal is tested on several experiments, and compared to some simulations, to demonstrate the validity of the plant and the optimization approach.
Paper VI161-09.8
PDF · Video · Real-Time Machine Learning-Based CLBF-MPC of Nonlinear Systems
Wu, Zhe	University of California, Los Angeles
Rincon, David	University of California, Los Angeles
Christofides, Panagiotis D.	University of California at Los Angeles
Keywords: Nonlinear process control, Model predictive and optimization-based control, Real time optimization and control Abstract: In this work, a real-time Control Lyapunov-Barrier Function-based model predictive control (CLBF-MPC) system using recurrent neural network (RNN) models is developed for a general class of nonlinear systems to ensure closed-loop stability and operational safety accounting for time-varying disturbances. An RNN model is first constructed for the nominal system (i.e., without disturbances) and utilized in the design of CLBF-MPC to provide state prediction. Subsequently, to improve the closed-loop performance in terms of operational safety and stability in the presence of disturbances, online learning of RNN models is incorporated within the real-time implementation of CLBF-MPC to update the RNN models using the most recent process measurement data. The proposed adaptive machine-learning-based CLBF-MPC method is evaluated using a nonlinear chemical process example.
Paper VI161-09.9
PDF · Video · Real-Time Optimization and Nonlinear Model Predictive Control for a Post-Combustion Carbon Capture Absorber
Patron, Gabriel David	University of Waterloo
Ricardez-Sandoval, Luis	University of Waterloo
Keywords: Real time optimization and control, Model predictive and optimization-based control, Control of large-scale systems Abstract: A framework to perform real-time optimization (RTO) and nonlinear model predictive control (NMPC) is presented for a post-combustion carbon capture absorber unit. The NMPC is implemented as a set point regulator with and without an accompanying RTO scheme. Moreover, a Kalman filter (KF) is used to perform state estimation for the scheme. The absorber RTO formulation considers solvent degradation cost, carbon tax, and electrical pumping costs. The two scenarios (with and without RTO) are assessed in situations with a fixed carbon tax, and a time-varying carbon tax. The results show that the RTO/NMPC scheme provides substantial economic benefit over the NMPC-only scheme, even for a short simulation time (~130 minutes). Furthermore, the RTO also aids in guaranteeing reachable set points for the NMPC, which may not occur otherwise.
Paper VI161-09.10
PDF · Video · Self-Optimizing Control of a Continuous-Flow Pharmaceutical Manufacturing Plant
Pérez Piñeiro, David	Norwegian University of Science and Technology
Nikolakopoulou, Anastasia	Massachusetts Institute of Technology
Jäschke, Johannes	Norwegian University of Science & Technology
Braatz, Richard D.	Massachusetts Institute of Technology
Keywords: Real time optimization and control, Control of large-scale systems, Advanced process control Abstract: This article considers the real-time optimization under uncertainty of a compact reconfigurable system for on-demand continuous-flow pharmaceutical manufacturing. Self-optimizing control is employed, which optimizes operation in the presence of uncertainty by controlling a carefully chosen combination of measurements to a constant setpoint. The method is applied to a simulated plant based on the physical process. The closed-loop simulations indicate that this simple policy is able to maintain the process operation close to optimality despite disturbances, sensor noise, and parametric model uncertainty.
Paper VI161-09.11
PDF · Video · Economic MPC of Nonlinear Processes Via Recurrent Neural Networks Using Structural Process Knowledge
Wu, Zhe	University of California, Los Angeles
Rincon, David	University of California, Los Angeles
Park, Michael	University of California, Los Angeles
Christofides, Panagiotis D.	University of California at Los Angeles
Keywords: Nonlinear process control, Process modeling and identification, Real time optimization and control Abstract: This work proposes three methods that incorporate a priori process knowledge into recurrent neural network (RNN) modeling of nonlinear processes to improve prediction accuracy and provide insights on the structure of neural network models. Specifically, we discuss a hybrid modeling method that integrates first-principles models and RNNs together, a partially-connected RNN modeling method that designs the RNN structure based on a priori structural process knowledge, and a weight-constrained RNN modeling method that introduces weight constraints in the optimization problem of RNN model training, respectively. The proposed RNN modeling methods are applied in the context of economic model predictive control of a chemical process example to demonstrate their improved approximation performance compared to a fully-connected RNN model that is developed as a black box model.

VI161-10
Modeling and Monitoring for Process Control	Regular Session
Chair: Imsland, Lars	Norwegian University of Science and Technology
Co-Chair: Mesbah, Ali	University of California, Berkeley
Paper VI161-10.1
PDF · Video · Data-Driven Fault Detection and Diagnosis of Industrial Scale Steam Methane Reformers Via Dynamic External Analysis
Kumar, Ankur	Linde
Flores-Cerrillo, Jesus	Linde
Bhattacharya, Apratim	Linde
Keywords: Active Fault Diagnosis, Monitoring and performance assessment Abstract: Steam methane reformers are key process units which form an integral part of every syngas plant. Fault-free reformer operation helps to keep plant reliability high and product yield optimal; however, reformers, being complex, large-scale, and high-temperature units, undergo various failures. Rapid detection of such failures is crucial to minimize failure costs (due to product loss, equipment repair) and prevention of unplanned shutdowns. Practical constraints on continuous manual monitoring of reformers by plant engineers necessitates the usage of automatic fault detection (FD) methodologies. The easy availability of process measurements and the difficulty of development of high-fidelity first-principle models of complex systems like reformers have motivated development of expert systems based on data-driven process monitoring methodologies. However, implementation of the plant-wide FD tools in chemical process industry has been low - lack of published work from industry on industrial FD applications and the subsequent dearth of industry-relevant practical guidelines can be attributed to the low industrial adoption. In this work, the capabilities of the FD methodologies are studied for real industrial steam methane reformers operating in hydrogen manufacturing plants. Real process data are used to compare the performances. It has been shown that external analysis - a combination of partial least squares regression and principal components analysis - can be effectively used for monitoring large-scale industrial steam methane reformers. Emphasis is added on the need for the FD methodology to be robust to dynamic process transients; in this work this is achieved through employment of dynamic variation of the external analysis method
Paper VI161-10.2
PDF · Video · Autonomous Process Model Identification Using Recurrent Neural Networks and Hyperparameter Optimization
Mercangöz, Mehmet	ABB Switzerland Ltd
Cortinovis, Andrea	ABB Switzerland Ltd
Schönborn, Sandro	ABB
Keywords: Advanced control technology Abstract: We demonstrate the application of automated machine learning to the problem of identifying dynamic process models using recurrent neural networks (RNNs). The general concept relies on continuous monitoring of input-output data from a plant and the processing of this data by a col-lection of algorithms. The data is first processed by a collaborative filtering system, which sug-gests a classification of system dynamics per output channel. The proposed classification and the number of input channels is used to initialize a search over RNN hyperparameters. The search al-gorithm uses subsets of historical data for training and validation to select the RNN architecture and determine the network parameters according to preselected objectives for balancing model accuracy and model compactness. The proposed approach is demonstrated on a simulated case study for online system identification of a chemical reactor, where the underlying dynamic char-acteristics of the simulated system are changed during the simulation as the system undergoes a number of disturbances and handles control tasks. Process models for the system in question are obtained via the automated machine learning approach and the models are updated as the sys-tem dynamics change. The results show good prediction accuracy of the models throughout the simulation representing changes in system dynamics.
Paper VI161-10.3
PDF · Video · Data-Driven Key Performance Indicator Fault Detection Approach Based on Sparse Direct Orthogonalization
Zhou, Hao	Tsinghua University
Ye, Hao	Tsinghua University
Yin, Shen	Harbin Institute of Technology
Keywords: Estimation and fault detection Abstract: In recent years, key performance indicator (KPI) detection has attracted much attention in large-scale process plants. Several methods have been developed to solve this issue. However, further studies find that post-processing methods have relatively high false alarm rates (FARs) for quality-unrelated faults. Also, methods combined with preprocessing, like orthogonal signal correction-modified partial least squares (OSC-MPLS), sometimes lack robustness. To deal with this problem, this paper proposes an enhanced pretreatment method, namely sparse direct orthogonalization (SDO), and a novel KPI-related fault detection approach called SDOMPLS is developed. Compared with OSC-MPLS, the proposed approach has more robust performance and better interpretability, while a numerical case and the Tennessee Eastman process (TEP) are used to demonstrate the effectiveness of the proposed approach.
Paper VI161-10.4
PDF · Video · Adaptive Ensemble of Gaussian Processes Models for Prediction in Filamentous Sludge Bulking Recognition
Yiqi, Liu	South China University of Technology
Xie, Min	City University of Hong Kong
Keywords: Estimation and fault detection Abstract: Filamentous sludge bulking is considered as the most serious problem or fault usually happening in wastewater treatment plants (WWTPs) adopting activated sludge process (ASP). Proper process monitoring of sludge-bulking-related but hard-to-measure variables are nowadays one of bottlenecks limiting WWTP management with significant safety and efficiency implications. In this light, Global Gaussian Processes Regression (GPR) models and Local GPR models are learned by ensemble learning for quality-related but hard-to-measure variables prediction. Such coordination is able to capture global and local process behaviors properly, and then to obtain more robust and accurate prediction. To further approach the prediction deterioration as time evolutes, this paper proposed an adaptive ranking strategy to ensemble the sub GPR models. In this adaptive strategy, we used the moving-window technique to rank and to select few of the best sub-model predictions, and then average them together to make the final predictions. Also, due to the use of GPR as the sub-model, the proposed methodology is able to describe the uncertainties properly. The proposed prediction model has been validated in a real WWTP with filamentous sludge bulking. The results show that the proposed methodology is able to predict the quality-related variable with RMSE being 25.6% and 21.6% better than the Bagging GPR model and the Average Ensemble GPR model, respectively.
Paper VI161-10.5
PDF · Video · TDLAS/WMS Embedded System for Oxygen Concentration Detection of Glass Vials with Variational Mode Decomposition
Luo, Qiwu	Central South University
Yang, Chunhua	Central South University
Song, Cao	Central South University
Zhou, Jian	Central South University
Gui, Weihua	Central South University
Keywords: Filtering and smoothing, Frequency domain identification, Errors in variables identification Abstract: Whether the oxygen content for medical glass vials can be measured accurately affects greatly the ingredient stability of sterile pharmaceuticals. Tunable diode laser absorption spectroscopy (TDLAS/WMS) based on wavelength modulation has the remarkable advantages of non-contact, low cost, high sensitivity, real-time response, which shows great potential in the field of in-site oxygen concentration detection. Due to the short optical path and various environmental disturbances, it is challenging to measure the headspace oxygen concentration in open-path optical environment. Targeting this challenge, this paper designs a TDLAS/WMS-based gas concentration sensing architecture and turns it into an embedded detection system. Then, a robust signal reconstruction method based on variational mode decomposition (VMD) is established to suppress the random noise of the demodulated harmonic signal. Hence, the oxygen concentration can be reliably inversed from the peak-to-peak values (Vp-p) of the 2nd harmonic signal. This detection framework is abbreviated as WMS+VDM+Vp-p. Encouragingly, the preliminary application on a glass vial encapsulation line demonstrate that the proposed method performs promising results with an absolute detection error of within ±1.5% and a minimal Allan deviation of 0.0010@(100s), which provides a good start for the on-site headspace oxygen concentration measurement for pharmaceutical glass vials.
Paper VI161-10.6
PDF · Video · The Automatic Analytics Framework for Multiple Oscillations in the Coupled Control Loops Via a New Variant of Slow Feature Analysis
Wang, Jie	Zhejiang University
Zhao, Chunhui	Zhejiang University
Fan, Haidong	Zhejiang Energy Group Research and Development
Zheng, Weijian	Zhejiang Energy Group Research and Development
Keywords: Monitoring and performance assessment, Data mining and multivariate statistics, Monitoring of product quality and control performance Abstract: Oscillation is a frequent type of control performance degradation in the process. Multiple oscillations may propagate in the coupled control loops, bringing challenges to detection and localization of oscillations. In this paper, a time-frequency analysis framework including detection, extraction, and localization of oscillations is proposed. The method is based on a new variant of slow feature analysis (SFA), termed multi-lag derivatives dynamic slow feature analysis (MDSFA), and a new indicator, termed oscillation matched degree (OMD). To detect and reveal the possible oscillation sources, MDSFA is proposed to extract features with different rates from the observed data and probe into the time-delay effect and multi-lag autocorrelations specific to control loops. To pinpoint the root loops and travel paths of oscillations, the OMD indicator is designed via the spectral analysis, which can measure the oscillation frequencies and amplitudes. The proposed method is verified to be able to detect and locate oscillations automatically and efficiently via the real thermal power process.
Paper VI161-10.7
PDF · Video · Monitoring a Segmented Fluid Bed Dryer by Hybrid Data-Driven/knowledge-Driven Modeling
Destro, Francesco	University of Padova
Salmon, Andrew James	Process Systems Enterprise Ltd
Pierantonio, Facco	University of Padova
Pantelides, Costas	Imperial College London
Bezzo, Fabrizio	Università of Padova
Barolo, Massimiliano	University of Padova
Keywords: Monitoring and performance assessment, Estimation and fault detection Abstract: Many data-driven and knowledge-driven methods for process monitoring have been developed in the last decade. In this study we show that the combined use of techniques from both categories can potentially outperform their standalone use. The proposed hybrid approach for fault detection and diagnosis is grounded in conventional multivariate statistical process monitoring. However, the datasets subject to analytics include not only field measurements, but also data obtained from a state estimator based on a mathematical model of the process. We apply the proposed methodology to a pharmaceutical case study, using the mechanistic model of a segmented fluid bed dryer from gPROMS FormulatedProducts. The hybrid framework demonstrates improved fault detection and diagnosis performances, when compared to data-driven monitoring or state estimation taken in isolation.
Paper VI161-10.8
PDF · Video · Adversarial Sample Based Semi-Supervised Learning for Industrial Soft Sensor
Feng, Liangjun	Zhejiang University
Zhao, Chunhui	Zhejiang University
Keywords: Monitoring and performance assessment, Industrial applications of process control Abstract: In industrial processes, soft sensor techniques are often utilized to predict the hard-to-measure quality variables. However, the labeled data which are obtained from the offline lab analysis can be quite rare. In the present work, a new divergence-based semi-supervised learning method is developed to exploit the unlabeled samples together with labeled ones for soft sensor application, namely adversarial tri-regression. First, the adversarial samples are generated based on the consideration of maximum disturbance, and through training on the combination of the adversarial samples and the original labeled samples, three regressors are initialized with divergence. Second, for each regressor, an unlabeled sample is labeled when the other two regressors agree on the labeling of this sample, which actually provides that regressor with some unknown information based on the divergence. As the three regressors label more and more samples for each other, the final regression model obtained by averaging the three base regressors presents increasingly more accurate prediction. The proposed method tackles a practical soft sensor problem for the industrial production process of cigarette.
Paper VI161-10.9
PDF · Video · An Integrated Application of Control Performance Assessment and Root Cause Analysis in Refinery Control Loops
Yağcı, Mehmet	Turkish Petroleum Refineries Co
Arkun, Yaman	Koc University
Keywords: Monitoring and performance assessment, Industrial applications of process control, Process control applications Abstract: Assessing the performance of control loops is an important component of Control Performance Monitoring (CPM) systems. Most of the industrial chemical processes have a large number of control loops interacting with each other in a complex way due to material and energy integration in the plant. A problem occurring in a certain control loop can easily upset the performance of the other control loops. Therefore, identification of the "bad" control loops causing a plant-wide disturbances is a crucial task. In this work, an integrated approach covering performance assessment and interaction analysis is proposed to detect the "bad" loops based on their performances. First, Minimum Variance Control (MVC) benchmark is used to screen-out the poor performing loops. Then, the spectral envelope method utilizing frequency analysis is used to identify the common oscillation periods among the loops under study. Finally, Granger causality is used to plot the interaction map between the loops. Even though these methods are well developed and used for several purposes separately, we present an integrated approach which focuses and analyzes the "bad loops". The developed approach has been tested in a refinery plant having 18 control loops. The results show that the proposed method is clearly able to identify and isolate the root-cause control loops. The validation of results and further improvements in the control loops under study have been given.
Paper VI161-10.10
PDF · Video · A Technological Demonstrator for Cloud-Based Performance Monitoring and Assessment of Industrial Plants: Present Architecture and Future Developments
Bacci di Capaci, Riccardo	University of Pisa
Scali, Claudio	University of Pisa
Vallati, Carlo	Department of Information Engineering, University of Pisa, Pisa,
Anastasi, Giuseppe	Department of Information Engineering, University of Pisa, Pisa,
Keywords: Monitoring and performance assessment, Industrial applications of process control, Process control applications Abstract: This paper presents the actual status and future developments of a technological demonstrator of key enabling technologies of Industry 4.0. The final scope of the project is the realization of a platform where different solutions addressing specific companies needs can be analyzed and their performance compared. Available Industry 4.0 technologies allows the realization of various architectures, even though the most appropriate solution has to be found by the company, accounting for different aspects, as economy, security, specific skills to be maintained or given in outsourcing. The first core of the platform, already working, consists in a Control Loop Performance Monitoring (CLPM) system which operates in cloud as a single module able to supervise routine data coming from different plants. This is an attractive solution for many companies allowing to avoid costs of local installations, linked to monitoring systems, human resources and additional effort for maintenance and upgrading. Some technical details about the application on a pilot-scale plant are given to illustrate the status of the activities. The scope of the project is to add new features to the system as: CLPM extended to plants located in different sites, equipment condition monitoring and environmental data analyses. To this aim, future developments of the platform are discussed in terms of improved technologies, different protocols and architectures.
Paper VI161-10.11
PDF · Video · Denoising of Industrial Oscillation Data Using EEMD with CCA
Lang, Xun	Information School, Yunnan University
Liu, Yan	Suzhou Institute of Biomedical Engineering and Technology
Zhang, Yufeng	Information School, Yunnan University
Xie, Lei	National Key Laboratory of Industrial Control Technology
Horch, Alexander	HIMA Paul Hildebrandt GmbH
Su, Hongye	Zhejiang University
Keywords: Monitoring and performance assessment, Signal processing for FDI Abstract: Industrial oscillation recordings are often contaminated with random noise, process disturbances and underlying nonstationarity, which obscure the useful information of the signal and complicate subsequent oscillation detection and diagnosis. This paper proposes a novel denoising technique to improve the quality of oscillation data, by jointly employing ensemble empirical mode decomposition (EEMD) with canonical correlation analysis (CCA). The proposed method first utilizes EEMD to decompose the single-loop data into a set of intrinsic mode functions (IMFs). Then CCA is applied to isolate the oscillation-dependent components from the decomposed IMFs. We evaluated the performance of the method through both numerical and industrial examples. The results demonstrate that this work is a promising tool for oscillation data preprocessing in the single control-loops.
Paper VI161-10.12
PDF · Video · Dynamic Model Reduction and Optimal Sensor Placement for Agro-Hydrological Systems
Sahoo, Soumya	University of Alberta
Yin, Xunyuan	University of Alberta
Liu, Jinfeng	University of Alberta
Shah, Sirish L.	University of Alberta
Keywords: Nonlinear model reduction, Estimation and fault detection, Control of large-scale systems Abstract: One of the essential aspects of developing advanced closed-loop irrigation is the estimation of soil moisture from a limited number of available sensors. One of the challenges is to find the optimal location of the sensors in a large heterogeneous field. In this work, we propose a method to find the optimal location of sensors in the presence of heterogeneous soil and non-uniform inputs. The key steps include dynamic order model reduction, minimum sensor selection, optimal sensor placement, and state estimation. The proposed method is applied to a three-dimensional field through simulations, and satisfying model reduction and state estimation results are obtained.
Paper VI161-10.13
PDF · Video · Dynamic Modelling of Hydrogen Production Plant Based on MHTRG
Liu, Miao	Tsinghua University
Dong, Zhe	Tsinghua University
Di, Jiang	Tsinghua University
Huang, Xiaojin	Tsinghua University
Keywords: Process modeling and identification Abstract: Hydrogen energy as a kind of clean energy has been widely studied in the world. It is very promising to use nuclear energy to produce hydrogen for realizing the sustainable hybrid energy system. In this paper, a new type of hydrogen production plant based on modular high temperature gas-cooled reactor (MHTGR), copper-chlorine (Cu-Cl) cycle and high temperature electrolysis (HTE) is proposed and the scheme feasibility is verified by the software in MATLAB/Simulink platform. The result shown that the plant can product hydrogen of 25.6t/h at full power operation and its transient characteristics is in accordance with the physical mechanism.
Paper VI161-10.14
PDF · Video · On-Line Calibration of Spectroscopic Sensors Based on State Observers
Sbarbaro, Daniel G.	Universidad De Concepción
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Process modeling and identification, Advanced process control, Process observation and parameter estimation Abstract: Spectroscopic sensors provide on-line information about process variables and they have been widely used for monitoring and control. These sensors measure the spectral responses at a large number of wavelengths correlated with the process variables of interest. However the spectral measurement can also be affected by external factors such as changes in temperature. In order to estimate the process variables from the acquired spectrum it is necessary the use multivariate calibration methods. Additive effects of external factors can be easily compensated by standard calibration methods, but multiplicative effects require complex off-line calibration procedures. This work, shows that this problem can be modeled by a non-linear state space equation. In addition, it also proposes an on-line calibration method based on a state observer for compensating multiplicative effects and at the same time estimating the desired process variable from the spectrum. The convergence of the observer requires an uniform observability condition to be satisfied. Simulation results obtained by using a spectral sensor for monitoring a mixing process under time-varying temperature show the main features and potential of the proposed approach. More complex spectral models for modeling the effect of temperature and other variables can be considered and included in the proposed framework.
Paper VI161-10.15
PDF · Video · Fault Detection in Hydroelectric Generating Units with Trigonometric Filters
Robert, Gerard	EDF - Hydro Engineering Centre
Besancon, Gildas	Ense3, Grenoble INP
Keywords: Process modeling and identification, Condition Monitoring, Signal and identification-based methods Abstract: A procedure based on trigonometric filters is proposed for parameter identification in a hydroelectric power generating unit approximated by a Multi Input - Single Output linear continuous-time varying system. First the discrete cosine transform is used as an interpolation filter and secondly an integral transform based on a Fourier kernel is applied to obtain a discrete-time model. Then a recursive least squares algorithm is performed to estimate abrupt changes of parameters and thus detect faults in the power plant. The whole method is successfully applied to a scenario fed with real sampled data featured by a poor excitation.
Paper VI161-10.16
PDF · Video · Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter - a Case Study
Hotvedt, Mathilde	Norwegian University of Science and Technology
Grimstad, Bjarne	ITK, NTNU
Imsland, Lars	Norwegian University of Science and Technology
Keywords: Process modeling and identification, Monitoring and performance assessment, Estimation and fault detection Abstract: Virtual flow meters, mathematical models predicting production flow rates in petroleum assets, are useful aids in production monitoring and optimization. Mechanistic models based on first-principles are most common, however, data-driven models exploiting patterns in measurements are gaining popularity. This research investigates a hybrid modeling approach, utilizing techniques from both the aforementioned areas of expertise, to model a well production choke. The choke is represented with a simplified set of first-principle equations and a neural network to estimate the valve flow coefficient. Historical production data from the petroleum platform Edvard Grieg is used for model validation. Additionally, a mechanistic and a data-driven model are constructed for comparison of performance. A practical framework for development of models with varying degree of hybridity and stochastic optimization of its parameters is established. Results of the hybrid model performance are promising albeit with considerable room for improvements.

VI161-11
Process Control	Regular Session
Chair: Van Impe, Jan F.M.	KU Leuven
Co-Chair: Guay, Martin	Queen's Univ
Paper VI161-11.1
PDF · Video · An Optimal Three Fractions Yielding Simulated Moving Bed Chromatographic Separation: Triple Switch SMBC
Mutika, Sumedha	Indian Institute of Technology Bombay
Bhartiya, Sharad	IIT Bombay
Keywords: Industrial applications of process control, Model predictive and optimization-based control, Process control applications Abstract: Among the various degrees of freedom Simulated moving bed chromatography possesses, the current work deals with manipulation of operating conditions comprising internal flow rates and switching period. The conventional mode of operation yields a single fraction of the extract and raffinate with a single set of operating conditions whereas the current work proposes a novel triple switch mode of operation which is characterised by three sets of internal flow rates and switching period and yields three fractions. Under optimal conditions, the higher degrees of freedom have the potential of yielding higher extract purities than conventional as well as dual switch modes of operation with two sets of operating conditions. A multi-objective optimisation problem has been solved which maximizes the purity of one of the three extract fractions, for a certain minimum extract recovery and minimum feed flow rate. It is through a lower purity in two of the three fractions that a superior extract purity is achieved. This finding has been corroborated by a modeling based study on the linear adsorption isotherm based separation of fructose-glucose in deionised water on a cation exchange resin.
Paper VI161-11.2
PDF · Video · Burden Control Strategy Based on Reinforcement Learning for Gas Utilization Rate in Blast Furnace
Shen, Xiaoling	China University of Geosciences, Wuhan
An, Jianqi	China University of Geosciences
Wu, Min	China University of Geosciences
She, Jinhua	Tokyo Univ. of Tech
Keywords: Industrial applications of process control, Nonlinear process control, Model predictive and optimization-based control Abstract: Gas utilization rate (GUR) is an important state parameter to reflect the energy consumption, the quality and production of the pig iron, and the distribution of the gas flow in a blast furnace. The GUR is mainly adjusted by burden distribution and hot-blast supply. According to the analysis of mechanism and data, burden distribution and hot-blast supply affect the GUR on a long-time scale and short-time scale, respectively. However, few of the previous researches proposed the control method for the GUR and they did not consider multi-time-scale characteristics. Thus, it is necessary to design a control strategy or system for the GUR considering the multi-time-scale characteristics, which can make the GUR have a reasonable development trend. This paper presented a burden control strategy based on a reinforcement learning algorithm for the GUR. The method improved the development trend of the GUR on a long-time scale. The experimental results demonstrated that the sequence of the parameters of the burden distribution given by the presented method ensured a reasonable development trend of the GUR on a long-time scale.
Paper VI161-11.3
PDF · Video · Design of Parallel Compensator and Stabilizing Controller to Mitigate Non-Minimum Phase Behaviour of the Czochralski Process
Bukhari, Halima Zahra	Norwegian University of Science and Technology (NTNU)
Hovd, Morten	Norwegian University of Technology and Science
Aftab, Muhammad Faisal	University of Agder (UiA)
Winkler, Jan	Fakultät Elektrotechnik Und Informationstechnik, TU Dresden
Keywords: Industrial applications of process control, Process control applications, Applications in semiconductor manufacturing Abstract: This paper addresses the design of a parallel compensator and a stabilizing controller for the simplified crystal growth dynamics of the Czochralski (CZ) process, i.e., the process for the production of monocrystalline silicon ingots of uniform diameter. The diameter control of the produced ingots is achieved by a CCD camera measurement used to sense the radius of the boundary between the base of the growing crystal and the surrounding glowing meniscus --- a raised melt surface connecting the crystal ingot with the flatter melt surface. Due to the intrinsic nature of the process, the bright ring radius measurement signal exhibits a non-minimum phase behaviour. A combination of the parallel compensator and a stabilizing controller is designed, such that the former provides for the mitigation of non-minimum phase behaviour, while the latter combined with the formal yields a suitable closed-loop performance.
Paper VI161-11.4
PDF · Video · Soft Sensor Design for the Optimisation of Parallel Debutaniser Columns: An Industrial Case Study
Küsel, Ralf	University of Pretoria
Wiid, Dries	University of Pretoria
Craig, Ian	University of Pretoria
Keywords: Industrial applications of process control, Process control applications, Process modeling and identification Abstract: This work demonstrates a practical implementation of a soft sensor to estimate the C5 hydrocarbon impurity in the butane product of a liquid petroleum gas (LPG) recovery system. Such a sensor can then subsequently be used to optimise the process. The process has two parallel debutaniser columns that feed a common LPG recovery system. The optimisation objective is to minimise the Reid vapour pressure (RVP) of the two debutanizer bottoms products. This optimisation problem can be solved with a simple advanced control implementation. However, the ability of the controller to minimise the process variation and drive the process to the optimal point is directly influenced by the quality of the constraining process variable. In this case, the key controlled variable (CV) is the debutaniser overheads C5 mass fraction. The designed soft sensor for this CV uses the general distillation shortcut (GDS) method, and is shown to represent the distillation column operation well. This work presents a derivation of the GDS method, and formulates a new approach for the feedback biasing of the two parallel debutaniser soft sensors.
Paper VI161-11.5
PDF · Video · Multi-Block Tensor Regression for the Quality Prediction and Root Cause Analysis in the Production of Active Pharmaceutical Ingredients
Munoz Lopez, Carlos Andre	KU Leuven
Lenaerts, Maité	Janssen Pharmaceutica
Peeters, Kristin	Janssen Pharmaceutica
Van Impe, Jan F. M.	KU Leuven
Keywords: Industrial applications of process control, Process performance monitoring/statistical process control, Batch and semi-batch process control Abstract: The large scale production of active pharmaceutical ingredients (APIs) is traditionally accomplished via batch processes. Nevertheless, their inherent complexity has limited the development and application of models for the processes as well as the use of advanced online monitoring, control and optimization strategies for their continuous improvement. The quality by design (QbD) strategy, defined by regulatory agencies, has brought a practical view into this. QbD seeks to determine methods to define the critical quality attributes (CQAs) of the product in terms of the critical material attributes (CMAs) and the critical process parameters (CPPs) of the input space along the whole process. This means not only on individual batch units but also throughout the multiple steps and stages of the production process. In this contribution, data-driven modelling methods were exploited to model two synthesis steps in the large scale production of an Active Pharmaceutical Ingredient (API). First, tensor factorization was applied to train correlation based models to capture the main directions of variability for each of the studied steps. Secondly, a partial least squares (PLS) model was trained to regress the concentration of an impurity on the product onto the latent variables of the primary monitoring models as well as the CMAs of the input materials. The proposed modelling approach was applied to data from the large scale production on an API. This resulted in an accurate model, which was validated on an independent data set and which captures meaningful correlations that helped on the root cause identification for variations encountered in the CQA of the product. These results are in line with the observations made on the process operation.
Paper VI161-11.6
PDF · Video · Bayesian-Based Anomaly Detection in the Industrial Processes
Pan, Yijun	Chinese Academy of Sciences
Zheng, Zeyu	Shenyang Institute of Automation, Chinese Academy of Sciences
Fu, Dianzheng	Shenyang Institute of Automation, Chinese Academy of Sciences
Keywords: Industrial applications of process control, Statistical methods/signal analysis for FDI Abstract: In general, the industrial processes are semi-automatic, and are controlled by the operators. Since the operation principles of the industrial processes are complicated, it is difficult to label observations. The disturbances may be contained in the observations. Therefore, the unsupervised anomaly detection method is promising for research in the industrial processes. In the paper, a multivariate anomaly detection method is proposed, which is unsupervised and online. The priori probability of anomaly occurrence is necessary, and a hazard function selection method is defined at first. Secondly, Bayesian-based method is adopted for anomaly detection. In final, the Dempster-Shafer theory is introduced for fusing the univariate anomaly detection results. The numerical simulation is used for illustrating the anomaly detection power of the proposed method, and the TE process is implemented for testing the fault detection effectiveness. A real data set collected from a bathyscaphe is applied for demonstrating the power of leakage detection.
Paper VI161-11.7
PDF · Video · An Improved Gramian-Based Interaction Measure for Time Delay Systems
Moaveni, Bijan	K. N. Toosi University of Technology
Birk, Wolfgang	Luleå University of Technology
Keywords: Interaction between design and control, Control system design, Advanced process control Abstract: In this paper, a modified Gramian based control configuration selection (CCS) method for linear multi-input multi-output (MIMO) plants with time delays in input-output channels is proposed. In contrast to the typical approach of approximating the delayed system, the time delay is directly integrated in the method by using the finite-time H_2 norm for the time- delay system (TDS). The methodology is based on an explicit formula for computing the finite-time H_2 norm for stable SISO systems. Gramian-based CCS methods are either insensitive to time delays or favor channels with large delays, while the proposed method suggests configuration which are more reasonable. A numerical examples is used to discuss and benchmark the method. It is concluded that the proposed methods provides adequate configuration suggestions and circumvents a well-known shortcoming.
Paper VI161-11.8
PDF · Video · A Control Oriented Pattern for Plant Design: The Homogeneous Population Pattern
Lucchese, Riccardo	Luleå University of Technology
Atta, Khalid	LTU
Guay, Martin	Queen's Univ
Keywords: Interaction between design and control, Process control applications, Control of large-scale systems Abstract: We consider an adaptive control problem for a homogeneous population of systems that operate in close conditions. Drawing a connection to Design of Experiments (DoE), we study an extremum seeking controller that operates the population economically by either minimizing a group cost or maximizing a group utility. The controller is formalized in full detail within a dynamic setting that extends the previous treatment. The applicability and effectiveness of the strategy is commented upon and supported through different examples. We argue that this class of control systems should be addressed as a design pattern where possible in view of its capacity to enable both simple and effective online optimizing control strategies.
Paper VI161-11.9
PDF · Video · Sliding Mode Controller Based on a Hybrid Surface for Tracking Improvement of Non-Linear Processes
Obando, Camila	Escuela Politecnica Nacional
Chávez, Danilo	Escuela Politencnica Nacional
Leica, Paulo	Escuela Politencnica Nacional
Camacho, Oscar	Escuela Politecnica Nacional
Keywords: Process control applications, Advanced control technology Abstract: This paper presents the synthesis of a sliding mode controller based on a hybrid surface (SMC-HS) as an alternative to improve the performance of the traditional SMC in its transient response. The combination of two sliding surfaces is carried out in order to obtain the advantages of both. Through reset actions, the use of one or other surface is prioritized. The improvement offered by the proposal is quantified by performance indexes when the new controller is tested in a non-linear, self-regulating model.
Paper VI161-11.10
PDF · Video · Process Tomography for Model Free Adaptive Control (MFAC) Via Flow Regime Identification in Multiphase Flows
Yan, Ru	University of South-Eastern Norway
Viumdal, Håkon	University of South-Eastern Norway
Mylvaganam, Saba	Campus Porsgrunn, University of South-Eastern Norway
Keywords: Process control applications, Advanced control technology, Process performance monitoring/statistical process control Abstract: Multiphase flows are frequently found with oil/gas/water/sand in the oil & gas industries, in processes handling dry particulates such as fluidized bed and particulate flow and slurries and sedimentation, to quote a few industrial applications. All these processes have different flow regimes with characteristic distribution of the different materials in the flow. With increasing sensor data from processes and associated possibilities for data fusion, process tomography offers non-intrusive real time sensing methods for identifying these flow regimes, which in certain cases can lead to hazards to personnel and plants in the process industries. In this paper, two scenarios of control using process tomography are presented from the oil and gas industries and powder technology. Twin plane Electrical Capacitance Tomography (ECT) with a plethora of other sensors for measuring pressure, flow rate in two phase flow involving water and air is one application. The other is particulate flow in a fluidized bed. In the case of water and air, ECT was used in a multiphase flow loop with different combinations of air and water mass flow rates enabling the generation of different flow regimes. In the case of particulate flow, different scenarios of flow conditions were generated using particulates and observing the flow regimes based on the distribution and flow rate of the particulates. For the identification of flow regimes, capacitance values from the 12-electrode ECT module at a rate of 100 frames in 200ms, were logged in for data analytics. In the final stages of using the processed data, in the case of two-phase flow 5 outputs consisting of the identified flow regimes, viz. plug, slug, annular, stratified and wavy flows were used as inputs for control and decision making. Similarly, in particulate flow ECT data were used to estimate the air velocity for fluidization as well as in identifying slug and plug flow, which are valuable to the process engineer in determining the range of air velocities for safe operation of the system used for particulate transport, often involving fluidization bed and pipelines. Tomography is used to discern features and tomometry is used in implementing the algorithms.
Paper VI161-11.11
PDF · Video · Fabrication and Characterization of a Microfluidic Device with Vertically Aligned Multi Walled Carbon Nanotube Channels
Nak, Handan	Istanbul Technical University
Gurkan, Idris	Istanbul Technical University
Cebeci, Hulya	Istanbul Technical University
Ergenc, Ali F.	Istanbul Technical University
Keywords: Process control applications, Control of micro- and nano-systems, Applications in advanced materials manufacturing Abstract: Microfluidic devices are state of the art technology which are used for many applications especially as lab-on-chips. Manufacturing and characterization of these devices are reported in literature but process control aspects of vertically aligned multiwalled carbon nanotubes are rarely investigated. Furthermore, nano exchange capabilities with such structures are scarcely studied. In this paper, an industrial quality chemical vapor deposition system is designed, built and controlled. A nonlinear PI controller is employed to control the temperature of the chemical synthesis system, where precise temperature control is crucial. This controller behavior depends on the ratio between the error signal and the reference which enables the controller to act faster while avoiding overshoot. A microfluidic nanoexchanger device is manufactured,flow characteristics are modeled and its nanoexchange capability is tested and proven experimentally. These devices have many applications both in industry and biomedical field. One of the promising applications is building artificial organs such as lungs and kidneys where nanoexchanges occur naturally.
Paper VI161-11.12
PDF · Video · Simultaneous Parameter and State Estimation of Agro-Hydrological Systems
Bo, Song	University of Alberta
Sahoo, Soumya	University of Alberta
Yin, Xunyuan	University of Alberta
Liu, Jinfeng	University of Alberta
Shah, Sirish L.	University of Alberta
Keywords: Process control applications, Process observation and parameter estimation, Nonlinear process control Abstract: The Richards equation plays an important role in the study of agro-hydrological systems. It models the water movement in soil in the vadose zone, which is driven by capillary and gravitational forces. Its states (capillary potential) and parameters (hydraulic conductivity, saturated and residual soil moistures and van Genuchten-Mualem parameters) are essential for the accuracy of mathematical modeling, yet difficult to obtain experimentally. In this work, an estimation approach is developed to estimate the parameters and states of the Richards equation simultaneously. Parameter identifiability and sensitivity analysis are used to determine the most important parameters for estimation purpose. Three common estimation schemes (extended Kalman filter, ensemble Kalman filter and moving horizon estimation) are investigated. The estimation performance is compared and analyzed based on extensive simulations.
Paper VI161-11.13
PDF · Video · Robust Controller Design for Modified Smith Predictor
Sindhuja, Princes	Anna University
Velappan, Vijayan	St.Joseph's College of Engineering, Anna University
Panda, Rames	CLRI(CSIR), Adyar, Chennai
Keywords: Process control, Analytic design, Sliding mode control Abstract: The present paper presents control of dead time processes using Sliding Mode Controller (SMC) in a Modified Smith Predictor (MSP) structure. The SMC working principle relies on the reaching phase and the sliding phase where the tuning parameters KD and delta play major roles in the speed, overshoot and chattering effects. Here in this paper, model based tuning rule is used to modify the KD rule/equation and is implemented to different processes with modified smith predictor (MSP) structure to counteract the constant load disturbance for an integrating process. It has been found that the proposed MSP-SMC combination provides improved performance and robustness behavior. The analyses are done for servo and regulatory response cases. Moreover, the robustness and invariance property of the SMC has been analyzed against parametric uncertainty and other various disturbances (noise). The results obtained are compared with that of available methods. Profile
Paper VI161-11.14
PDF · Video · An Application of Modifier Adaptation with Quadratic Approximation on a Pilot Scale Plant in Industrial Environment
Gottu Mukkula, Anwesh Reddy	Technische Universität Dortmund
Kern, Simon	Bundesanstalt Für Materialforschung Und -Prüfung (BAM), Berlin U
Salge, Malte	INVITE GmbH
Holtkamp, Manuel	INVITE GmbH
Guhl, Svetlana	Bundesanstalt Für Materialforschung Und -Prüfung (BAM)
Fleischer, Christoph	INVITE GmbH
Meyer, Klas	Bundesanstalt Für Materialforschung Und -Prüfung (BAM)
Remelhe, Manuel Pereira	Bayer AG
Maiwald, Michael	Bundesanstalt Für Materialforschung Und -Prüfung (BAM)
Engell, Sebastian	TU Dortmund
Keywords: Real time optimization and control, Industrial applications of process control, Process control applications Abstract: The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties.
Paper VI161-11.15
PDF · Video · Modelling and Real-Time Optimisation of a Heat-Exchanger Network
Marcos, Maria P	University of Valladolid
Pitarch, Jose Luis	Universidad De Valladolid
de Prada, Cesar	Univ. of Valladolid
Keywords: Real time optimization and control, Monitoring and performance assessment, Industrial applications of process control Abstract: This work proposes a hybrid mathematical model and an optimisation-based tool to support the management of a heat-recovery section (formed by several heat exchangers) in a fibre-production factory. The purpose of the network is to heat different products using several hot sources, employed as utilities. Furthermore, concerns about the degradation of the equipment due to fouling are explicitly taken into account. Hence, the goals are to allocate the hot sources to heat exchangers and to suggest which heat exchanger should be cleaned to achieve optimal economic operation. Experimental models for the overall heat-transfer coefficients with respect to the flows have been identified, and production constraints are considered too. The problem is formulated such that it can be solved in a real-time optimisation fashion via mixed-integer non-linear programming. The approach has been tested through plant historical situations.
Paper VI161-11.16
PDF · Video · Experimental Real Time Optimization of a Continuous Membrane Separation Plant
Gottu Mukkula, Anwesh Reddy	Technische Universität Dortmund
Valiauga, Petra	Slovak University of Technology in Bratislava
Fikar, Miroslav	Slovak University of Technology in Bratislava
Paulen, Radoslav	Slovak University of Technology in Bratislava
Engell, Sebastian	TU Dortmund
Keywords: Real time optimization and control, Process control applications Abstract: This paper deals with the optimal operation of a continuously operated laboratory membrane separation plant. The goal is to find an economically optimal regime of operation using the transmembrane pressure (TMP) and the operating temperature as adjustable set-points for the low-level controllers. The main challenge is to identify the optimum in the absence of an accurate process model. We employ an iterative real-time optimization scheme, modifier adaptation with quadratic approximation (MAWQA), to identify the plant optimum in the presence of the plant-model mismatch and measurement noise. Two experiments are performed; one with and one without a productivity constraint. The experimental results show the capabilities of the MAWQA scheme to identify the process optimum in real-world scenarios. The optimum identified by the MAWQA scheme coincides with the optimum of a surrogate model that was built using a larger data set.
Paper VI161-11.17
PDF · Video · Short-Term Multiproduct Batch Scheduling Considering Storage Features
Wu, Ouyang	BASF SE
Dalle Ave, Giancarlo	ABB
Harjunkoski, Iiro	ABB AG, Corporate Research
Bouaswaig, Ala Eldin	Technische Universität Dortmund
Schneider, Stefan	TU Kaiserslautern
Roth, Matthias	Technische Universität Kaiserslautern
Imsland, Lars	Norwegian University of Science and Technology
Keywords: Control and optimization of supply chains, Batch and semi-batch process control, Process control applications Abstract: In this paper, modeling of storage constraints and material transfer are considered for short-term batch scheduling. The key features of storage and quality checks are inspired from a case study of a multiproduct batch plant. The case study presents two strategies for assigning batch orders to each individual storage tank during batch production, which are modeled in the proposed scheduling formulations as two scenarios of storage policies. A continuous-time MILP formulation is applied for the assignment and sequencing of batches in the multistage processes. The proposed approach is tested using the case study problems, and the computational results illustrate the performance of the scheduling formulations.
Paper VI161-11.18
PDF · Video · Observer-Based Robust Control of a Continuous Bioreactor with Heterogeneous Community
dos Reis de Souza, Alex	Inria Lille Nord Europe
Efimov, Denis	Inria
Polyakov, Andrey	INRIA Lille Nord-Europe
Gouze, Jean-Luc	INRIA
Keywords: Estimation and control in biological systems, Nonlinear process control, Process control applications Abstract: This work addresses the problem of robust control of the continuous bioreactor -- namely the chemostat -- using an observer-based approach. We design a control law aiming to regulate the growth of a certain species and to stabilize the output -- a growth-associated product of interest -- in a prescribed level. In addition, to avoid the single-species dogma (which takes only one species into account for control design), we add to the microbial community unknown species competing for the limiting substrate. Finally, this control architecture is able to maintain the productivity, despite this competing heterogeneity (or biodiversity) of the community.
Paper VI161-11.19
PDF · Video · Working Distance-Based Feedforward Control for Weld Bead Height Control in Directed Energy Deposition
Stoppok, Johann	Ruhr-University Bochum
Dillkoetter, David	Ruhr Universität Bochum
Thiele, Magnus	Ruhr-University Bochum
Esen, Cemal	Ruhr-University Bochum
Leonow, Sebastian	Ruhr University Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Process control applications, Process modeling and identification Abstract: Due to large temperature gradients and high thermal conductivities, additive manufacturing processes for metals have challenging dynamics. A high process reliability and repeatability hinges upon the base layer control of the melt pool and the resulting weld bead geometry. The material feed rate has proven to be an appropriate manipulated variable for weld bead height control, but it can only be varied slowly and is subject to deadtimes. We propose to use the distance of the process head to the build surface (the working distance) as an alternative manipulated variable. We derive a simple nonlinear dynamic model that captures the effect of the working distance on the weld bead height. We show scanning velocity fluctuations, which can be treated as known disturbances, can be compensated with working distance feedforward control. We apply the proposed controller to a real DED process and demonstrate working distance control is an alternative to material feed rate control.
Paper VI161-11.20
PDF · Video · Model-Based Temperature Offset Compensation for Additive Manufacturing by Directed Energy Deposition
Dillkoetter, David	Ruhr Universität Bochum
Stoppok, Johann	Ruhr-University Bochum
Thiele, Magnus	Ruhr-University Bochum
Esen, Cemal	Ruhr-University Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Process control applications, Process observation and parameter estimation, Measurement and instrumentation Abstract: Laser based directed energy deposition (DED), also known as laser metal deposition or laser cladding, is an additive manufacturing technology for building 3D freeform parts. Reliable temperature measurements are of obvious interest and importance for the control of these processes. We propose a model-based method for the correction of temperature measurements from an imperfectly aligned sensor, which is a pyrometer in our process. We show that the proposed method can improve the reliability of the pyrometer-based temperature measurements even if the pyrometer is carefully aligned and calibrated according to industrial standards. We apply the proposed method to a powder-based directed energy deposition process. Due to its simplicity, the proposed method can easily be adapted to other additive manufacturing process types.
Paper VI161-11.21
PDF · Video · Minimum-Time Feedforward Control in Ratio Control Systems
Visioli, Antonio	University of Brescia
Hagglund, Tore	Lund University
Keywords: Process control Abstract: In this paper we propose a ratio control scheme for industrial processes that exploits a two-state feedforward action in order to achieve a minimum-time set-point transient response, by considering the actuator constraints. A Tracking Ratio Station is then used to achieve the desired ratio value when the two processes have a different dynamics. The control architecture can easily be implemented with standard industrial hardware. Simulation results show the effectiveness of the methodology.
Paper VI161-11.22
PDF · Video · Round-Trip Engineering for Petrochemical Industry Automation
Cruz, Marcus Vinícius Silva	Federal University of Santa Catarina, Automation and Control Sys
Damo, Thaise Poerschke	Federal University of Santa Catarina
Becker, Leandro	Federal University of Santa Catarina
Keywords: Model-driven systems engineering, Maintenance models and services, Systems interoperability Abstract: The petrochemical industry is becoming increasingly complex and, as a result, different software platforms are used to assist in system design. Generally, it happens that the same component of the physical plant is (re)modeled on different software platforms, so the reuse of these models becomes difficult, compromises system interoperability, and generates the need for rework in projects. Previous work proposed the infrastructure named M4PIA (Model-Driven Engineering for Petrochemical Industry Automation), which allows to represent industrial plants through different, compatible and object-oriented models. By means of model transformations, it supports automatic code generation from a high-level abstraction model to specific software platforms. The present work provides the integration of Round-Trip Engineering (RTE) in the M4PIA infrastructure so that from a platform-specific model it allows to obtain, through model-to-model (M2M) transformation, a platform-independent model. In order to validate the implemented RTE transformations, it was developed a case study related to a simplified gas compression system.

VI162
Power and Process System - Mining, Mineral and Metal Processing
VI162-01 Monitoring and Control for Mining, Minerals and Metals   Open Invited Session, 14 papers
VI162-02 Artificial Intelligence in Mining, Mineral and Metal Processing   Regular Session, 8 papers
VI162-03 Control in Mining, Mineral and Metal Processing   Regular Session, 5 papers
VI162-04 Estimation, Monitoring, and Modeling in Mining, Mineral and Metal Processing   Regular Session, 13 papers

VI162-01
Monitoring and Control for Mining, Minerals and Metals	Open Invited Session
Chair: Le Roux, Johan Derik	University of Pretoria
Co-Chair: Luo, Hao	Harbin Institute of Technology
Organizer: Chen, Zhiwen	School of Automation, Central South University
Organizer: Sun, Bei	Central South University
Organizer: Le Roux, Johan Derik	University of Pretoria
Organizer: Craig, Ian	University of Pretoria
Organizer: Luo, Hao	Harbin Institute of Technology
Paper VI162-01.1
PDF · Video · A Steady-State Model of the High-Pressure Grinding Rolls (I)
Thivierge, Alex	Laval University
Bouchard, Jocelyn	Université Laval
Desbiens, Andre	Universite Laval
Keywords: Identification and modelling, Process optimisation Abstract: This paper presents a steady-state model of the high-pressure grinding rolls (HPGR) based on population balance methods. It simulates the power draw, flow rate, and particle size distribution of both the edge and center products from the operating pressure, rotating speed, and size-by size feed rates. Upgrades from previous work include the addition of the edge cutter setting (in distance unit) as an input parameter, and the equation for the variation of density along the rolls width to account for inaccuracy in throughput prediction generally compensated using an extrusion or slip correction factor. Results appears qualitatively coherent, but remains to be validated with experimental data.
Paper VI162-01.2
PDF · Video · A Novel Kernel-Based Extreme Learning Machine with Incremental Hidden Layer Nodes (I)
Min, Mengcan Min	Central South University
Chen, Xiaofang	Central South University
Yongxiang, Leiyongxiang	Central South University
Chen, Zhiwen	School of Automation, Central South University
Xie, Yongfang	Central South University
Keywords: Process optimisation, Neural networks in process control, Neural fuzzy modelling and control Abstract: Extreme learning machine (ELM) is widely used in various fields because of its advantages such as short training time and good generalization performance. The input weights and bias of hidden layer of traditional ELM are generated randomly, and the number of hidden layer nodes is determined by human according to experience, which is an empirical value. Only by adjusting parameters manually can an appropriate network structure be found. This training method is complex and time-consuming, which increases the workload of human workers. To solve this problem, the incremental extreme learning machine (I-ELM) is used to determine the appropriate number of hidden layer nodes and construct a compact network structure in this paper. At the same time, a new hidden layer activation function STR is proposed, which avoids the disadvantages of incomplete output information of hidden layer due to uneven distribution of sample data. The proposed algorithm is evaluated by public data sets and applied to the classification of superheat degree (SD) in aluminum electrolysis industry. The experimental results show that STR activation function has a good learning speed, and the proposed algorithm is superior to the existing SD identification algorithm in terms of accuracy and robustness.
Paper VI162-01.3
PDF · Video · Flotation Bubble Size Distribution Detection Based on Semantic Segmentation (I)
Zhang, Lei	Central South University
Degang, Xu	Central South University
Keywords: Monitoring of product quality and control performance, Process observation and parameter estimation Abstract: In mineral foam flotation, characteristic information of bubble images is closely related to the flotation process condition and production indicators, among which the bubble size distribution is a key feature. Therefore, accurately obtaining the bubble size distribution is of great significance for optimizing and controlling the flotation process. Froth segmentation is the main technique to obtain bubble size information of flotation cells. In this paper, one semantic segmentation algorithm is adopted to segment flotation froth image, and a new froth segmentation algorithm based with improved U-Net is proposed. The experiment results indicate that the developed algorithm not only successfully solves the problem of over-segmentation and under-segmentation, but also improves the segmentation accuracy, which is suitable for different process conditions and lighting conditions.
Paper VI162-01.4
PDF · Video · Estimation of Quality Parameters of Trimmed Steel Plates Using Laser Sensors (I)
Zeiler, Alexander	TU Vienna
Steinboeck, Andreas	Vienna University of Technology
Kemmetmueller, Wolfgang	TU Wien, Automation and Control Institute
Jochum, Martin	AG Der Dillinger Hüttenwerke
Kugi, Andreas	Vienna University of Technology
Keywords: Monitoring of product quality and control performance, Process observation and parameter estimation, Measurement and instrumentation Abstract: This paper deals with the estimation of the contour of hot-rolled steel plates and of quality parameters characterizing the trimmed edge. Suboptimal process parameters can cause camber or a saw-tooth shaped contour and imperfections on the trimmed edges. Quantitative measures of these imperfections enable a seamless quality control and can be used as input quantities for data-based or control engineering applications. The presented method utilizes measurements from 2D-laser sensors installed at the side of the production line after a trimming shear. A model-based optimization algorithm estimates the contour and a possible rotation of the plate. Signal processing and sensor fusion are employed to estimate additional quality parameters. Validation with measurement data from a rolling mill demonstrates the high accuracy of the proposed method. The camber is estimated with an accuracy lower than ±0.04mm/m, which reveals that the proposed method is more accurate than existing solutions for camber estimation.
Paper VI162-01.5
PDF · Video · A Survey on the Status of Industrial Flotation Control (I)
Le Roux, Johan Derik	University of Pretoria
Oosthuizen, Daniël Jacobus	ProcessIQ
Mantsho, Sydney	Mintek
Craig, Ian	University of Pretoria
Keywords: Measurement and instrumentation, Process observation and parameter estimation Abstract: A survey was conducted to establish the status-quo of industrial flotation control. The survey focussed on the measurements and actuators generally available in industry, the reliability and accuracy of measurements, and how important process variables are controlled. It is evident from the survey that regulatory control is well established with reliable and relatively accurate measurements available throughout a plant. The introduction of froth image analysers seems to gain good traction and enables improved control of mass pull to achieve consistent concentrate grade. Although supervisory control may soon be the new standard for flotation plants, on-line grade optimisation requires further work.
Paper VI162-01.6
PDF · Video · Nonlinear Fault Detection Based on Fault-Related Multiphase Principle Polynomial Analysis for Al Stack Etch Process (I)
Zhang, Chuanfang	University of Science and Technology Beijing
Peng, Kaixiang	Univ of Science and Technology, Beijing, China
Dong, Jie	Univ of Science and Technology, Beijing, China
Zhang, Kai	Univ of Science and Technology, Beijing, China
Keywords: Data mining and multivariate statistics, Applications in semiconductor manufacturing, FDI for nonlinear Systems Abstract: In integrated circuit manufacturing industry, etch process is a complex nonlinear batch process. Al stack etch is the penultimate layer of dry etch. Based on the specific steps of the recipe, it has the multiphase characteristic and the can exhibit significantly different behaviors over different phases. However, conventional fault detection methods cannot effectively monitor Al stack etch process due to nonlinear and multiphase characteristics. Moreover, they are usually modeled by normal process data. In Al stack etch process, fault process data can be obtained from the datalog of equipments. In order to utilize these data, a novel nonlinear fault detection method called fault-related multistage principal polynomial analysis (FMPPA) is proposed in this work. FMPPA is efficient to deal with nonlinearity of the multiphase batch process. Furthermore, it can make full use of fault data by decomposing original feature space into three subspaces. FMPPA is applied to monitoring the Al stack etch process. Simulation results demonstrate that FMPPA is superior to other methods.
Paper VI162-01.7
PDF · Video · A Dynamic Grey-Box Model and Its Application in the Sintering Process of Ternary Cathode Material (I)
Chen, Jiayao	Central South University
Gui, Weihua	Central South Univ
Chen, Ning	Central South Universiy
Dai, Jiayang	Central South University
Yang, Chunhua	Central South University
Li, Xu	Hunan Shanshan Energy Technology Co. , LTD
Keywords: Measurement and instrumentation, Identification and modelling, Process observation and parameter estimation Abstract: Soft-sensor technique is often used to estimate key variables in industrial manufacturing, of which the commonly used approaches as the first-principle modeling and data-driven modeling both have their limitations. To take full advantage of the modeling methods and overcome the problems of unmodeled dynamics in industrial manufacturing, a grey-box modeling method combining the first-principle analysis with dynamic data-driven model is developed in this paper. In the framework of the presented grey-box model, the unmodeled dynamics in the first-principle model are obtained by the dynamic probabilistic latent variable model. On this basis, availability of models can be improved. Finally, the actual industrial data in the roller kiln of ternary cathode material manufacturing is used for simulation to verify the validity of the model. The results have practical guiding significance.
Paper VI162-01.8
PDF · Video · Detection of Sensor Precision Degradation by Monitoring Second-Order Statistics (I)
Hou, Hui	Shandong University of Science and Technology
Ji, Hongquan	Shandong University of Science and Technology
Keywords: Process performance monitoring/statistical process control, Monitoring and performance assessment, Data mining and multivariate statistics Abstract: For industrial processes, there are usually a number of measurement sensors equipped for monitoring and control purposes. In practice, sensors may suffer from the precision degradation phenomenon due to several aspects such as aging and ambient interference. This phenomenon may lead to imprecise or even incorrect control commands and indications, so the corresponding fault detection task is of vital importance. In this paper, inspired by the fact that precision degradation of a sensor can result in the increase of the variable's variance, an algorithm based on second-order statistics analysis is proposed to accomplish the detection task for sensor precision degradation faults. By employing the sliding window technique, second-order statistics of process variables are first extracted. Then, conventional principal component analysis (PCA) is used as a dissimilarity quantification tool, with detection statistics and corresponding control limits established, to perform fault detection. Finally, simulations on a numerical example and the continuous stirred tank reactor (CSTR) benchmark process are performed to illustrate the effectiveness and advantages of the proposed method, in comparison with some existing methods such as PCA, dynamic PCA, and dissimilarity (DISSIM).
Paper VI162-01.9
PDF · Video · A Novel Propagation Path Identification Framework for Faults in Industrial Processes (I)
Ma, Liang	University of Science and Technology Beijing
Peng, Kaixiang	Univ of Science and Technology, Beijing, China
Dong, Jie	Univ of Science and Technology, Beijing, China
Keywords: Fault diagnosis and fault tolerant control Abstract: In modern industry, timely and accurate fault diagnosis plays an important role in satisfying the demands of production safety and stability of production quality. This paper dedicates on propagation path identification of faults in industrial processes, which will offer a feasible technology or solution to take corrective and timely maintenance measures for field engineers. Specifically, a recurrent neural networks-based Granger causality analysis approach is developed, which has sufficiently considered the nonlinear and dynamic relationships among time series after faults happen. Finally, we validate our approach on a typical industrial process,finishing mill process, to demonstrate the efficiency of the proposed scheme.
Paper VI162-01.10
PDF · Video · FeO Content Prediction for an Industrial Sintering Process Based on Supervised Deep Belief Network (I)
Yuan, Xiaofeng	Central South University
Gu, Yongjie	School of Automation, Central South University
Wang, Yalin	Central South University
Chen, Zhiwen	School of Automation, Central South University
Sun, Bei	Central South University
Yang, Chunhua	Central South University
Keywords: Artificial intelligence, Monitoring of product quality and control performance, Identification and modelling Abstract: In industrial sintering processes, it is very important to monitor and control key quality indicators, which are often difficult to measure online. Soft sensor technology is a good solution for online prediction of quality indicators. Nowadays, deep learning is widely used in soft sensors due to its powerful ability in processing nonlinear data. In this paper, a supervised deep belief network (SDBN) is proposed by introducing quality variable into the input variables at each restricted Boltzmann machine to extract quality-related features for soft sensor. With case study on an actual industrial sintering process, SDBN shows much better prediction performance than the original deep belief network and stacked autoencoder.
Paper VI162-01.11
PDF · Video · The Use of a Semi-Rigorous SAG Mill Model for a Hands-On Workshop (I)
Bauer, Margret	University of Pretoria
Brooks, Kevin	BluESP
Burchell, John James	Sibanye-Stillwater
Coetzee, Lodewicus Charl	Mintek
Le Roux, Johan Derik	University of Pretoria
McCoy, John Themba	Stone Three Digital
Miskin, Jason John	Opti-Num Solutions
Winter, Danielle Joy	Opti-Num Solutions
Keywords: Identification and modelling, Process observation and parameter estimation, Advanced process control Abstract: This paper describes the extension of a grinding mill model that is publicly available for educational and training purposes. This industrially derived model of a mill is used to explain complex concepts of advanced process control (APC) such as model predictive control and soft sensing. The resulting concepts were developed in a hands-on workshop in the wake of the IFAC MMM 2019 conference entitled "Modern Data Analytics for Control in Minerals Processing". The workshop and the material presented here are aimed at control engineers to explain the use of APC methods to improve process performance. Both academic and industrial control engineers attended the workshop, highlighting the relevance of the application of real-life process control problems.
Paper VI162-01.12
PDF · Video · Optimization of the Electric Efficiency of the Electric Steel Making Process (I)
Hernandez, Jesus	Acciai Speciali Terni
Onofri, Luca	Acciai Speciali Terni
Engell, Sebastian	TU Dortmund
Keywords: Process optimisation, Advanced process control, Process control applications Abstract: This paper reports numerical and practical results of an open-loop optimal control formulation that reduces the power consumption of the electric arc furnace (EAF) steel production process. A control vector parametrization technique is used to optimize the batch trajectory with the goal to minimize the energy losses of the process. First principles models are utilized to describe the dynamics, as well as the influence of the voltage and impedance set-points on the process. The results of the dynamic optimization provided a sequence of set-points (called a melting profile) that aligns well with intuition: the profile utilizes high power levels during the high efficiency stages of the process, and low power levels as the batch moves towards a more energy inefficient state. The benefits of the proposed optimized mode of operation are demonstrated by an experimental study case. An optimal melting profile was calculated and implemented in a fully operative ultra-high power EAF. For a series of 19 test batches, the energy consumption and the batch time of the process were reduced by 4.5% and 4.6% for one type of steel.
Paper VI162-01.13
PDF · Video · PH Prediction of a Neutral Leaching Process Using Adaptive-Network-Based Fuzzy Inference System and Reaction Kinetics (I)
Long, Shuang	Central South University
Li, Weijian	Central South University
Yang, Wei	Central South University
Sun, Bei	Central South University
Yang, Chunhua	Central South University
Gui, Weihua	Central South Univ
Keywords: Identification and modelling, Neural fuzzy modelling and control Abstract: pH value is an important index to measure the quality of product in neutral leaching process (NLP). However, due to the harsh production environment, there is almost no pH measuring device that can be applied to the site for a long time. To solve this problem, an effective pH prediction method for NLP is proposed in this paper. Firstly, the reaction kinetics of the NLP was researched, and the mechanism models under different running conditions were established. Secondly, ANFIS (Adaptive-Network-Based Fuzzy Inference System) is used to establish the data models of the process based on the idea of fuzzy training. Finally, according to the characteristics of two models and the "model mismatch" phenomenon in NLP, an effective model integration method based on fuzzy membership of running conditions is proposed, and the optimal integration was realized. Data show that the integrated model has better predictive performance than a single one, and pH predictive output of the model can also provide effective guidance for NLP.
Paper VI162-01.14
PDF · Video · Multivariable Feeding Control of Aluminum Reduction Process Using Individual Anode Current Measurement (I)
Shi, Jing	University of New South Wales
Yao, Yuchen	University of New South Wales
Bao, Jie	The University of New South Wales
Skyllas-Kazacos, Maria	University of New South Wales
Welch, Barry	University of New South Wales
Keywords: Advanced process control, Measurement and instrumentation, Process observation and parameter estimation Abstract: In the Hall-Héroult process, the alumina concentration and its distribution play an important role in determining the process efficiency, but it is difficult and costly to measure the concentration regularly. The recent advances in individual anode current measurement provide the possibilities to develop better control strategies and algorithms for alumina concentration. This paper presents a multivariable feeding control method, aiming to achieve a uniform distribution of alumina concentration, and hence improve cell operation. Also, the Extended Kalman Filter (EKF) is used to estimate the localized alumina concentration. The simulation results show that the proposed control strategy can significantly reduce the variations in alumina concentration compared to the traditional control method.

VI162-02
Artificial Intelligence in Mining, Mineral and Metal Processing	Regular Session
Chair: Frisk, Erik	Linköping University
Co-Chair: Aldrich, Chris	Curtin University
Paper VI162-02.1
PDF · Video · A Dynamic Firefly Algorithm-Based Fractional Order Fuzzy-PID Approach for the Control of a Heavy-Duty Gas Turbine
Haji Haji, Vahab	Young Researchers and Elite Club, Borujerd Branch, Islamic Azad
Fekih, Afef	Univ of Louisiana at Lafayette
Monje, C. A.	University CArlos III of Madrid
Keywords: Artificial intelligence, Neural fuzzy modelling and control, Control system design Abstract: Heavy duty gas turbines have long played an important role in energy production. Advanced turbine designs are expected to be highly efficient, able to quickly ramp the output power up and down and promptly tolerate loading variations without breaching emissions regulations. Control design plays an important role in ensuring high efficiency and performance of gas turbines. This paper proposes a fractional order PID approach for a heavy duty gas turbine. The controller gains are optimized using a Firefly algorithm enhanced with a dynamic parameter selection. This latter is used to speed up the convergence rate of the Firefly algorithm, optimize the gains of the fractional order PID and enhance the performance and efficiency of the gas turbine. The proposed approach is implemented to the speed loop of a gas turbine in order to maintain the output temperature and the turbine’s speed within their desired values during either a sudden change in loading or a drop in frequency. A comparison analysis with a standard Firefly algorithm-based approach was carried out to further assess the performance of the proposed evolved firefly algorithm-based approach.
Paper VI162-02.2
PDF · Video · Deep Learning in Mining and Mineral Processing Operations: A Review
Fu, Yihao	Curtin University
Aldrich, Chris	Curtin University
Keywords: Artificial intelligence, Neural networks in process control, Measurement and instrumentation Abstract: In this paper, the application of deep learning in the mining and processing of ores is reviewed. Deep learning is strongly impacting the development of sensor systems, particularly computer vision systems used in mining and mineral processing automation, where it is filling a gap not currently achievable by traditional approaches. To a lesser extent, deep learning is also being considered in the automation of decision support systems. There is significant scope for the application of deep learning to improve operations, but access to industrial data and big data infrastructure in operational environments are critical bottlenecks to the development and deployment of the technology.
Paper VI162-02.3
PDF · Video · Virtual Sensors of Nonlinear Industrial Processes Based on Neighborhood Preserving Regression Model
Wei, Chihang	Zhejiang University
Song, Zhihuan	Zhejiang University
Keywords: Monitoring of product quality and control performance, Data mining and multivariate statistics, Artificial intelligence Abstract: The micro perspective of manifold proximity would indicate local relationships with their unique spatial geometric distribution characteristics among the data samples, which are usually neglected by traditional data-driven virtual sensors. This would not guarantee a good prediction performance. In this paper, a regression model with localized construction named neighborhood preserving regression (NPR) model is proposed. It extends the unsupervised neighborhood preserving embedding (NPE) to the supervised form. The projection vector is learned from input process variables and the output quality variable, synchronously exploring the manifold structure of the input process variables for the dimension reduction and developing the regression relationship between the projected input process variables and the output quality variable. The model is developed as a novelly designed optimization whose analytical solution would be compactly and directly calculated without any iterative procedures. The effectiveness of the proposed algorithm is demonstrated by case studies carried out on a simulated penicillin production process.
Paper VI162-02.4
PDF · Video · Developing Variational Autoencoders with Differential Entropy Soft Sensor Models for Nonlinear Processes
Tanny, Dave	Chung Yuan Christian University
Chen, Junghui	Chung-Yuan Christian Univ
Wang, Kai	Central South University
Keywords: Neural networks in process control, Data mining and multivariate statistics, Industrial applications of process control Abstract: Developing a good soft sensor for prediction has been a major interest, given the time lag to obtain quality data. Deep learning based variational autoencoders (VAE) have been implemented in industrial plants because of their capacities in dealing with the complex stochastic nonlinearity with better probabilistic interpretation. However, unsupervised VAE is inapplicable to the prediction. This article proposes a nonlinear soft sensor, which is an extension of the VAE framework with differential entropy (VAE_DE) loss function to construct a prediction model. The proposed VAE_DE model structure allows all the available data to be used for training although the data consist of process-quality data pairs and/or solely process data. Also, VAE_DE enhances the prediction performance and its robustness through capturing the inter-correlations between process data and quality data in the nonlinear probabilistic model. Under the proposed framework, VAE_DE model can be used for quick quality estimates of process data with unavailable quality data. The prediction quality of the proposed method is testified through a numerical case and an industrial case.
Paper VI162-02.5
PDF · Video · Scheduling Knowledge Retrieval Based on Heterogeneous Feature Learning for Byproduct Gas System in Steel Industry
Liu, Yangyi	Dalian University of Technology
Lv, Zheng	Dalian University of Technology, Faculty of Electronics Informat
Zhao, Jun	Dalian University of Technology
Liu, Ying	Dalian University of Technology
Wang, Wei	Dalian University of Technology
Keywords: Neural networks in process control, Modeling and simulation of power systems, Maintenance scheduling and production planning Abstract: In the steel industry, the scheduling decision of byproduct gas system is made based on a large number of scheduling rules. It is important to establish an effective retrieval method for scheduling knowledge, for the process of scheduling decision is complex and the number of scheduling rules is large. In this paper, a retrieval method based on heterogeneous data feature learning is proposed, which could search the rules related to the current system state from a large number of scheduling knowledge, and help to make scheduling decisions. Considering that the data structures between the monitoring data and the scheduling knowledge texts are different, a feature learning method based on convolution neural network is proposed to extract the key features of the scheduling knowledge, and the full-connected neural network is used to extract the corresponding working condition features from the monitoring data. Due to the features of these two kinds of data are heterogeneous, a correlation analysis model for heterogeneous features based on canonical correlation analysis is constructed, and the features are matched by the matching of maximal canonical correlation. The experimental results showed that the proposed method could effectively extract relevant data features and solve the heterogeneous gaps between the real-time data and the knowledge texts, thus effectively retrieve the corresponding scheduling knowledge in different working conditions providing supports for the scheduling work.
Paper VI162-02.6
PDF · Video · Enhanced Big Data Approximating Control of an Industrial Paste Thickener
Langarica, Saúl	Pontificia Universidad Católica De Chile
Núñez, Felipe	University of California, Santa Barbara
Keywords: Advanced process control, Artificial intelligence, Industrial applications of process control Abstract: The Big Data revolution refers to using a large amount of data to improve decision making. In process control applications, the use of big data techniques has been restricted to complementing classical control schemes as model-based or PID approaches. This work focuses on a model-free purely data-driven control strategy known as Big Data approximating control (BDAC), which was recently introduced in the context of process control. In particular, this work proposes two modifications to the classical BDAC formulation and presents a real implementation of the enhanced BDAC technique to a real industrial paste thickener.
Paper VI162-02.7
PDF · Video · Automated Usage Characterization of Mining Vehicles for Life Time Prediction
Jakobsson, Erik	Epiroc Rock Drills AB
Frisk, Erik	Linköping University
Krysander, Mattias	Linköping University
Pettersson, Robert	Epiroc Rock Drills AB
Keywords: Measurement and instrumentation, Neural networks in process control, Maintenance scheduling and production planning Abstract: The life of a vehicle is heavily influenced by how it is used, and usage information is critical to predict the future condition of the machine. In this work we present a method to categorize what task an earthmoving vehicle is performing, based on a data driven model and a single standalone accelerometer. By training a convolutional neural network using a couple of weeks of labeled data, we show that a three axis accelerometer is sufficient to correctly classify between 5 different classes with an accuracy over 96% for a balanced dataset with no manual feature generation. The results are also compared against some other machine learning techniques, showing that the convolutional neural network has the highest performance, although other techniques are not far behind. An important conclusion is that methods and ideas from the area of Human Activity Recognition (HAR) are applicable also for vehicles.
Paper VI162-02.8
PDF · Video · A Comprehensive Evaluation Method for States Adjustment Priority of Drilling Process
Zhou, Yang	China University of Geosciences
Chen, Xin	China University of Geosciences
Wu, Min	China University of Geosciences
Cao, Weihua	China University of Geosciences
Keywords: Process observation and parameter estimation, Identification and modelling, Artificial intelligence Abstract: Drilling is an important means of obtaining resources. It is important to determine appropriate drilling states adjustment priority to guide operation of the drilling. However, the priority of drilling states adjustment is diffcult to determine because of the influence of multiple parameters. In this paper, a priority comprehensive evaluation method is developed to solve this problem. Firstly, support vector regression (SVR) method and long short-term memory (LSTM) neural network are introduced to build rate of penetration (ROP) prediction model and mud pit volume (MPV) prediction model, respectively. Then, the comprehensive evaluation vector is obtained by fuzzy comprehensive evaluation method based on analysis of formation drillability, rock characteristic, pump pressure variation, ROP and MPV fluctuations. Finally, the drilling states adjustment priority is determined by the principle of maximum membership and comprehensive analysis method. The simulation based on actual drilling data indicates that the proposed method can determine the adjustment priority and guide the operation of the drilling process.

VI162-03
Control in Mining, Mineral and Metal Processing	Regular Session
Chair: Lee, Dongjun	Seoul National University
Co-Chair: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Paper VI162-03.1
PDF · Video · Optimal Control of Plate Motion and Camber in a Reversing Rolling Mill
Pietschnig, Christopher	TU Wien
Ettl, Andreas	TU Wien, Christian Doppler Laboratory for Model-Based Process Co
Knechtelsdorfer, Ulrich	TU Wien, ACIN
Steinboeck, Andreas	Vienna University of Technology
Kugi, Andreas	Vienna University of Technology
Keywords: Advanced process control, Identification and modelling, Model predictive and optimization-based control Abstract: In plate rolling, reversing roughing mills are commonly used as a first processing step after casting. They are typically equipped with edger rolls for width reduction. During a rolling pass, lateral asymmetries like temperature gradients or thickness inhomogeneities can cause two major problems. The plate may rotate in the rolling gap and thus move in lateral direction. Another problem is that the plate may leave the mill stand with a cambered shape. In the worst case, these problems entail collisions with the mill stand or other equipment along the roller table. It is an essential control task to avoid such problems. In general, the exit thickness profile and the motion of the plate are controlled by adjusting the roll gap height. The latter has also an influence on the contour shape but, for active control of the plate width and contour shape, the use of edger rolls is more common. This is especially true if the roll gap adjustment is self-retaining, meaning that it cannot be adjusted during a rolling pass. In this work, such a roughing mill and its edger rolls are considered. A mathematical model for the motion and the camber of the plate is derived. Based on this model, a linear quadratic regulator (LQR) for both the plate motion and the resulting camber is developed. It uses the lateral forces of the edgers as control inputs. In a cascaded control structure, these forces are regulated by a subordinate admittance controller. The developed control system is validated in simulation studies.
Paper VI162-03.2
PDF · Video · Temperature Control for Induction Heating of Thin Strips
Roetzer, Florian	TU Wien
Aschauer, Alexander	TU Wien
Jadachowski, Lukasz	TU Wien
Steinboeck, Andreas	Vienna University of Technology
Kugi, Andreas	Vienna University of Technology
Keywords: Advanced process control, Process observation and parameter estimation, Identification and modelling Abstract: In this work, a model-based temperature controller for an induction heating system for moving thin metal strips is developed. The most significant disturbance of the system is an uncertain air gap geometry caused by flatness defects of the metal strip. A computationally expensive calculation of the electromagnetic field is avoided by using an equivalent circuit model and the energy balance. A thermal model of the moving strip is derived in the form of a convection-reaction equation and simplified to a linear time-invariant model. A 2-degrees-of-freedom controller is designed based on the simplified model and tested using a finite-element simulation model of the induction heating system. The simulations demonstrate that the proposed controller clearly outperforms standard feedback control strategies.
Paper VI162-03.3
PDF · Video · Tracking Control for Directional Drilling Systems Using Robust Feedback Model Predictive Control
Georgiou, Anastasis	Imperial College London
Evangelou, Simos	Imperial College
Jaimoukha, Imad M.	Imperial College London
Downton, Geoff	Schlumberger
Keywords: Advanced process control, Process optimisation, Identification and modelling Abstract: A rotary steerable system (RSS) is a drilling technology which has been extensively studied and used for over the last 20 years in hydrocarbon exploration and it is expected to drill complex curved borehole trajectories. RSSs are commonly treated as dynamic robotic actuator systems, driven by a reference signal and typically controlled by using a feedback loop control law. However, due to spatial delays, parametric uncertainties and the presence of disturbances in such an unpredictable working environment, designing such control laws is not a straightforward process. Furthermore, due to their inherent delayed feedback, described by delay differential equations (DDE), directional drilling systems have the potential to become unstable given the requisite conditions. This paper proposes a Robust Model Predictive Control (RMPC) scheme for industrial directional drilling, which incorporates a simplified model described by ordinary differential equations (ODE), taking into account disturbances and system uncertainties which arise from design approximations within the formulation of RMPC. The stability and computational efficiency of the scheme are improved by a state feedback strategy computed offline using Robust Positive Invariant (RPI) sets control approach and model reduction techniques. A crucial advantage of the proposed control scheme is that it computes an optimal control input considering physical and designer constraints. The control strategy is applied in an industrial directional drilling configuration represented by a DDE model and its performance is illustrated by simulations.
Paper VI162-03.4
PDF · Video · Effect of Direct Slicing on Precision Additive Manufacturing
Gohari, Hossein	UOIT
Barari, Ahmad	University of Ontario Institute of Technology
Kishawy, Hossam	UOIT
Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Keywords: Process optimisation, Advanced process control Abstract: An intelligent process planning for additive manufacturing (AM) is proposed in a paper presented at IFAC-IMS 2019 . An important aspect of the intelligent process planning is to directly slice CAD models to generate paths for AM machines. In this paper an experimental approach is carried out to investigate the improvements in the results of fabrication using direct slicing approach. In the proposed process, a CAD model is directly sliced and layer contours are extracted from the ideal surface. The curvature based parametrization using a multi-step method is implemented for finding the position of layers. The dimensional errors are investigated first by comparing the errors generated during the tessellation process with the ideal surfaces. Then the results of printing using paths generated from STL files and the ideal surface defined in an IGES file are compared. The results show considerable improvements in surface continuity and dimensional accuracy of the parts fabricated form the direct slicing approach.
Paper VI162-03.5
PDF · Video · Optimal Estimation and Feedforward Control of Strip-Longitudinal Hardness for Thickness Hunting Suppression of Tandem Cold Mill Process (I)
Lee, Hoyong	Seoul National University
Hur, Seung Min	POSTECH
Woo, Kyeongsik	Hyundai Steel
Lee, Dongjun	Seoul National University
Keywords: Measurement and instrumentation, Identification and modelling, Process observation and parameter estimation Abstract: Following the recent trend of weight reduction in car industry, producing high quality cold-rolled AHSS (advanced high-strength steel) strip becomes important. Thickness hunting (or fluctuation) problem can be more prominent for this cold-rolled AHSS strip making, which can stem from the non-uniformity of hot-rolled strip and can severely degrade product quality. In this paper, we propose a novel framework to estimate the strip-longitudinal hardness of the TCM (tandem cold mill) process and its feedforward control to substantially reduce the thickness hunting, while fully incorporating the interconnected nature and sensing sparsity of the TCM process. In particular, our estimator consists of the following two complementary loops: 1) fast real-time hardness estimation loop, which optimally fuses the process model and sensing information; and 2) slower constant process-parameter estimation loop via optimization utilizing the nonlinear process model and (stored/measured) sensor data. Efficacy of the proposed estimation and control frameworks are then validated with high-precision TCM process physics simulator.

VI162-04
Estimation, Monitoring, and Modeling in Mining, Mineral and Metal Processing	Regular Session
Chair: Huang, Biao	Univ. of Alberta
Co-Chair: Jadachowski, Lukasz	TU Wien
Paper VI162-04.1
PDF · Video · An Industrial Process Monitoring Scheme with Moving Window Slow Feature Analysis
Zhu, Li	Dalian University of Technology
Li, Zhe	Yangzhou University
Chen, Junghui	Chung-Yuan Christian Univ
Keywords: Data mining and multivariate statistics, Monitoring of product quality and control performance, Fault diagnosis and fault tolerant control Abstract: With the development of the modern industries, the requirement for comprehensive and effective monitoring scheme of the industrial production process is growing significantly. Conventional monitoring methods treat the deviations as the abnormities and thus result in the invalid monitoring results, because the dynamic information cannot be extracted accurately, which may be caused by the transient process or new operation conditions, and real faults cannot be separated from the normal process changes. To cope with this limitation, a moving window slow feature analysis is proposed in this paper. First, the temporal dynamic features of the industrial production process are extracted to separate the temporal dynamics from the steady state. Second, an adaptive monitoring strategy is presented to accurately acquire the normal changes of the production process, including the normal shift of operation conditions and the slow time-varying behaviors, through updating model parameters and monitoring statistics when a query sample comes. In this way, the real dynamic anomalies can be distinguished from the normal dynamic behaviors and reduce the false alarms effectively. Finally, the effectiveness and practicality are demonstrated through an evaporation process.
Paper VI162-04.2
PDF · Video · Gap Metric Based Performance Assessment of Subcool Control in Steam Assisted Gravity Drainage Wells
Alipouri, Yousef	University of Alberta
Raveendran, Rahul	University of Alberta
McClure, Ken	Spartan Controls Ltd
Mitchell, Warren Ross	Spartan Conrtols Ltd
Huang, Biao	Univ. of Alberta
Keywords: Identification and modelling, Advanced process control, Monitoring of product quality and control performance Abstract: Steam assisted gravity drainage (SAGD) is a widely adopted oil extraction technique for heavy oil reservoirs in Alberta, Canada. One of the common approaches by which the producers optimize the production from SAGD reservoirs is by controlling the emulsion level above the producer well bores, a strategy known as subcool control within the industry. In this study, we assess and compare performances of two subcool control strategies, one of which makes use of classic control strategy (PID) and the other is of advanced control strategy (model predictive controller (MPC)). As the controlled process in this case is a non-linear process, we propose a gap metric-based control performance assessment (CPA) method. By this method, the local models as well as their associated weights are determined using the gap metric. We show that the MPC-based strategy outperforms the PID loops-based strategy in subcool control application.
Paper VI162-04.3
PDF · Video · Pipe Clogging in the Fertilizer Industry, Opportunities and Challenges for Computer Vision
Dias, Jovania	Fundação Universidade Federal Do Rio Grande - FURG
Duarte, Marta	Universidade Federal Do Rio Grande
Coch, Victor	Federal University of Rio Grande
Duarte, Nelson	Universidade Federal Do Rio Grande
Menezes de Oliveira, Vinicius	Federal Univ of Rio Grande
Drews Jr, Paulo	Federal University of Rio Grande
Botelho, Silvia	Universidade Federal Do Rio Grande
Keywords: Identification and modelling, Artificial intelligence, Neural networks in process control Abstract: In the context of industry 4.0 where the use of new technologies is required to meet productivity and profitability demands, this paper addresses 3D scanning, thermal imaging and computer vision to identify pipe clogging caused by waste accumulation in the fertilizer industry. This paper presents a study using thermal images and the use artificial neural network to model the waste distribution in industrial pipes.
Paper VI162-04.4
PDF · Video · Identification of Fractional-Order Models for Condition Monitoring of Solid-Oxide Fuel Cell Systems
Dolenc, BoŠtjan	JoŽef Stefan Institute
Nusev, Gjorgji	Jozef Stefan Institute
Juricic, Dani	Jozef Stefan Inst
Subotic, Vanja	Graz University of Technology
Hochenauer, Christoph	Graz University of Technology
Boskoski, Pavle	Jozef Stefan Institute
Keywords: Identification and modelling, Condition Monitoring, Signal and identification-based methods Abstract: With rising market deployment the condition monitoring of solid oxide fuel cell systems is gaining particular importance. The conventional approaches mainly use electrochemical impedance spectroscopy based on the repeated sinusoidal perturbation over a range of frequencies. One of the notable weaknesses of the approach is excessively long perturbation time needed to properly evaluate the impedance curve. In this paper, we propose a time-efficient approach in which, a short, persistently exciting and small-amplitude perturbation is used to excite all the relevant system eigenmodes. A model structure from a class of linear fractional order models is selected to describe the perturbed dynamics and to account for anomalous diffusion processes in the cells. Then, the model parameters are estimated directly from measured input and output records. The paper presents a computationally efficient parameter estimation procedure in which the numerical issues of differentiation of noisy signals are alleviated by using modulating functions. In practice, that means a combination of filtering and application of conventional least squares. The approach is applied on a case of health assessment of solid oxide fuel cells.
Paper VI162-04.5
PDF · Video · State Affine Modeling and Observer Design for Hall-Héroult Process
da Silva Moreira, Lucas José	Université Grenoble Alpes
Fiacchini, Mirko	GIPSA-Lab, CNRS
Besancon, Gildas	Ense3, Grenoble INP
Ferrante, Francesco	Université Grenoble Alpes
Roustan, Herve Yves Guy Bernard Louis	Rio Tinto Aluminium Pechiney LRF
Keywords: Identification and modelling, Process observation and parameter estimation Abstract: Hall-Heroult process is a complex electrolysis procedure to produce aluminum. Due to the extreme operational conditions, it is difficult to continuously measure certain important values. This paper presents an approach to model and estimate the alumina concentration and anode-cathode distance based on the available measurements. Initially, a state affine model is obtained using a combination of physical-chemical relations and system identification. Then, a linear Kalman observer is designed to recover the desired signals. The proposed approach is validated on an industrial platform.
Paper VI162-04.6
PDF · Video · Systematic Calibration of a Simulated Semi-Autogenous/ball-Mill Grinding Circuit
Pérez-Garcia, Edgar-Manuel	Laval University
Bouchard, Jocelyn	Université Laval
Poulin, Eric	Laval University
Keywords: Identification and modelling, Process observation and parameter estimation, Advanced process control Abstract: With no doubt, modeling and simulation are powerful tools improving the performance of current optimisation and control strategies. At least in the mineral processing field, however, one of the major gaps in literature is that authors frequently skip specific details on the model calibration methodologies, mainly those concerning data acquisition and processing, calibration sequence, cost function formulation (including constraints), optimisation problem solution, parameter uncertainty, etc. As a contribution to that matter, this paper presents a detailed calibration procedure for a grinding circuit model from plant and laboratory data. The methodology integrates both a global search routine to avoid cost function local minima, and a Jack-knife resampling and recalibration technique to estimate the parameter confidence. The simulator will serve in future work for the coupling of separation processes, and thus the development of plant-wide model-based optimisation and control strategies.
Paper VI162-04.7
PDF · Video · Simulated Dataset to Verify the Overlapping and Segregation Problem on Computer Vision Granullometry of Fertilizers
Mendonça, Julio Cezar Oliveira	Universidade Federal Do Rio Grande
Alves Goulart, Douglas	Federal University of Rio Grande
Traversi, Nelson	FURG
Rodrigues, Ricardo	Universidade Federal Do Rio Grande
Estrada, Emanuel da Silva Diaz	Universidade Federal Do Rio Grande
Drews Jr, Paulo	Federal University of Rio Grande
Botelho, Silvia	Universidade Federal Do Rio Grande
Keywords: Measurement and instrumentation, Industrial applications of process control, Control of particulate processes Abstract: Fertilizers are an important tool for agriculture to correct the nutrients of the soil. Several analyses are made to guarantee the quality of this product. The particle size analysis indicates how well the fertilizer will penetrate in the soil by the size. The idea is to estimate the size of the grain during the production process. The production of fertilizers is a very complex production involving meters of pipes and conveyor belts where the grains are composed and transformed into the final product. The classic method to estimate the size is the mechanical sieving, an invasive and time-consuming method. A non-invasive and cost-effective method is the digital image processing (DIP) technique applied online in the production flow. In this case, a camera can be localized in the top of a conveyor belt capturing grain images directly during their composition. However, due to the number of grains (tons of grains) present on the image, this method depends on particle separation to avoid the particle segregation and grain overlapping on sampled images. In this work, we investigate how a digital image processing algorithm for particle size analysis of fertilizers is affected by the segregation and overlapping issues. We propose a grain surface simulator to create different scenarios of particle dispersion, a useful tool to speed up the process of creation of data-sets about fertilizers. The results show how the overlapping and segregation of grains influences in the particle size analysis by DIP, and how these interferences in extreme situations could generate biased results.
Paper VI162-04.8
PDF · Video · Estimating Ore Particle Size Distribution Using a Deep Convolutional Neural Network
Olivier, Laurentz Eugene	Moyo / University of Pretoria
Maritz, Michael Gerhard	University of Pretoria
Craig, Ian	University of Pretoria
Keywords: Measurement and instrumentation, Monitoring of product quality and control performance, Neural networks in process control Abstract: In this work the ore particle size distribution is estimated from an input image of the ore. The normalized weight of ore in each of 10 size classes is reported with good accuracy. A deep convolutional neural network, making use of the VGG16 architecture, is deployed for this task. The goal of using this method is to achieve accurate results without the need for rigorous parameter selection, as is needed with traditional computer vision approaches to this problem. The feed ore particle size distribution has an impact on the performance and control of minerals processing operations. When the ore size distribution undergoes significant changes, operational intervention is usually required (either by the operator or by an automatic controller).
Paper VI162-04.9
PDF · Video · State Estimation of Material Flow Rate in a Hot Rolling Mill for Steel Bars
Schaefer, Marc-Simon	University of Siegen
Wahrburg, Juergen	University of Siegen
Roth, Hubert	Univ Siegen
Keywords: Process observation and parameter estimation, Process optimisation, Identification and modelling Abstract: We present a solution for the estimation of the material flow rate for a hot rolling mill for steel bars. In this mill, a high number of uncertainties influences the rolling process. The partly unmeasured flow rate is a critical state for the plant stability. A meaningful estimation increases the operator efficiency. For this, a developed and adapted model of a six-stand finishing mill is used for optimization purpose. The flow rate is estimated with an moving horizon estimator (MHE) with the help of the CasADi framework. The main contribution is the adaption of a simulation model with the usage for online state estimation. The proposed solution is linked with real plant measurements.
Paper VI162-04.10
PDF · Video · An Interactive Visualization and Analysis Software Platform for the Heavy Plate Production Big Data
Zhang, Tongkang	Northeastern University
Ma, YuFei	Northeastern University
Xu, Depeng	Northeastern University
Liu, Changxin	Northeastern University
Ding, Jinliang	Northeastern University
Keywords: Monitoring of product quality and control performance, Data mining and multivariate statistics, Artificial intelligence Abstract: This paper develops an interactive visualization system, called iHPPVis, to analyze and locate the cause of quality-related faults for the heavy plates production. A time distribution of the products under different operating conditions based on Marey`s graph is presented and the process data for corresponding conditions to identify clusters and outliers is visualized, which utilizes the alternative dimension reduction algorithms. The crucial stage that leads to the abnormality of product quality is also diagnosed, and the data distribution of heterogeneous process variables in the crucial stage is exhibited. By integrating alternative algorithms with interactive visual analysis to achieve quality-related fault diagnosis, iHPPVis can facilitate the improvement of heavy plates quality. A case study is conducted to demonstrate its effectiveness and exhibit a pilot application of visual analytics for the heavy plates production.
Paper VI162-04.11
PDF · Video · Monitoring the Moisture Content in Pharmaceutical Batch Fluidized Bed Dryers Using Observer-Based Soft Sensors
Roseberry, Marc-Olivier	Université Laval
Gagnon, Francis	Université Laval
Desbiens, Andre	Universite Laval
Bouchard, Jocelyn	Université Laval
Lapointe-Garant, Pierre-Philippe	Pfizer
Keywords: Process observation and parameter estimation, Batch and semi-batch process control Abstract: Tablet manufacturing in the pharmaceutical industry involves batch fluidized bed drying for particle moisture removal. This paper introduces five approaches for moisture content monitoring, relying either on a complex phenomenological model or its simplified version. The first two soft sensors consist of open-loop estimators, i.e. they simply simulate the models fed by the manipulated variables. Three closed-loop moving horizon estimators based on the simplified model are also proposed for improved robustness. In the first one, the measurements of the inlet gas and particle temperatures feed back the soft sensor. The last two closed-loop observers additionally can take into account infrequent delayed moisture content measurements, such as at-line loss on drying analysis. A validation of the soft sensors is performed with experimental data collected on a pilot scale fluidized bed dryer. Results show that the closed-loop observer with the delayed moisture content measurements still has an accuracy that is equivalent (and sometimes better) than the complex phenomenological model.
Paper VI162-04.12
PDF · Video · In-Line Estimation of the Magnetization Curve of Steel Strips in a Continuous Induction Furnace
Jadachowski, Lukasz	TU Wien
Roetzer, Florian	TU Wien
Steinboeck, Andreas	Vienna University of Technology
Kugi, Andreas	Vienna University of Technology
Keywords: Process observation and parameter estimation, Identification and modelling, Advanced process control Abstract: An in-line parameter estimation strategy for continuous inductive heating of ferromagnetic steel strips is developed and investigated. During strip processing in a longitudinal flux induction furnace, the parameters of the magnetization curve (B-H curve) of the strip material are identified by a moving horizon estimator (MHE). The estimator uses a tailored 2D spatial-temporal model of the furnace which takes into account both the thermal and the electromagnetic subsystem. Other model parameters are identified in a scenario, where the magnetization curve of the strip is known. For model validation, the simulated strip temperature at the furnace exit is compared with measurements. To approximate the solution of the nonlinear Maxwell equations, the effective magnetization approach is applied. Here, a sophisticated hysteretic magnetization model is avoided in favor of the computing time, while magnetic saturation effects in the strip are still captured. The developed MHE is validated in a simulation scenario based on a strip with a known magnetization curve.
Paper VI162-04.13
PDF · Video · A Model Combining Seq2Seq Network and LightGBM Algorithm for Industrial Soft Sensor
Li, Yanrui	Zhejiang University
Yang, ChunJie	Zhejiang University
Zhang, Hanwen	Zhejiang University
Jia, Chao	Electronics Standardization Institute
Keywords: Process observation and parameter estimation, Neural networks in process control Abstract: As a key technology for industry 4.0, data-driven soft sensing plays an important role in the control and optimization of industrial processes. However, due to the large-scale, nonlinear and dynamic characteristics of industrial data, it is difficult to process industrial data. To solve these difficulties, a soft sensor modeling method based on sequence to sequence model and gradient boosting tree algorithm is developed. In this method, an unsupervised trained Seq2Seq model is used to extract dynamic features at first. Then a high-precision model based on LightGBM is constructed with dynamic features and original features as input. The developed method is validated on pulping data and compared with other machine learning methods such as RNN and SVR. The result shows the developed method has better performance.

VI163
Power and Process System - Power Plants and Power Systems
VI163-01 Advanced Condition Monitoring and Control in Microgrids   Invited Session, 5 papers
VI163-02 Advanced Modeling, Simulation and Control of Large Wind Energy Systems   Invited Session, 7 papers
VI163-03 Advances in Renewable Energy under Smart Grid Environment   Invited Session, 5 papers
VI163-04 Grid-Based Flexibility Integration within a South German Showcase   Invited Session, 5 papers
VI163-05 Intelligent Optimization in Smart Grid Operation and Control   Invited Session, 3 papers
VI163-06 Recent Advances in Distributed Control and Analysis for Microgrids   Invited Session, 6 papers
VI163-07 Wave Energy Systems: Control and Estimation   Invited Session, 14 papers
VI163-08 Approaching Floating Off-Shore Wind Turbines: Modelling, Optimization and Control   Open Invited Session, 4 papers
VI163-09 Control of Power Electronic Converters   Open Invited Session, 8 papers
VI163-10 Emerging Challenges and Directions of Advanced Battery Management   Open Invited Session, 13 papers
VI163-11 Modelling, Control and Optimization of Power Generation Systems: From Conventional to Renewable   Open Invited Session, 9 papers
VI163-12 Optimal Operation and Control in Smart Grids   Open Invited Session, 8 papers
VI163-13 Wind Turbine and Wind Farm Control: Control Challenges and Solutions   Open Invited Session, 10 papers
VI163-14 Estimation and Control for Batteries   Regular Session, 5 papers
VI163-15 Control of Renewable Energy Resources   Regular Session, 28 papers
VI163-16 Energy Management and Control in Microgrids   Regular Session, 24 papers
VI163-17 Modeling and Simulation of Power Systems   Regular Session, 22 papers
VI163-18 Optimal Operation and Control of Power Systems   Regular Session, 32 papers
VI163-19 Power Electronics Control   Regular Session, 13 papers
VI163-20 Stability of Power Systems   Regular Session, 24 papers

VI163-01
Advanced Condition Monitoring and Control in Microgrids	Invited Session
Chair: Zhang, Youmin	Concordia University
Co-Chair: Badihi, Hamed	Concordia University
Organizer: Zhang, Youmin	Concordia University
Organizer: Badihi, Hamed	Concordia University
Paper VI163-01.1
PDF · Video · Marine Current Turbine Imbalance Fault Detection Method Based on Angular Resampling (I)
Xie, Tao	Shanghai Maritime University
Wang, Tianzhen	Shanghai Maritime University
Diallo, Demba	University of Paris-Sud
Keywords: Condition Monitoring Abstract: Marine current power generation is increasingly attracting worldwide attention. However, mechanical imbalance fault often occurring when MCT blades are biofouled or corroded. This is a challenging problem due to the varying shaft rotating frequency (SRF) generate by the variable current flow. To deal with the imbalance fault, an angular resampling method based on the instantaneous power signal is proposed. This method monitors the output power of a variable-speed MCT generator and first processes the data using an angular resampling algorithm is to obtain a stationary signal. In the second step, a low-pass filter removes high frequencies and extract the fault characteristic. The simulation and the experiments verify the effectiveness of the proposed method for the MCT imbalance faults. The comparison with the motor current or voltage signature analysis has shown its superiority in terms of sensitivity to fault severity.
Paper VI163-01.2
PDF · Video · Youla Parameterization Based Control Performance Degradation Online Recovery of Single Inverter Control Systems in Microgrids: A PnP Approach (I)
Liu, Yannian	University Duisburg Essen
Hu, ChangBin	North China University of Technology
Lu, Heng	North China University of Technology
Ding, Steven X.	Univ of Duisburg-Essen
Li, Linlin	University of Science and Technology Beijing
Peng, Xin	East China University of Science and Technology
Wang, Yang	North China University of Technology
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Application of power electronics Abstract: In an inverter control system of smart microgrids, the control performance degradation due to load fluctuations, unbalanced loads and other factors, is one of the considerable factors affecting the output power quality. In this paper, a plug-and-play (PnP) technology based on Youla parameterization is proposed to achieve system performance recovery without modifying the existing controller. By 'plugging-in' a residual generator and a compensator, a dynamic feed-back of residual signals is embedded into the original inverter control system. In order to realize PnP, an online parameter estimation scheme of the compensator is developed. Finally, an inverter control system is applied to show the effectiveness of the proposed approach.
Paper VI163-01.3
PDF · Video · Short-Term Power Load Forecasting of GWO-KELM Based on Kalman Filter (I)
Chen, Xiaoyu	Beijing University of Chemical Technology
Wang, Yulin	Beijing University of Chemical Technology
Tuo, Jianyong	Beijing University of Chemical Technology
Keywords: Modeling and simulation of power systems, Smart grids, Power systems stability Abstract: Short-term power load forecasting plays a significant role in power system security management. The prediction model in this paper is the grey wolf optimization algorithm to optimize kernel extreme learning machine (GWO-KELM). First, the Kalman filter is used to reduce the noise for the random noise interference existing in the power load data. Then determine the input and output of the prediction model. In this paper, the ELM model of three different kernel functions is used for comparative experiments, and the mean absolute percentage error is used as the evaluation model index. It is concluded from the experimental results that the GWO-KELM model used in this article has the advantages of high prediction accuracy and strong generalization ability, so it is practicable to apply the model to short-term electric load forecasting.
Paper VI163-01.4
PDF · Video · Fault Diagnosis in Microgrids with Integration of Solar Photovoltaic Systems: A Review (I)
Jadidi, Saeedreza	Concordia University
Badihi, Hamed	Concordia University
Zhang, Youmin	Concordia University
Keywords: Smart grids, Applications of FDI and FTC, FDI for hybrid systems Abstract: Microgrids are essential components to help create the future electric grid which features a significant penetration of renewable and clean energy resources. However, a critical challenge in the protection of microgrids is the fault detection and diagnosis process, particularly in the presence of high uncertainties and varying topologies of microgrids. Faults in microgrids can cause instabilities, inefficient power generation, and other losses. Therefore, not only does it matter to understand various fault/failure modes and their root causes and effects, but it is also essential to develop real-time automated diagnosis tools to capture early signatures of fault evolution and enable proper mitigating actions. Given the significance of this issue, the present paper starts with a review of different failure modes occurring in various components of grid-connected photovoltaic systems, before offering a deeper review of the state of the art of fault diagnosis techniques specifically applied to solar photovoltaic systems in microgrids.
Paper VI163-01.5
PDF · Video · Passive Fault-Tolerant Model Predictive Control of AC/DC PWM Converter in a Hybrid Microgrid (I)
Jadidi, Saeedreza	Concordia University
Badihi, Hamed	Concordia University
Zhang, Youmin	Concordia University
Keywords: Smart grids, Design of fault tolerant/reliable systems, Applications of FDI and FTC Abstract: This paper aims at presenting a novel fault-tolerant control (FTC) scheme for an AC/DC pulse-width modulation (PWM) converter operating in a microgrid framework. A group of interconnected loads and distributed renewable energy resources such as wind farm, solar photovoltaic (PV) farm, and a battery energy storage are considered to form a microgrid. The control system for the AC/DC PWM converter aims at tolerating the fault effects due to power-loss malfunctions in the solar system. A passive fault-tolerant control scheme based on model predictive control (MPC) is proposed and the effectiveness of the designed scheme is demonstrated in an advanced microgrid benchmark model implemented in MATLAB/Simulink environment.

VI163-02
Advanced Modeling, Simulation and Control of Large Wind Energy Systems	Invited Session
Chair: Gambier, Adrian	Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems
Co-Chair: Fekih, Afef	Univ of Louisiana at Lafayette
Organizer: Gambier, Adrian	Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems
Organizer: Fekih, Afef	Univ of Louisiana at Lafayette
Organizer: Yang, Qinmin	Zhejiang University
Paper VI163-02.1
PDF · Video · Model-Free Optimization Scheme for Efficiency Improvement of Wind Farm Using Decentralized Reinforcement Learning (I)
Xu, Zhiwei	Tsinghua University
Geng, Hua	Tsinghua University
Chu, Bing	University of Southampton
Qian, Menghao	Tsinghua University
Tan, Ni	Tsinghua University
Keywords: Intelligent control of power systems, Control of renewable energy resources, Optimal operation and control of power systems Abstract: Wake interactions caused by the complex wakes between the turbines within a wind farm have significant adverse effect on the total power generation of the wind farm. To mitigate the effect of wake interactions and optimize the total power output of wind farm, this paper proposes a model-free control scheme using reinforcement learning by developing a decentralized Q learning method. The proposed approach guarantees that the output power of wind farm converges to the optimal total power under different wind conditions, and further ensures the gradual changes of control variables of wind turbines and thus avoids the unexpected sharp drop of the power generation performance of wind farm. Simulation results are provided to demonstrate the effectiveness of the proposed method.
Paper VI163-02.2
PDF · Video · A Fractional Order SMC Approach to Improve the Reliability of Wind Energy Systems During Grid Faults (I)
Musarrat, Md Nafiz	University of Louisiana at Lafayette
Fekih, Afef	Univ of Louisiana at Lafayette
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Design of fault tolerant/reliable systems Abstract: This paper proposes a fractional order sliding mode approach for the converters of a DFIG-based wind energy system. It aims at mitigating grid faults and improving power reliability in the presence of uncertainties and sudden load variations. Its reliance on fractional calculus results in smoother control actions and reduced chattering compared to standard SMC. It also implements a super-capacitor as energy storage for its faster response compared to a conventional battery. The proposed approach was validated using a DFIG-based wind energy system installed in a small-scale standalone power supply network. Its performance was further compared to that of a standard PI approach. The obtained results showed significant improvement in the performance of the wind energy system during grid faults.
Paper VI163-02.3
PDF · Video · Aerodynamic-Efficiency-Constrained Short-Term Frequency Support Control of Wind Turbine Generators (I)
Zhang, Zhengyang	Nanjing University of Science and Technology
Chen, Zaiyu	Nanjing University of Science and Technology
Yu, Guoqiang	Jiangsu Frontier Electric Technology Co. LTD
Zhang, Tianhai	Jiangsu Frontier Electric Technology Co. LTD
Yin, Minghui	Nanjing University of Science and Technology
Zou, Yun	Nanjing University of Science and TechnologyNanjing
Keywords: Control of renewable energy resources Abstract: Wind turbine generators (WTGs) can provide short-term frequency support at a frequency event via the stepwise inertial control (SIC) scheme. However, WTGs deviate from the maximum power point tracking (MPPT) operating point when SIC is implemented. A reasonable trade-off between the effectiveness of frequency support and the aerodynamic efficiency of WTGs should be reached in SIC parameters configurations. This paper proposes a modified SIC scheme where the SIC parameters are determined with consideration of wind energy capture losses. Simulation results validate that the proposed scheme improves the system frequency response without causing significant wind energy capture losses.
Paper VI163-02.4
PDF · Video · Optimization Control for Flapping Load Mitigation and Output Power Levelling of Wind Turbine (I)
Peng, Chao	University of Electronic Science and Technology of China
Zou, Jianxiao	School of Automation Engineering, University of Electronic Scien
Li, Yan	School of Automation Engineering, University of Electronic Scien
Geng, Hua	Tsinghua University
Zhang, Zhenzhen	College of Electrical & Information Engineering, Southwest Unive
Keywords: Control of renewable energy resources, Optimal operation and control of power systems, Control system design Abstract: Fatigue load affects the secure and stability of wind turbine operation. Flapping load is the main source of fatigue load endured by wind turbine operating above the rated wind speed. In this paper, a novel optimization control method for wind turbine flapping load mitigation and output power leveling is proposed. At first, wind turbine flapping load is analyzed and its calculation model is presented. Secondly, principle of the proposed control method is presented. Considering on coupling between flapping load and output power, a multi-objective optimization model and differential evolution based flapping load optimization controller are then designed. Additional PID-based output power leveling controller is employed to keep the output power leveling around the rated power. Finally, the effectiveness of the proposed control method is demonstrated by NREL 5MW wind turbine simulations.
Paper VI163-02.5
PDF · Video · Hardware-In-The-Loop Simulation and Control for Developing Very Large Wind Energy Systems (I)
Basilios, Rami	Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems
Gambier, Adrian	Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Control system design Abstract: Nowadays, simulation is a very important tool in order to design control systems of large wind turbines due to the fact that large complex wind turbines are not available as experimental set-up and down scaled systems show a completely different behaviour as the large ones. On the other hand, digital simulation is not enough to test control algorithms since the analysis of controllers in a real-time environment is essential. Hence, the combination of wind turbine simulation and direct digital real-time control becomes significant and this leads to the concept of Hardware-in-the-Loop (HiL) simulation and control. The present contribution proposes a Hardware-in-the-Loop configuration for the real-time simulation and control of large-sized wind turbines, where a well-known simulation tool is integrated with a control hardware that is often used in real wind turbines. Software and hardware choices are analysed, the implemented architecture is described and satisfactory results of a numerical experiment based on a 20 MW wind turbine is presented.
Paper VI163-02.6
PDF · Video · Adaptive Dual-Layer Sliding Mode Control for Wind Turbines with Estimated Wind Speed (I)
Jiao, Xuguo	Zhejiang University
Yang, Qinmin	Zhejiang University
Meng, Wenchao	Zhejiang University
Li, Siliang	Windmagics (Wuhan) Renewable Energy Technology Co., Ltd
Shen, Yun	Windmagics (Wuhan) Renewable Energy Technology Co., Ltd
Keywords: Control system design, Control of renewable energy resources Abstract: Under the circumstance of inaccurate and intermittent wind speed measurement,maximum power capture control of wind turbines is still a hot and challenging topic in wind power generation field. This paper aims at improving wind turbines' power production via an adaptive dual-layer sliding mode controller, with the help of estimated rotor effective wind speed. First, a novel effective wind speed estimation algorithm is proposed based on broad learning system (BLS), the training of which is completed by using data collected from the supervisory control and data acquisition (SCADA) system. Further, the trained BLS can deliver the estimated wind speed in an online manner to determine the optimal generator power command for maximum wind power extraction. In addition, a low-pass filter is designed to smooth the output, which is beneficial for drive train systems' mechanical loads. Thereafter, a sliding mode control theory based maximum power point tracking (MPPT) controller is developed. To compensate for the uncertainties and mitigate the chattering phenomena, dual- layer adaptation laws are designed for the sliding mode controller. Finally, the effectiveness of the proposed control scheme is validated and demonstrated by the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) tool.
Paper VI163-02.7
PDF · Video · Exploiting Bend-Twist Coupling in Wind Turbine Control for Load Reduction (I)
Wiens, Marcus	Fraunhofer Institute for Wind Energy Systems IWES
Meyer, Tobias	Fraunhofer Institute for Wind Energy Systems
Wenske, Jan	Fraunhofer Institute for Wind Energy Systems IWES
Keywords: Control system design, Control of renewable energy resources, Instrumentation and control systems Abstract: The ever-increasing dimensions of wind turbines are ssociated with higher structural loads. Therefore, there is a demand for advanced load reduction techniques. In the design of rotor blades, the bend-twist coupling effect is used for passive load reduction. This research shows how this effect can be augmented with active load reduction through controls that exploit bendtwist coupling. The twist rate of the rotor blades is utilized for gust detection. In addition to regular closed-loop pitch control, the twist rate is used to adjust the collective pitch angle using feedforward control. Extreme loads for flap-wise bending moment can be reduced on average by up to 6 % and tower acceleration is reduced by 15 %. Overall, this method is suitable for reducing extreme loads while maintaining fatigue damage compared to the reference case.

VI163-03
Advances in Renewable Energy under Smart Grid Environment	Invited Session
Chair: Mori, Hiroyuki	Nakano Campus, Meiji University
Co-Chair: Nohara, Daisuke	Central Research Institute of Electric Power Industry
Organizer: Mori, Hiroyuki	Nakano Campus, Meiji University
Paper VI163-03.1
PDF · Video · Arbitrary Polynomial Chaos Based Simulation of Probabilistic Power Flow Including Renewable Energies (I)
Iwamura, Kazuaki	Waseda University
Katagiri, Yuki	Waseda University
Nakanishi, Yosuke	Waseda University
Takano, Sachio	Fuji Electric Co., Ltd
Suzuki, Ryohei	Fuji Electric Co., Ltd
Keywords: Modeling and simulation of power systems, Smart grids Abstract: In this paper, a method is introduced for probabilistic power flow calculations based on arbitrary polynomial chaos. For the polynomial chaos, orthogonal polynomial sets are used to represent the uncertainties of renewable power generation, and these orthogonal polynomials are generated from actual data. The aforementioned method is applied to probabilistic power flow calculations, and its applicability is confirmed in application to an actual transmission network. The calculation time and accuracy achieved using the arbitrary polynomial chaos method are compared with those achieved using the popular Monte Carlo method. The results show that the calculation speed is 246–680 times greater than that with the direct Monte Carlo method, while the accuracy is almost same.
Paper VI163-03.2
PDF · Video · Probabilistic Wind Power Prediction Based on Ensemble Weather Forecasting (I)
Nohara, Daisuke	Central Research Institute of Electric Power Industry
Ohba, Masamichi	Central Research Institute of Electric Power Industry
Watanabe, Takeshi	Central Research Institute of Electric Power Industry
Kadokura, Shinji	Central Reseach Institute of Electric Power Industry
Keywords: Real time simulation and dispatching, Smart grids, Control of renewable energy resources Abstract: Despite the growing popularity of the use of renewable (e.g., wind and solar) energy, the volatility of the corresponding sources, partially due to the natural variability of weather conditions, hinders their further commercialization and necessitates the development of cost-effective and easily implementable predictive models such as those that simulate power generation. Despite the recent increase in the accuracy of numerical weather prediction models, most of them still face problems such as the poor predictability of wind ramp event intensity, location, and timing. However, these challenges can be addressed through the use of probabilistic modeling. Herein, we present a probabilistic wind power prediction method based on a numerical weather prediction model, using a power curve empirically estimated from the relationship between area-averaged wind speed and area-integrated wind power generation to project wind power while accounting for the inherent uncertainty associated with the power curve. The established probabilistic prediction method exhibits high statistical consistency and reliably captures the confidence interval of wind power variability; thus, it is well suited for ramp event prediction.
Paper VI163-03.3
PDF · Video · Impact of Power Output Curtailment Control of Photovoltaic Power Generation on Grid Frequency (I)
Kato, Takeyoshi	Nagoya Univ
Imanaka, Masaki	Nagoya University
Kurimoto, Muneaki	Nagoya Univ
Sugimoto, Shigeyuki	Chubu Electric Power Co., Inc
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Optimal operation and control of power systems Abstract: In a power system with high penetration photovoltaic power (PV) generation, the curtailment of PV power will be necessary to maintain a power supply and demand balancing. PV power can be effectively utilized by controlling the curtailment at a certain interval based on forecasting and nowcasting of aggregated power output of PV systems. By using an optimum unit commitment scheduling model, this paper assesses the effect of a scheduled curtailment control at 30 min interval on the reduction of curtailed PV power in comparison with a fixed curtailment control throughout a day. Then, by using an electricity supply - demand simulation model, this paper discusses the effect of ramp rate control of curtailed PV power for avoiding the steep change in grid frequency due to the stepwise change in curtailment hence the steep change in residual electricity load.
Paper VI163-03.4
PDF · Video · Integration of Deep Boltzmann Machine and Generalized Radial Basis Function Network for Photovoltaic Generation Output Forecasting (I)
Ogawa, Shota	Meiji University
Mori, Hiroyuki	Nakano Campus, Meiji University
Keywords: Control of renewable energy resources, Intelligent control of power systems, Modeling and simulation of power systems Abstract: In this paper, an efficient method is proposed to deal with photovoltaic generation output forecasting with Deep Boltzmann Machine. In recent years, the penetration of photovoltaic generation has been widely spread in the world due to clean energy. However, it has brought about uncertainties for generation schedules in a way that power system operators have to consider the significant variations of generation. As a result, the forecasting model of photovoltaic generation output with high accuracy is required in the industries. This paper proposes a Deep Neural Network (DNN) model that integrates Deep Boltzmann Machine with Generalized Radial Basis Function Network (GRBFN) of Artificial Neural Network (ANN). The proposed model is tested for real data of photovoltaic generation output.
Paper VI163-03.5
PDF · Video · An Efficient Method for Wind Power Generation Forecasting by LSTM in Consideration of Overfitting Prevention (I)
Ookura, Soichiro	Meiji University
Mori, Hiroyuki	Nakano Campus, Meiji University
Keywords: Control of renewable energy resources, Smart grids, Modeling and simulation of power systems Abstract: This paper proposes an efficient method for wind power generation forecasting by Long Short Term Memory (LSTM) of Deep Neural Network (DNN). It is one of recurrent neural networks that make use of past output of the network, but replaces hidden layers of the conventional networks with the LSTM Block with memory and three gates of input, output and forget. Artificial and Deep Neural Networks are inclined to overfit leaning data in learning process. This paper proposes a modified LSTM that considers to prevent LSTM from overfitting with two strategies. One is Dropout to exclude some nodes randomly and change network topology while the other is Weight Decay that evaluates smaller weights between neurons. The effectiveness of the proposed method is demonstrated for real data of wind power generation.

VI163-04
Grid-Based Flexibility Integration within a South German Showcase	Invited Session
Chair: Lens, Hendrik	University of Stuttgart
Co-Chair: Weissbach, Tobias	TransnetBW GmbH
Organizer: Enzenhoefer, Rainer	TransnetBW
Organizer: Lens, Hendrik	University of Stuttgart
Organizer: Weissbach, Tobias	TransnetBW GmbH
Paper VI163-04.1
PDF · Video · Continuous Learning of Deep Neural Networks to Improve Forecasts for Regional Energy Markets (I)
He, Yujiang	University of Kassel
Henze, Janosch	University of Kassel
Sick, Bernhard	University of Kassel
Keywords: Smart grids, Intelligent control of power systems, Modeling and simulation of power systems Abstract: Germany generated 54.5% of electricity from renewable energy in March 2019, according to the data collected by the Fraunhofer Institute for Solar Energy Systems. Forecasting power generation and consumption play an essential role in establishing a regional smart energy market. Numerous researches contributed to the field of power forecasting using machine learning and deep learning technologies. However, developing and perfecting energy markets lead to an unavoidable problem of adjusting the architectures of neural networks to adapt to new situations, e.g., new consumers or producers in the power grid. Another critical challenge is to learn new knowledge from the sequentially collected measurements efficiently and how to integrate the new information into the current neural network model. When retrained for a new task with a regular training process, neural network models could perform poorly on the previously learned tasks, which is referred to as the catastrophic forgetting problem. In this article, we design two real-world continuous learning scenarios for those challenges. The scenarios are based on the historical power data, which are obtained from a regional power grid in Germany. The results show that well-known continuous learning algorithms can be used to improve power forecasts with a sequential data stream in such scenarios. We believe that the work is the first step towards establishing an adaptively updating forecast system to assist the highly dynamic intelligent energy markets.
Paper VI163-04.2
PDF · Video · Top-Down Modelling of Distributed Fexibility for Usage at Higher Voltage Levels (I)
Estermann, Thomas	FfE Munich
Köppl, Simon	FfE Munich
Ostermann, Adrian	FfE Munich
Keywords: Modeling and simulation of power systems, Smart grids Abstract: The number of units on both the generation and consumption sides of the electric sector continue to increase over the course of the energy transition, especially at lower voltage levels. Many of these systems (e.g. heat pumps or battery storage systems) offer the potential to provide fexibility, although the low power level of single units limits their network effect when operated individually. By modelling aggregations of the respective exibility type, a remarkable fexibility potential can be made available for the grid operator to use for e.g. congestion management at a point upstream.
Paper VI163-04.3
PDF · Video · Test and Evaluate an Automated Low Voltage Grid Management System through Utilization of CLS-Gateways to Control a Decentralized Energy Resource (I)
Ebe, Falko	Ulm University of Applied Sciences
Morris, Jeromie	University of Applied Sciences Ulm
Chen, Shuo	University of Applied Sciences Ulm
Idlbi, Basem	Technische Hochschule Ulm
Graeber, Dietmar	University of Applied Sciences Ulm
Heilscher, Gerd	University of Applied Sciences Ulm
Keywords: Smart grids, Test and documentation, Distribution automation Abstract: The implementation of a Smart Meter infrastructure in Germany offers the opportunity to gather grid measurements in the low voltage grid and control small scale systems like PV systems (Photovoltaik). The actual control of decentralized energy systems can be realized via the CLS (Controllable-Local-System)-Gateway which is implemented as a second device. Advanced grid management systems can use the Smart Meter/CLS-Infrastructure for grid optimization to prevent grid asset overloading and voltage band violation. A second use case is the "automated actions request" by superimposed/overlaid medium & high voltage grid operators. This contribution will present the results from laboratory testing utilizing the Software-/Controller-in-the-Loop methodology.
Paper VI163-04.4
PDF · Video · Optimal Control of Distributed Energy Generation & Storages for Flexibility Provision on the Residential Level (I)
Wille-Haussmann, Bernhard	Fraunhofer ISE
Selinger-Lutz, Oliver	Fraunhofer ISE
Keywords: Control of renewable energy resources, Optimal operation and control of power systems, Smart grids Abstract: Increased adoption of decentralized, variable renewable energy generators will require improved and up-dated methods for managing the increasingly complex energy balancing procedures in future networks. One way to aid in accomplishing this is by exploiting demand side management opportunities available from operating flexibilities and storages available in micro grids. This research aims to quantify and visualize the maximum potential deviations in grid experienced power flows, referred to as flexibility corridors found in residential micro gird systems which could be accessible for use by grid services. To achieve this, a model is developed through sets of mixed integer linear program- ming formulations, representing a residential PV-CHP micro grid with thermal and electric storages. An energy management system is operated using a rolling horizon optimization approach. Flexibilities are then evaluated based on the predicted state of certain critical components in the system. The system is then resimulated reflecting scenarios in which grid operators signal systems to exploit the entirety of both positive and negative flexibility options. Reactions to the system after such events are then analysed and cost modifications in the altered system operations are deter-mined.
Paper VI163-04.5
PDF · Video · Coordinated Dynamic Use of Dispersed Flexibility to Maximize the Time-Variant Aggregated Potential for Redispatch (I)
Müller, Benjamin	University of Stuttgart
Lens, Hendrik	University of Stuttgart
Keywords: Optimal operation and control of power systems, Real time simulation and dispatching, Modeling and simulation of power systems Abstract: During recent years, the European interconnected transmission system has been affected by a significant increase of grid congestion. Nowadays, large-scaled power plants are providing redispatch power, but will be phased out in coming decades. Besides this development, new technologies like renewable energies or battery storage systems emerged in power systems. These technologies are typically small-scaled, dispersed and connected to distribution systems. Dispersed generation units, storage systems, electric vehicles, and controllable loads may be capable of providing flexible power. Coordinated dynamic use of flexible power from large numbers of small units could become a key contribution to cope with grid congestion in the future. The paper presents a methodology to determine the maximum, time-variant potential for redispatch of distributed units aggregated in a virtual power plant. It is based on parameter-based optimization and takes into account dynamic and energy capacity related constraints. Moreover, the constraints of distribution and transmission systems as well as the impact on power flows is considered and investigated for multiple scenarios by using linearized power flow sensitivities.

VI163-05
Intelligent Optimization in Smart Grid Operation and Control	Invited Session
Chair: Majanne, Yrjö	Tampere University
Co-Chair: Grillo, Samuele	Politecnico Di Milano
Organizer: Mori, Hiroyuki	Nakano Campus, Meiji University
Paper VI163-05.1
PDF · Video · Evaluation of Renewable Energy Project by Risk Sensitive Value Measure Method (I)
Miyauchi, Hajime	Kumamoto University
Yoshimoto, Daigo	Kumamoto University
Koga, Takahiro	Kumamoto University
Izutsu, Harumi	Kumamoto University
Misawa, Tetsuya	Nagoya City University
Keywords: Analysis and control in deregulated power systems, Smart grids Abstract: Due to the uncertainty of electric power price and output of renewable energies, investors are facing risks when they invest renewable energy. Net Present value (NPV) is one of conventional asset evaluation methods, however, NPV cannot evaluate risk correctly because it evaluates only the expected value of future cash flow. Then, we have already proposed to use asset evaluation using Risk Sensitive Value Measure (RSVM). As RSVM evaluates the probabilistic distribution of random NPV considering uncertainties, the attitude of investors towards the risk can be evaluated through utility function. In this paper, we present the evaluation of the renewable energy project. RSVM can be made clear the optimum and the maximum investment for renewable energy project. Furthermore, RSVM also can select the location of wind turbine generator project by evaluating the distribution of wind velocity even if the average wind velocity is almost similar. Thus, we make clear the effectiveness of RSVM for renewable energy project.
Paper VI163-05.2
PDF · Video · Simple Estimation of Operating Lifetime for Electrical Distribution Components Utilizing Their Inspection and Maintenance Records (I)
Takano, Hirotaka	Gifu University
Nakae, Kan	Gifu University
Tokunaga, Tatsuya	Kansai Transmission and Distribution, Inc
Hayashi, Toshihiro	Kansai Transmission and Distribution, Inc
Keywords: Smart grids, Intelligent control of power systems, Condition Monitoring Abstract: Operators of electrical power distribution systems inspect electrical components and evaluate their conditions to sustain the reliability of power supply. These results have been accumulated in databases and utilized to the judgement of maintenance necessity. The authors propose to utilize the inspection and the maintenance records in estimation of operating lifetime of newly constructed electrical components in the distribution systems. A decision tree learning analyzes the relationship between the initial information and the operating lifetime obtained by the inspection and the maintenance records, and as a result, constructs a tree-like model. The resulting model can estimate the operating lifetime of newly constructed components using their initial information only. Usefulness of the estimation method is verified on actual records stored in a Japanese electric power company. In addition, factors that have strong influence on the operating lifetime are specified by the feature of decision tree.
Paper VI163-05.3
PDF · Video · An Optimization Problem for Day-Ahead Planning of Electrical Energy Aggregators (I)
Conte, Francesco	University of Genova
Saviozzi, Matteo	University of Genova
Grillo, Samuele	Politecnico Di Milano
Keywords: Smart grids, Intelligent control of power systems, Optimal operation and control of power systems Abstract: The widespread diffusion of distributed energy resources, especially those based on renewable energy, and energy storage devices has deeply modified power systems. As a consequence, demand response, the ability of customers to respond to regulating signals, has moved from large high-voltage and medium-voltage end-users to small, low-voltage, customers. In order to be effective, the participation to demand response of such small players must be gathered by aggregators. The role and the business models of these new entities have been studied in literature from a variety of viewpoints. Demand response can be clearly applied by sending a dedicated price signal to customers, but this methodology cannot obtain a diverse, punctual, predictable, and reliable response. These characteristics can be achieved by directly controlling the loads units. This approach involves communication problems and technological readiness. This paper proposes a fully decentralized mixed integer linear programming approach for demand response. In this framework, each load unit performs an optimization, subject to technical and user-based constraints, and gives to the aggregator a desired profile along with a reserve, which is guaranteed to comply with the constraints. In this way, the aggregator can trade the reserve coming from several load units, being the only interface to the market. Upon request, then, the aggregator communicates to the load units the modifications to their desired profiles without either knowing or caring how this modification would be accomplished. The effectiveness is simulated on 200 realistic load units.

VI163-06
Recent Advances in Distributed Control and Analysis for Microgrids	Invited Session
Chair: Kölsch, Lukas	Karlsruhe Institute of Technology (KIT)
Co-Chair: Raisch, Joerg	Technische Universitaet Berlin
Organizer: Hohmann, Soeren	KIT
Organizer: Raisch, Joerg	Technische Universitaet Berlin
Organizer: Krebs, Stefan	Karlsruhe Institute of Technology
Organizer: Kölsch, Lukas	Karlsruhe Institute of Technology (KIT)
Paper VI163-06.1
PDF · Video · Sequence Impedance-Based Stability Analysis of AC Microgrids Controlled by Virtual Synchronous Generator Control Methods (I)
Dokus, Marc	Leibniz University Hannover
Stallmann, Frederik	Leibniz University Hannover
Mertens, Axel	Leibniz Universität Hannover
Keywords: Power systems stability, Smart grids, Modeling and simulation of power systems Abstract: In this paper, sequence impedance-based modelling is applied to two different grid-forming converters which are based on virtual synchronous generator (VSG) concepts including a dual loop voltage control. The considered controls only differ in the feedback design (PLL-driven or not) of the power-related control loop. In general, impedance modelling is a suitable method to analyse stability issues related to converter controls for use in larger power networks. In this work, the analytical model of a voltage-controlled converter is illustrated first. Sequence impedance models are then proposed, which do not only predict the effect of two different VSG controls on the system’s stability, but also reveal its frequency coupling effect and analogy to the classical droop control. In addition, a small power system consisting of VSG-controlled converters is analysed by their equivalent output impedances. These models and the stability of the converter cluster are validated by time-domain simulations and laboratory experiments. The close correlation between sequence impedance model, time-domain simulation and experimental results confirms the effectiveness of the derived models.
Paper VI163-06.2
PDF · Video · Distributed Frequency and Voltage Control for AC Microgrids Based on Primal-Dual Gradient Dynamics (I)
Kölsch, Lukas	Karlsruhe Institute of Technology (KIT)
Wieninger, Katharina	Karlsruhe Institute of Technology (KIT)
Krebs, Stefan	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Optimal operation and control of power systems, Control system design, Intelligent control of power systems Abstract: With the gradual transformation of power generation towards renewables, distributed energy resources are becoming more and more relevant for grid stabilization. In order to involve all participants in the joint solution of this challenging task, we propose a distributed, model-based and unifying controller for frequency and voltage regulation in AC microgrids, based on steady-state optimal control. It not only unifies frequency and voltage control, but also incorporates the classic hierarchy of primary, secondary and tertiary control layers with each closed-loop equilibrium being a minimizer of a user-defined cost function. By considering the individual voltage limits as additional constraints in the corresponding optimization problem, no superordinate specification of voltage setpoints is required. Since the dynamic model of the microgrid has a port-Hamiltonian structure, stability of the overall system can be assessed using shifted passivity properties. Furthermore, we demonstrate the effectiveness of the controller and its robustness against fluctuations in active and reactive power demand by means of numerical examples.
Paper VI163-06.3
PDF · Video · Passivity Conditions for Plug-And-Play Operation of Nonlinear Static AC Loads (I)
Strehle, Felix	Karlsruhe Institute of Technology (KIT)
Malan, Albertus Johannes	Karlsruhe Institute of Technology (KIT)
Krebs, Stefan	Karlsruhe Institute of Technology
Hohmann, Soeren	KIT
Keywords: Power systems stability, Control system design, Smart grids Abstract: The complexity arising in AC microgrids from multiple interacting distributed generation units (DGUs) with intermittent supply behavior requires local voltage-source inverters (VSIs) to be controlled in a distributed or decentralized manner at primary level. In (Strehle et al., 2019), we use passivity theory to design decentralized, plug-and-play voltage and frequency controllers for such VSIs. However, the stability analysis of the closed-loop system requires a load-connected topology, in contrast to real grids where loads are arbitrarily located. In this paper, we expand our former approach by considering the more realistic and general case of nonlinear static AC loads (ZIP and exponential) at arbitrary locations within an AC microgrid. Investigating the monotonicity of differentiable mappings, we derive sufficient inequality conditions for the strict passivity of these nonlinear static AC loads. Together with our plug-and-play VSI controller, this allows us to use passivity arguments to infer asymptotic voltage and frequency stability for AC microgrids with arbitrary topologies. An illustrative simulation validating our theoretical findings concludes our work.
Paper VI163-06.4
PDF · Video · A Performance Comparison of PLL Implementations in Low-Inertia Power Systems Using an Observer-Based Framework (I)
Rueda-Escobedo, Juan G.	Brandenburg University of Technology Cottbus-Senftenberg
Tang, Shiqing	University of Shanghai for Science and Technology
Schiffer, Johannes	Brandenburg University of Technology
Keywords: Power systems stability, Control of renewable energy resources, Control system design Abstract: Phase-locked loop (PLL) implementations are critical components for the control and operation of grid-connected converters. Hence, they have to exhibit a highly reliable behavior under a wide range of operating conditions. Available implementations and performance analyses mainly focus on the impact of unbalances and harmonics. However, in converter-dominated low-inertia power systems an additional important type of perturbation will arise from fast variations in the grid frequency. Motivated by this, we show that the structure of several popular PLL implementations is closely related to that of high-gain observers and, by using this framework, provide a tuning criterion for the PLL gains that mitigates the impact of the rate of change of the frequency (RoCoF) on the estimation performance. This criterion is then used to conduct a numerical comparison of four popular PLL implementations under three distorted conditions: unbalances, harmonics and frequency variations.
Paper VI163-06.5
PDF · Video · Iterative Learning Control in Prosumer-Based Microgrids with Hierarchical Control (I)
Strenge, Lia	Technische Universität Berlin, EN 11
Jing, Xiaohan	Technische Universität Berlin
Boersma, Ruth	TU Berlin
Schultz, Paul	Potsdam Institute for Climate Impact Research
Hellmann, Frank	Potsdam Institute for Climate Impact Research
Kurths, Juergen	Humboldt University of Berlin
Raisch, Joerg	Technische Universitaet Berlin
Seel, Thomas	Technische Universitaet Berlin
Keywords: Intelligent control of power systems, Control of distributed systems, Control of large-scale systems Abstract: Power systems are subject to fundamental changes due to the increasing infeed of renewable energy sources. Taking the accompanying decentralization of power generation into account, the concept of prosumer-based microgrids gives the opportunity to rethink structuring and operation of power systems from scratch. In a prosumer-based microgrid, each power grid node can feed energy into the grid and draw energy from the grid. The concept allows for spatial aggregation such that also an interaction between microgrids can be represented as a prosumer-based microgrid. The contribution of this work is threefold: (i) we propose a decentralized hierarchical control approach in a network including different time scales, (ii) we use iterative learning control to compensate periodic demand patterns and save lower-layer control energy and (iii) we assure asymptotic stability and monotonic convergence in the iteration domain for the linearized dynamics and validate the performance by simulating the nonlinear dynamics.
Paper VI163-06.6
PDF · Video · Agent Based Modeling in Energy Systems: Parametrization of Coupling Points (I)
Shahbakhsh, Arash	Group Energy Informatics, Leibniz University Hannover
Nieße, Astrid	Group Energy Informatics, Leibniz University Hannover
Keywords: Control of distributed systems, Modeling and simulation of power systems, Smart grids Abstract: Future multimodal energy systems (MES) including heat, gas and electricity sectors will be equipped with control systems, which have some degree of autonomy, and are adaptive to their environment. Smart control systems are able to communicate with other systems and other autonomous controllers. The resulting systems can be analyzed as a complex adaptive system (CAS), which has been successfully investigated using agent based modeling (ABM) in the past. In this study, the operational behavior of a MES using different agent parametrizations for coupling points is investigated. These properties can be categorized as fast-acting agents and slow-acting as well agents with and without dead-band and saturation. The result of every scenario points out the temporal evolution of pressure in gas , temperature in heat and voltage in electricity sectors. The bottom-up perspective allocates agents' parametrizations to the whole system behavior. The study shows the effect of dead-band, saturation and the gain of coupling points controller on the MES. In addition, the role of observers in analyzing systems in CAS paradigm is discussed. The results pave the way for setting up proper agents' parameters and designing proper observers.

VI163-07
Wave Energy Systems: Control and Estimation	Invited Session
Chair: Ringwood, John	Maynooth University
Co-Chair: Henriques, Joao	IDMEC/Instituto Superior Tecnico
Organizer: Ringwood, John	Maynooth University
Paper VI163-07.1
PDF · Video · The Impact of Modelling and Prediction Errors on the Performance of Optimally Controlled Multi-DOF Wave Energy Converters (I)
Hillis, Andrew John	University of Bath
Yardley, Joshua	University of Bath
Plummer, Andrew	University of Bath
Chapman, John	Marine Power Systems Ltd
Keywords: Control of renewable energy resources Abstract: A well-conceived real-time control strategy can greatly increase the captured power for a wave energy converter (WEC). Optimal strategies rely on a dynamic model of the WEC and prediction of the wave excitation force several seconds into the future. Both the modelling and prediction processes are subject to errors. This paper investigates the impact of these errors on the performance of a multi-DOF submerged point absorber WEC. A state-space model of the system in its nominal position is derived and used by the control strategy. This idealised system is tested in multiple numerically generated irregular sea states with perfect estimation and prediction of the excitation force assumed. An optimally tuned passively damped system is used as a performance benchmark. The idealised system under optimal control is capable of more than doubling the captured power compared to the passively damped system. The control strategy is then applied to a full kinematic model of the WEC in the WEC-Sim environment. Real-time estimation and prediction of the excitation forces and constraints on motion and control force are also included. Under these more realistic conditions, the power gain is a more modest 68% at best across the tested sea states, and for one tested sea state there is no power gain compared to the passive system. Overall the gains are still significant and demonstrate the potential benefits of such control strategies for application to multi-DOF WECs, though more robust alternatives may be preferable.
Paper VI163-07.2
PDF · Video · Wave Energy Control: Status and Perspectives 2020 (I)
Ringwood, John	Maynooth University
Keywords: Control of renewable energy resources, Control system design Abstract: Wave energy has a significant part to play in providing a carbon-free solution to the world's increasing appetite for energy. In many countries, there is sufficient wave energy to cater for the entire national demand, and wave energy also has some attractive features in being relatively uncorrelated with wind, solar and tidal energy, easing the renewable energy dispatch problem. However, wave energy has not yet reached commercial viability, despite the first device designs being proposed in 1898. Control technology can play a major part in the drive for economic viability of wave energy and this paper charts the progress made since the first wave energy control systems were suggested in the 1970s, and examines current outstanding challenges for the control community.
Paper VI163-07.3
PDF · Video · Parametric Study of a Vibro-Impact Wave Energy Converter (I)
Guo, Bingyong	Maynooth University
Ringwood, John	Maynooth University
Keywords: Modeling and simulation of power systems, Dynamic interaction of power plants, Control of renewable energy resources Abstract: In this study, a non-linear vibro-impact mechanism is integrated inside a semi-submerged cylindrical heaving point absorber in order to enhance its power capture by utilising the non-linearity of vibro-impact events. A piece-wise linear model is derived considering linear wave-buoy interaction and the non-linear vibro-impact mechanism. Since the dynamics and performance of the vibro-impact wave energy converter (WEC) are sensitive to design parameters, a parametric study and analysis are conducted numerically by varying the design parameters in a broad range to evaluate their influence on the vibro-impact WEC's dynamics and performance, in terms of response amplitude operator, average power output and peak-to-average power ratio. Numerical simulations show that there exist some optimal sets of the design parameters to achieve a trade-off among the aforementioned performance indices. Hence, the parametric study in this paper can give some basic guidelines for optimising and prototyping the design of the vibro-impact WEC for wave tank testing.
Paper VI163-07.4
PDF · Video · Model Predictive Control of Wave Energy Converters with Prediction Error Tolerance (I)
Zhang, Yao	Queen Mary University of London; Harbin Institute of Technology
Zhan, Siyuan	Queen Mary University of London
Li, Guang	Queen Mary University of London
Keywords: Control of renewable energy resources, Control system design, Model predictive and optimization-based control Abstract: Sea wave energy converter (WEC) control is a non-causal optimal control problem, and the control performance relies on the accuracy of the prediction of incoming wave profile and the fidelity of the control-oriented model. To maximize energy conversion in real scenario, three issues should be fully considered: (a) the existing wave prediction methods inevitably introduce prediction errors, which degrades the control performance; (b) the model mismatch between the linearized state-space model and the hydrodynamic model also affects the control performance; (c) safe operations with limited power take-off (PTO) should be ensured to rule out the possibility of device damages. To explicitly deal with these problems, this paper proposes a novel control scheme to maximize the energy output subject to inaccurate predictions, model mismatch and multiple constraints. This is achieved by applying a feedback model predictive control (MPC) to handle the constraints and a sliding mode control (SMC) to compensate for the prediction error and model mismatch. Due to the extra input, the state and input constraints of MPC subsystem are further tightened to ensure constraints on both the states and the control input to be satisfied. Theoretical proof and simulation results show that the proposed controller is robust to achieve the maximal energy output subject to inaccurate prediction and inaccurate control-oriented model.
Paper VI163-07.5
PDF · Video · Switching Sequences for Non-Predictive Declutching Control of Wave Energy Converters (I)
Garcia-Rosa, Paula B.	SINTEF Energi; Norwegian University of Science and Technology
Fosso, Olav Bjarte	Norwegian University of Science and Technology
Molinas, Marta	Norwegian University of Science and Technology
Keywords: Control of renewable energy resources Abstract: Aiming at improving the energy absorption from waves, a number of studies have considered declutching control - a phase-control method that consists of disengaging the power take-off (PTO) system from the oscillating body at specific intervals of time. The on/off sequences with the instants to engage/disengage the PTO are usually determined by optimization procedures that require the knowledge of future excitation force, which remains an open challenge for practical implementation. This paper presents a comprehensive numerical study with different PTO damping coefficients for declutching control. It is shown that the value of the damping plays an important role on the efficacy of the control method and on the optimal time to engage (or disengage) the PTO. Then, two switching sequences that use current information of the body motion are proposed, and compared with the threshold unlatching strategy. When the body velocity vanishes, the PTO is clutched (declutched) if the current estimation of the mean excitation force frequency is lower (higher) than the body resonant frequency. The instant to declutch (clutch) again depends on the damping coefficient. The resultant PTO force profiles are not optimal, but act in an effective way to improve the energy absorption, while not requiring wave short-term predictions and numerical optimization solutions that can be time-consuming depending on the fidelity of numerical models and the prediction horizon. Numerical simulations consider real ocean waves and synthetic waves.
Paper VI163-07.6
PDF · Video · Robust Gain Scheduling Control for Wave Energy Conversion (I)
Ferri, Francesco	Aalborg University
Kramer, Morten Bech	Aalborg University
Keywords: Control of renewable energy resources Abstract: Enhancing the power performance of wave energy converters is undoubtedly a step required to reduce the cost of energy from this source of renewable energy, thereby making it competitive to other sources of renewable energy. Increasing the power absorption can be achieved by utilizing smart and advanced control algorithms. There are theories for a variety of advanced control algorithms, but few have proved stable and reliable for real applications. An often used, and robust method for practical applications, is to apply a simple gain scheduling controller where the control gains are parameterized in function of the sea state, and not at wave-by-wave level. This paper presents a wave-by-wave adaptive controller, which has proven a robust method that can increase the power absorption performance. The use of the wave by wave adaptive controller is achieved by the identification of the instantaneous fundamental frequency in real time. One numerical procedure to achieve this frequency is using non-linear Kalman filters. But the pitfall of these non-linear filters is their sensitivity to the parameter tuning, which decreases practical usability, reliability and robustness. This paper focuses on two complementary topics. The first topic will tackle the implementation of a reliable filter for the identification of the instantaneous fundamental frequency using a particle filter. The second topic will demonstrate the implementation of the wave-by-wave gain scheduling controller. The case study is a scaled absorber of the Floating Power Plant wave and wind energy converter.
Paper VI163-07.7
PDF · Video · A Self-Tuning WEC Controller for Changing Sea States (I)
Forbush, Dominic	Sandia National Laboratories
Bacelli, Giorgio	Sandia National Laboratories
Spencer, Steven	Sandia National Laboratories
Coe, Ryan	Sandia National Laboratories
Keywords: Control of renewable energy resources, Real time optimization and control, Monitoring and performance assessment Abstract: A self-tuning proportional-integral control law was tested in experiment on a three degree-of-freedom wave energy converter. The control objective was to maximize electrical power. The control law relied upon an identified model of device intrinsic impedance to generate a frequency-domain estimate of the wave-induced excitation force, but did not require any additional external sensing. The control law was tested in regular and irregular sea-states that evolved over hours (a rapid, but realistic time-scale) and sea-states that changed instantly (an unrealistic condition to evaluate controller response). For both cases, the controller converges to gains that closely approximate the post-calculated optimal gains for all degrees of freedom. Convergence to near-optimal gains occurred reliably over a sufficiently short time for realistic sea states. In addition, electrical power was found to be relatively insensitive to gain tuning over a broad range of gains, implying that an imperfectly tuned controller does not result in a large penalty to electrical power capture. An extension of this control law that allows for adaptation of the device impedance model over time is proposed for long-term deployments, as well as an approach to explicitly handle constraints within this architecture.
Paper VI163-07.8
PDF · Video · LTI Energy-Maximising Control for the Wave Star Wave Energy Converter: Identification, Design, and Implementation (I)
García Violini, Demián	Universidad Nacional De Quilmes
Peña-Sanchez, Yerai	Maynooth University
Faedo, Nicolás	Maynooth University
Windt, Christian	Centre for Ocean Energy Research, Maynooth University
Ringwood, John	Maynooth University
Keywords: Control of renewable energy resources, Control system design, Real time simulation and dispatching Abstract: Considering the Wave Star wave energy converter (WEC), which is a standard point absorber prototype, this study addresses the complete energy maximising control design procedure. The WEC model is obtained using system identification routines. Then, using the identified model, a LTI energy maximising control strategy, recently presented in the literature, is designed. Additionally, for the wave excitation force estimation, a standard Kalman filter with a harmonic oscillator is considered. Finally, for the assessment of the performance of the complete system, the controller and estimator are implemented in the numerical WEC simulation environment WEC-Sim. The system is tested under realistic conditions and satisfying performance of the LTI controller is shown. Thus, through a non-conventional approach, and considering a realistic software environment, a novel energy maximising controller is implemented, obtaining results which indicate the feasibility of the approach.
Paper VI163-07.9
PDF · Video · Ex-Post Analysis of the WEC Control Competition Results Using a Fourier Spectral Control Approach (I)
Merigaud, Alexis	IFP Energies Nouvelles
Ngo, Caroline	IFP Energies Nouvelles
Nguyen, Hoai-Nam	IFP Energies Nouvelles
Sabiron, Guillaume	IFP Energies Nouvelles
Tona, Paolino	Control, Signal and System Department - IFP Energies Nouvelles
Keywords: Control of renewable energy resources Abstract: The wave energy converter control competition (WECCCOMP) allowed several real-time control approaches to be assessed, both in numerical and physical experiments. The solution retained by IFPEN, which won the numerical simulation and experimental evaluation phases, consists of a receding-horizon MPC algorithm, including an estimator and a predictor for the wave excitation torque. The control objective function, solved by a quadratic programming (QP) optimiser in the real-time implementation, is weighted over the receding time horizon by means of weighting coefficients, which are optimised off-line for each sea state, in order to take into account the non-ideal power take-off (PTO) efficiency. Given the potential complexity of the interaction between the different components involved in the control implementation (estimation, prediction, QP solution, choice of weightings), it is useful to carry out an ex-post analysis, in order to understand if, and how, the solution proposed by IFPEN could have been improved. To that end, a Fourier spectral control algorithm is implemented, which is able to calculate the optimal trajectory and control torque for the totality of a signal, simulated from WECCCOMP sea states, taking the non-ideal PTO efficiency into account. By comparing MPC results with the theoretically optimal solutions provided by the spectral method, it is found that, in the studied WECCCOMP sea states, the IFPEN MPC algorithm performance lies within approximately 10% of the optimal solution, in terms of electric power. The influence of the MPC forecast accuracy and prediction horizon is examined. Finally, some challenges associated with the offline MPC weighting optimisation are identified.
Paper VI163-07.10
PDF · Video · Constrained Sliding Mode Control for Oscillating Water Column Wave Energy Converters (I)
Gaebele, Daniel Tim	Oregon State University
Magaña, Mario Edgardo	Oregon State University
Brekken, Ted K.A.	Oregon State University
Henriques, Joao	IDMEC/Instituto Superior Tecnico
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems Abstract: Maintaining a setpoint to maximize energy harvest of wave energy converters (WECs) with the uncertainties induced by the ocean waves irregular excitation can be ensured by using sliding mode control. In practice, the infinite switching frequency in the sliding mode is limited by the actuators bandwidth. This work compares multiple second-order sliding mode controllers (SMC) designed for an array of floating oscillating water column (OWC) WECs with varying order of discontinuity. All algorithms enable bounding the control input to respect the physical constraints, e.g. maximal torque introduced by the generators attached to the bi-radial turbines that are driven by the oscillating motion of the air trapped inside the OWC chamber. Practical implementation of the algorithms is facilitated by a smooth approximation of the signum function and a smooth switching between different cases or hysteresis and compared to the ideal switching. The performance of the presented control laws is evaluated while maintaining a constant turbine rotational speed inside the floating OWC WEC array, and the generated power is compared to an ideal control law for different irregular sea states.
Paper VI163-07.11
PDF · Video · Excitation Forces Estimation for Non-Linear Wave Energy Converters: A Neural Network Approach (I)
Bonfanti, Mauro	Politecnico Di Torino
Carapellese, Fabio	Politecnico Di Torino
Sirigu, Sergej Antonello	Politecnico Di Torino
Bracco, Giovanni	Politecnico Di Torino
Matiazzo, Giuliana	Politecnico Di Torino
Keywords: Identification and modelling, Process observation and parameter estimation, Control of renewable energy resources Abstract: Investigating optimal control algorithms is a continuing concern within the Wave Energy field. A considerable amount of literature has been published on optimal control architectures applied to Wave Energy Converter (WEC) devices. However, most of them requires the knowledge of the wave excitation forces acting on the WEC body. In practice such forces are unknown and an estimate must be used. In this work a methodology to estimate the wave excitation forces of a non-linear WEC along with the achievable accuracy, is discussed. A feedforward Neural Network (NN) is applied to address the estimation problem. Such a method aims to map the WEC dynamics to the wave excitation forces by training the network through a supervised learning algorithm. The most challenging aspects of these techniques are the ability of the network to estimate data not considered in the training process and their realiability in presence of model uncertanities. Numerical simulations under different irregular sea conditions demonstrate accurate estimation results of the NN approach as well as a small sensitivity to small changes in the plant parameters relative to the case study presented.
Paper VI163-07.12
PDF · Video · Adapting Optimal Velocity Tracking Control to Account for WEC Constraints and Power Take-Off Efficiencies (I)
Stock, Adam James	University of Strathclyde
Tom, Nathan	National Renewable Energy Laboratory
Gonzalez, Carlos	Renewable Dynamics
Keywords: Control of renewable energy resources, Control system design Abstract: Wave energy converters (WECs) come in many different forms, from point absorbers and oscillating water columns to bulge wave devices. This paper focuses on the control of point absorber WECs, which typically have a narrow-banded frequency response and, therefore, control is well placed to improve the energy capture of such WECs. The acausal nature of the control problem means that, theoretically optimal control is almost impossible to achieve in practice; however, optimal velocity tracking (OVT) offers a simple and robust approximation to optimal control that can achieve better power capture than passive linear damping methods, albeit with necessarily higher force demands. OVT is a form of impedance matching and the magnitude of the power-take-off (PTO) force demand is often not linearly proportional to the WEC velocity, which can lead to PTO force and speed combinations far from the optimal PTO efficiency. The highly nonlinear PTO force and speed to efficiency mapping can, without remedial measures, severely diminish the effectiveness of OVT techniques. In this paper, improvements to OVT are made, particularly regarding the limits on motion. In particular, a limit on acceleration is added and drift of the position when the acceleration and/or velocity are limited is prevented through the addition of a new integral term. An anti-wind up methodology to prevent controller integral wind up is also included. These additions allow OVT to be more easily applied in practice. The effect of PTO efficiency is explored, and a novel potential solution to the problem of adapting control to account for efficiency is presented. Both aspects of the work presented highlight the requirement for co-design of the WEC, PTO, and controller.
Paper VI163-07.13
PDF · Video · Robust Data-Driven Estimation of Wave Excitation Force for Wave Energy Converters (I)
Shi, Shuo	University of Hull
Patton, Ron J.	University of Hull
Liu, Yanhua	University of Hull
Keywords: Control of renewable energy resources, Identification and modelling, Artificial intelligence Abstract: This paper proposes a data-driven technique to estimate the wave excitation force (WEF) which is an essential signal for wave forecasting and implementing power efficiency maximization control of Wave Energy Converters (WECs). The paper uses a robust Bayesian filter in WEC hydrodynamic system which is described by a probabilistic model. Specifically, the WEF uncertainty can be estimated based on observations through Gaussian Process (GP) modeling techniques. This modern way of incorporating the first principle model into a probabilistic framework is more robust than calculating estimates of a parametric function representation. Unlike other sample-based non-linear Kalman filters, the means and covariances of joint probabilities can be directly computed based on analytic moment matching that allow for reliable state-dependent uncertainty propagation. Our evaluations demonstrate the accuracy and robustness of the proposed data-driven wave excitation force estimator.
Paper VI163-07.14
PDF · Video · Wave Excitation Force Estimator Using Kalman Filtering Approach for Point Absorber Wave Energy Converters under Different Modeling and Operation Scenarios (I)
Jama, Mohammed	UAE University
Wahyudie, Addy	UAE University
Keywords: Estimation and fault detection, Modeling and simulation of power systems, Control system design Abstract: In this research, one of the most important research questions that influence the effectiveness of the used control strategies in heaving wave energy converters (WECs) is addressed. A nonlinear extended Kalman filter (EKF) based state estimator to estimate the wave excitation force and heave velocity in real-time is proposed. A holistic nonlinear model involving both the mechanical and electrical sides of the WEC system is used. The proposed estimator was compared with a simpler linear Kalman filter (KF) estimator under varying sea state environment and electric loading conditions. Generally, both estimators produced "statistically" good estimates, however, the EKF estimators outperformed its counterpart in both the estimation accuracy and maintaining low incident energy drop.

VI163-08
Approaching Floating Off-Shore Wind Turbines: Modelling, Optimization and Control	Open Invited Session
Chair: Santos, Matilde	Universidad Complutense De Madrid
Co-Chair: Garcia-Cerezo, A.	Univ. De Malaga
Organizer: Santos, Matilde	Universidad Complutense De Madrid
Organizer: Tomas-Rodriguez, Maria	City University
Organizer: Martynowicz, Paweł	AGH University of Science and Technology
Paper VI163-08.1
PDF · Video · Inerter-Based Passive Structural Control for Barge Floating Offshore Wind Turbines (I)
Villoslada, Daniel	Universidad Complutense De Madrid
Santos, Matilde	Universidad Complutense De Madrid
Tomas-Rodriguez, Maria	City University
Keywords: Modeling and simulation of power systems, Artificial intelligence Abstract: Floating offshore wind turbines (FOWT) stand as a promising concept to expand the wind energy generation into the more productive deep-water areas, where conventional bottom-fixed turbines are infeasible. Barge-type floating wind turbines experience an inverted pendulum effect which produces a coupling with the wind turbine response, resulting in large structural loads. In this paper, the authors investigate passive structural control to mitigate the tower fatigue, in the form of a tuned mass damper (TMD) installed in the nacelle. The study focuses on evaluating the benefits of adding a parallel-connected inerter device to the TMD. Based on a reduced dynamics model for the barge-type offshore wind turbine identified using the FAST-SC synthetic reference data, an optimization of the TMD and the inerter parameters is carried out. To that end, genetic algorithms were used taking the tower fatigue as a fitness function, derived from the tower top displacement. The results confirm that the inerter has limitations when installed in a traditional TMD, but show significant benefits when the TMD stroke is constrained by stops. It is found that the improved performance including the inerter is dependent on the stroke limitation with respect to the ideal TMD stroke without stops. Therefore, the use of the inerter is especially useful to enhance performances for both mass and stroke constrained applications. The load reduction for the selected baseline model improved up to 6 % over the TMD with stops and 12 % over the TMD without stops.
Paper VI163-08.2
PDF · Video · Fuzzy Logic Tuning of a PI Controller to Improve the Performance of a Wind Turbine on a Semi-Submersible Platform under Different Wind Scenarios (I)
Zambrana-Lopez, Pablo	Universidad De Málaga
Fernández-Quijano, Javier	EnerOcean SL
Fernandez-Lozano, J. Jesus	Universidad De Málaga
Garcia-Cerezo, A.	Univ. De Malaga
Mayorga Rubio, Pedro M.	EnerOcean SL
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems Abstract: The integration of renewable energy sources in power systems, specially wind energy, is growing as environmental concerns arise in society. Nevertheless, the low amount of viable sites onshore or in shallow waters restricts the use of wind energy. In this sense, offshore semi-submersible platforms appear as an option, which in addition enables the integration of complementary elements, for instance wave energy converters. However, the complexity of the system increases due to the interactions between the platform movements and the wind turbine, and traditional control techniques do not enable to cope with these interactions in an easy way, hence limiting the efficiency of energy harvesting. Intelligent control techniques are an option with a great potential to take full account of the said interactions and to improve energy production efficiency. Still, it is required to have simulation models including those effects beforehand, so that the effects of a designed controller on the system can be evaluated. This paper presents an original fuzzy logic controller that tunes a reference controller, improving its performance according to a developed methodology that allows evaluation of controllers for wind turbines in semi-submersible platforms. The resulting fuzzy logic controller allows higher efficiency concerning mechanical loads in the system, electric energy production and tracking error of the speed reference.
Paper VI163-08.3
PDF · Video · Power and Motion Control of a Floating Wind Turbine: An Original Solution Based on Adaptive Second Order Sliding Mode Control (I)
Zhang, Cheng	Ecole Centrale De Nantes - LS2N
Plestan, Franck	Ecole Centrale De Nantes-LS2N
Keywords: Control of renewable energy resources Abstract: A new control scheme based on adaptive super-twisting algorithm is proposed for a floating wind turbine equipped by a permanent magnet synchronous generator. The adaptive control method is especially efficient for systems with uncertainties and external perturbations and, therefore, is well adapted to wind turbines systems. Such controller can be implemented with very limited knowledge of system model (only the relative degree is required) that greatly reduces the controller gains tuning effort. Simulations are made on FAST software and compared with a standard gain-scheduled PI controller.
Paper VI163-08.4
PDF · Video · Structural Vibration Control of NREL 5.0 MW FOWT Using Optimal-Based MR Tuned Vibration Absorber (I)
Martynowicz, Paweł	AGH University of Science and Technology
Santos, Matilde	Universidad Complutense De Madrid
Keywords: Control system design, Optimal operation and control of power systems Abstract: In this work, a National Renewable Energy Laboratory (NREL) 5.0 MW floating offshore wind turbine (FOWT) model equipped with nonlinear, magnetorheological (MR) tuned vibration absorber (TVA) is analysed. Several optimal-based MR damper control solutions are regarded against passive TVA configurations and the structure without the TVA system. Tower and barge/platform angular displacement amplitude frequency responses are compared, proving the efficiency and robustness of the adopted vibration reduction solutions, as well as their capability to minimise the amplitude of the vibrating structure, the demanded actuator (e.g. MR damper) force and stroke range.

VI163-09
Control of Power Electronic Converters	Open Invited Session
Chair: Zhong, Qing-Chang	Illinois Institute of Technology
Co-Chair: Bratcu, Antoneta Iuliana	Grenoble Institute of Technology, Gipsa-Lab, ControlSystems Department
Organizer: Zhong, Qing-Chang	Illinois Institute of Technology
Paper VI163-09.1
PDF · Video · Extension of the Linearity Range of a 3-Phase Boost Inverter for Stand-Alone Photovoltaic Panel-Based Emergency Application (I)
Fadel, Maurice	Laplace - Inpt-Cnrs
Rachmildha, Tri Desmana	ITB
Keywords: Application of power electronics, Control system design, Modeling and simulation of power systems Abstract: In the context of autonomous applications isolated from electrical energy it is necessary to develop direct conversion structures giving a three-phase voltage system from a DC source. In this context, the booster inverter is an interesting solution since it limits the conversion stages. Output voltages are generally limited by the Boost conversion ratio, whose efficiency decreases rapidly. In this work we propose to extend the linearity range of the inverter function by injecting a suitable zero-sequence voltage.
Paper VI163-09.2
PDF · Video · Single Stage PLL-Less Decoupled Active and Reactive Power Control for Weak Grid Interactive Inverters (I)
Khan, Ahmad	Kansas State University
Hosseinzadehtaher, Mohsen	Kansas State University
Shadmand, Mohammad B.	Kansas State University
Keywords: Control of renewable energy resources, Application of power electronics, Control system design Abstract: This paper presents a single stage phase locked loop-less (PLL-less) active and reactive power (PQ) control for single-phase weak grid interactive inverters. The absence of the PLL requirement in the proposed PQ control enhances the stability margin comparing to conventional current control approaches in both the stationary or the synchronous reference frame. Additionally, the proposed control scheme enables direct PQ control with a single loop control structure. This paper demonstrates that the proposed PLL-less PQ control scheme is asymptotically stable if the controller gains are positive. The necessary conditions for supplying the rated active power into the weak grid are derived. The provided analysis shows that certain amount of reactive power injection is necessary to avoid point of common coupling (PCC) voltage collapse when the rated active power is injected into the weak grid. Several case studies are provided to demonstrate the performance of the proposed PLL-less PQ control scheme under weak grid condition.
Paper VI163-09.3
PDF · Video · State-Feedback Control of Grid and Circulating Current in Modular Multilevel Converters (I)
Bratcu, Antoneta Iuliana	Grenoble Institute of Technology, Gipsa-Lab, ControlSystems Depa
Teodorescu, Remus	Aalborg University
Keywords: Application of power electronics, Control system design Abstract: This paper proposes a state-feedback control of both grid and circulating current in modular multilevel converters (MMCs), which ensures that the input-coupled dynamics of the two currents to be controlled within a multi-input–multi-output (MIMO) approach. A systematic design procedure is detailed and the strategy is validated on a comprehensive MATLAB®/Simulink® model of a three-phase MMC. Simulation results show that, compared with the conventional control featuring two separate control loops, the proposed control shows better performance under unbalanced grid conditions.
Paper VI163-09.4
PDF · Video · Power Loss Analysis of Bidirectional ACFC-SR Based Active Cell Balancing System (I)
Shi, Kai	University of Warwick
Dinh, Truong Quang	University of Warwick
Marco, James	University of Warwick
Keywords: Application of power electronics, Control system design Abstract: With the expansion of the number of electric vehicles (EV) over the world, the research on the battery and the battery management system (BMS) have become more popular. The active balancing, which is working as an advanced function in the modern BMS, has attracted researchers' attention in order to enhance battery system performance and prolong the battery pack life via integration of specially designed power electronic circuit with proper control and optimisation strategies in the BMS. This paper develops the power-loss and efficiency models of the bidirectional active clamp forward converter with synchronous rectifier (ACFC-SR) based active cell balancing system. The developed models can be involved in the power loss analysis of the active cell balancing system to underpin the energy efficiency performance evaluation and the balancing control system design of active balancing systems. The optimal balancing current with which the converter would operate at the maximum efficiency point can be obtained via the developed efficiency model. A case study is also included to illustrate the efficiency performance of the active balancing system.
Paper VI163-09.5
PDF · Video · Decentralized Multivariable Vector Current Control of Grid-Connected Voltage Source Inverters
Sadabadi, Mahdieh	University of Sheffield
Shafiee, Qobad	University of Kurdistan
Keywords: Control system design, Dynamic interaction of power plants, Application of power electronics Abstract: Increasing the number of grid-connected inverters in power systems imposes several challenges. One of the main challenges is the complexity and uncertainty of the dynamical model of the inverters due to the large numbers of grid-connected inverters and disconnection of inverters. To address this challenge, we present a scalable direct-quadrature current control strategy for parallel voltage source inverters in a rotating reference frame. The control structure is based on a decentralized multivariable proportional integral (PI) current control mechanism and provides stability and zero steady-state errors. The proposed control approach has the main advantages of flexibility, allowing disconnection/connection of inverters on the basis of the required power level. The effectiveness of the proposed vector current control strategy is evaluated through simulation case studies in MATLAB/Simscape Electrical.
Paper VI163-09.6
PDF · Video · Adaptive Voltage Regulation of an Inverter-Based Power Distribution Network with a Class of Droop Controllers
Chong, Michelle	Eindhoven University of Technology
Sandberg, Henrik	KTH Royal Institute of Technology
Keywords: Control system design, Control of renewable energy resources Abstract: The voltage received by each customer connected to a power distribution line with local controllers (inverters) is regulated to be within a desired margin through a class of slope-restricted controllers, known conventionally as droop controllers. We adapt the design of the droop controllers according to the known bounds of the net power consumption of each customer in each observation time window. A sufficient condition for voltage regulation is provided for each time window, which guides the design of the droop controllers, depending on the properties of the distribution line (line impedances) and the upper bound of all the customers' power consumption during each time window. The resulting adaptive scheme is verified on a benchmark model of a European low-voltage network by the CIGRE task force.
Paper VI163-09.7
PDF · Video · Virtual Synchronous Machines with Fast Current Loop
Shivratri, Shivprasad	Tel Aviv University
Kustanovich‬‏, Zeev	Israel Electricity Company
Weiss, George	Tel Aviv University
Shani, Benny	Tel Aviv University
Keywords: Control system design, Modeling and simulation of power systems, Application of power electronics Abstract: Virtual synchronous machines (VSM) are inverters that behave towards the power grid like synchronous generators. One popular way to realize such inverters are synchronverters, whose control algorithm has evolved over time, but both theoretical analysis and practical observations show that the output currents of a synchronverter are very sensitive to grid voltage measurement errors and processing delay, as well imprecisions in the PWM process. To overcome this problem (of excessive sensitivity), we propose in this paper to use a different type of control to realize a VSM, that includes a fast current controller as the internal control loop of the inverter. Our simulations and experiments show that this results in a dramatic reduction of the sensitivity of the VSM to various kinds of measurement errors and imprecision, and hence to the proper operation of such inverters.
Paper VI163-09.8
PDF · Video · Repetitive Control of Neutral-Point Voltage in NPC Three-Level Inverters Based on EID Compensation
Zhang, Kai Liang	School of Automation, Central South University
Liu, Fang	Central South University
Li, Yong	Hunan University
Keywords: Control system design, Control of renewable energy resources, Application of power electronics Abstract: Neutral-Point clamped (NPC) three-level inverters have a broad application prospect. However, the voltage imbalance of the capacitors and the drafting of its neutral-point voltage will generate voltage stresses on the switches and even increase the total harmonic distortion (THD) rate in their output. In this paper, an improved repetitive control method based on the idea of equivalent input disturbance (EID) compensation is adopted. By adding an additional neutral-point branch, the neutral-point voltage control problem is transformed into a disturbance suppression problem. The case studied are tested using MATLAB/SIMULINK software and the experiment results show that this proposed control strategy can overcome both periodic and non-periodic disturbance, restraining the voltage fluctuation at the neutral point to a lower level.

VI163-10
Emerging Challenges and Directions of Advanced Battery Management	Open Invited Session
Chair: Fang, Huazhen	University of Kansas
Co-Chair: Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Organizer: Fang, Huazhen	University of Kansas
Organizer: Lin, Xinfan	University of California, Davis
Organizer: Howey, David	University of Oxford
Organizer: Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Paper VI163-10.1
PDF · Video · Optimal Fast Charging Control for Lithium-Ion Batteries (I)
Ouyang, Quan	Nanjing University of Aeronautics and Astronautics
Ma, Rui	Nanjing University of Aeronautics and Astronautics
Wu, Zhaoxiang	Nanjing University of Aeronautics and Astronautics
Wang, Zhisheng	Nanjing University of Aeronautics and Astronautics
Keywords: Optimal operation and control of power systems, Control system design, Control of renewable energy resources Abstract: Fast charging has gained an increasing interest in the convenient use of Lithium-ion batteries. This paper develops a constrained optimization based fast charging control strategy, which is capable of meeting needs in terms of charging time, energy loss, and safety-related charging constraints. To solve it with less computational effort, a two-layer optimization strategy is proposed, where a charging time region contraction method is utilized to search the minimum expected charging time in the top layer, and the bottom layer uses the barrier method to calculate the corresponding optimal charging current with the charging time given by the top layer. Through utilizing this two-layer optimization method, the optimal charging current can be obtained that leads to the shortest charging period while guaranteeing the charging constraints with relatively low computational complexity. Extensive simulation results are provided to validate the proposed optimal fast charging control strategy, which well outperforms the constant current-constant voltage method.
Paper VI163-10.2
PDF · Video · Empirical Battery Modelling for High Currents: The Effect of Nonlinear Overpotential and Inevitable Self-Heating (I)
Hoekstra, Fsj	Eindhoven University of Technology
Heuts, Yjj	Eindhoven University of Technology
Bergveld, Henk Jan	Eindhoven University of Technology
Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Keywords: Modeling and simulation of power systems Abstract: Electric race cars are a challenging application for battery management. The main issue is that the use of extremely high currents leads to additional nonlinear behaviour in the battery. The source of this nonlinear behaviour can be found in the nonlinear Butler-Volmer relation between currents and overpotentials, as well as self-heating that occurs when large currents are drawn due to the electrical resistance of the battery. As a result, nonlinearities in the input-output behaviour are caused by both factors. To accurately model the nonlinear overpotential behaviour using empirical battery models, it is necessary to be able to distinguish between the contribution of both sources of nonlinearities. In this paper, this problem is tackled by identifying a temperature- and current-dependent electrical model on lap data of an electric race car using a global approach to estimating state-space linear parameter-varying models. To aid the distinction between both effects, the influence of the temperature on the behaviour is distilled from local data, i.e., at constant temperatures. This is used as initialisation for the global optimisation problem, which identifies the effect of both phenomena from a single data set. Lap data of four race cycles is available. One cycle is used for parameter estimation of the battery model and the other three are used to validate the model. The results show that this approach brings a significant improvement to the modelling accuracy and presents opportunities to develop BMS applications, such as state estimators or even online power limiters for extreme battery-electric-vehicle applications.
Paper VI163-10.3
PDF · Video · Light-Weighted Battery State of Charge Estimation Based on the Sigma-Delta Technique (I)
Liu, Kailong	University of Warwick
Tang, Xiaopeng	The Hong Kong University of Science and Technology
Widanage, Widanalage Dhammika	The University of Warwick
Keywords: Modeling and simulation of power systems, Instrumentation and control systems Abstract: In this paper, a light-weighted state-of-charge (SoC) estimator is proposed to ensure the estimation accuracy as well as significantly reduce the computational effort. Specifically, the sigma-delta technique is employed to extract battery SoC under noisy measurements (up to 100mV and 100mA) and validated under different battery aging conditions. Illustrative results demonstrate that in this circumstance, the proposed estimator presents low sensitivity to model accuracy and is also suitable for the non-Gaussian noises. Besides, the second-order Sigma-Delta estimator is capable of achieving a satisfactory accuracy (RMSEs are all within 1.5% for different aging batteries), while its computational effort is just 15% of that of the extended Kalman filter. These features pave a solution to the design of a light-weighted SoC estimator based on general micro-controller unit, further making the proposed Sigma-Delta estimator become suitable for improving the reliability and practicability of battery management especially for electrical vehicle applications.
Paper VI163-10.4
PDF · Video · Structural Identifiability of a Pseudo-2D Li-Ion Battery Electrochemical Model (I)
Drummond, Ross	University of Oxford
Duncan, Stephen	Univ of Oxford
Keywords: Identification and modelling, Control of renewable energy resources Abstract: Growing demand for fast charging and optimised battery designs is fuelling significant interest in electrochemical models of Li-ion batteries. However, estimating parameter values for these models remains a major challenge. In this paper, a structural identifiability analysis was applied to a pseudo-2D Li-ion electrochemical battery model that can be considered as a linearised and decoupled form of the benchmark Doyle-Fuller-Newman model. From an inspection of the impedance function, it was shown that this model is uniquely parametrised by 21 parameters, being combinations of the electrochemical parameters like the conductivities and diffusion coefficients. The well-posedness of the parameter estimation problem with these parameters was then established. This result could lead to more realistic predictions about the internal state of the battery by identifying the parameter set that can be uniquely identified from the data.
Paper VI163-10.5
PDF · Video · A Split-Future MPC Algorithm for Lithium-Ion Battery Cell-Level Fast-Charge Control (I)
Araujo Xavier,, Marcelo	Ford
Kawakita de Souza, Aloisio Henrique	University of Colorado at Colorado Springs
Trimboli, Scott	University of Colorado
Keywords: Control of renewable energy resources, Model predictive and optimization-based control, Advanced control technology Abstract: Constrained predictive control has emerged as a viable candidate for generating optimal real-time charging strategies for lithium ion batteries. Able to conform to hard constraints on problem variables, model predictive control (MPC) formulates an optimal 2-norm solution at each time step and can thus assure safe and reliable fast-charge operation. Standard MPC implementations make certain simplifying assumptions regarding future control actions beyond a specified control horizon. This paper demonstrates the potential gains that can be realized for the battery charge problem by relaxing these assumptions.
Paper VI163-10.6
PDF · Video · Practical Considerations for Customer-Sited Energy Storage Dispatch on Multiple Applications Using Model Predictive Control (I)
Cortés, Andrés	EPRI
Sharma, Vinayak	University of North Carolina at Charlotte
Garg, Aditie	Electric Power Research Institute
Stevens, David	Electric Power Research Institute
Cali, Umit	University of North Carolina at Charlotte
Keywords: Real time simulation and dispatching, Control system design, Optimal operation and control of power systems Abstract: Government subsidies for energy storage and renewable generation have led to the cost of energy storage come down during recent years. This has motivated people to deploy behind-the-meter energy storage units, to reduce their monthly electricity bill. For optimal control of the battery to incorporate maximum photovoltaic energy generation as well as demand charge reduction, data-driven and advanced Battery Energy Storage System (BESS) control strategies are required. This paper explores different use cases where customers could deploy energy storage systems for demand charge reduction as well as when customers could deploy energy storage systems for demand charge reduction while satisfying a utility set objective. From historical load and PV data, different use cases are simulated using a Model Predictive Control (MPC) based BESS control model. MPC requires machine-learning (ML) based forecasts of photovoltaic (PV) as well as load as inputs. A sensitivity analysis on the effect of different energy forecasts on the performance of MPC is presented in the paper. A degradation analysis with as a function of charge/discharge cycles is also presented in the paper to evaluate the trade-off between economic objectives and battery health.
Paper VI163-10.7
PDF · Video · Continuous Near-Optimal Control of Energy Storage Systems (I)
de Hoog, Julian	IBM Research Australia
Kolluri, Ramachandra Rao	IBM Research Australia
Ilfrich, Peter	IBM Research Australia
Keywords: Control of renewable energy resources, Real time optimization and control, Optimal operation and control of power systems Abstract: Energy storage plays an essential role in enabling greater uptake of renewable generation. In many applications, energy storage must be used for multiple (sometimes competing) purposes in order to provide the maximum possible economic return. A common approach is to find an optimal sequence of charge and discharge rates for a set of discrete time intervals across the horizon of interest. However, calculating optimal solutions at a high temporal resolution can be computationally expensive. In addition, conditions can change instantly as renewable generation fluctuates and loads are switched on and off. What is needed, therefore, is an approach that can both track some long-term optimal trajectory, while still responding to changing conditions in real-time. In this work, we propose two approaches that aim to achieve this. In the first, we calculate a discrete optimal solution, but then convert this into a schedule for simple rule-based controllers that can respond to changes continuously. In the second, we use historical optimal solutions and rule-based schedules to train a neural network that generates a similar schedule. We find that both approaches offer significant advantages over standard discrete optimal solutions: they provide a similar amount of value (and in some cases more), while being 30x less computationally expensive to compute.
Paper VI163-10.8
PDF · Video · Nonlinear State and Parameter Estimation for Li-Ion Batteries with Thermal Coupling (I)
Zhang, Dong	University of California, Berkeley
Couto, Luis D.	Université Libre De Bruxelles
Park, Saehong	University of California, Berkeley
Gill, Preet	University of California, Berkeley
Moura, Scott	UC Berkeley
Keywords: Estimation and fault detection, Identification and modelling, Control of renewable energy resources Abstract: Advanced Lithium-ion battery management systems rely on accurate cell-level state of charge (SOC) and parameter estimation for safe and efficient real-time monitoring. However, the design of combined state and parameter estimators that are provably convergent is notoriously difficult. A robust observer framework based on a coupled equivalent circuit-thermal model for a cylindrical battery is proposed. The coupled model also takes into account SOC and temperature-dependent electrical parameters for higher accuracy. In the literature, the model parameters are often treated as constants to simplify model structure and observer analysis. The problem considered in this work is particularly challenging due to (i) nonlinear two-way coupling between electrical and thermal sub-models, and (ii) nonlinear dependence of model parameters on the system states. A single aggregated observer for both SOC and thermal estimation becomes intractable due to lack of convergence certification caused by complex model coupling. We tackle this problem by proposing a sequential estimation scheme such that every sub-estimator converges separately, which is mathematically verified by Lyapunov stability analysis. Simulation results demonstrate the performance of the proposed state and parameters estimation framework.
Paper VI163-10.9
PDF · Video · Health-Aware Battery Charging Via Iterative Nonlinear Optimal Control Syntheses (I)
Vu, Minh	Washington University in St. Louis
Zeng, Shen	Washington University in St. Louis
Fang, Huazhen	University of Kansas
Keywords: Control of renewable energy resources, Advanced control technology, Nonlinear process control Abstract: There is an increasing recognition of the critical importance of charging for the safety and life of lithium-ion batteries. This paper proposes a computationally efficient optimal control approach for the problem of real-time charging control. By incorporating specific constraints that must be satisfied during charging, a health-aware operation is promoted. To determine the optimal charging current in the given setup, a recently proposed iterative framework for solving constrained optimal control problems is leveraged. It is found that the resulting optimal charging currents can be expressed in terms of a piecewise-affine time-invariant state feedback law, which results in a high computational efficiency for the optimal control solution.
Paper VI163-10.10
PDF · Video · Li-Ion Battery Fault Detection in Large Packs Using Force and Gas Sensors (I)
Cai, Ting	University of Michigan
Mohtat, Peyman	University of Michigan
Stefanopoulou, Anna G.	Univ of Michigan
Siegel, Jason	University of Michigan
Keywords: Applications of FDI and FTC Abstract: Internal short circuits are a leading cause of battery thermal runaway, and hence a major safety issue for electric vehicles. An internal short circuit with low resistance is called a hard internal short, which causes a high internal current flow that leads to an extremely fast temperature rise, gas generation, cell swelling, and ultimately battery rupture and failure. Thus it is crucial to detect these faults immediately after they get triggered. In large battery packs with many cells in parallel, detecting an internal short circuit event using voltage is difficult due to suppression of the voltage signal from the faulty cell by the other healthy cells connected in parallel. In contrast, analyzing the gas composition in the pack enclosure can provide a robust single cell failure detection method. At elevated temperature, decomposition of the battery materials results in gas generation and cell swelling. The cell structure is designed to rupture at a critical gas pressure and vent the accumulated CO2 gas, in order to prevent explosive forces. In this paper, we extend our previous work by combining the models of cell thermal dynamics, swelling, and CO2 gas generation. In particular, we developed a fast and high confidence level detection method of hard internal short circuit events for a battery pack by measuring cell expansion force and monitoring CO2 concentrations in a pack enclosure.
Paper VI163-10.11
PDF · Video · Bayesian Parameter Estimation Applied to the Li-Ion Battery Single Particle Model with Electrolyte Dynamics (I)
Aitio, Antti	Oxford University
Marquis, Scott	University of Oxford
Ascencio, Pedro	University of Oxford
Howey, David	University of Oxford
Keywords: Identifiability, Bayesian methods, Particle filtering/Monte Carlo methods, battery Abstract: This paper presents a Bayesian parameter estimation approach and identifiability analysis for a lithium-ion battery model, to determine the uniqueness, evaluate the sensitivity and quantify the uncertainty of a subset of the model parameters. The analysis was based on the single particle model with electrolyte dynamics, rigorously derived from the Doyle-Fuller-Newman model using asymptotic analysis including electrode-average terms. The Bayesian approach allows complex target distributions to be estimated, which enables a global analysis of the parameter space. The analysis focuses on the identification problem (i) locally, under a set of discrete quasi-steady states of charge, and in comparison (ii) globally with a continuous excursion of state of charge. The performance of the methodology was evaluated using synthetic data from multiple numerical simulations under diverse types of current excitation. We show that various diffusivities as well as the transference number may be estimated with small variances in the global case, but with much larger uncertainty in the local estimation case. This also has significant implications for estimation where parameters might vary as a function of state of charge or other latent variables.
Paper VI163-10.12
PDF · Video · Core Temperature Observer Design and Model Parameter Uncertainty Analysis for a Lithium Battery
Nissing, Dirk	Rhine-Waal University of Applied Sciences
Birnale, Himani	Hochschule Rhein-Waal
Keywords: Application of power electronics, Condition Monitoring Abstract: Temperature monitoring for Lithium ion batteries is an important factor for its properties. Since the core temperature is difficult to measure, a thermal model is used for estimation. In this paper, an offline parameter identification procedure is applied, by which the parameters of a three state lumped thermal model can be identified. Based on the model a Luenberger observer is designed with the strength of compensating variations of the model parameters. Only the easily accessible and measurable temperature of the copper pole is fed back to the observer. The paper deals with the robustness analysis of the proposed observer in that the actual plant differs from the model considered in the observer. The capability of the approach is beneficial as an online (and computational power consuming) parameter identification is no longer required. Instead, the thermal model is obtained offline and the observer is robust against model parameter variations, e. g. ageing, so that a continuous update of the model is not required.
Paper VI163-10.13
PDF · Video · Distributed Control of Second Life Batteries in a Parallel Connected Network (I)
Bagherpour, Michael	UC San Diego
de Callafon, Raymond	University of California, San Diego
Keywords: Intelligent control of power systems Abstract: Used batteries that are no longer fit for their original applications can be combined to form usable battery packs. Cells can be connected in series to form modules with higher voltage, and these modules can be connected in parallel to build up the capacity of the battery pack. Parallel connections may cause stray currents within the battery pack due to heterogeneous operational parameters of the modules, so the current output by each module must be controlled to eliminate this problem. We present an approach to control such a configuration by buck regulating the terminal voltage of each module. The novelty of the proposed control algorithm is to separate the control into two components: an occasional update to estimates of slow-varying system parameters, and a frequent update of control inputs to accommodate fluctuations in the load. The estimated system parameters are communicated infrequently by a central processor, while the modules individually calculate control inputs. The required communication between modules and the central processor is greatly reduced by distributing the calculation of control inputs, allowing the system to scale up efficiently even as the number of modules grows large

VI163-11
Modelling, Control and Optimization of Power Generation Systems: From Conventional to Renewable	Open Invited Session
Chair: Sun, Li	Southeast University
Co-Chair: Li, Donghai	Tsinghua University
Organizer: Sun, Li	Southeast University
Organizer: Li, Donghai	Tsinghua University
Organizer: Zheng, Song	College of Electrical Engineering and Automation, Fuzhou Univers
Paper VI163-11.1
PDF · Video · Control of the Fluidized Bed Combustor Based on Active Disturbance Rejection Control and Bode Ideal Cut-Off (I)
Wu, Zhenlong	Tsinghua Unversity
Shi, Gengjin	Tsinghua University
Li, Donghai	Tsinghua University
Chen, YangQuan	University of California, Merced
Zhang, Yu-Long	Tsinghua University
Keywords: Optimal operation and control of power systems, Process control applications, Control system design Abstract: The fluidized bed combustor (FBC) boiler faces many control challenges such as high-order dynamics and strong nonlinearity. A hybrid control structure combining active disturbance rejection control (ADRC) and Bode ideal cut-off (BICO) is proposed to handle with these control difficulties and speed up the output responses. An empirical tuning procedure is summarized for the hybrid control structure. Simulation results show that the hybrid control structure has the best tracking performance compared with other control strategies. In addition, the hybrid control structure can obtain the satisfactory disturbance rejection performance when the FBC system has the coal quality variation or input disturbances. The superiority of the hybrid control structure can ensure the satisfactory control performance and shows a great potential in industrial applications.
Paper VI163-11.2
PDF · Video · Shaft Speed Control of the Gas Turbine Based on Active Disturbance Rejection Control (I)
Shi, Gengjin	Tsinghua University
Wu, Zhenlong	Tsinghua Unversity
He, Ting	Jinan University
Li, Donghai	Tsinghua University
Ding, Yanjun	Tsinghua University
Liu, Shangming	Tsinghua University
Keywords: Control system design, Modeling and simulation of power systems, Real time simulation and dispatching Abstract: As a clean energy engine, the gas turbine has many challenges in its shaft speed control such as strong nonlinearity and various external disturbances. However, conventional controllers such as proportional-integral-derivative (PID) controllers are not able to obtain satisfactory performance in disturbance rejection when the operating point is changing. To handle with the strong nonlinearity and reject possible disturbances more effectively, the linear active disturbance rejection controller (LADRC) is applied to the shaft speed control system of the gas turbine based on an experimental tuning procedure. Moreover, Skogestad Internal Model Control-PID (SIMC-PID) and fractional order PID (FOPID) are chosen as comparative controllers. Eventually, Monte Carlo trials are carried out and maximum sensitivities are calculated in order to test the robustness of controllers. Simulation results illustrate the advantages of LADRC in both reference tracking and rejections of different disturbances.
Paper VI163-11.3
PDF · Video · Local Model Network Based Multi-Model Predictive Control for a Boiler -Turbine System (I)
Zhu, Hongxia	Nanjing Institute of Technology
Zhao, Gang	Southeast University
Sun, Li	Southeast University
Lee, Kwang Y.	Baylor University
Keywords: Advanced process control, Model predictive and optimization-based control, Control system design Abstract: A controller-weighted multi-model predictive control (MMPC) strategy based on local model network (LMN) is proposed to address the nonlinearity and wide operating range of the boiler-turbine (B-T) system with constraints. The LMN model of the nonlinear plant is identified off-line based on data-driven modeling method. Since each local model is valid only in local regime, different local constraints are considered in designing local predictive controllers corresponding to different local models. The local controllers are run in parallel and each controller is assigned with a weight by the implicit scheduling unit. The weighted sum of the outputs of local controllers is taken as a global control signal and applied to the plant. The efficacy of the proposed MMPC is validated by simulations on a boiler-turbine system.
Paper VI163-11.4
PDF · Video · Robust Exponential Load Frequency Control for Time Delay Power System Considering Wind Power (I)
Jin, Li	China University of Geosciences
Shang-Guan, Xingchen	China University of Geosciences
He, Yong	China University of Geosciences
Zhang, Chuan-Ke	China University of Geosciences
Jiang, Lin	The University of Liverpool
Wu, Min	China University of Geosciences
Keywords: Power systems stability, Control of renewable energy resources Abstract: The injection of intermittent wind power reduces the equivalent inertia of power systems, and therefore, the change rate of frequency deviation for the load frequency control (LFC) schemes is increased. LFC schemes employ communication channels to transmit signals, which introduces time delays resulting in badly dynamic performance. This paper presents a delay-dependent approach to obtain the robust load frequency controllers based on decay rate for a multi-area LFC scheme integrated with wind power. An index of decay rate related to settling time is introduced. For a preset delay upper bound, controller gains are optimized by maximizing the decay rate. Also, the controller gains can be designed under desired decay rate while obtaining the allowable maximum delay margins. Case studies are based on the deregulated multi-area LFC system to verify the robustness of developed controller against inertia reduction. Moreover, the proposed method enables the frequency deviation to be restrained and eliminated within a few seconds.
Paper VI163-11.5
PDF · Video · Interval-Based Modeling of High-Temperature Fuel Cells for a Real-Time Control Implementation under State Constraints (I)
Cont, Noel	University of Rostock, Chair of Mechatronics
Frenkel, Wiebke	University of Rostock, Chair of Mechatronics
Kersten, Julia	University of Rostock
Rauh, Andreas	University of Rostock
Aschemann, Harald	University of Rostock
Keywords: Control system design, Optimal operation and control of power systems, Model predictive and optimization-based control Abstract: Interval-based state estimation techniques represent promising approaches for the quantification of worst-case bounds of those sets of state variables that are reachable over a finitely long time horizon under the consideration of bounded uncertainty. In previous work, it has been shown that such estimation techniques cannot only be employed for the class of linear uncertain systems but also for nonlinear ones if they are reformulated in terms of quasi-linear state-space representations. However, naive polytopic uncertainty models may lead to quite conservative enclosures of the reachable states. Those, in turn, lead to conservative control strategies if the aforementioned interval enclosures are combined with strategies for the design of robust feedforward and feedback controllers. Therefore, this paper aims at the reduction of pessimism during interval-based state estimation by means of novel uncertainty models, relying on a parameter bounding approach that is implemented by means of a correlation analysis as well as a suitable principle axes transformation of the parameter space. The practical applicability of the proposed procedure is visualized for an experimentally validated thermal model of a solid oxide fuel cell stack, for which the computed interval bounds of reachable states represent a fundamental requirement for the design of a combined feedforward and feedback control allowing for preventing the violation of upper temperature limits in a guaranteed way.
Paper VI163-11.6
PDF · Video · Load/Frequency Control in the Presence of Renewable Energy Systems: A Reference-Offset Governor Approach (I)
Tedesco, Francesco	Università Degli Studi Della Calabria
Casavola, Alessandro	Universita' Della Calabria
Keywords: Optimal operation and control of power systems, Constraint and security monitoring and control, Control of renewable energy resources Abstract: In this paper a supervisory strategy for load/frequency control problems in networked multi-area electrical micro-grids in the presence of Renewable Energy Systems (RES) is presented. The proposed strategy exploits a recently developed constrained supervision methodology known in the literature as the Reference-Offset Governor (ROG) approach. Here, the ROG approach is extended to operate in the presence of rate-bounded disturbances acting as non-manipulable inputs on the plant. The main aim is at adequately orchestrating, during the on-line operations, the switching among different ROG configurations, suitably calibrated on the intensity of the disturbances, to efficiently satisfy the prescribed constraints. It is shown that the use of a bank of ROGs, instead of a single one, can remarkably reduce the conservativeness of the solution and improve the overall performance if the disturbance intensity changes. The effectiveness of the proposed approach is demonstrated on a two-area power system subject to coordination constraints on maximum frequency deviations, exchanged and generated powers and injected power from local RESs.
Paper VI163-11.7
PDF · Video · Density-Based Control of Air Coolers in Supercritical CO2 Power Cycles (I)
Casella, Francesco	Politecnico Di Milano
Mangola, Giovanni	Dipartimento Di Elettronica, Informazione E Bioingegneria, Polit
Alfani, Dario	Dipartimento Di Energia, Politecnico Di Milano
Keywords: Modeling and simulation of power systems, Control system design, Control of renewable energy resources Abstract: In this paper, the problem of controlling the thermodynamic state at the outlet of the air cooling unit in a supercritical CO2 Brayton cycle is addressed. First-principle modelling analysis of the cooler model with boundary conditions representing the interaction with the full plant reveals that the dynamic response of the CO2 outlet density to small changes of the cooling air flow has a much higher gain and a much more regular behaviour across the whole operating range of the system than the outlet temperature, suggesting to use the former variable for feedback control instead of the latter. Furthermore, it is shown how adaptive density feedback controllers can be designed with simple gain scheduling policies based on the plant load level and on the cooling air temperature.
Paper VI163-11.8
PDF · Video · Flexible Control of Nuclear Cogeneration Plants for Balancing Intermittent Renewables (I)
Dong, Zhe	Tsinghua University
Keywords: Control system design, Dynamic interaction of power plants, Power systems stability Abstract: Due to the complementarity between the intermittent renewable energy (IRE) and the nuclear, it is at-tractive to interconnect them to supply clean energy consistently and continuously in a large-scale. The flexibility of for integrating the IRE can be provided by actively adjusting the electric power output of nuclear cogeneration plants (NCPs), which induces frequent redistribution of main steam to the turbine and cogeneration process. For the main steam redistribution, it is necessary to guarantee the stability of grid frequency and main steam pressure, which heavily relies on the flexible control of NCPs. In this pa-per, a new flexible control of NCPs with saturated main steam is proposed based upon the idea of ac-tively suppressing the total disturbance in the dynamics of grid frequency and that of main steam pres-sure. The stabilization problems of pressure and frequency are transferred to the disturbance attenuation problem of a second-order system, and an active disturbance rejection control (ADRC) is then proposed. This ADRC is applied to the flexible control of a NCP composed of a nuclear heating reactor (NHR), a turbine-generator set and a multi-effect-desalination and thermal-vapor-compression (MED-TVC) pro-cess for seawater desalination. Numerical simulation results in the cases of load stepping show that the flexibility of this NCP is satisfactory in balancing the grid.
Paper VI163-11.9
PDF · Video · A Dual Splitting Method for Distributed Econonmic Dispatch in Multi-Energy Systems
Wang, Zhibin	Shanghai Jiao Tong University
Xu, Jinming	Zhejiang University
Zhu, Shanying	Shanghai Jiao Tong University
Chen, Cailian	Shanghai Jiao Tong University
Keywords: Real time simulation and dispatching Abstract: Multi-energy systems which bring together different forms of energy, such as electricity, gas and heat, to coordinate in the process of supply, transmission and consumption provide much higher flexibility over traditional energy systems in energy utilization. This paper deals with the economic dispatch problem in multi-energy systems in a distributed manner. Each agent optimizes its local objective function with regard to local coupled limits and a global constraint via local communications only. A novel distributed algorithm is proposed based on duality analysis and splitting methods.This algorithm adopts a non-linear mapping method to linearize the nonlinearity arisen from coupling relationship among energy carriers. We show that the proposed algorithm converges at a nonergodic rate of O(1/k). Simulations are demonstrated to show the effectiveness of the algorithm.

VI163-12
Optimal Operation and Control in Smart Grids	Open Invited Session
Chair: Vale, Zita	Polytechnic Institute of Porto
Co-Chair: Faria, Pedro	Polytechnic Institute of Porto
Organizer: Vale, Zita	Polytechnic Institute of Porto
Organizer: Rueda, Jose L.	Delft University of Technology
Organizer: Faria, Pedro	Polytechnic Institute of Porto
Paper VI163-12.1
PDF · Video · Large-Scale Optimization of Households with Photovoltaic-Battery System and Demand Response (I)
Lezama, Fernando	Polytechnic of Porto
Faia, Ricardo	Polytechnic of Porto
Abrishambaf, Omid	Polytechnic of Porto
Faria, Pedro	Polytechnic Institute of Porto
Vale, Zita	Polytechnic Institute of Porto
Keywords: Smart grids, Modeling and simulation of power systems Abstract: The adoption of distributed resources by households, e.g., storage units and renewables, open the possibility of self-consumption (on-site generation), sell energy to the grid as a small producer, or do both according to the context of operation. In this paper, a framework capturing the interactions between an aggregator and a large number of households is envisaged. We consider households equipped with distributed resources and simple smart technologies that look for the reduction of energy bills and can perform demand response actions. A mixed integer linear programming formulation is developed for obtaining the optimal scheduling of household devices that provides minimal operation costs. Results show that the model can efficiently be applied considering up to 10000 households. Moreover, households can reduce up to 20% of their energy bill on average using storage units and demand response. Besides, the aggregator can attain profits by offering the resulting exibility to upper level players of the energy chain such as the distribution system operator.
Paper VI163-12.2
PDF · Video · Model Predictive Control of the AC Voltage of an Electric-Vehicle Charging Station with ESS (I)
Kim, Daejin	Korea Institute of Energy Research
Lee, Young Il	Seoul National Univ of Science and Technology
Keywords: Control system design, Optimal operation and control of power systems, Power systems stability Abstract: With the recent rapid expansion of electric vehicles, a large number of Electric Vehicle Supply Equipment (EVSE) have been installed. As a result, the impact of EV chargers on the power system is being significantly increased. In particular, the EVSE connected to the distribution network line may act as a peak load, which can adversely affect the voltage stability of the distribution network system when the electric vehicle is quickly charged. In this paper, a Model Predictive Control (MPC) algorithm with disturbance observer (DOB) is proposed for stabilizing voltage of EVs Charging Station which is composed of EV chargers, Photovoltaic (PV), Energy Storage System (ESS) and Loads. The proposed DOB estimate the sum of total current which is the source of voltage fluctuations due to line impedance in the EV charging station. The grid voltage remains stable under the various operating condition including the extreme scenarios by proposed methods. Simulations are performed by means of MATLAB/SIMULINK and result shows the effectiveness of the proposed DOB and MPC control scheme.
Paper VI163-12.3
PDF · Video · Production Scheduling Considering Dynamic Electricity Price in Energy-Efficient Factories (I)
Soares, João	Polytechnic of Porto
Canizes, Bruno	Polytechnic of Porto
Faria, Pedro	Polytechnic Institute of Porto
Vale, Zita	Polytechnic Institute of Porto
Ramos, Carlos	Polytechnic Institute of Porto
Keywords: Smart grids, Real time simulation and dispatching, Optimal operation and control of power systems Abstract: Factories account for more than 42% of global energy consumption. In order to contribute to reduce carbon footprint and increase energy efficiency, it is important to optimize the tasks and time of product manufacturing according to the renewable generation and lower prices of the grid but without compromising production quality and output. This paper aims to develop flexible optimization platform for industrial production processes. The proposed production scheduling model is formulated as a 15-minute interval of one week time-span adopting mixed-integer linear optimization model and solved in TOMLAB. The model considers general production constraints for different products and takes into account with the photovoltaic generation of the factory as well as the dynamic price of the grid. The results are compared with a reference case without photovoltaic and where the dynamic price is not considered. The energy cost savings can amount up to 29% or 100 euro in the considered example.
Paper VI163-12.4
PDF · Video · Power Flow Management in Multi-Source Electric Vehicle Charging Station (I)
Arwa, Erick Odhiambo	University of Cape Town
Folly, Komla	University of Cape Town
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Smart grids Abstract: Grid-tied renewable energy sources (RES) with battery-behind-meter (BBM) architectures have successfully been used to ensure effective energy cooperation between the grid and RES-based microgrids. Such environments are quite stochastic, thus making power management very challenging. This paper presents the use of an asynchronous Q-learning in performing a power flow management task in a multi-source electric vehicle charging station with the integration of vehicle-to-microgrid technology. The power scheduling problem is first formulated as a Markov decision process. Asynchronous Q-learning is then used to solve it. The algorithm is tested with a typical charging station load profile over a 24-hour period and compared with a simple rule-based algorithm. Simulation results show that the proposed method is able to select a power schedule that reduces the energy cost with a better utilization of both the battery storage system and the vehicle to microgrid energy compared to the rule-based method.
Paper VI163-12.5
PDF · Video · A Consumer Trustworthiness Rate for Participation in Demand Response Programs (I)
Silva, Catia	Polytechnic of Porto
Faria, Pedro	Polytechnic Institute of Porto
Vale, Zita	Polytechnic Institute of Porto
Keywords: Smart grids Abstract: Local energy communities with information from the real-time market may improve the market operation but also increase the complexity of the management problem thanks to the uncertainty associated with the actual response of these resources. For instance, consumers with price knowledge may change their power consumption to lower-cost periods. The authors present a model to deal with uncertainty from the Aggregator perspective: apply reliability rates to each consumer according to their actual response in events of Demand Response (DR). The consumers with higher rates are chosen to participate in the local flexibility markets. To compute the final rate, three different independent rates are used: Historical rate with past information, Cut-rate from the response in the actual period and the Last Day Rate which is the final reliability rate from the previous day. In the present paper, the influence of each independent rate, through the weight used, is studied.
Paper VI163-12.6
PDF · Video · Key Performance Indicators to Support the Participation in Demand Response Programs: A Testing Framework for End Users (I)
São José, Débora	Polytechnic of Porto
Faria, Pedro	Polytechnic Institute of Porto
Silva, Catia	Polytechnic of Porto
Vale, Zita	Polytechnic Institute of Porto
Keywords: Smart grids Abstract: With the new challenges and complexity in power electricity management, demand response programs can be a way to reduce stress and strengthen power grids. However, as demand response implies end users to intentionally change their consuming patterns to adapt to grids needs, some decision-making support tools are necessary. The present paper proposes an energy management and controlling tool to assist electricity end users to make their decision to change consumption pattern in a DR scenario while using key performance indicators. The tool was tested using a group of 20 end users and showed a consistent result throughout all the elements in the sample.
Paper VI163-12.7
PDF · Video · Clustering Direct Load Control Appliances in the Context of Demand Response Programs in Energy Communities (I)
Barreto, Ruben	Polytechnic of Porto
Faria, Pedro	Polytechnic Institute of Porto
Silva, Catia	Polytechnic of Porto
Vale, Zita	Polytechnic Institute of Porto
Keywords: Smart grids Abstract: The demand response program explained in this article is designed to be implemented in communities seeking to achieve a self-sustaining system, namely through renewable energy such as photovoltaic energy. This article, through concepts such as prosumer and clustering, aims to make the most efficient management of the resources provided by the energy community. The developed demand response clusters the different consumers who have the same type of consumption throughout the day. That is, it brings together those whose behavior of the respective loads resemble each other and can be viewed from the perspective of an individual load or even clustered with one or more loads. The study comprises three villages with different numbers of consumers and charges, where, through their participation, it is estimated that there are reductions in electricity bills and, for those who collaborated for the study, it is attributed a remuneration according to their performance.
Paper VI163-12.8
PDF · Video · Flexible Charging Optimization for Electric Vehicles Using MDPs-Based Online Algorithms
Tomin, Nikita	Energy Systems Institute
Maasmann, Jonas	TU Dortmund University
Domyshev, Aleksandr	Esi Sb Ras
Keywords: Intelligent control of power systems, Control of renewable energy resources, Smart grids Abstract: In the paper, we formulate the problem of charging electric vehicles with a time-dependent energy source as a Markov Decision Process (MDP), with states defining the presence of cars, their individual levels of charge as well as the level of available renewable energy and storage devices. We exploit MDPs-based online algorithms such as Monte-Carlo Tree Search (MCTS) to overcome the scalability issues associated with charging of a large number of EVs, which corresponds to real distributed networks with flexible options. Using MCTS, we were able to generate optimal policies that balanced the energy toll on the electric grid with the final charge levels of each vehicle. We compare the performance of offline MDP solvers (Discrete Value Iteration algorithm) and online MDP solvers (MCTS) as well as reinforcement learning-based solvers (Q-learning) to find the optimal policy for EV's flexible charging optimization.

VI163-13
Wind Turbine and Wind Farm Control: Control Challenges and Solutions	Open Invited Session
Chair: van Wingerden, Jan-Willem	Delft University of Technology
Co-Chair: Pao, Lucy Y.	Univ of Colorado at Boulder
Organizer: van Wingerden, Jan-Willem	Delft University of Technology
Organizer: Fleming, Paul	NREL
Organizer: Schlipf, David	University of Stuttgart
Organizer: Johnson, Kathryn	Colorado School of Mines
Organizer: Pao, Lucy Y.	Univ of Colorado at Boulder
Paper VI163-13.1
PDF · Video · A Distributed, Rolling-Horizon Demand Side Management Algorithm under Wind Power Uncertainty (I)
Scarabaggio, Paolo	Politecnico Di Bari
Grammatico, Sergio	Delft Univ. of Tech
Carli, Raffaele	Politecnico Di Bari
Dotoli, Mariagrazia	Politecnico Di Bari
Keywords: Renewable Energy System Modeling and Integration, Energy and Distribution Management Systems, Energy Storage Operation and Planning Abstract: In this paper, we consider a smart grid where users behave selfishly, aiming at minimizing cost in the presence of uncertain wind power availability. We adopt a demand side management (DSM) model, where active users (so-called prosumers) have both private generation and local storage availability. These prosumers participate to the DSM strategy by updating their energy schedule, seeking to minimize their local cost, given their local preferences and the global grid constraints. The energy price is defined as a function of the aggregate load and the wind power availability. We model the resulting problem as a non-cooperative Nash game and propose a semi-decentralized algorithm to compute an equilibrium. To cope with the uncertainty in the wind power, we adopt a rolling-horizon approach, and in addition we use a stochastic optimization technique. We generate several wind power production scenarios from a defined probability density function (PDF), determining an approximate stochastic cost function. Simulations results on a real dataset show that the proposed approach generates lower individual costs compared to a standard expected value approach.
Paper VI163-13.2
PDF · Video · Gaussian Processes Modifier Adaptation with Uncertain Inputs for Distributed Learning and Optimization of Wind Farms (I)
Andersson, Leif Erik	Norwegian University of Science and Technology
Bradford, Eric	Norwegian University of Science and Technology
Imsland, Lars	Norwegian University of Science and Technology
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Real time optimization and control Abstract: A modifier adaptation scheme based on Gaussian processes is presented to optimize the control inputs of a wind farm. Often an approximate model of the wind farm is available, however due to the high complexity of the process plant-model mismatch is prevalent. For example the mechanics of wakes is not well-understood, which may have a profound impact on the power production of wind farms. Therefore, Gaussian process (GP) regression is exploited to account for this deviation. A distributed learning approach is used to learn the plant-model mismatch of each individual turbine considering explicitly the uncertainty of the uncontrolled inputs, like the wind direction. Afterwards, a distributed optimization scheme using alternating direction method of multipliers is applied to iteratively attain the wind farm optimum despite the presence of plant-model mismatch.
Paper VI163-13.3
PDF · Video · A Fatigue-Oriented Cost Function for Optimal Individual Pitch Control of Wind Turbines (I)
Collet, David	IFP New Energy
Alamir, Mazen	Gipsa-Lab (CNRS-University of Grenoble)
Di Domenico, Domenico	IFP Energies Nouvelles
Sabiron, Guillaume	IFP Energies Nouvelles
Keywords: Control of renewable energy resources, Optimal operation and control of power systems, Control system design Abstract: In a context of wind power production growth, it is necessary to optimize the levelized cost of energy by maximizing the profit of operating wind turbines, which is defined as the difference between gains (e.g. energy sold) and losses (e.g. operation and maintenance cost). Operation and maintenance cost is intimately related to fatigue damage. However, considering fatigue directly in an optimization needs to be carefully done because its faithful model does not fit standard forms. In this paper, it is first shown that the variance of a signal and its corresponding damage using fatigue theory are nonlinearly related. Therefore, this relationship is used to design a convex cost function approximating fatigue. Preliminary tests suggest promising results regarding the relevance of this formulation in optimizing fatigue trade-off when compared to a family of quadratic cost functions. The proposed formulation allows to directly consider economic parameters in the cost function, limiting thus the sensitivity to parameter tuning.
Paper VI163-13.4
PDF · Video · Wind Tunnel Testing of an Optimal Feedback/feedfoward Control Law for Wind Turbines (I)
Sinner, Michael	University of Colorado Boulder
Petrović, Vlaho	University of Oldenburg
Berger, Frederik	University of Oldenburg
Neuhaus, Lars	University of Oldenburg
Kühn, Martin	University of Oldenburg
Pao, Lucy Y.	Univ of Colorado at Boulder
Keywords: Control of renewable energy resources Abstract: With the development of lidar technology for measuring wind disturbances ahead of a wind turbine, various feedforward control techniques have been proposed to utilize preview disturbance information for rotor speed regulation. Among these is model predictive control (MPC), which generates an optimal control trajectory subject to system constraints, but very few physical tests have been conducted using MPC for wind turbines presumably due to the challenges involved in solving an optimization problem online. In this paper, we test an optimal feedback/feedforward control algorithm that maintains the clear disturbance inclusion of MPC but results in a linear control law that can be implemented easily. On the other hand, the proposed controller is not able to handle physical system constraints explicitly---full MPC is the subject of future work. A scaled wind turbine model in a wind tunnel is used for testing.
Paper VI163-13.5
PDF · Video · Kalman-Based Interacting Multiple-Model Wind Speed Estimator for Wind Turbines (I)
Lio, Wai Hou	Technical University of Denmark
Meng, Fanzhong	Technical University of Denmark
Keywords: Control of renewable energy resources, Control system design, Estimation and fault detection Abstract: The use of state estimation technique offers a means of inferring the rotor-effective wind speed based upon solely standard measurements of the turbine. For the ease of design and computational concerns, such estimators are typically built based upon simplified turbine models that characterise the turbine with rigid blades. Large model mismatch, particularly in the power coefficient, could lead to degradation in estimation performance. Therefore, in order to effectively reduce the adverse impact of parameter uncertainties in the estimator model, this paper develops a wind sped estimator based on the concept of interacting multiple-model adaptive estimation. The proposed estimator is composed of a bank of extended Kalman filters and each filter model is developed based on different power coefficient mapping to match the operating turbine parameter. Subsequently, the algorithm combines the wind speed estimates provided by each filter based on their statistical properties. In addition, the proposed estimator not only can infer the rotor-effective wind speed, but also the uncertain system parameters, namely, the power coefficient. Simulation results demonstrate the proposed estimator achieved better improvement in estimating the rotor-effective wind speed and power coefficient compared to the standard Kalman filter approach.
Paper VI163-13.6
PDF · Video · Fast Adaptive Fault Accommodation in Floating Offshore Wind Turbines Via Model-Based Fault Diagnosis and Subspace Predictive Repetitive Control (I)
Liu, Yichao	Delft University of Technology
Wu, Ping	Zhejiang Sci-Tech University
Ferrari, Riccardo M.G.	Delft University of Technology
van Wingerden, Jan-Willem	Delft University of Technology
Keywords: Control of renewable energy resources, Fault diagnosis and fault tolerant control, Reconfigurable control, sensor and actuator faults Abstract: As Floating Offshore Wind Turbines (FOWTs) operate in deep waters and are subjected to stressful wind and wave induced loads, they are more prone than onshore counterparts to experience faults and failure. In particular, the pitch system may experience Pitch Actuator Stuck (PAS) type of faults, which will result in a complete loss of control authority. In this paper, a novel fast and adaptive solution is developed by integrating a model- based Fault Diagnosis (FD) scheme and the Subspace Predictive Repetitive Control (SPRC). The FD role is to quickly detect and isolate the failed pitch actuator. Based on the fault isolation results, a pre-tuned adaptive SPRC is switched online in place of the existing one, whose initial values of the parameters has been tuned offline to match the specific faulty case. After that, SPRC employs subspace identification to continuously identify a linear model of the wind turbine over a moving time window, and thereby formulate an adaptive control law to alleviate the PAS-induced loads. Results show that the developed architecture allows to achieve a considerable reduction of the PAS-induced blade loads. More importantly, the time needed to reduce the PAS-induced loads are significantly shortened, thus avoiding further damage to other components during the adaption time and allowing continued power generation.
Paper VI163-13.7
PDF · Video · Fatigue Load Reduction and Variable-Structure Control Techniques for DFIM-Based Wind Farm Scenarios
Cacciolatto, Andrea	Politecnico Di Torino
Capello, Elisa	Politecnico Di Torino, CNR-IEIIT
Wada, Takayuki	Osaka University
Fujisaki, Yasumasa	Osaka Univ
Keywords: Energy systems, Sliding mode control Abstract: This paper proposes a trade-off approach between fatigue reduction and power extraction for wind farm scenarios, in which a simplified model for a Horizontal Axis Wind Turbine is developed. Both the aerodynamics and the electrical-mechanical model are implemented, considering a Doubly-Fed Induction Machine (DFIM). This model is controlled and connected to the grid by a back-to-back converter, composed of two bi-directional voltage source inverters. Moreover, the stator windings of the generator are directly linked to the grid and the rotor windings are connected to the grid through the power converter. The control of the VSIs is based on super-twisting sliding mode control (STW-SMC), which guarantees robustness and low chattering effects. A wake model and an optimization problem for the reduction of the loads are included, to reduce the maximum fatigue load without compromising the power extraction. The results show a performance tracking of a desired rotational speed for the DFIMs and reduction of fatigue and damage, with a limited power reduction compared with the maximum power point tracking.
Paper VI163-13.8
PDF · Video · Dynamometer Test Rig Drive Train Control with a High Dynamic Performance: Measurements and Experiences
Neshati, Mohsen	Fraunhofer Institute for Wind Energy Systems
Wenske, Jan	Fraunhofer Institute for Wind Energy Systems IWES
Keywords: Control system design, Test and documentation, Instrumentation and control systems Abstract: This paper presents the control design and dynamic performance evaluation for a 10 MW dynamometer test rig for wind turbine nacelles. The purpose is to control the applied torque by the drive train, required for an accurate emulation of rotor characteristics in the laboratory. This is implemented in a hardware-in-the-loop simulation framework for electrical certification test procedures, introducing high dynamic requirements. Therefore, a feedback-feedforward as well as a H-infinity controller is implemented to benefit from high dynamic and robustness capabilities, respectively. Furthermore, due to the lack of a suitable torque measurement in the meganewton-meter range, model-based algorithms are incorporated and the implemented time-varying Kalman filter provides the unmeasured variables. In addition, for performance analysis independent of any specimen, exclusive experiments are designed and executed using small signal perturbation under load conditions. The results are analysed here elaborately and control bandwidth is distinguished under realistic conditions. Overall, the measurements demonstrate an effective control with a bandwidth of up to 30 Hz.
Paper VI163-13.9
PDF · Video · Wind Turbine Lifetime Control Using Structural Health Monitoring and Prognosis (I)
Do, Manh Hung	University of Duisburg Essen
Söffker, Dirk	Univ of Duisburg-Essen
Keywords: Control of renewable energy resources, Control system design, Impact of deregulation on power system Control Abstract: In wind energy operation and maintenance costs significantly contribute to the overall cost. This paper proposes a novel adaptive lifetime control approach for wind turbines to reduce operation and maintenance costs. The approach is based on a cascade structure with the outer loop utilizing structural health monitoring and prognosis techniques to determine suitable controller parameters and reference values of the inner loop. The trade-off between power production and load reduction is balanced to achieve predefined service lifetime using the knowledge of current system state-of-health and predicted future damage accumulation behavior. Unscheduled downtime is avoided by guaranteeing the predefined lifetime, hence reducing the maintenance cost. Simulation results using a reference wind turbine model show that the proposed control strategy can regulate the lifetime or the accumulated damage to the desired value with a reasonable sacrifice in harvested power.
Paper VI163-13.10
PDF · Video · Closed Loop Control of Aerodynamic Load Fluctuations on Wind Turbine Airfoil Using Surface Plasma Actuators
Nelson-Gruel, Dominique	University of Orleans
Joseph, Pierric	Arts Et Métiers - Institute of Technology
Paulh-Manssens, Alexis	University of Orléans, INSA-CVL, PRISME, EA4229
Leroy, Annie	French Air Force Academy
Aubrun, Sandrine	Ecole Centrale De Nantes
Chamaillard, Yann	University of Orléans
Keywords: Real time control of environmental systems, Natural and environmental systems Abstract: In a century where the green energy is a vital challenge, research about wind turbine is taking its place to give an alternative solution to polluting and fossil energies. Various scales of studies are possible for wind turbine as the farm, the wind turbine and the blade. In this study we focused on the load alleviation produced by airflow speed and incidence angle variation by means of active flow control. Wind turbine greatly loses its efficiency when faced to wind gusts, moreover, the blade life span is reduced by the oscillation created by the wind. Thus, a control law based on Plasma actuator is studied to reduce the blade oscillation and actively keep a constant lift. Plasma actuator is used to change the air circulation around the blade, thus, the lift. Proofs of concepts are conducted thanks to experiments in a wind tunnel and through numerical model.

VI163-14
Estimation and Control for Batteries	Regular Session
Chair: Namerikawa, Toru	Keio University
Co-Chair: Cagliano, Anna Corinna	Politecnico Di Torino
Paper VI163-14.1
PDF · Video · An Artificial Potential Field-Based Lithium-Ion Battery SOC Equilibrium Method in Electric Vehicles
Jiang, Fu	Central South University
Jin, Cheng	Central South University
Liao, Hongtao	Central South University
Li, Heng	Central South University
Wu, Yue	Central South University
Liu, Yongjie	Central South University
Peng, Jun	Central South University
Huang, Zhiwu	Central South University
Keywords: Application of power electronics, Control system design Abstract: A novel cell equilibrium algorithm which is used for battery state of charge equilibrium of battery pack is proposed in this paper. Cell equilibrium algorithm is a key technology for lithium-ion battery pack in the energy storage systems. In order to eliminate the imbalance of battery state of charge, it's generally controlled by adjusting the charging current. The artificial potential field can construct a virtual force function, which provides the mapping between state of charge deviation and charging current. Therefore, an artificial potential field-based equilibrium method to balance battery state of charge was proposed in this paper. By reasonably distributing the charging current of the battery, the equilibrium of the battery state of charge can be achieved. A laboratory testbed has been built to verify the effectiveness of the proposed method compared with conventional method. Experiment results analyzed the energy consumption and the convergence speed of state of charge deviation under artificial potential field control with different parameters.
Paper VI163-14.2
PDF · Video · Lithium-Ion Battery Procurement Strategies: Evidence from the Automotive Field
Cagliano, Anna Corinna	Politecnico Di Torino
Mangano, Giulio	Politecnico Di Torino - Department of Management and Production
Rafele, Carlo	Politecnico Di Torino
Carlin, Antonio	Politecnico Di Torino
Keywords: Intelligent control of power systems, Control and optimization of supply chains, Process optimisation Abstract: Electric and hybrid vehicle diffusion is nowadays promising but still limited, also due to the high costs of key components such as lithium-ion batteries (LIBs). A significant contribution to these relevant economic values is given by not optimized supply chain structures. Therefore car manufacturers approaching electrification are considering different strategies to either purchase complete LIBs or producing them in-house. However, literature lacks quantitative studies assessing the logistics implications of LIB procurement policies in the automotive sector. The present work proposes a decision-making approach leveraging the main logistics and environmental issues involved in both internally producing and buying complete LIB packs. Such a framework is intended to increase the awareness about the complexity of the supply chain of batteries for electric and hybrid vehicles in order to further stimulate its investigation. Future research will extend the approach to include additional aspects as well as procurement configurations.
Paper VI163-14.3
PDF · Video · Hybrid Estimation Algorithm for Lithium-Ion Battery Based on PI Observer
Huang, Denggao	CATARC
Wang, Yuehui	CATARC
Zhao, Jing	CATARC
Wang, Xu	CATARC
Zhu, Zhongwen	CATARC
Wang, Tong	CATARC
Zhou, Yilu	CATARC
Jin, Peng	CATRAC
Li, Cheng	China Automotive Technology & Research Center
Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Control of renewable energy resources Abstract: In view of poor adaptive ability and accuracy when estimating SOC with a single algorithm, a hybrid estimation algorithm with PI observer and Coulomb counting method is proposed in this paper. The algorithm firstly uses the RLS (Recursive Least Squares) method to identify parameters of the battery. Secondly, the open circuit voltage is calculated by the PI observer. Based on the difference between the calculated value and the estimated value, a PI dynamic adjustment is performed. Thus the integration coefficient of the Coulomb integration is optimized in real time. The research shows that, the method can dynamically correct the cumulative deviation of the Coulomb method.
Paper VI163-14.4
PDF · Video · Frequency Response-Based Initial Parameter Estimation for SOC of Lithium-Ion Battery
Natori, Kohei	Keio University
Mizuno, Keisuke	Keio University
Namerikawa, Toru	Keio University
Sartori, Sabrina	University of Oslo
Eliassen, Frank	University of Oslo
Keywords: Smart grids, Control of renewable energy resources, Intelligent control of power systems Abstract: In this paper, we propose a novel parameter initial value estimation method of Lithium-ion battery for state of charge (SOC) estimation by using Local Regression Modeling (LRM) and Vector Fitting (VF). To estimate SOC accurately using nonlinear Extended Kalman filter, an adequate set of initial parameters of the battery model are required. Therefore, we apply LRM and VF method to derive the initial parameters and the battery model from database of the frequency response. In addition, we show the SOC estimation method using EKF by determined initial value and model. Finally, the effectiveness of the proposed method is shown via several experimental results.
Paper VI163-14.5
PDF · Video · Model-Based End of Discharge Temperature Prediction for Lithium-Ion Batteries
Faraji Niri, Mona	University of Warwick
Bui, Truong Minh Ngoc	University of Warwick
Yu, Tung Fai	University of Warwick
Marco, James	University of Warwick
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Hybrid and alternative drive vehicles, Vehicle dynamic systems Abstract: Battery fast charging is one of the key techniques that affects the public acceptability and commercialization of electric vehicles. Temperature is the critical barrier for fast charging as at low temperatures an increased risk of lithium plating and at high temperatures safety concerns limits the charging rate. To facilitate a fast charging mechanism, preconditioning the battery and maintaining its temperature is vital. Battery temperature prediction before a fast charging event can help reducing the energy consumption for battery preconditioning. In this paper, we propose a method for battery end of discharge temperature prediction for fast charging purposes. Firstly, a Gaussian mixture data clustering is performed on battery load data characterisation, subsequently a Markov model is trained for load prediction, and finally a battery lumped parameter equivalent circuit and thermal model is developed and employed for end of discharge time and ultimately end of discharge temperature prediction. Cylindrical lithium-ion battery is selected to prove the concept and both simulations and experiments show the capabilities of the proposed method for temperature prediction of batteries under load profiles obtained from real-world drive cycles of electric vehicles.

VI163-15
Control of Renewable Energy Resources	Regular Session
Chair: Faulwasser, Timm	TU Dortmund University
Co-Chair: Vermillion, Christopher	NC State
Paper VI163-15.1
PDF · Video · Active Power Control Based on Hydrogen Availability in a Storage Power Plant
Ahmed, Nayeemuddin	University of Rostock
Gerdun, Paul	University of Rostock
Weber, Harald	University of Rostock
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Power systems stability Abstract: The concept of Electrical Energy Storage (EES) has progressively gained prominence as a means to large-scale integration of intermittent Renewable Energy Sources (RES). The Storage Power Plant (SPP), which uses hydrogen as its primary fuel, is one such solution that can autonomously supply or store electrical energy in bulk according to the requirements of the network. Previous investigations have verified the ability of such a power plant to provide the required ancillary services in order to ensure a secure electrical power supply system. However, one aspect that has remained untested is the effect of diminishing or excess stored hydrogen on the operation of this power plant. In practice, the SPP can be exposed to such extreme situations when it is required to generate or store energy for long periods. Thus, in this paper, a controller model has been recommended which can protect the SPP system when the hydrogen mass in its storage reaches alarming levels. Based on the control mechanism, whenever the hydrogen mass in its storage is about to surpass the upper or lower permissible limits, the SPP can seamlessly transition from one mode to another and adjust its power output. This enables the SPP to regulate the level of its stored hydrogen mass.
Paper VI163-15.2
PDF · Video · Power System Resiliency Enhancement with Ternary Pumped – Storage Hydropower
Nag, Soumyadeep	Baylor University
Lee, Kwang Y.	Baylor University
Keywords: Modeling and simulation of power systems, Dynamic interaction of power plants, Power systems stability Abstract: This paper investigates, how Ternary Pumped Storage Hydropower (T-PSH) can help enhance power system resiliency by contributing primary frequency regulation in both pumping and generating modes. As renewable penetration increases, power system inertia decreases. Simultaneously, the frequency of storms and earthquakes have increased. As such power system resiliency is a key issue in low inertia power systems. To cater to this issue, the authors investigate the ability of T-PSH to provide primary frequency support in pumping and generating mode. The governor dynamics of the IEEE 9-bus system and T-PSH have been modeled and integrated. When the system is subjected to a step increase or decrease in load, results display that not only can the T-PSH provide pump mode regulation using the hydraulic short-circuit, but it can also transit smoothly between pumping and generating mode within a few seconds using the clutch. By changing its mode the T-PSH unit can provide a regulation capability equal to twice that of the unit rating.
Paper VI163-15.3
PDF · Video · A Model Predictive Control Scheme to Improve Performance of a Path-Following Controller for Airborne Wind Energy
Fernandes, Manuel C. R .M.	Universidade Do Porto
Paiva, Luis Tiago	Universidade Do Porto
Fontes, Fernando A. C. C.	Universidade Do Porto
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Control system design Abstract: Airborne Wind Energy Systems involve, in most solution concepts, flying kites at high speeds on a pre-specified, crosswind, optimized path. We develop a heading angle controller, using Model Predictive Control (MPC) on top of a guidance logic control, to maintain the kite within the desired path. The computed MPC law is used to enhance an existing controller and is able to preserve its stabilizing properties. The performance of the overall scheme can only improve upon the one of the basis controller. The optimization problems involved in the MPC algorithm are solved in an efficient way since the optimizer starts from a feasible solution. Nevertheless, even when the optimizer fails to provide an adequate solution in time, a guaranteed stabilizing law is used.
Paper VI163-15.4
PDF · Video · Optimal Cyclic Spooling Control for Kite-Based Energy Systems
Daniels, Joshua	North Carolina State University
Reed, James	North Carolina State University
Cobb, Mitchell	North Carolina State University
Siddiqui, Ayaz	North Carolina State University
Vermillion, Christopher	NC State
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Modeling and simulation of power systems Abstract: This paper presents a control strategy for optimizing the the spooling speeds of tethered energy harvesting systems that generate energy through cyclic spooling motions that consist of high-tension spool-out and low-tension spool-in. Specifically, we fuse continuous-time optimal control tools, including Pontryagin's Maximum Principle, with an iteration domain co-state correction to develop an optimal spooling controller for energy extraction. In this work, we focus our simulation results specifically on an ocean kite system where the goal is to optimize the spooling profile while remaining at a consistent operating depth and corresponding average tether length. This paper demonstrates a 14-45% improvement (depending on the operating tether length and corresponding flow speed) in power generation compared to a baseline, heuristic, control strategy.
Paper VI163-15.5
PDF · Video · Hierarchical Control Design and Performance Assessment of an Ocean Kite in a Turbulent Flow Environment
Reed, James	North Carolina State University
Cobb, Mitchell	North Carolina State University
Daniels, Joshua	North Carolina State University
Siddiqui, Ayaz	North Carolina State University
Muglia, Michael	Coastal Studies Institute
Vermillion, Christopher	NC State
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems Abstract: This paper presents a hierarchical control framework for a kite-based marine hydrokinetic (MHK) system that executes power-augmenting cross-current flight, along with simulation results based on a high-fidelity turbulent flow model that is representative of flow conditions in the Gulf Stream. The hierarchical controller is used to robustly regulate both the kite's flight path and the intra-cycle spooling behavior, which is ultimately used to realize net positive energy production at a base station motor/generator system. Two configurations are examined in this paper: one in which the kite is suspended from a surface-mounted platform, and another in which the kite is deployed from the seabed. To evaluate the robustness of this control framework in a realistic ocean environment, we present simulation results whereby we superimpose low-frequency data from the Mid Atlantic Bight South Atlantic Bight Regional Ocean Modeling System and acoustic Doppler current profiler measurements with a high-frequency turbulence model, resulting in a high-fidelity 3D spatiotemporal flow field that is presented to the kite system. Based on this simulation framework, we demonstrate the effectiveness of the control system both in terms of robust flight and power generation.
Paper VI163-15.6
PDF · Video · Nonlinear Control of Wind Energy Conversion System Based on DFIG with a Mechanical Torque Observer
Noussi, Karim	Faculty of Sciences Ben M'sik, University Hasan II
Abouloifa, Abdelmajid	EMI
Katir, Hanane	Faculty of Sciences Ben M'sik, University Hasan II
Lachkar, Ibtissam	EMI
Giri, Fouad	University of Caen Normandie
Guerrero, Josep M.	Aalborg University, Denmark
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems Abstract: In this paper, an advanced nonlinear backstepping control approach is developed and applied to the whole nonlinear system including the AC/DC/AC converters combined with the doubly-fed induction generator(DFIG). A high gain observer is synthesized, in order to provide an estimated value of the mechanical torque whereas, a wind speed estimation block is designed based on roots polynomial method; followed by sensorless maximum power point tracking (MPPT). The control objectives are fourfold: (i) Forcing the generator speed to track the reference signal given by the MPPT block, (ii) adjusting the stator reactive power injected into the grid to be null, (iii) Regulating the DC-link voltage between the rotor side and the grid side converters at the desired level, (iv) assuring a unitary power factor in the grid side. The achievement of these control objectives leans on a multi-loop regulator which shows a satisfying performance as far as it concerns the simulation results.
Paper VI163-15.7
PDF · Video · Optimal Operation Strategy for Electric Vehicles Charging Stations with Renewable Energy Integration
Diaz-Londono, Cesar	Politecnico Di Torino
Ruiz, Fredy	Politecnico Di Milano
Mazza, Andrea	Politecnico Di Torino
Chicco, Gianfranco	Politecnico Di Torino
Keywords: Control of renewable energy resources, Control system design, Optimal operation and control of power systems Abstract: This paper proposes an aggregator for the optimal scheduling of a Electric Vehicle (EV) charging station. Assuming that the station charging can consume energy from the power grid and also from a renewable source at no cost, Day-Ahead and Real-Time strategies are developed for the station, considering uncertainty in the local renewable generation source. First, a scheduler decides the energy to buy in the day ahead market from the power grid considering a renewable source forecast and an EVs schedule. An autoregressive model developed from 5 years of historical solar radiation data is applied. In real time, a model predictive control strategy is designed to follow the scheduled power from the grid, compensating variations in renewable generation by exploiting exibility in the EVs charging process. The resulting optimization problems are convex programming problems that can be solved efficiently. Simulation analysis show the effectiveness of the strategy in absorbing the variability of the renewable source, minimizing the deviations between the day ahead schedule and the actual real time consumption from the grid.
Paper VI163-15.8
PDF · Video · Nonlinear Model Predictive Control Applied to Concentrated Solar Power Plants
Jesuino Dettmer, Ramon	Federal University of Santa Catarina
da Costa Mendes, Paulo Renato	System Analysis, Prognosis and Control
Normey-Rico, Julio Elias	Federal Univ of Santa Catarina
Keywords: Control of renewable energy resources, Control system design, Optimal operation and control of power systems Abstract: This papers presents a nonlinear model predictive controller (NMPC) for temperature control in solar collector fields. The proposed NMPC uses feedback linearization for handling the systems nonlinearities in a mixed integer quadratic programming (MIQP) formulation that makes the constraints convex in the new coordinates, making the controller solution an optimal one. Several simulations are shown with real data and a validated model of solar field to illustrate the advantages of the proposed strategy over other general-purpose NMPC methods, showing great improvement in constraint satisfaction.
Paper VI163-15.9
PDF · Video · Robust Local Controllers Design for the AC Grid Voltage Control of an Offshore Wind Farm
Diaz-Sanahuja, Carlos	Jaume I University
Peñarrocha-Alós, Ignacio	Universitat Jaume I De Castelló
Vidal-Albalate, Ricardo	Jaume I University
Keywords: Control of renewable energy resources, Control system design, Power systems stability Abstract: In this paper we deal with the problem of voltage control of the AC grid in an offshore wind farm by means of several converters, all of them connected to the AC offshore grid at the Point of Common Coupling (PCC) through different transmission lines. We propose to control the voltage simultaneously by all the connected converters, i.e., we have multiple actuators with the same goal. However, the number of operative converters can change during the wind farm operation and dynamics changes. Thus, it is necessary to assure the stability of the whole system in all different scenarios. In order to achieve a global design and implementation strategy, we propose the use of same controller parameters for all converters. For this kind of wind farm topology, we address the design of controllers as an optimization problem where we seek to maximize the robustness against uncertainty in the model of transmission lines and changes in the number of connected wind turbines guaranteeing the stability of the whole system in all different scenarios as well as a given settling time. Due to the proposed design strategy it is not necessary communication between different converters and controllers do not need to be re-tuned when the number of connected converters changes.
Paper VI163-15.10
PDF · Video · Inter-Turn Short-Circuit Fault Ride-Through for DFIG Wind Turbines
Ma, Kuichao	Aalborg University
Zhu, Jiangsheng	Aalborg University
Soltani, Mohsen	Aalborg University
Hajizadeh, Amin	Aalborg University
Zhe, Chen	Aalborg University
Keywords: Control of renewable energy resources, Fault accommodation and Reconfiguration strategies Abstract: Inter-Turn Short-Circuit (ITSC) of the stator winding is one of the most common faults in asynchronous generators. A significant feature of ITSC is the increase of the current in the faulty phase. Improper treatment may lead to unnecessary power loss or further deterioration. Therefore, this paper proposes a fault ride-through strategy under the stator ITSC fault for Doubly-Fed Induction Generator (DFIG) wind turbines. When the closed-loop state observer detects the fault and the current is higher than the rated current, the faulty wind turbine switches to down-regulation mode for protecting the faulty generator. The rotational speed reference is kept at the maximum value. Then the difference between the current and the rated current with the proportion-integration operation is superimposed to the original generator torque reference. Simulation results show that the faulty phase current can be decreased to the rated value, effectively. Although the power output is reduced as well, the impact of the fault does not develop to a failure. So the faulty wind turbine can continue to operate before the maintenance. The proposed strategy can avoid the unnecessary power loss caused by shut-down, improve the operational capacity of wind turbines and reduce the maintenance costs under the ITSC fault.
Paper VI163-15.11
PDF · Video · Simultaneous State and Fuel Property Estimation in Biomass Boilers - Theory and Practice
Zemann, Christopher	BEST – Bioenergy and Sustainable Technologies GmbH
Gölles, Markus	BEST – Bioenergy and Sustainable Technologies GmbH
Horn, Martin	Graz University of Technology
Keywords: Control of renewable energy resources, Instrumentation and control systems, Constraint and security monitoring and control Abstract: A key factor for the further distribution of biomass boilers in modern energy systems is the capability of changing the applied feedstock during normal plant operation. This is only possible with the application of advanced control strategies that utilize knowledge about the state variables and varying fuel properties. However, neither the state variables nor the fuel properties are measurable during plant operation and, thus, need to be estimated. This contribution presents a method for the simultaneous real-time estimation of the state variables and the fuel properties in fixed-bed biomass boilers which is a novel approach in the field of biomass boilers. The method bases on an Extended Kalman Filter using a nonlinear dynamic model and measurement data from the combustion process. The estimated variables are the masses of dry fuel and water in the fuel bed as well as the fuel's bulk density, water content, chemical composition and lower heating value. The proposed method is easy to implement and requires moderate computational effort which increases the potential of its application at actual biomass boilers. The proposed method is verified with simulation studies and by test runs performed at a representative small-scale fixed-bed biomass boiler. The estimation results show a good agreement with the actual values, demonstrating that the proposed method is capable of accurately estimating the biomass boiler’s state variables and simultaneously its fuel properties. For this reason, the presented method is a key technology to ensure the further distribution of biomass boilers in modern energy systems.
Paper VI163-15.12
PDF · Video · Cooperative Control of a Flywheel Energy Storage System with Identical Damping
Liang, Zeren	South China University of Technology
Cai, He	South China University of Technology
Keywords: Control of renewable energy resources, Intelligent control of power systems, Control system design Abstract: Motivated by the work of Cai and Hu (2018), this paper considers the dual objective control problem of a ywheel energy storage system targeting simultaneous state-of-energy balancing and reference power tracking. It is first shown that, in the presence of flywheel damping, the steady state solution subject to the dual control objective exists and is defined by a virtual dynamic system. Second, under the identical damping condition, it is proven that the control law proposed in Cai and Hu (2018) can still solve the dual objective control problem.
Paper VI163-15.13
PDF · Video · An Iterative Learning Approach to Economic Model Predictive Control for an Integrated Solar Thermal System
Morrison, Jacob	University of British Columbia
Nagamune, Ryozo	University of British Columbia
Grebenyuk, Vladimir	Ascent Systems Technologies
Keywords: Control of renewable energy resources, Model predictive and optimization-based control Abstract: An iterative learning (IL) approach to disturbance prediction for economic model predictive control (EMPC) is proposed and applied to a domestic integrated solar thermal system (ISTS). The disturbance in the ISTS, which is the user hot water demand, is predicted iteratively by taking advantage of the repetitive nature of domestic hot water consumption. The predicted disturbance is then utilized by EMPC for improved ISTS control performance. Various user load scenarios are developed for simulations based on historical data, and the performance of the proposed control method is compared against an idealistic EMPC scheme with perfect load information along with existing EMPC methods and a baseline proportional-integral controller. It is demonstrated that the proposed IL approach to EMPC achieves electrical costs within 1% of the idealistic case while outperforming all other methods in both energy savings and output temperature management.
Paper VI163-15.14
PDF · Video · Nonlinear Model Predictive Control to Reduce Pitch Actuation of Floating Offshore Wind Turbines
Sarkar, Saptarshi	Trinity College Dublin
Fitzgerald, Breiffni	Trinity College Dublin
Basu, Biswajit	Trinity College Dublin
Keywords: Control of renewable energy resources, Model predictive and optimization-based control Abstract: Modern-day wind turbines use active pitch control to reduce mechanical loads on the turbines in addition to regulating generator power. These control algorithms increase blade pitch actuation, primarily to reduce the 1P (once per revolution) component of the aerodynamic load. However, it is also known that the failure of the blade pitch system is a significant source of turbine downtime. Control algorithms that increase pitch actuation will only add to this problem. Therefore, increasing blade pitch actuation to reduce mechanical loads may not be the best solution is every situation. Hence, in this paper, an individual pitch control strategy is proposed to reduce pitch actuation without deteriorating rotor speed regulation or increasing structural vibrations. The controller is developed under a Non-linear Model Predictive Control (NMPC) framework. It is assumed that a preview of the inflow wind field is available in the form of LIDAR (LIght Detection And Ranging) wind speed measurements. The results presented in this paper show that it is possible to reduce blade pitch actuation below the baseline level while maintaining rated rotor speed.
Paper VI163-15.15
PDF · Video · Active Control of the Reliability of Wind Turbines
Requate, Niklas	Fraunhofer Institute for Wind Energy Systems IWES
Meyer, Tobias	Fraunhofer Institute for Wind Energy Systems
Keywords: Control of renewable energy resources, Model predictive and optimization-based control Abstract: Wind turbines operation is always a trade-off between reliability and functionality. A turbine's main functionality is power generation, but this induces loads on the structure. These ultimately lead to damage and thus reduce reliability. A suitable trade-off for safe and prolonged operation needs to be found during the design process. During operation, however, the selected trade-off will not be ideal for each individual turbine because of site specific influences. Multiple trade-offs can be obtained with different turbine controller configurations. These allow for an adaptation to the individual reliability and functionality of a specific wind turbine. A closed loop supervisory reliability control for wind turbines is implemented and tested. It is based on a feedback of the current turbine condition and continuously selects the optimal controller from a predefined set of controller configurations. Simulations are conducted to evaluate the effect of reliability control on wind turbine reliability and power production over several years of operating time. Results show that a desired reliability of a wind turbine can be actively controlled even on a slow time scale and with a small number of feasible turbine controller configurations. Reference tracking is sufficiently good despite uncertain wind conditions.
Paper VI163-15.16
PDF · Video · Fully Robust Sensorless Control of Direct-Drive PMSG Wind Turbine Feeding a Water Pumping System
Benzaouia, Soufyane	MIS, University of Picardie Jules Verne
Rabhi, Abdelhamid	M.I.S (Modelisation, Information Et Systèmes)
Zouggar, Smail	University Mohammed 1st, School of Technology, Laboratory of Ele
Elhafyani, Mohamed	LEEM, University Mohammed 1st, High School of Technology
El Hajjaji, Ahmed	Univ. De Picardie Jules Verne
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Intelligent control of power systems Abstract: In this paper, we propose a fully sensorless control strategy that possess the robustness and the stability properties. The aim is maximizing the extracted power and ensuring an optimum control without mechanical sensors and with a low cost. Firstly, a fuzzy logic technique has been used to estimate the wind speed information. Then an improved model reference adaptive system based on sliding mode controller adaptation mechanism has been developed to estimate the permanent-magnet synchronous generator speed. The proposed control strategy contains two control loops, an outer control loop based on fuzzy variable gain super twisting algorithm used to regulate the generator speed to its optimal value and to provide the optimum DC side current, and an internal control loop based on sliding mode controller used to regulate the DC side current to its optimal value and provides the appropriate signal for the DC-DC boost converter. The considered system in this work is supposed supplying a water pumping system for the use in isolated areas. The proposed control strategy has been compared to the conventional MPPT control method based on the concept of perturbation and observation. The obtained results show, a good estimation performance for the wind speed estimator and the improved MRAS speed observer, a good tracking performance and a good stability around the maximum power point. Comparing to the classical MPPT strategy, the current technique can greatly reduce the ripples that can generate vibrations and significant noise on the generator and the motor-pump group.
Paper VI163-15.17
PDF · Video · Sliding Mode & Single Input Fuzzy Logic Controllers for Voltage Regulation of an Asynchronous Wind Turbine Using STATCOM
Mokhtari, Mohammed	University Mohammed 1st, School of Technology Oujda
Zouggar, Smail	University Mohammed 1st, School of Technology, Laboratory of Ele
Msirdi, Nacer	AIX Marseille III
Elhafyani, Mohamed	LEEM, University Mohammed 1st, High School of Technology
Keywords: Control of renewable energy resources, Modeling and simulation of power systems, Intelligent control of power systems Abstract: This paper demonstrate the fiability and the efficiency of a proposed control law based on a combination of sliding mode and single input fuzzy logic controllers, used to command a static synchronous compensator in order to improve voltage profile and stability of an asynchronous wind turbine despite wind speed and load variation. All simulation results as well as the modeling of the wind power system and the design of the proper controllers are described in detail in this document.
Paper VI163-15.18
PDF · Video · Min-Max Operation Optimization of Renewable Energy Combined Cooling, Heating, and Power Systems Based on Model Predictive Control
Dong, Xing	Shangdong University
Lu, Jianbo	Shanghai Jiao Tong University
Sun, Bo	Shandong University
Keywords: Control of renewable energy resources, Optimal operation and control of power systems Abstract: The renewable energy combined cooling, heating, and power (CCHP) systems can effectively utilize the residual heat generated by the system to provide thermal energy or cooling energy for users, which can highly improve the utilization efficiency of primary energy. However, the prediction error of renewable energy sources (RES) and load can affect the optimal operation of the system. This paper considers the prediction error of RES and load. According to the dynamic characteristics of energy storage unit, an energy optimization model with prediction error is proposed. On this basis, a min-max optimization operation strategy based on model predictive control (MPC) is proposed. The operating cost of the system is taken as the objective function. By optimizing the output of each device in the system, the operating cost of the system is minimized under the maximum prediction error.
Paper VI163-15.19
PDF · Video · Model Predictive Control for Wave Energy Converters: A Moving Window Blocking Approach
Guerrero-Fernández, Juan	The University of Sheffield
Gonzalez Villarreal, Oscar Julian	University of Sheffield
Rossiter, J. Anthony	Univ of Sheffield
Jones, Bryn L.	University of Sheffield
Keywords: Control of renewable energy resources, Optimal operation and control of power systems, Modeling and simulation of power systems Abstract: Ocean wave energy is one of the most concentrated sources of renewable energy. However, until now it has not reached the economic feasibility required to be commercialised. To improve the efficiency of wave energy converters, several advanced control strategies have been proposed, including Model Predictive Control (MPC). Nevertheless, the computational burden of the underlying optimisation problem is a drawback of conventional (Full-Degree of Freedom, F-DoF) MPC, which typically limits its application for real-time control of systems. In this paper, a Moving Window Blocking (MWB) approach is proposed to speed-up the time required for each optimisation problem by reducing the number of decision variables using input parameterised solutions. Numerical simulation of a generic single device point absorber wave energy converter controlled by this scheme confirms the potential of this approach.
Paper VI163-15.20
PDF · Video · Starting-Up Strategies for Solar Thermal Fields Attending to Time and Economic Criteria: Application of Hierarchical Control
Gil, Juan Diego	Universidad De Almería
Roca, Lidia	CIEMAT - Plataforma Solar DeAlmería
Berenguel, Manuel	University of Almeria
Keywords: Control of renewable energy resources, Process control applications, Model predictive and optimization-based control Abstract: Solar thermal fields are usually coupled to storage tanks to improve the dispatchability of this energy. In direct configuration and without an auxiliary energy source, the state of the storage tank at the beginning of the operation is very relevant. If the storage device is stratified or unloaded in terms of energy, the start-up phase until reaching the desired operating point can take long time and reduce the benefits. Consequently, this paper presents a two layer hierarchical controller aimed at reducing the costs and time spent in this operating phase. The upper layer is based on a Nonlinear Model Predictive Control (NMPC) strategy, and the lower one is composed by Proportional Integral Derivative (PID) controllers. The proposed technique was applied to a real facility located at Plataforma Solar de Almería (southest of Spain). Moreover, a comparative simulation study with manual and previous approaches proposed in literature was performed to evidence the important economic and time savings achieved by the application of the developed technique.
Paper VI163-15.21
PDF · Video · Improving Solar and PV Power Prediction with Ensemble Methods
Dao, Le Anh	Politecnico Di Milano
Ferrarini, Luca	Politecnico Di Milano
La Carrubba, Dario	Politecnico Di Milano
Keywords: Control of renewable energy resources, Smart grids Abstract: Estimation of the generated power of renewable energy resources is in general important for planning operations as well as demand balance and power quality. This paper addresses the problem of the estimation of the short-term (3-hour ahead) and medium-term (1-day ahead) generated power of a photovoltaic plant. Firstly, the design of day-ahead SR predictors is investigated with different setups of time series models, and with their combinations with the weather forecast services using ensemble methods. Support Vector Machine methods are also adopted in this stage, to cluster data. Secondly, under a similar ensemble framework, the Generated Power (GP) prediction is investigated. The whole GP and Solar Radiation (SR) prediction tasks are then implemented on a low-cost, embedded mini PC module Raspberry Pi 3. As an application, the GP prediction is employed in the control system of a typical microgrid settings focusing on energy management problem. The impact of the quality of GP prediction on the performance of the controller is also evaluated in this paper.
Paper VI163-15.22
PDF · Video · A DFIG-Based Wind Turbine Operation under Balanced and Unbalanced Grid Voltage Conditions
Boukili, Yassine	University of Porto, Faculty of Engineering, Porto
Aguiar, A. Pedro	Faculty of Engineering, University of Porto (FEUP)
Carvalho, Adriano	University of Porto, Faculty of Engineering
Keywords: Power systems stability, Application of power electronics, Smart grids Abstract: This paper presents a case study of a Doubly Fed Induction Generator (DFIG) wind turbine in operation subject to balanced and unbalanced grid voltage conditions. Three scenarios are addressed: balanced grid, symmetrical and asymmetrical voltage dips. We describe the DFIG model and the control strategies adopted to stabilize the system during voltage faults, in order to protect the converters. Several simulation experiments are presented to illustrate the performance and effectiveness of the described control strategies.
Paper VI163-15.23
PDF · Video · Model Predictive Control for Optimal Energy Management of an Island Wind Storage Hybrid Power Plant
Aguilera-González, Adriana	ESTIA Institute of Technology
Lopez-Rodriguez, Ruben	ESTIA Institute of Technology
Vechiu, Ionel	ESTIA Institute of Technology
Bacha, Seddik	Grenoble Institute of Technology, Grenoble ElectricalEngineerin
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Smart grids Abstract: This paper presents a Model Predictive Control-based Energy Management System for compliance with the day-ahead power dispatching plan of a hybrid power plant connected to the Guadeloupe Island electrical grid. The hybrid power plant combines a wind farm and a Li-ION battery energy storage system. The proposed EMS handles several operation rules, in order to solve the optimization problem while considering the production forecasting data as well as the battery lifespan. A simulation study is implemented via PowerFactory and Matlab.
Paper VI163-15.24
PDF · Video · Hybrid Automaton Control of Three Phase Reduced Switch Shunt Active Power Filter Connected Photovoltaic System
Hekss, Zineb	TI Lab, Faculty of Sciences Ben M’sick, Hassan II University, BP
Abouloifa, Abdelmajid	EMI
Janik, Jean-Marie	Université De Caen Normandie
Lachkar, Ibtissam	EMI
Echalih, Salwa	TI Lab, Faculty of Sciences Ben M’sick, Hassan II University, BP
Chaoui, Fatima-Zahra	ENSET, Université Mohammed V
Giri, Fouad	University of Caen Normandie
Keywords: Control system design, Control of renewable energy resources, Modeling and simulation of power systems Abstract: In this paper, a new controller design method based on hybrid automaton approach is proposed to solve the problem of controlling a three-phase reduced switch shunt active power filter (SAPF) connected to photovoltaic system. The control objective is two-fold: (i) ensuring a satisfactory power factor correction (PFC) by compensating the harmonic and reactive currents absorbed by the nonlinear load; (ii) regulating the voltage in the output of the photovoltaic panels to track a reference provided by the MPPT block in order to guarantee the power exchange between the photovoltaic source and three-phase electrical power grid. The considered control objectives are dealt with using a new two-loop cascaded controller. The hybrid automaton approach is applied in the inner loop, which ensures the operation modes of switching design in order to ensure a unity power factor. A proportional-integral (PI) regulator is used in the outer-loop to ensure the tight regulation of the voltage across the photovoltaic panels with a well-known P&O algorithm (MPPT). Finally, it is demonstrated through simulation results under Matlab/Simulink SimPowerSystems environment that the proposed automaton model and its controller can achieve the desired objectives.
Paper VI163-15.25
PDF · Video · Nonlinear Control of Multicellular Single-Stage Grid Connected Photovoltaic Systems with Shunt Active Power Filtering Capability
Aourir, Meriem	University HASSAN II of Casablanca
Abouloifa, Abdelmajid	EMI
Aouadi, Chaouqi	University HASSAN II, Faculty of Science Ben M'sik
El Otmani, Fadwa	University HASSAN II of Casablanca
Lachkar, Ibtissam	EMI
Giri, Fouad	University of Caen Normandie
Guerrero, Josep M.	Aalborg University, Denmark
Keywords: Modeling and simulation of power systems, Control system design, Control of renewable energy resources Abstract: This work deals with the nonlinear control of grid connected photovoltaic (PV) systems with shunt active power filtering functionality. The Proposed power plant consists of two PV generators, a single-phase power grid connected to non-linear loads at point of common coupling (PCC) and a multicellular inverter that will play a dual role, on one hand, compensating harmonic currents and reactive power caused by non-linear loads, and on the other hand, injecting active power provided by the PV generators into the electrical grid. The proposed nonlinear controller is designed in order to achieve the following objectives: i) guarantee a balanced distribution of the input voltage over the power switching devices, ii) ensure a unity power factor in the grid by compensating harmonic currents and reactive power, iii) operate the PV panels in their optimal operating points by extracting the maximum power despite the climatic variations. In order to achieve these objectives, a cascaded non-linear controller, consisting of two loops is designed, an outer loop based on a filtered PI controller for the regulation of PV panels voltages and, an inner loop developed based on Lyapunov approach for power factor correction as well as flying capacitors voltages regulation. Furthermore, a state observer is combined with the non-linear controller to perform the grid voltage estimation. The proposed power plant and control strategies are verified and validated by numerical simulation using Matlab/SimPowerSystems environment to assess their performance.
Paper VI163-15.26
PDF · Video · Advanced Nonlinear Control of a Grid-Connected Photovoltaic Power System Using N-Cascaded H-Bridge Multilevel Inverters
Katir, Hanane	University Hassan II of Casablanca, Faculty of Sciences Ben M’si
Abouloifa, Abdelmajid	EMI
Lachkar, Ibtissam	EMI
Noussi, Karim	Faculty of Sciences Ben M'sik, University Hasan II
Giri, Fouad	University of Caen Normandie
Guerrero, Josep M.	Aalborg University, Denmark
Keywords: Modeling and simulation of power systems, Control system design, Control of renewable energy resources Abstract: The present paper discusses the modelling and the nonlinear control of a DC/AC conversion system composed of photovoltaic arrays, boost converters, DC bus capacitors, N-cascaded H-bridge multilevel inverters (CHBMI) and an L-filter linked to a single-phase grid. This work aims at achieving threefold control objectives: i) regulating the voltages across the PV panels in order to extract the available maximum power, ii) guaranteeing a unitary power factor (UPF) by forcing the grid current to be sinusoidal and in phase with the electric network voltage, iii) controlling the DC-link voltages to track their given references. The achievement of these objectives is done thanks to a regulator based on a multi-loop structure. Indeed, on one hand, each panel is individually controlled to track the maximum power point; on the other hand, two cascaded loops aim at ensuring a satisfactory power factor correction and DC-link voltages regulation. The proposed regulator is developed using the nonlinear backstepping approach and some tools from Lyapunov stability. The simulation results, obtained using MATLAB/SIMULINK/ SimPowerSystems environment, prove that the synthesized regulator meets its objectives and presents interesting performance in terms of tracking and regulation.
Paper VI163-15.27
PDF · Video · Dynamic Matrix Control of Thermal Power for Multiple NSSS Modules
Di, Jiang	Tsinghua University
Dong, Zhe	Tsinghua University
Keywords: Instrumentation and control systems, Model predictive and optimization-based control, Control system design Abstract: To suppress the fluctuation from both load side and intermittent renewable energy (IRE), nuclear power plants (NPPS) should be operated in load-following mode to improve economic competitiveness. The modular high temperature gas-cooled reactor (MHTGR) belongs to the category of small nuclear reactor (SMRs) and is suitable for load-following by the virtue of online refueling ability and inherent safety. To realize economies of scale for MHTGR, multi-modular scheme that multiple nuclear steam supply system (NSSS) modules are connected in parallel providing superheated steam for common turbine is recommended to achieve desired power ratings. However, because of the large heat capacity in the pebble-bed of MHTGR and thermal coupling of different NSSSs through common secondary loop fluid network, the current control strategy which suppresses the nuclear power, coolant temperatures measurement from their set-points without considering thermal dynamic of NSSS itself, may not favorable for heat transfer in the NSSS. To improve the load-following ability, a multivariable dynamic matrix control (DMC) is constituted to dynamic compensate the thermal energy variation of NSSS. The implementation of the DMC has a typical cascade structure, where DMC revises the set-points of NSSS module in outer loop and the existing PID control law is adopt for stabilization in inner loop. Numerical results show that this cascade dynamic matrix control can improve the transient of thermal power under power maneuvering.
Paper VI163-15.28
PDF · Video · Analysis of Impact of Harmonic Disturbances on the Mechanical System of Wind Turbine
Cai, Lijun	University of Rostock
Yin, Hang	Global Energy Interconnection Research Institute Europe GmbH
Lan, Yuanliang	Global Energy Interconnection Research Institute Europe GmbH
Lan, Tian	Global Energy Interconnection Research Institute Europe GmbH
Wu, Xiang	Global Energy Interconnection Research Institute Europe GmbH
Karaagac, Ulas	Hong Kong Polytechnic University
Mahseredjian, Jean	Polytechnique Montréal
Eckel, Hans-Günter	University of Rostock
Weber, Harald	University of Rostock
Keywords: Modeling and simulation of power systems, Dynamic interaction of power plants, Control of renewable energy resources Abstract: This paper analyzes the influence of harmonic frequencies on mechanical parts of wind turbines. Pitch system and drive train behavior of both doubly fed induction generator (DFIG) and full converter (FC) based wind turbines will be analyzed in detail.

VI163-16
Energy Management and Control in Microgrids	Regular Session
Chair: Scattolini, Riccardo	Politecnico Di Milano
Co-Chair: Fagiano, Lorenzo	Politecnico Di Milano
Paper VI163-16.1
PDF · Video · Adaptive Output Feedback Controller of Voltage Source Inverters in Microgrid Connected Mode
Ammeh, Leila	ENSA, Ibn Tofail University, Kenitra
El Fadil, Hassan	ENSA, Ibn Tofail Univesity
Oulcaid, Mustapha	ENSA, Ibn Tofail University, Kénitra
Giri, Fouad	University of Caen Normandie
Ahmed-Ali, Tarek	Université De Caen Normandie
Keywords: Application of power electronics, Control of renewable energy resources, Smart grids Abstract: This paper deals with the control of voltage source inverters (VSI) connected to the main grid. The controller aim is fourfold: i) enforcing the current injected by the VSI to follow a given reference, ii) estimating the grid resistance and inductance, iii) estimating the current load and the grid voltage, iv) assuming an asymptotic stability of the system. To achieve these aims, we designed an adaptive output feedback controller using the backstepping technique and the high gain approach. Moreover, the controller has the ability to compensate the reactive power of the local load. The system stability was analyzed by Lyapunov theory. The controller performances were illustrated by simulations with grid parameter and load current variations.
Paper VI163-16.2
PDF · Video · Scalable PI Voltage Stabilization in DC Microgrids
Sadabadi, Mahdieh	University of Sheffield
Shafiee, Qobad	University of Kurdistan
Keywords: Control of renewable energy resources, Application of power electronics, Smart grids Abstract: This paper addresses the problem of decentralized PI-based voltage stabilization in islanded DC microgrids with DC-DC buck converters. We propose a voltage control approach with a decentralized PI control structure. The proposed voltage control design is scalable and does not rely on the global model of the microgrids and parameters of the distribution lines. Moreover, it guarantees the asymptotic stability of the DC microgrid systems. The scalability of the design and asymptotic stability are ensured by the use of a separable quadratic-type Lyapunov function, with a fixed-structure Lyapunov matrix, as well as the LaSalle's invariance principle. The effectiveness of the proposed voltage control strategy is evaluated through simulation case studies.
Paper VI163-16.3
PDF · Video · Pinning-Based Distributed Predictive Control of Secondary Voltage for an Islanded Microgrid
Yu, Yi	Wuhan University
Liu, Guoping	University of South Wales
Hu, Wenshan	Wuhan University
Zhou, Hong	Wuhan Univ
Keywords: Control of renewable energy resources, Intelligent control of power systems, Smart grids Abstract: In this study, a pinning-based distributed predictive control of secondary voltage is proposed for an autonomous microgrid (MG) with communication constraints. The proposed predictive control is fully distributed, which requires the information of each distributed generator (DG) on an islanded microgrid and that of its neighbors. In particular, the predictive control scheme can compensate for the communication constraints actively rather than passively. Moreover, it could reduce the computation burden of the controller owing to the developed pinning-based control scheme. It is worthwhile to mention that the purpose of voltage restoration based on distributed predictive control is achieved by minimization of the utility function, which not only ensures the feasibility of the control input but also simultaneously restores the voltage of an autonomous microgrid to a prescribed level through an introduction of tracking and coordination cost. Finally, simulation results are presented to validate the effectiveness of the proposed control methodology.
Paper VI163-16.4
PDF · Video · Using Microgrids for Critical Load Restoration in Distribution Systems
Noludwe, Sibabalo	University of Cape Town
Folly, Komla	University of Cape Town
Keywords: Control of renewable energy resources, Smart grids Abstract: This paper proposes a restoration strategy using microgrids to restore power to critical loads to enhance distribution system resilience after an extreme event. The restoration problem is posed as an optimization problem to maximize the number of critical loads restored after the extreme event has resulted into multiple faults. After the fault, the restoration strategy alters the topological structure of the distribution network by removing the faulted lines and applies minimum spanning tree algorithm to find a possible topology that will be used for the restoration. The service time to the restored critical loads is incorporated as one of the constraints to ensure continuous supply for the duration of the outage. The problem is modeled as a mixed-integer linear program (MILP) and solved using the CPLEX solver on the MATLAB platform. The effectiveness of the proposed restoration strategy is validated using the modified IEEE 33-bus test system under multiple fault scenarios that represent damage resulted from the extreme event.
Paper VI163-16.5
PDF · Video · Voltage Synchronization of Discrete-Time Microgrids Over Analog Fading Channels
Lai, Jingang	RWTH Aachen University
Lu, Xiaoqing	Wuhan University
Keywords: Control of renewable energy resources, Smart grids, Control of distributed systems Abstract: In this paper, a novel distributed leader-follower consensus control scheme is developed for discrete-time DC microgrids with multiplicative communication noises. The specific objective is to regulate the output voltage of microgrids to the desired value by employing a sparse communication network with multiplicate noises. For efficient coordination of distributed generators (DGs), a distributed leader-follower consensus control protocol with shared communication framework and considering multiplicative noise disturbances is considered. Specifically, in order to restore the output voltage sag of DGs caused by the local loads changes, the proposed distributed cooperative controllers are designed to restore the output voltage of DGs to the desired value. Then the closed-loop stability analysis of the whole system is carried out, accordingly we derive the sufficient conditions to achieve all the DERs' output voltage synchronization in mean square. Moreover, the control gains have been designed to guarantee the convergence. With the proposed scheme, control derivation of voltage produced during the primary control stage can be well remedied even if the multiplicative communication noises exist. Finally, numerical results validate the robustness of our proposed method against multiplicative communication noises effect.
Paper VI163-16.6
PDF · Video · A Load Power Sharing Strategy for Virtual Oscillator-Based Photovoltaics Generation in Islanded Microgrid
Tran, Thai Trung	Institute for Automation of Complex Power Systems
Raisz, David	Institute for Automation of Complex Power Systems
Monti, Antonello	RWTH Aachen University
Min Htut, Han	Sirindhorn International Thai-German Graduate School of Engineer
Keywords: Control system design, Control of renewable energy resources, Application of power electronics Abstract: This paper proposes a method to control the power-sharing between parallel connected photovoltaics generation in an islanded microgrid. The two-stage converter-based PV generation is used combined with modified virtual oscillator control and cascade sliding mode control. With this proposed control configuration, the power-sharing in proportion to the inverter power rating and maximum power point tracking is guaranteed autonomously without the need of energy storage system, while maintaining the primary advantages of the virtual oscillator control method. The effectiveness of the proposed control scheme is validated through simulations in MATLAB/Simulink.
Paper VI163-16.7
PDF · Video · Distributed Event-Triggered Consensus-Based Control for Current Sharing and Voltage Stabilization of DC Microgrids
Mola, Mina	Qatar University
Meskin, Nader	Qatar University
Khorasani, Khashayar	Concordia Univ
Massoud, Ahmed	Qatar University
Keywords: Control system design, Distribution automation, Smart grids Abstract: In this paper, the problem of distributed event-based control of large scale power systems is addressed. Towards this end, a Direct Current (DC) microgrid that is composed of multiple interconnected Distributed Generation Units (DGUs) is considered. Voltage stability is guaranteed by utilizing decentralized local controllers for each DGU. A distributed discrete-time event-triggered (ET) consensus-based control strategy is then designed for current sharing in the DGUs. In this mechanism, the transmissions occur while a specified event is triggered to prevent unessential utilization of communication resources. The asymptotic stability of the ET-based controller is shown formally by using Lyapunov stability via linear matrix inequality (LMI) conditions. The effectiveness of the proposed methodology is demonstrated and substantiated in simulation case study.
Paper VI163-16.8
PDF · Video · Power Quality Management of Interconnected Microgrids Using Model Predictive Control
Garcia-Torres, Felix	Spanish National Center on Hydrogen
Vazquez, Sergio	Universidad De Sevilla, Sevilla, Spain
Bordons, Carlos	Universidad De Sevilla
Moreno-Garcia, Isabel	Universidad De Cordoba, Cordoba, Spain
Gil, Aurora	Universidad De Cordoba, Cordoba, Spain
Roncero-Sanchez, Pedro	University of Castilla-La Mancha, Ciudad Real, Spain
Keywords: Dynamic interaction of power plants Abstract: In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems.
Paper VI163-16.9
PDF · Video · Droop-Based Two-Layer Cooperation for Multiple DC Microgrid Clusters
Lu, Xiaoqing	Wuhan University
Lai, Jingang	RWTH Aachen University
Keywords: Intelligent control of power systems, Control of renewable energy resources, Control of distributed systems Abstract: Enabling energy exchange among multiple dc microgrids (MGs) and adjusting the current outputs of all converters proportional to their power capacities can significantly improve power supply reliability as well as effectively avoid overloaded or uncertainty. By dividing all converters within each dc MG cluster into the leader-converters and follower-converters according to their physical cluster topology structure, the leader and follower control layers are respectively formulated. Then a droop-based two-layer cooperative strategy is developed, under which the weighted average voltage of all converters can be regulated to their rated references, meanwhile, the accurate current sharing can be simultaneously realized not only within each dc MG but also among multiple dc MG clusters. All controllers are fully distributed and can be applied in all sparse two-layer cyber networks, control time constant related sufficient conditions are also derived to ensure the whole system stability. The effectiveness of the results are verified through different cases in MATLAB/SimPowerSystems.
Paper VI163-16.10
PDF · Video · A Hierarchical Approach for Balancing Service Provision by Microgrids Aggregators
La Bella, Alessio	Politecnico Di Milano
Bonassi, Fabio	Politecnico Di Milano
Sandroni, Carlo	RSE SpA
Fagiano, Lorenzo	Politecnico Di Milano
Scattolini, Riccardo	Politecnico Di Milano
Keywords: Optimal operation and control of power systems, Analysis and control in deregulated power systems, Smart grids Abstract: Volatile renewable energy resources are gaining more and more diffusion throughout the power system, and their intermittent production calls for enhanced balancing efforts. With a recent regulation, the European Union endorsed the participation of aggregated microgrids to the balancing of power system. The resulting assets optimization problem, however, features privacy constraints that prevent a full exchange of information, making fully centralized approaches not suitable. To this purpose, this work proposes a hierarchical approach allowing microgrids' aggregators to provide balancing services in an efficient and privacy-friendly fashion. This approach is based on a novel method to describe the power flexibility that each microgrid can provide, allowing to significantly decrease the computational effort.
Paper VI163-16.11
PDF · Video · Optimal Frequency Restoration of Inverter-Interfaced Microgrids Via Distributed Energy Management
Xu, Yiqiao	University of Manchester
Parisio, Alessandra	The University of Manchester
Ding, Zhengtao	The University of Manchester
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Smart grids Abstract: Despite the potential role of microgrids is well recognized in supporting the integration of renewable energy sources into the future power system, the impacts of intermittence renewable generation on the microgrid frequency stability is still being explored, and the related challenges remain to be addressed. In this paper, we focus on an islanded inverter-interfaced microgrid and present a consensus-based gradient algorithm for optimal frequency restoration via distributed energy management, preserving the standard hierarchical control architecture but merging the interdependent layers. The network-preserving model is applied to prevent loss of network topology and transient characteristics. Furthermore, not only distributed generators but also demand-side customers are considered to be actively participating in the proposed architecture. Convergence analysis implies that the closed-loop system is asymptotically stable, and its equilibrium will converge to the optimal solution of the associated energy management problem, which is consistent with the observation from the simulation study, including intermittent generation and load perturbation, carried out on a 6-bus test microgrid system. Therefore, the effectiveness of the proposed algorithm is verified.
Paper VI163-16.12
PDF · Video · Optimal Power Flow for a Multi-Energy Vector MicroGrid
Wang, Chaoyun	Efficacity
Faille, Damien	Electricité De France
Galai-Dol, Lilia	Efficacity
Damm, Gilney	Paris-Saclay University
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Smart grids Abstract: The paper introduces a combined modeling that can allow the Optimal Power Flow of a Multi-Energy Vector merging electric and thermal networks. This topic is motivated by the goal of introducing larger shares of renewable energy in the overall energy consumption, which is hindered by the intermittent nature of these renewable energies. To tackle this problem, it is acknowledged that almost half energy consumption in urban environments is used for thermic objectives. For this reason, a possible solution is to use in parallel electric and thermic networks, called the Multi-Energy Vector. It is then first proposed a combined model, and then aiming at cost optimization, it is performed an optimal power flow, such as to supply references for lower-level controllers, attaining the desired objectives, and keeping all variables inside their operational margins. The proposed scheme is applied to both electric and thermal networks of the under-construction Moulon quarter of Paris-Saclay University. The simulation results illustrate the economic gains that can be made with this joint operation.
Paper VI163-16.13
PDF · Video · Stochastic Optimization Model for Energy Management of a Hybrid Microgrid Using Mixed Integer Linear Programming
Franke, Georg	Technische Universität Darmstadt
Schneider, Maximilian	Technische Universität Darmstadt
Weitzel, Timm	Technische Universität Darmstadt, Institute of Production and Su
Rinderknecht, Stephan	Technische Universitaet Darmstadt
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Smart grids Abstract: In the context of increasing decentralization of the energy supply system, the concepts of microgrids are well suited to realise a reduction of CO2-emissions and create opportunities for new business models. For this the operation of the microgrid has a significant impact. In real systems, however, the consideration of uncertainties in generation and consumption data is essential for the operating strategy. Therefore, in this paper we propose an optimization model based on mixed-integer linear programming for the hybrid microgrid of a residential building district and include stochastic optimization in a computing efficient way. For this, a two-stage approach is used. In a first step, we do a day-ahead optimization to determine a schedule for the combined heat and power plant and the power exchanged with the grid. In a second step, based on the results of the day-ahead optimization and the observed values for the uncertain parameters the intraday optimization is carried out. Using a numerical example, we demonstrate the advantages of this stochastic optimization over conventional optimization based on point forecasts. The data used originates from a real life project in Darmstadt, Germany.
Paper VI163-16.14
PDF · Video · Handling Power Losses in a DC Microgrid through Constrained Optimization
Zafeiratou, Igyso	National Technical University of Athens
Prodan, Ionela	INP Grenoble
Boem, Francesca	University College London
Lefevre, Laurent	Univ. Grenoble Alpes
Keywords: Optimal operation and control of power systems, Control system design, Modeling and simulation of power systems Abstract: This paper extends a hierarchical control approach for power balancing in a meshed DC microgrid while minimizing the power losses in the central transmission network. The control strategy is divided into three layers in hierarchical framework: i) the high level solves a continuous-time optimization problem which minimizes the DC-bus power loss and the electricity cost from the external grid power purchase through the combined use of differential flatness with B-splines parametrization; ii) the middle level employs a tracking Model Predictive Control (MPC) method which mitigates the discrepancies among the optimal and the actual profiles; iii) the low level controller handles the switching activity of the converters. The proposed approach is validated in simulation for a specific meshed DC microgrid system.
Paper VI163-16.15
PDF · Video · A Droop Approach for the Passivity--Based Control of Microgrids
Ortega Velazquez, Isaac	Universidad Nacional Autónoma De México
Avila-Becerril, Sofia	Universidad Nacional Autonoma De Mexico
Espinosa-Perez, Gerardo	Universidad Nacional Autonoma De Mexico
Keywords: Power systems stability, Control system design, Application of power electronics Abstract: In this paper, the stability properties of a microgrid in closed-loop with local inverters' controllers and a droop power-sharing scheme are studied. The main result is the formal statement that this system is asymptotically stable concerning the equilibrium point that satisfies desired operating conditions. In contrast to the results reported in the literature, neither the stability analysis of the inverter's dynamics is omitted, nor is it assumed that the only dynamic behavior is that corresponding to the droop scheme. The contribution exploits the inclusion of a passivity-based control law for the inverters and the input-to-state stability properties exhibited by the considered droop algorithm. The validity of the analysis is illustrated via a numerical evaluation.
Paper VI163-16.16
PDF · Video · Adaptive Variable Synthetic Inertia from a Virtual Synchronous Machine Providing Ancillary Services for an AC MicroGrid
Perez, Filipe	CentraleSupélec, L2S Laboratory
Damm, Gilney	Paris-Saclay University
Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Ribeiro, Paulo	ISEE Institute, Federal University of Itajuba
Monaro, Renato	University of São Paulo, Polytechnic School
Keywords: Power systems stability, Control system design, Dynamic interaction of power plants Abstract: The paper proposes an adaptive variable synthetic inertia strategy to provide frequency and voltage support (ancillary services) in a AC MicroGrid (weak grid) composed of diesel generators and loads. A DC MicroGrid is connected to the AC one by a Voltage Source Converter (VSC). The VSC converter is driven as a Virtual Synchronous Machine (VSM), where the control strategy follows a swing equation such the converter emulates a synchronous machine, including inertial support. A rigorous stability analysis is developed based on Lyapunov technique assuring proper stability conditions for an adaptive inertia designated, such that, frequency stability is improved and power oscillations are reduced. This strategy can be exploited in low inertia systems like MicroGrids or grids with high penetration of renewables. Simulation results illustrate the performance of the proposed control and the system's operation, where a comparison with droop control is presented.
Paper VI163-16.17
PDF · Video · Denial of Service Attacks on Centralized Controlled DC Microgrids: Vulnerability Assessment and Recommendations
Saleh, Mahmoud	Department of Electrical and Computer Engineering, Florida Polyt
El Hariri, Mohamad	Florida International University
Keywords: Smart grids Abstract: This paper aims to provide more insight on the impact of Denial of Service (DOS) attacks on centralized controlled DC Microgrids. A mathematical model, which the author previously developed to represent microgrid stability during delays, will be utilized to investigate the impact of DOS attacks. A vulnerability analysis will be conducted to highlight the attack timing and strategy that could jeopardize the microgrid operation.
Paper VI163-16.18
PDF · Video · Consensus Based Synchronization of Clocks to Diminish the Effect of Clock Drifts in Microgrids
Parada Contzen, Miguel	Universidad Del Bio Bio
Keywords: Smart grids, Control system design, Modeling and simulation of power systems Abstract: Inverter based microgrids implemented with more than one Grid Forming source can suffer of, so called, clock drifts when inaccurate time measurement is present. Considering that the main cause of this problem is the, slightly, different value of the time register at each clock, the synchronization approach seems like a natural choice even when additional hardware for the implementation of the sources might be required. We explore several alternatives for improving synchronization, understood as the clocks sharing the same value for their respective time register. This leads to propose a consensus based algorithm for synchronization with relatively low communication and computation requirements. The analysis is complemented with simulation examples to show the main characteristic of the different algorithms.
Paper VI163-16.19
PDF · Video · Simultaneous Active and Reactive Power Sharing with Frequency Restoration and Voltage Regulation for Single Phase Microgrids
Parada Contzen, Miguel	Universidad Del Bio Bio
Keywords: Smart grids, Intelligent control of power systems, Power systems stability Abstract: The control of microgrids at secondary hierarchical level offers multiple challenges. When the entire microgrid is seen as a Multiple-Input-Multiple-Output (MIMO) system and the Voltage Source Inverters (VSI) connected as control actuators, distributed controllers have been proposed to independently achieve active power sharing, reactive power sharing, frequency restoration, or voltage regulation around nominal values. Here we address these issues simultaneously in generic single phase mesh-micro-grids with arbitrary non-linear loads, in order to derive formal conditions that can be used to check if a given controller allows to reach all four mentioned control objectives. The paper is complemented with a simulation example where the main characteristics of the proposed methodology can be seen.
Paper VI163-16.20
PDF · Video · Optimal Hierarchical Control of DC Microgrids: Modelling and Experimental Validation
Pendieu Kwaye, Marcel	RSE SpA
Vignali, Riccardo	RSE SpA
Lazzari, Riccardo	RSE SpA
Keywords: Smart grids, Optimal operation and control of power systems, Control of renewable energy resources Abstract: DC Microgrids are receiving a growing interest thanks to the advantages offered for the integration of renewable sources. This paper presents an optimal hierarchical control for DC microgrids that performs multiple control objectives, like: (i) voltage regulation, (ii) minimization of the losses, (iii) power sharing, (iv) energy storage management and (v) economic savings. The hierarchical control is made up of sequential actions such that, at the higher level, the optimal planning for power generators and storage systems is generated and then sent to the secondary control level. This level, based on model predictive control, is the core of this study and has three main function such as (i) voltage regulation, (ii) energy storage management and (iii) tracking of the optimal planning, taking into account the different characteristics of the DC components. The proposed control based on optimization has been validated with good results on the real low-voltage DC microgrid in RSE.
Paper VI163-16.21
PDF · Video · Smart Energy Dispatch for Networked Microgrids Systems Based on Distributed Control within a Hierarchy Optimization
Brahmia, Ibrahim	Shanghai Jiao Tong University
Wang, Jingcheng	Shanghai JiaoTong Univ
Shi, Yuanhao	Shanghai Jiaotong University
Lan, Yang	Shanghai Jiao Tong University
Keywords: Smart grids, Optimal operation and control of power systems, Control of renewable energy resources Abstract: Cooperative microgrids considered the next generation of smart energy trading technology. A promising solution is proposed in this paper, for smart energy management of cooperative multi microgrids (MMGs) systems based on dual level distributed strategy, achieved by two layers model predictive control (MPC) for optimal operation and energy scheduling of the DERs, and energy trading among multi-microgrids system, with efficient economic cost reduction. We employed a distributed system operator (DSO) as a supervisory layer for energy trading and dynamic power balance ensuring. Along with the local controller as a lower layer for tracking a reference trajectory from the upper layer, we developed an online algorithm with a hierarchical structure to solve the energy dispatching problem within dual-level optimization, offering an environmental-friendly control solution, due to reduction of fuel consumption. Finally, simulation results are presented to witness the advantages of our distributed algorithm approach in comparison to a non-cooperative strategy
Paper VI163-16.22
PDF · Video · Plug-And-Play Solvability of the Power Flow Equations for Interconnected DC Microgrids with Constant Power Loads
Jeeninga, Mark	University of Groningen
De Persis, Claudio	University of Groningen
van der Schaft, Arjan J.	Univ. of Groningen
Keywords: Smart grids, Optimal operation and control of power systems, Power systems stability Abstract: In this paper we study a power grid which consists of interconnected DC microgrids. These microgrids are equipped with constant-power loads, and the lines in the grid are assumed to be purely resistive. For this setup we present a sufficient condition which ensures that the power flow equations are feasible. The novelty of this condition is its plug-and-play property: If one would connect a new microgrid to the grid, there is a test for the new microgrid to guarantee that the interconnection satisfies this condition, and hence is feasible.
Paper VI163-16.23
PDF · Video · A Micro-Grid Energy Management Strategy Integrating Photovoltaic Energy Prediction
Ioli, Daniele	Politecnico Di Milano
Falsone, Alessandro	Politecnico Di Milano
Busboom, Axel	Munich University of Applied Sciences
Prandini, Maria	Politecnico Di Milano
Keywords: Smart grids, Optimal operation and control of power systems, Control of renewable energy resources Abstract: This paper deals with the integration in the electrical grid of distributed generation from renewables through energy management operations at the micro-grid level. We consider a micro-grid with a solar power plant and propose an energy management strategy that sets the energy exchange with the main grid during a one-day time horizon so as to minimize the electrical energy costs. In order to counteract uncertainty, the proposed strategy implements a predictive approach that decides at each time step how to operate the micro-grid on the residual time horizon based on a forecast of the photovoltaic energy production. To this purpose, we introduce a predictor of the photovoltaic energy production that is designed based on historical data. Validation on a testbed and simulation results show that the proposed method is promising.
Paper VI163-16.24
PDF · Video · Voltage Regulation and Current Sharing for Multi-Bus DC Microgrids
Bai, Handong	Southwest Jiaotong University
Zhang, Hongwei	Southwest Jiaotong Univ
Li, Chaoyong	Zhejiang University
Keywords: Smart energy grids, Remote and distributed control Abstract: It is well know that accurate voltage regulation and current sharing are conflicting control objectives for DC microgrids. By taking electrical network into consideration, this paper analyzes the relation between voltage regulation and current sharing. Based on this relationship, a novel control scheme, which simultaneously considers both voltage regulation and current distribution, is proposed. It significantly simplifies the design complexity and is able to adjust the degree of compromise between accurate voltage consensus and accurate current sharing.

VI163-17
Modeling and Simulation of Power Systems	Regular Session
Chair: Monti, Antonello	RWTH Aachen University
Co-Chair: Boje, Edward	University of Cape Town
Paper VI163-17.1
PDF · Video · Unsupervised Learning Method for Clustering Dynamic Behavior in the Context of Power Systems
Mitrentsis, Georgios	University of Stuttgart
Lens, Hendrik	University of Stuttgart
Keywords: Modeling and simulation of power systems Abstract: Aggregated dynamic equivalent models of active distribution networks (ADNs) are commonly derived using the measurement-based approach. This method exploits acquired data in order to estimate the model parameters using system identification techniques. However, most of the approaches assume that the system maintains the same dynamics for different operating conditions, even though the load mix and the distributed generation (DG) composition are constantly changing. To this end, this paper presents a novel method, which can be used as the first step of the system identification procedure, in order to take into account different system dynamics in ADN modeling. To do so, three unsupervised learning methods for clustering the various dynamic behaviors are introduced, yielding groups of measurements that represent different dynamics. In this context, the proposed methods leverage four clustering algorithms of different notion and complexity, namely k-means++, k-medoids, fuzzy c-means (FCM) and hierarchical clustering. To assess the validity of the proposed approach, real measurements acquired within a year in six real substations in Southern Germany are processed. The results highlight the remarkable difference in system dynamics justifying the necessity of an initial cluster analysis. Finally, the ratio of "Within Cluster sum of squares" to "Between Cluster Variation" (WCBCR) is deployed to compare the effectiveness of the clustering algorithms.
Paper VI163-17.2
PDF · Video · POG Modeler: The Web Power-Oriented Graphs Modeling Program
Zanasi, Roberto	Univ of Modena and Reggio Emilia
Keywords: Modeling and simulation of power systems Abstract: In this paper the Power-Oriented Graphs (POG) technique is introduced and a new modeling program named ``POG Modeler'', freely available on the web, is presented. In the POG Modeler program the physical systems can be defined graphically using an ascii commend-line interface and referring to predefined graphic symbols. The POG Modeler automatically analyzes the given physical system and provides the following outputs: 1) the differential equations of the given system in symbolic form: 2) The POG block scheme of the considered system; 3) the Simulink block scheme of the given system ready for the Matlab environment. The POG systems are simple block schemes that can be easily used also by beginners.
Paper VI163-17.3
PDF · Video · A Quantitative Risk Framework for DER-Rich Power System Planning and Decision Making
Demazy, Antonin	The University of Melbourne
Alpcan, Tansu	The University of Melbourne
Mareels, Iven	The University of Melbourne
Keywords: Modeling and simulation of power systems, Artificial intelligence, Control of renewable energy resources Abstract: The increased penetration of Distributed Energy Resources (DERs) within power networks is bringing challenges, an important one being the potential voltage excursions within the system that must be mitigated, as voltage must be maintained within statutory range at all time and at any node of the system by regulation. This paper proposes a scalable framework based on machine learning techniques (ML) to assess voltage excursion risks node by node and derive the related marginal probabilities in response to any net-loads under various DER penetration scenarios. The framework is then used to quantify the resulting financial impact of voltage excursion in large-scale networks. Therefore, this novel end-to-end risk framework supports decision making in the planning phase of networks in response to any intermittent DER penetration scenario. We show through simulations that the framework is both scalable to high-dimensional systems and efficient to handle vast number of scenarios. In our simulations, the use of ML technique enables to lower the computing time by a factor of 800 compared to load flow solving, while maintaining an accuracy greater then 95% , enabling the assessment of vast number of scenarios.
Paper VI163-17.4
PDF · Video · Construction of a State Space Model for an OTEC Plant Using Rankine Cycle with Heat Flow Rate Dynamics
Matsuda, Yoshitaka	Saga University
Suyama, Daiki	Saga University
Sugi, Takenao	Saga University
Goto, Satoru	Saga University
Yasunaga, Takeshi	Saga University
Ikegami, Y.	Saga Univ, Japan
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Control system design Abstract: In this research, a state space model for an ocean thermal energy conversion (OTEC) plant using Rankine cycle is proposed by considering the heat transfer dynamics. The model is constructed by using an existing simple dynamic model. The temperatures and heat flow rates of warm and cold seawater are selected as the state variables. The difficulty of the static calculation in the simple dynamic model on the construction of state space model is also clarified. To cope with this issue, in this research, the relationships between the state variables at steady state and the manipulated variable of warm seawater flow rate are derived. The usefulness and limitation of the proposed model is verified by simulation results.
Paper VI163-17.5
PDF · Video · Modelling of Variable Speed Hydropower for Grid Integration Studies
Reigstad, Tor Inge	Norwegian University of Science and Technology (NTNU)
Uhlen, Kjetil	NTNU
Keywords: Modeling and simulation of power systems, Control of renewable energy resources, Optimal operation and control of power systems Abstract: This paper proposes a hydraulic model based on the Euler turbine equations suitable for the purpose of grid integration studies of variable speed hydropower (VSHP). The work was motivated by the need to assess how the dynamic performance might change when a hydropower plant is operated at variable speed. The Euler model considers the water flow dependency on the turbine rotational speed and calculates the turbine power as a non-linear function of water flow, turbine rotational speed and guide vane opening. A waterway model is included, based on the 1-D momentum and continuity balance for a water-filled elementary pipe to simulate water hammer, mass oscillation and tunnel losses. These detailed and accurate models are necessary for recognising possible limitations in the hydraulic system, to model the turbine power and rotational speed correctly and thereby to be able to maximise power delivery for system control purposes. All Euler model parameters can be derived from the physical dimensions of the turbine and waterway, ensuring easy implementation. State-space representation of the Euler model is approximated by utilising a lumped-parameter equivalent of the penstock dynamics. Dynamic simulations and eigenvalue analysis show the strength of the Euler model compared to conventional hydropower models.
Paper VI163-17.6
PDF · Video · Modeling and Voltage Control of Bidirectional Resonant DC/DC Converter for Application in Marine Power Systems
Josevski, Martina	RWTH Aachen University
Korompili, Asimenia	RWTH Aachen Univesity
Monti, Antonello	RWTH Aachen University
Keywords: Modeling and simulation of power systems, Control system design, Application of power electronics Abstract: DC/DC converters have gained popularity in a number of industrial applications like electric vehicles or marine power systems, due to their high efficiency and power density levels. Pulse width modulation (PWM) and resonant converters are two main types of DC/DC converters. Thereby, the resonant converters happen to be the preferred technology in the design of modern marine power systems since these converters are more suitable for the high and middle voltage DC applications. The resonant converters are, however, highly nonlinear systems, which limits the use of linear control methods. In this study, we propose a comprehensive analysis, modeling and control concept of a DC/DC resonant converter in marine power systems. First, a mathematical model of the DC/DC resonant converter in the so-called CLLC topology is derived based on the generalized state-space averaging method. The model is used to design a dual-loop voltage control, which aims to regulate the voltage level at the low-voltage DC bus of the resonant converter. The dual-loop voltage control consists of the primal linear controller, which directly regulates the voltage and the reference generator, which dynamically modifies the voltage reference of the primal controller. The major advantage of the suggested control concept is the improved performance of the simple controller without the need to substitute it as well as the possibility to realize, if required, a multi-rate control concept. Simulation studies under different load conditions show that the suggested modeling and control concept improves voltage control and the closed-loop system response.
Paper VI163-17.7
PDF · Video · Analysis of Self-Oscillations in Three-Level Hysteresis Current Controlled H-Bridge
Krämer, Andreas	University of Applied Sciences Würzburg-Schweinfurt
Bohn, Christian	Clausthal University of Technology
Ali, Abid	University of Applied Sciences Würzburg-Schweinfurt
Keywords: Modeling and simulation of power systems, Control system design, Power systems stability Abstract: In direct-current control scheme, self-oscillations or limit cycles occur due to the hysteresis controller. In this contribution, the different types of self-oscillations in a three-level hysteresis current controlled H-bridge are analyzed. The investigations are based on Tsypkin's method for self-oscillations in relay control systems. So, the conditions for the different types of self-oscillations are given and the frequency of the oscillation and the on-to-off-ratio or pulse width of the switching hysteresis output are calculated exactly. The values correspond to the switching frequency and the duty cycle of the H-bridge. Furthermore, some analyses about the transfer characteristic of the control loop are made.
Paper VI163-17.8
PDF · Video · Quantitative Feedback Theory Design of Valve Position Control for Co-Ordinated Superheater Control of Main Steam Temperatures of Power Plant Boilers
Polton, Cheriska	University of Cape Town
Boje, Edward	University of Cape Town
Keywords: Modeling and simulation of power systems, Control system design, Process control applications Abstract: This paper presents an application of a single-input single-output (SISO) controller and a valve position controller (VPC) using robust PI controllers designed using Quantitative Feedback Theory (QFT) specifications to control superheater outlet steam temperatures of a 600MW once through boiler. To illustrate the methodology, a dynamic model of a tower-type boiler was modelled using Flownex® to test the valve position controller design application with structured uncertainty under varying load and disturbance conditions. The results show that the valve position controller application is more efficient than the SISO technique, allowing the final attemperator more bandwidth to deal with unexpected temperature changes.
Paper VI163-17.9
PDF · Video · Day-Ahead Building Load Forecasting with a Small Data-Set
Lauricella, Marco	Politecnico Di Milano
Cai, Zhongtian	Politecnico Di Milano
Fagiano, Lorenzo	Politecnico Di Milano
Keywords: Time series modelling, Bounded error identification, Machine learning Abstract: A new method is presented, to derive an algorithm that provides a forecast of one-day-ahead electricity consumption of a building. The approach aims to obtain high accuracy with a small data-set of 1-2 weeks, motivated by practical situations where the building is new or subject to relatively frequent changes, and/or limited local computation and memory are available. The method introduces a fictitious input signal that captures the prior information on the periodic behavior of building load time series. Moreover, the use of a linear model structure enables the derivation of guaranteed accuracy bounds on the forecast error, which can be used in day-ahead energy scheduling and optimization. Using an experimental data-set with measurements collected from an office building, it is found that the fictitious input can largely improve the prediction accuracy of the model, outperforming linear predictors and scoring a performance similar to that of nonlinear ARX models, such as recurrent neural networks, while retaining the capability to provide guaranteed accuracy bounds.
Paper VI163-17.10
PDF · Video · Evaluating the Environmental Benefit of Energy Symbiosis Networks in Eco-Industrial Parks
Marinelli, Simona	Università Di Modena E Reggio Emilia
Butturi, Maria Angela	University of Modena and Reggio Emilia
Rimini, Bianca	Universita' Di Modena E Reggio Emilia
Gamberini, Rita	University of Modena and Reggio Emilia
Marinello, Samuele	University of Modena and Reggio Emilia
Keywords: Modeling and simulation of power systems, Dynamic interaction of power plants, Control of renewable energy resources Abstract: In order to evaluate the environmental benefits of energy industrial symbiosis networks with the inclusion of renewable technologies, a model that minimises greenhouse gases emissions has been developed. A validation of the model has been carried out comparing the results with those calculated with a life cycle assessment of a reference case. The study demonstrates that energy industrial symbiosis networks integrating renewable energy technologies have the potential to significantly reduce greenhouse gases emissions and suggests a methodology to optimise energetic symbiosis connections inside eco-industrial parks.
Paper VI163-17.11
PDF · Video · Capacity Configuration of Integrated Energy System Considering Equipment Inertia
Li, Yuxuan	Southeast University
Zhang, Junli	Southeast University
Wu, Xiao	Southeast University
Shen, Jiong	Southeast University
Lee, Kwang Y.	Baylor University
Keywords: Modeling and simulation of power systems, Dynamic interaction of power plants, Optimal operation and control of power systems Abstract: The integrated energy system (IES) plays an important role in the development of clean energy through the complementary advantages of multi energy and the absorption capacity of renewable energy. However, because of the multi energy coupling and the intermittence of renewable energy, the risk of system dynamic instability increases. In order to solve the above issues, this paper considers the influence of the dynamic characteristics of the system from the level of planning and design stage. Based on the solar intensity and load demand curve of typical winter days and considering the daily economic operation of typical days and the dynamic characteristics of the system, an IES capacity configuration optimization model is established, which takes into account the system investment cost and the dynamic characteristics of the system. Then the genetic algorithm with penalty function is used to optimize the solution. Finally, according to the typical winter day data of a certain area in Nanjing, P.R.China, the rationality and validity of the model are verified, and the scientific configuration of an IES capacity considering dynamic performance is realized, which provides ideas and support for the planning and design of an IES later.
Paper VI163-17.12
PDF · Video · Feature Extraction for Day-Ahead Electricity-Load Forecasting in Residential Buildings
Kychkin, Aleksey	National Research University Higher School of Economics
Chasparis, Georgios C.	Software Competence Center Hagenberg GmbH
Keywords: Modeling and simulation of power systems, Identification and modelling, Process observation and parameter estimation Abstract: In the context of electricity demand response, an important task is to generate accurate forecasts of energy loads for groups of households as well as individual consumers. We consider the problem of short-term (one-day-ahead) forecasting of the electricity consumption load of a residential building. In order to generate such forecasts, historical energy consumption data are used, presented in the form of a time series with a fixed time step. In this paper, we first review existing (one-day-ahead) forecasting methodologies including: a) naive persistence models, b) autoregressive-based models (e.g., AR and SARIMA), c) triple exponential smoothing (Holt-Winters) model, and d) combinations of naive persistence and auto-regressive-based models (PAR). We then introduce a novel forecasting methodology, namely seasonal persistence-based regressive model (SPR) that optimally selects between lower- and higher-frequency persistence and temporal dependencies that are specific to the residential electricity load profiles. Given that the proposed forecasting method equivalently translates into a regression optimization problem, recursive-least-squares is utilized to train the model in a computationally efficient manner. Finally, we demonstrate through simulations the forecasting accuracy of this method in comparison with the standard forecasting techniques (a)-(d).
Paper VI163-17.13
PDF · Video · Performance Analysis of Long Horizon Predictive Control with Modified Sphere Decoding Algorithm
Touati, Mohamed Tamim	Shanghai Jiao Tong University
Li, Shaoyuan	Shanghai Jiao Tong Univ
Wu, Jing	Shanghai Jiao Tong University
Keywords: Modeling and simulation of power systems, Optimal operation and control of power systems, Application of power electronics Abstract: The complexity of the optimization problem arises in multistep model predictive control for power electronics as they are discrete by nature and have predefined control actions given as integer control variables. Generally, Sphere Decoding Algorithm (SDA) is used to solve the optimization problem. In this paper, we present an SDA with an Evolutionary Optimization attitude (EO) to simplify the complex exhaustive search that is brought by the long prediction horizon. The presented technique reconstructs a smaller search area from a large search area which decreases the number of candidate solutions. The performance of the optimization algorithm is evaluated through statistical analysis and computation burden.
Paper VI163-17.14
PDF · Video · Modeling and Simulation of Fractional Order PI Control Limiters for Power Systems
Murad, Mohammed Ahsan Adib	University College Dublin
Tzounas, Georgios	University College Dublin
Milano, Federico	UCD
Keywords: Modeling and simulation of power systems, Power systems stability Abstract: The paper focuses on the modeling and simulation of Fractional Order PI (FOPI) control limiters for power system applications. One windup limiter and three anti-windup limiter models, namely back calculation; automatic reset; and conditional integrator method, are considered and compared. A numerical convergence issue that emerges in models that include FOPIs with the conditional integrator method is duly described. In the case study, the proposed FOPI models are utilized for voltage regulation through a static synchronous compensator. The limiter models are compared by carrying time domain simulations on the IEEE 14-bus benchmark system.
Paper VI163-17.15
PDF · Video · Passivity Properties for Regulation of DC Networks with Stochastic Load Demand
Silani, Amirreza	University of Groningen
Cucuzzella, Michele	University of Groningen
Scherpen, Jacquelien M.A.	University of Groningen
Yazdanpanah, Mohammad Javad	University of Tehran
Keywords: Modeling and simulation of power systems, Power systems stability, Control system design Abstract: In this paper we present new (stochastic) passivity properties for Direct Current (DC) power networks, where the unknown and unpredictable load demand is modeled by a stochastic process. More precisely, the considered power network consists of distributed generation units supplying ZIP loads, i.e., nonlinear loads comprised of impedance (Z), current (I) and power (P) components. Differently from the majority of the results in the literature, where each of these components is assumed to be constant, we consider time-varying loads whose dynamics are described by a class of stochastic differential equations. Finally, we prove that an existing distributed control scheme achieving current sharing and (average) voltage regulation ensures the asymptotic stochastic stability of the controlled network.
Paper VI163-17.16
PDF · Video · Enhancements of the Numerical Simulation Algorithm for Natural Gas Networks Based on Node Potential Analysis
Rüdiger, Jens	University of Applied Science Wildau (TH Wildau)
Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Analysis and control in deregulated power systems Abstract: A reliable energy supply for the economy of every country is a matter of national importance. Powerful simulation tools for natural gas networks are essential for operators of gas networks. In this paper, enhancement algorithms of previous developed node potential analysis algorithm are presented. These enhancement algorithms are used for a reasonable setting of initial values in the numerical gas net simulation algorithm. The setting of the initial values has a significant influence on the convergence behavior of the numerical simulation. The presented enhancement algorithms are explained and simulation results are evaluated.
Paper VI163-17.17
PDF · Video · Probabilistic Look-Ahead Contingency Analysis Integration with Commercial Tool and Practical Data
Chen, Yousu	Pacific Northwest National Laboratory
Ren, Huiying	Pacific Northwest National Laboratory
Wu, Jun	GE Grid Solutions
Hou, Zhangshuan	Pacific Northwest National Laboratory
Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Constraint and security monitoring and control Abstract: This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with a commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments (practical data with commercial tool), significant efforts have been made to prepare test cases, modify the commercial tool to interface with the probabilistic algorithm, and adapt an extreme value distribution algorithm to analyze the commercial tool's violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.
Paper VI163-17.18
PDF · Video · A New Modeling Approach for Power Grid Online Analysis
Zhou, Michael	State Grid Electric Power Research Institute
Feng, Donghao	KeDong Electric Power Control System Company
Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Power systems stability Abstract: A new modeling approach for power grid online analysis is proposed to support the realization of a new online analysis system architecture. The model-driven software development, automatic code generation, and in-memory computing techniques are employed in the modeling approach. Data source adapters are developed for the integration of the model with the existing EMS system. A large-scale power grid online network data model (~40K-bus) is used for the model performance testing in a Lab environment. The proposed modeling approach was used to develop a new online analysis application, which was deployed and running in a provincial grid dispatching control center. The Lab and field performance measurement shows that the modeling approach-based application can achieve second-order end-to-end responsiveness.
Paper VI163-17.19
PDF · Video · A Model for Renewable Energy Symbiosis Networks in Eco-Industrial Parks
Butturi, Maria Angela	University of Modena and Reggio Emilia
Sellitto, Miguel	Universidade Do Vale Do Rio Dos Sinos - Unisinos
Lolli, Francesco	University of Modena and Reggio Emilia
Balugani, Elia	University of Modena and Reggio Emilia
Neri, Alessandro	University of Modena and Reggio Emilia
Keywords: Modeling and simulation of power systems, Smart grids, Control of renewable energy resources Abstract: Renewable energy technologies integration within industrial districts can boost carbon emissions reduction in the industry sector. The eco-industrial parks model promotes the sustainable use of energy and the application of energy synergies and energy exchanges that can include renewable sources of energy. This paper presents an optimization methodology based on a multi-stakeholder perspective to evaluate energy symbiosis including the integration of renewable energy sources within the parks. The study results in three scenarios providing to managers of single firms and parks relevant information for supporting decision making regarding the economic sustainability and the environmental impacts of the energy synergies. The results show that the optimization of the collective point of view ensures more efficient management of the energy supplied by renewables as well as by firms that can provide an energy surplus.
Paper VI163-17.20
PDF · Video · On the Flat Representation for a Particular Class of Port-Hamiltonian Systems
Zafeiratou, Igyso	National Technical University of Athens
Prodan, Ionela	INP Grenoble
Lefevre, Laurent	Univ. Grenoble Alpes
Keywords: Modeling and simulation of power systems, Smart grids, Control system design Abstract: This paper pertains to the flat representation of a class of port-Hamiltonian (PH) systems and advocates the use of bicausality of Bond graphs for finding appropriate flat outputs. Systems which are differentially flat have several useful properties which can be exploited to generate, for example, optimal trajectories/profiles which ensure constraints satisfaction. For the special case of PH systems combining the power preserving property with the flatness properties leads to effective control strategies for multi-physical systems. Hence, the purpose of this paper is to explore the implications and features of a particular class of PH systems (which can be retrieved from a Bond Graph representation) in finding their flat output representation. We concentrate on the example of an electrical storage system of a DC microgrid to illustrate the proposed theory.
Paper VI163-17.21
PDF · Video · Performance Bounds for Continuous Trading on Balancing Power Markets
Perninge, Magnus	Linnaeus University
Eriksson, Robert	Royal Institute of Technology
Keywords: Optimal operation and control of power systems, Real time simulation and dispatching, Power systems stability Abstract: In power systems the system frequency is a good indicator of the networks resilience to major disturbances. In many deregulated markets, eg the Nordic power market, the system operator controls the system frequency manually by calling off bids handed in to a market, called the balancing power market. In this paper we consider the problem of optimal bid call-off on the balancing market, that the system operator is faced with each operating period. We formulate the problem as a stochastic optimal control problem of impulse type. When searching for numerical solutions a complicating factor is the structure of the balancing power market, where the overall marginal price applies to all bids. To retain numerical tractability we propose computationally efficient upper and lower bounds for the value function in the dynamic programming algorithm.
Paper VI163-17.22
PDF · Video · A Topology Identification and Impedance Estimation Method for Distribution Network with Distributed Generations
Zhang, Zhenyu	Hunan University
Li, Yong	Hunan University
Zhang, Jun	Hunan University
Duan, Jing	Hunan University
Cao, Yijia	Hunan University
Keywords: Smart grids, Distribution automation Abstract: This paper proposes a topology identification and impedance estimation (TIIE) method for the distribution network with distributed generation (DG) units. When the DG unit is connected to the distribution grid, the power injections between the different buses in the distribution grid are no longer independent of each other. This paper demonstrates that the topology identification result has to be corrected when the existing voltage measured based methods are applied to the distribution network involving DG units. To solve the problem, we develop the TIIE method to correct the topology identification error by using the estimation of line impedance. The proposed method does not require any prior knowledge of the network. The case results show a high accuracy on the connectivity identification as well as the estimation of line parameter.

VI163-18
Optimal Operation and Control of Power Systems	Regular Session
Chair: Raisch, Joerg	Technische Universitaet Berlin
Co-Chair: Lee, Kwang Y.	Baylor University
Paper VI163-18.1
PDF · Video · Amplitude Design of Perturbation Signal in Frequency-Domain Analysis of Grid-Connected Systems
Alenius, Henrik	Tampere University of Technology
Luhtala, Roni	Tampere University of Technology
Roinila, Tomi	Tampere University of Technology
Keywords: Application of power electronics, Optimal operation and control of power systems, Power systems stability Abstract: The rise of renewable electricity production has driven the power grid to a remarkable transformation, where a large share of the electricity production is integrated to the grid through power-electronic inverters. The inverters have fast internal dynamics and no inherent inertia, which makes the power grid prone to stability issues. The stability analysis to ensure system robustness can be performed based on the impedance ratio of the inverter and power grid. The grid impedance is often an unknown parameter, and methods for grid impedance measurements are required. Past studies have presented a number of measurement methods based on a broadband perturbation, such as pseudo-random binary sequence (PRBS), and Fourier techniques for obtaining the grid impedance. However, only a little attention has been paid to the injection-amplitude design, and most often, the amplitude has been selected based on trial and error. This work presents an algorithm based on the total harmonic distortion (THD) levels of grid currents and voltages for choosing a suitable perturbation amplitude. The proposed method makes it possible to fully automate the stability analysis of a grid-connected system. Experimental results based on a three-phase grid-connected inverter are presented and used to demonstrate the effectiveness of the proposed method.
Paper VI163-18.2
PDF · Video · Control Strategy for the Combustion Optimization for Waste-To-Energy Incineration Plant
Falconi, Franco	CNAM - Schneider Electric
Guillard, Hervé	Conservatoire National Des Arts Et Métiers
Capitaneanu, Stefan	Schneider Electric
Raïssi, Tarek	Conservatoire National Des Arts Et Métiers
Keywords: Control system design, Modeling and simulation of power systems, Optimal operation and control of power systems Abstract: Waste disposal is becoming more and more challenging. Indeed, global population is still increasing and countries that do not have enough space to create big landfills need to find other solutions to deal with this problem. The incineration of municipal solid waste (MSW), if well controlled, is a possible solution. According to Cheng and Hu (2010) incineration can reduce the volume occupied by MSW down to 90% while producing thermal and/or electrical energy. Also the clinker of incineration can be used in road building and the construction industry. But air pollution control remains a major problem in the implementation of incineration for solid waste disposal. Despite the long history of work in this area, the proposed control schemes of these waste-to-energy plants are quite basic. This paper presents a way to optimize such a plant by using Advanced Control techniques. The aim of this operation is to control the steam flow rate, and, therefore the energy production, while ensuring a complete combustion, which is synonym of minimal pollution emission.
Paper VI163-18.3
PDF · Video · Application of the Nested Convex Programming to the Optimal Power Flow in MT-HVDC Grids
Garces, Alejandro	Universidad Tecnologica De Pereira
Azhmyakov, Vadim	Universidad EAFIT
Keywords: Optimal operation and control of power systems, Control of renewable energy resources, Modeling and simulation of power systems Abstract: This paper deals with an application of the nested convex programming to the optimal power flow (OPF) in multi-terminal high-voltage direct-current grids (MT-HVDC). The real-world optimization problem under consideration is non-convex. This fact implies some possible inconsistencies of the conventional numerical minimization algorithms (such as interior point method). Moreover, the constructive numerical treatment of this problem is usually based on some approximative approaches, namely, on the suitable linearizations and problem relaxations. The resulting convex programming model constitutes an approximated model and can naturally involve the significant (approximation) errors. In difference to the strongly approximate computational approaches mentioned above, the numerical scheme we propose takes into account the specific bi-linear structure of the problem and operates with the originally given non-convex formulation of the problem. We implement the proposed nested optimization approach and study the numerical consistency of the resulting optimal design. The Python based numerical experiments demonstrate the imlementability of the proposed methodology. Optimization problem of the modified version of the CIGRE MT-HVDC is next used as a benchmark test for the approach we developed.
Paper VI163-18.4
PDF · Video · A Fully Distributed Control Scheme for Power Balancing in Distribution Networks
La Bella, Alessio	Politecnico Di Milano
Bonassi, Fabio	Politecnico Di Milano
Klaus, Pascal	Ecole Polytechnique Federale De Lausanne
Scattolini, Riccardo	Politecnico Di Milano
Keywords: Optimal operation and control of power systems, Control system design, Distribution automation Abstract: The progressive diffusion of generation units based on intermittent renewable energy sources, as well as the increasing volatile power demand, calls for a new framework to compensate the power variability in a local fashion. In this context, the European Union instituted the fgure of the Balance Responsible Party, i.e. an entity entitled of internally compensating the power uctuations, exploiting a portfolio of local dispatchable units. Considering a distribution network carrying balance responsibility, this work devises a scalable, fully distributed, multilayer control strategy for internal power balancing. The proposed scheme features multiple local MPC regulators, performing an autonomous power balancing; a supervisory layer based on Distributed Consensus ADMM is introduced to coordinate local regulators when some of them exhausts its local resources. Numerical results eventually show the effectiveness of the approach.
Paper VI163-18.5
PDF · Video · Coordinated Control for Combined Heat and Power Load of an Integrated Energy System
Jin, Yuhui	Southeast University
Zhang, Junli	Southeast University
Wu, Xiao	Southeast University
Shen, Jiong	Southeast University
Lee, Kwang Y.	Baylor University
Keywords: Optimal operation and control of power systems, Control system design, Modeling and simulation of power systems Abstract: Most stand-alone integrated energy systems (IES) with renewable energy can only meet the demand of electrical load, not both electrical load and thermal load. Those studies on combined heat and power cogeneration systems mainly focus on the optimal scheduling of each source, ignoring the difference in dynamic response between electrical and thermal processes. In fact, the different response speeds of electrical and thermal objects will bring in challenges to control. In order to specify and solve the issue, this paper proposes a detailed mechanism model of a standard IES. A model predictive control (MPC) controller is designed and tuned based on the state-space form of the system. The control simulation results imply the feasibility of the MPC controller in coordinating both electricity and heat.
Paper VI163-18.6
PDF · Video · An Optimal Day-Ahead Bidding Strategy and Operation for Battery Energy Storage System by Reinforcement Learning
Dong, Yi	University of Manchester
Zhao, Tianqiao	Southern Methodist University
Ding, Zhengtao	The University of Manchester
Keywords: Optimal operation and control of power systems, Intelligent control of power systems, Smart grids Abstract: The Battery Energy Storage System (BESS) plays an important role in the smart grid and the ancillary market offers high revenues. It is reasonable for the owner of the BESS to maximise their profits by deciding how to bid with their rivals and balance between the different market offers. Therefore, this paper proposes an optimal bidding model of the BESS to maximise the total profit from the Automation Generation Control (AGC) market and the energy market, while taking the charging/discharging losses and the life of the BESS into consideration. Taking advantages of function approximation approaches, a reinforcement learning algorithm is introduced to the designed model, which can cope with the continuous and massive states of the proposed model and avoid the dimension curse. The resultant novel bidding model would help the BESS owners to decide their biddings and operational schedules profitably. Several case studies illustrate the effectiveness and validity of the proposed model.
Paper VI163-18.7
PDF · Video · An Optimization Methodology for Self-Consumption of Residential Photovoltaic Energy
Amabile, Loris	MINES ParisTech
Bresch-Pietri, Delphine	MINES ParisTech
El Hajje, Gilbert	EDF Lab
Labbé, Sébastien	EDF Lab
Petit, Nicolas	MINES ParisTech
Keywords: Optimal operation and control of power systems, Intelligent control of power systems, Smart grids Abstract: This paper considers the optimization of the self-consumed power locally produced by residential photovoltaic panels. We focus on a simplified set-up where only the Electric Water Heater (EWH) is regulated, while the rest of the appliances represents an uncontrollable load. We formulate an unconstrained optimization problem by inverting the EWH dynamics and prove that the corresponding objective function is continuously differentiable. Thanks to an explicit characterization of its critical points, we propose a tailored and computationally efficient optimization algorithm. Simulations performed in Dymola over a one-year horizon allow us to demonstrate the merits and performances of the proposed method.
Paper VI163-18.8
PDF · Video · Constrained Transactive Control in Power Systems Based on Population Dynamics
Baron-Prada, Eder	Universidad Nacional De Colombia
Mojica-Nava, Eduardo	Universidad Nacional De Colombia
Keywords: Optimal operation and control of power systems, Intelligent control of power systems, Smart grids Abstract: The power system has gone through an evolutionary process towards a smart grid, this process is a challenge for the system operator, these challenges are related to implementation in real time, as well as problems with the control and stability of the system. We propose a distributed transactive control algorithm based on population games to dynamically manage the distributed generators and smart loads in the system to reach the optimum social welfare. The proposed algorithm preserve stability and guarantee optimality conditions considering several constraints on the real-time operation. Loads are modeled flexible and base loads. Stability analysis and Nash equilibrium of the proposed game is studied by means of potential games concepts. Simulation results of the proposed algorithm shows the stability and convergence of the proposed algorithm.
Paper VI163-18.9
PDF · Video · Frequency Regulation with Heat Pumps Using Robust MPC with Affine Policies
Bünning, Felix	ETH Zürich, Automatic Control Laboratory
Warrington, Joseph	Baringa
Heer, Philipp	Empa, Urban Energy Systems
Smith, Roy S.	Swiss Federal Institute of Technology (ETH)
Lygeros, John	ETH Zurich
Keywords: Optimal operation and control of power systems, Intelligent control of power systems, Smart grids Abstract: The increase in the renewable energy sources connected to the electricity grid has resulted in an increased need for frequency regulation. On the demand side, frequency regulation services can be provided by electrified heating/cooling systems exploiting the energy stored in thermal mass of buildings. To provide such services a first principles model of the building is needed, which is often difficult to obtain in practice. This issue can be overcome by using a buffer storage between the heating/cooling source and the building. Here, we present a solution based on robust optimization to offer frequency regulation reserves with such a system comprising a heat pump, a thermal storage in the form of a warm water buffer tank, and heating demand from a building that needs to be served. We mitigate the problem of limited thermal storage by introducing affine policies on uncertain variables. In three experiments with a real heat pump and warm water buffer storage and an emulated heating demand, we demonstrate that the system can indeed offer reserves and can successfully track a regulation signal while meeting the heating demand at all times.
Paper VI163-18.10
PDF · Video · Dynamic Tracking of Power Demand for Integrated Fuel Cell Systems Using Nonlinear Model Predictive Control
Neisen, Verena	RWTH Aachen University
Mannhardt, Jacob	Institute of Automatic Control, RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Optimal operation and control of power systems, Model predictive and optimization-based control, Nonlinear process control Abstract: Transient changes in the power demand of state-of-the-art fuel cell systems are compensated by a battery in order to operate the fuel cell system safely within its physical boundaries. More concretely, oxygen starvation in the fuel cell is conventionally prevented by directly controlling the oxygen excess ratio. However, this limits the transient response of the fuel cell and the system's overall flexibility and efficiency. In order to overcome these limitations, we ascribe the task of the dynamic but safe response in a hybrid system to the fuel cell. For this purpose, we present a nonlinear model predictive control approach which is able to realize efficient transient power tracking, while considering the oxygen excess ratio explicitly as a boundary. We address the control challenges of a nonlinear, coupled, and bounded system with an adequate control design using a real-time capable nonlinear controller model. The controller is validated as proof of concept in simulation with a detailed dynamic plant model. Our contribution realizes a collaborative power setting by fuel cell and compressor. Moreover, system efficiency both in stationary and in transient operation is achieved, while preventing oxygen starvation as well as compressor surge and choke throughout the entire operation.
Paper VI163-18.11
PDF · Video · Process Operation Optimization Using System Identification
Yang, Chao	ZheJiang University
Zhu, Yucai	Zhejiang University
Keywords: Optimal operation and control of power systems, Modeling and simulation of power systems Abstract: Process optimization is an important topic in process industry, most process industry optimization works are based on mechanism models or performance test methods. However, it is very difficult to carry out optimization in actual operation because of the difficulty in obtaining the mechanism model, the difficulty in on-line measurement of objective function and the high test cost. In order to solve the problem, an online optimization method based on system identification is proposed. By replacing the unmeasurable variable with the measurable variable, the process model is identified on-line, and the gain of identified model is used as the optimization gradient to find the optimal variable value on-line. The method is verified using both simulation and real plant data.
Paper VI163-18.12
PDF · Video · Over-Voltage Disconnection of DER Inverters: Assessing Customer Savings
de Carvalho, Wilhiam Cesar	The Australian National University
Ratnam, Elizabeth Louise	The Australian National University
Blackhall, Lachlan	The Australian National University
von Meier, Alexandra	University of California, Berkeley
Murray, Alan	University of Newcastle
Keywords: Optimal operation and control of power systems, Modeling and simulation of power systems Abstract: Distributed energy resource (DER) owners experience a loss in economic benefits due to prolonged and/or frequent inverter disconnection. In this paper, we investigate the economic savings that customers accrue when combining rooftop solar photovoltaic (PV) generation with battery storage systems, considering a time-of-use pricing tariff and the steady-state over-voltage disconnection of inverters. In particular, we compare four quadratic program (QP) optimization-based approaches to designing the charge and discharge schedule of residential batteries. The objective of the first optimization-based approach is to increase the economic savings that PV customers with battery storage accrue. The next two approaches additionally modulate the power to and from the grid, reducing the occurrence of inverter-based disconnection for improved economic savings. By contrast, the fourth approach directly manages customer-based power flows to and from the electric grid to smooth distribution load curve peaks and valleys, without explicitly considering energy savings that accrue to customers. By means of a case study, we observe the over-voltage disconnection of residential-scale inverters decreases with the proliferation of behind-the-meter batteries until an integration level of 60% is reached. At battery integration levels beyond 60%, the fourth grid-focused optimization-based approach continues to improve the grid voltage preventing inverter-based disconnections.
Paper VI163-18.13
PDF · Video · Short-Term Optimization of the Operation of the CHP District Heating Plant with Heat Accumulator
Turunen, Joel	Ensense
Majanne, Yrjö	Tampere University
Vilkko, Matti Kalervo	Tampere University
Keywords: Optimal operation and control of power systems, Modeling and simulation of power systems, Control of renewable energy resources Abstract: In this work, the operating cost of the CHP production is reduced by creating optimization model to schedule the operation of the heat storage. The objective function of the model targets to minimize heat production costs and maximize profits of electricity production. To implement the optimization model in practice and automate the operation, the heat storage operation in every normal production situation of the CHP production with its real-life process constraints is modelled. To model the time-variant and non-linear system detailed enough, a MILP (Mixed Integer Linear Programming) model was selected and used to create a piecewise linear model of the system. A sliding time window method was used in the optimization to enable the most optimal heat storage operation in practice. The output of the optimization model is the operation plan of a heat storage for the next day, which provides the smallest operating cost for CHP production. The model can be also applied for heat storage investment planning.
Paper VI163-18.14
PDF · Video · BEV Fast Charging Strategy Optimization
Ji, Wei	Zhejiang Lab
Keywords: Optimal operation and control of power systems, Modeling and simulation of power systems, Control of renewable energy resources Abstract: This paper presents different approaches to optimize battery electric vehicles (BEVs) fast charging strategy. A rule-based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore the potential variance of congestion at fast charging stations, which could cause longer than four-hour waiting at the most congested station. Genetic algorithm was performed to explore the potential minimum waiting time at fast charging stations, and it can decrease the waiting time at the most congested station to be shorter than one hour. A deterministic approach results in feasible suggestions that people could consider to take fast charging as soon as the state of charge is approaching 40-miles range while remaining relative short waiting time at charging stations.
Paper VI163-18.15
PDF · Video · Economic Dispatch Cost Reduction in Box-Based Robust Unit Commitment
Cho, Youngchae	Tokyo Institute of Technology
Ishizaki, Takayuki	Tokyo Institute of Technology
Ramdani, Nacim	Université D'Orléans
Imura, Jun-ichi	Tokyo Institute of Technology
Keywords: Optimal operation and control of power systems, Power systems stability, Modeling and simulation of power systems Abstract: This paper proposes a box expanding method to reduce the economic dispatch (ED) cost in the box-based robust unit commitment model (BUC). As a non-anticipative robust unit commitment model for a power system under demand uncertainty, BUC co-optimizes the commitment schedule and the feasible set of the ED problem to minimize the total operating cost for the worst-case realization in a set of possible demand scenarios; the feasible set of the ED problem is modeled as a box to enable the non-anticipative real-time dispatch. Meanwhile, as BUC considers the worst-case total operating cost, the actual total operating cost may be unnecessarily high. In this paper, the box feasible set of the ED problem in BUC is expanded to a larger one via multi-objective optimization with a no-preference method. The expanded box forms a new feasible set of the ED problem, which increases the chance of reducing the actual ED cost and thus the actual total operating cost. Simulation results using 5-, 14-, and 30-bus test systems demonstrate the effectiveness and generality of the proposed method.
Paper VI163-18.16
PDF · Video · Transmission Loss Minimization Using Artificial Intelligent Algorithm for Nordic44 Network Model Based on Hourly Load Variation
Monshizadeh, Shohreh	University South Estern Norway
Uhlen, Kjetil	NTNU
Hegglid, Gunne J.	University College of Southeast Norway
Keywords: Optimal operation and control of power systems, Power systems stability, Modeling and simulation of power systems Abstract: Optimal power flow is a nonlinear optimization method to enhance the performance and flexibility of a power system, in order to find optimal set points of power output among available generators by optimal adjustment of control variables. This paper focuses on solving a single objective function of optimal power flow problem using particle swarm optimization (PSO) algorithm as an intelligent technique of optimization, applied under different operating scenarios on the Nordic44 power network model. The minimization of power losses as the single objective function of OPF problem is considered that it can be solved using PSO algorithm as intelligent method in cooperating of Newton Raphson as conventional method, while setting the constraints of control variables and dependent variables. To test the effectiveness of proposed method, different operation conditions of Nordic 44 model are tested, including maximum import and maximum export from Norway to the other Nordic networks, as well as hourly load data variations. The Nordic 44 model is the test system that has been used to analyze stability and control problems that are relevant for the Nordic power network. The simulation results show the usefulness of PSO algorithm as intelligent method for solving OPF problem under various load cases including heavy or light loading of Nordic 44 test system, compared to the other classical method like Newton Raphson method.
Paper VI163-18.17
PDF · Video · An Application of Model-Based Predictive Control for Renewables-Intensive Power Distribution Grids
Dkhili, Nouha	PROMES-CNRS (UPR 8521), University of Perpignan Via Domitia
Salas, David	Instituto De Ciencias De La Ingenieria, O'Higgins University
Eynard, Julien	University of Perpignan Via Domitia
Thil, Stéphane	Laboratoire PROMES (UPR 8521)
Grieu, Stéphane	University of Perpignan Via Domitia
Keywords: Smart grids, Control system design, Optimal operation and control of power systems Abstract: In recent years, growing penetration of renewable-energy-based distributed generation into power distribution grids has been compromising operational constraints. In this paper, a model-based predictive control (MPC) strategy is proposed for demand/supply balance and voltage regulation in a power distribution grid with prolific distributed generation using flexible assets (water tower and biogas plant). Then, the impact that errors of photovoltaic (PV) power generation and grid load forecasts have on its performance is examined. Results show that the proposed control scheme is efficient and resilient to forecasting errors.
Paper VI163-18.18
PDF · Video · Distributed Control Enforcing Group Sparsity in Smart Grids
Sauerteig, Philipp	Technische Universität Ilmenau
Jiang, Yuning	ShanghaiTech University
Houska, Boris	ShanghaiTech University
Worthmann, Karl	Technische Universität Ilmenau
Keywords: Smart grids, Control system design, Optimal operation and control of power systems Abstract: In modern smart grids, charging of local energy storage devices is coordinated within the distribution grid to compensate the volatile aggregated power demand on the time interval of interest. However, this results in a perpetual usage of all batteries which in return reduces their lifetime. In this paper, we enforce group sparsity by using an l_{p,q}-regularization on the control to counteract this phenomenon. This leads to a non-smooth convex optimization problem, for which a tailored Alternating Direction Method of Multipliers algorithm is proposed. Furthermore, the algorithm is embedded} in a Model Predictive Control framework. Numerical simulations show that the proposed scheme yields sparse control while achieving reasonable overall peak shaving.
Paper VI163-18.19
PDF · Video · Optimal Planning of Charging Stations and Electric Vehicles Traffic Assignment: A Bi-Level Approach
Ferro, Giulio	University of Genoa
Minciardi, Riccardo	Univ of Genova
Parodi, Luca	Università Degli Studi Di Genova
Robba, Michela	University of Genoa
Keywords: Smart grids, Model predictive and optimization-based control, Optimal operation and control of power systems Abstract: A new bi-level approach is proposed for the location and sizing of charging stations, considering both the transportation and energy demands. The lower level considers the User Equilibrium traffic assignment conditions for Electric Vehicles (EVs) which are derived and inserted as constraints in the overall optimization problem. The higher level presents the formalization of an optimization problem for the optimal planning of locations, sizes and unit prices of a set of new charging stations in a territory characterized by the presence of an already existing set of charging stations. A case study in the Genoa Municipality is considered for the application of the proposed model.
Paper VI163-18.20
PDF · Video · Day-Ahead Scheduling of Thermal Storage Systems Using Bayesian Neural Networks
Capone, Alexandre	Technical University of Munich
Helminger, Conrad	Technical University of Munich
Hirche, Sandra	Technical University of Munich
Keywords: Smart grids, Optimal operation and control of power systems, Artificial intelligence Abstract: The increased need for energy efficiency in buildings requires sophisticated scheduling strategies. A considerable challenge when developing such strategies is to address the stochasticity of demand appropriately. In this paper, we propose a day-ahead scheduling technique, which aims to minimize electricity costs, as well as power grid congestion. Our method considers energy storage systems with heat pumps and backup resistance heaters under uncertain heat demand. We employ a Bayesian neural network to model the stochastic consumer demand, which takes historical measurements as training inputs, and is able to model complex stochastic patterns. The model is then employed to generate sample demands, which are used to approximate the expected costs. The minimization of the resulting cost function corresponds to a stochastic optimal control problem with quadratic costs and mixed integer constraints. In a numerical simulation of a single-family building, the proposed approach is shown to perform better than a standard neural network-based scheduling scheme.
Paper VI163-18.21
PDF · Video · A Distributed Approach to the Optimal Power Flow Problem for Unbalanced and Mesh Distribution Networks
Ferro, Giulio	Università Degli Studi Di Genova
Robba, Michela	University of Genoa
Dachiardi, David	Massachusetts Institute of Technology
Haider, Rabab	Massachusetts Institute of Technology
Annaswamy, Anuradha	Massachusetts Inst. of Tech
Keywords: Smart grids, Optimal operation and control of power systems, Control of renewable energy resources Abstract: In the present paper we introduce a new distributed optimization approach to the solution of general Optimal Power Flow (OPF) problem. First of all, a new convex formulation, based on McCormick envelopes (MCE), is proposed for the OPF problem for unbalanced and mesh distribution networks. Then, we propose a new decomposition profile and a distributed approach based on proximal coordination, proving the algorithm's convergence with convergence rate o(1/tau) (with tau number of iterations). The approach is validated on a modified IEEE 13 bus network, with added distributed energy resources (DERs) including distributed generation (DG) and demand response (DR).
Paper VI163-18.22
PDF · Video · Maestro: A Python Library for Multi-Carrier Energy District Optimal Control Design
Gorecki, Tomasz Tadeusz	Centre Suisse D’electronique Et De Microtechnique (CSEM)
Martin, William	Centre Suisse D’electronique Et De Microtechnique (CSEM)
Keywords: Smart grids, Optimal operation and control of power systems, Control system design Abstract: This paper introduces the Maestro library. This library for Python focuses on the design of predictive controllers for small to medium-scale energy networks. It allows non-expert users to describe multi-carrier (electricity, heat, gas) energy networks with a range of energy production, conversion, and storage component classes; together with consumption patterns. Based on this description a predictive controller can be synthesized and tested in simulation. This controller manages the dispatch of energy in the network, making sure that the demands are met while minimizing the total energy cost. Alternative objectives can be specified. The library uses a mixed-integer linear modeling framework to describe the network and can be used in stand-alone based on standardized input files or as part of the larger energy network control platform PENTAGON.
Paper VI163-18.23
PDF · Video · H2-Norm Transmission Switching to Improve Synchronism of Low-Inertia Power Grids
Han, Tong	The University of Hong Kong
Hill, David J.	The University of Hong Kong
Keywords: Smart grids, Optimal operation and control of power systems, Power systems stability Abstract: This paper investigates the utilization of transmission switching to improve synchronization performance of low-inertia grids. The synchronization performance of power girds is first measured by the H2 norm of linearized power systems. Laplacian-based bounds and a close-form formulation of the H2-norm synchronization performance metric are derived to reveal the influence of network structure on synchronization performance. Furthermore, a transmission switching approach is developed by analyzing the sensitivity of the H2-norm metric to perturbation of network susceptance. Effectiveness of the proposed approach to improve synchronization performance is demonstrated using the SciGRID network for Germany.
Paper VI163-18.24
PDF · Video · Optimal Guaranteed Cost Event-Triggered Control of Smart Grid against Time Delay Switch Attack
Yang, Feisheng	Northwestern Polytechnical University
Kang, Peipei	Northwestern Polytechnical University
Guan, Xiaohong	Xi'an Jiaotong University
Keywords: Smart grids, Optimal operation and control of power systems, Power systems stability Abstract: This paper mainly studies the optimal robust guaranteed cost load frequency control (LFC) problem for a class of uncertain power system under time delay switch (TDS) attack. The closed-loop power system is modelled as time delay system when an event-triggered communication scheme is adopted to reduce bandwidth consumption. In order to obtain less conservative stability criteria of the system with additive time delays, a novel Lyapunov-Krasovskii (L-K) functional is proposed and some latest integral inequalities are applied as well. Then, an optimal guaranteed cost controller is designed to eliminate the system uncertainty and frequency fluctuation, and the minimum upper bound of the performance index can be obtained by solving a convex optimization problem.
Paper VI163-18.25
PDF · Video · Optimal Experiment Design for AC Power Systems Admittance Estimation
Du, Xu	ShanghaiTech University
Engelmann, Alexander	Karlsruhe Institute of Technology
Jiang, Yuning	ShanghaiTech University
Faulwasser, Timm	TU Dortmund
Houska, Boris	ShanghaiTech University
Keywords: Smart grids, Process observation and parameter estimation, Optimal operation and control of power systems Abstract: The integration of renewables into electrical grids calls for the development of tailored control schemes which in turn require reliable grid models. In many cases, the grid topology is known but the actual parameters are not exactly known. This paper proposes a new approach for online parameter estimation in power systems based on optimal experimental design using multiple measurement snapshots. In contrast to conventional methods, our method computes optimal excitations extracting the maximum information in each estimation step to accelerate convergence. The performance of the proposed method is illustrated on a case study.
Paper VI163-18.26
PDF · Video · A Further Study on the Cooperative Control of Energy Storage Systems under Unreliable Communication Network
He, Yuheng	South China University of Technology
Cai, He	South China University of Technology
Keywords: Control of renewable energy resources, Intelligent control of power systems, Power systems stability Abstract: In Cai and Hu (2018), a dual objective control problem for an energy storage system was solved by a distributed control scheme which can achieve both state-of-energy balancing and power tracking. However, it relies on the assumption that the communication network is reliable and fixed. In this work, we further consider the same problem for the case that the communication network is unreliable and switched. It is proven that, under certain connectivity condition on the communication network, the same control law as in Cai and Hu (2018) can still achieve the dual control objective.
Paper VI163-18.27
PDF · Video · MPPT Based Sliding Mode Control for Fuel Cell Connected Grid System
El Otmani, Fadwa	FSBM, University Hassan 2 of Casablanca
Abouloifa, Abdelmajid	EMI
Lachkar, Ibtissam	EMI
Aourir, Meriem	University HASSAN II of Casablanca
Assad, Fz	University of Hassan
Giri, Fouad	University of Caen Normandie
Guerrero, Josep M.	Aalborg University, Denmark
Keywords: Control of renewable energy resources, Control system design, Modeling and simulation of power systems Abstract: The fuel cell has become a promising alternative to fossil sources due to its clean and efficient energy. However, it is challenging to connect the fuel cell generator to the electrical grid due to the high nonlinearity of the fuel cell. This paper deals with the problem of controlling a Proton-exchange membrane fuel cell connected to the electrical grid. In fact, a high step-up DC stage composed of an interleaved boost and a three-level boost converter, is used to ensure the maximum point power tracking, and to enhance the fuel cell voltage. Then the DC power is delivered to a half-bridge inverter and injected into the grid via an LCL filter. This study aims to design a nonlinear controller based on the sliding mode approach in order to ensure the following objectives: i) Guarantee the maximum power of the PEM Fuel cell ii) Guarantee the proper current sharing among models of IBC. iii) Regulate the interior voltage in order to improve and stabilize the FC energy. iv) Regulate the DC link voltage. v) Ensure the three-level boost series voltage balance. vi) Ensure the power factor correction. The efficiency of the proposed controller is verified and validated through numerical simulation using Matlab Simulink environment.
Paper VI163-18.28
PDF · Video · Detection of Defaulting Participants with Time-Varying Failure Rates in Demand Response
Xu, Fangyuan	Nagoya University
Azuma, Shun-ichi	Nagoya University
Kobayashi, Koichi	Hokkaido University
Yamaguchi, Nobuyuki	Tokyo University of Science
Ariizumi, Ryo	Nagoya University
Asai, Toru	Nagoya University
Keywords: Smart grids, Constraint and security monitoring and control, Power systems stability Abstract: In contract-based demand response, there is a possibility that some participants may default on providing their scheduled negawatt energy. Therefore, one of the essential functions of the aggregator is to detect defaulting participants. This paper aims at solving the problem of detecting defaulting participants with time-varying failure rates in contract-based demand response, provided that the aggregator can inspect the total negawatt energy and the individual negawatt energy of a limited number of participants via smart meters.By assuming that there are only a few defaulting participants and they default in all periods, we propose a detection algorithm based on block-sparse reconstruction. The proposed algorithm is demonstrated through numerical simulation.
Paper VI163-18.29
PDF · Video · Scheduling and Control of Flexible Building Loads for Grid Services Based on a Virtual Battery Model
Wu, Di	Pacific Northwest National Laboratory
Wang, Peng	Pacific Northwest National Laboratory
Ma, Xu	Pacific Northwest National Laboratory
Kalsi, Karanjit	Pacific Northwest National Laboratory
Keywords: Smart grids, Control system design, Real time simulation and dispatching Abstract: This paper presents a framework for modeling, scheduling, and controlling residential thermostatically controlled loads (TCLs) to provide multiple grid services, such as energy shifting, peak load reduction, and ancillary services. A modeling method is proposed to characterize aggregate flexibility from heterogeneous TCLs using a virtual battery model. Based on the flexibility model, a multi-period optimal scheduling formulation is developed to best utilize the flexibility from building loads and maximize total benefits from stacked value streams. An algorithm is proposed to control individual TCLs to follow the desired power consumption in real-time. The proposed methods are illustrated and validated through simulations.
Paper VI163-18.30
PDF · Video · A Demand Response Framework to Overcome Network Overloading in Power Distribution Networks
Ejaz, Muhammad Jibran	National University of Sciences and Technology, Islamabad
Nasir, Hasan	The University of Melbourne
Qureshi, Faran Ahmed	EPFL
Ali, Usman	Georgia Institute of Technology
Jones, Colin N.	EPFL
Keywords: Smart grids, Optimal operation and control of power systems, Control system design Abstract: This paper considers the problem of network overloading in the power distribution networks of Pakistan, often resulting from the inability of the transmission system to transfer power from source to end-user during peak loads. This results in frequent power-outages and consumers at such times have to rely on alternative energy sources, e.g. Uninterrupted Power Supply (UPS) systems with batteries to meet their basic demand. In this paper, we propose a demand response framework to eliminate the problem of network overloading. The flexibility provided by the batteries at different houses connected to the same grid node is exploited by scheduling the flow of power from mains and batteries and altering the charging-discharging patterns of the batteries, thereby avoiding network overloading and any tripping of the grid node. This is achieved by casting the problem in an optimal control setting based on a prediction of power demand at a grid node and then solving it using a model predictive control strategy. We present a case study to demonstrate the application and efficacy of our proposed framework.
Paper VI163-18.31
PDF · Video · Improving Superheated Steam Temperature Control Using United Long Short-Term Memory and MPC
Wang, Qianchao	Southeast University
Pan, Lei	Southeast University
Lee, Kwang Y.	Baylor University
Keywords: Control system design, Intelligent control of power systems, Dynamic interaction of power plants Abstract: Superheated steam temperature is one of the most important process variables for controlling the steam quality of thermal power units. In order to improve the accuracy of superheated steam temperature and the stability of valves for desuperheating water, this paper proposed a novel control strategy called united long short-term memory (LSTM) and model predictive control (MPC), which is weighted by particle swarm optimization. First, a deeply learnt inverse model is made to express the potential nonlinear dynamic characteristics of data and to predict the future valve opening in short-term. Secondly, model prediction control is used to control the secondary superheated steam temperature. Thirdly, the two predicted valve opening are weighted by particle swarm optimization. The combined deep learning inverse model control and MPC can make up the deficiencies of each other, i.e., over fitting of deep learning inverse model and linearity of MPC. The simulation experiments proved the advantage of LSTM-MPC in comparison with traditional PID and single MPC control.
Paper VI163-18.32
PDF · Video · Reinforcement-Learning-Based Optimization for Day-Ahead Flexibility Extraction in Battery Pools
Chasparis, Georgios C.	Software Competence Center Hagenberg GmbH
Lettner, Christian	Software Competence Center Hagenberg GmbH
Keywords: Analysis and control in deregulated power systems, Control of renewable energy resources, Smart grids Abstract: We address the problem of trading energy flexibility, derived from pools of residential Photovoltaic and battery-storage systems, to the Day-ahead electricity market. By flexibility, we imply any additional energy that can be stored to or withdrawn from the participating batteries/households at a given time during the next day. The optimization variables include the selection/activation of a subset of participating batteries and the amount of flexibility that should be extracted. Furthermore, the optimization objective corresponds to the expected forecast revenues that can be generated by trading this flexibility to the Day-ahead electricity market. Given the high computationally complexity of a full scale optimization in the case of a large number of participating batteries, we propose a reinforcement-learning-based methodology, which admits linear complexity with the number of participating batteries. The proposed methodology advances prior work with respect to the integration of a large number of batteries. Furthermore, it extends prior work of the authors with respect to providing analytical performance guarantees in comparison with the baseline/nominal operation of the battery. Finally, we compare through simulations the performance of the proposed method with a Linear-Programming-based optimization that provides the exact optimum.

VI163-19
Power Electronics Control	Regular Session
Chair: Boiko, Igor	Khalifa University of Science and Technology
Co-Chair: Tibken, Bernd	Univ of Wuppertal
Paper VI163-19.1
PDF · Video · Direct Sliding Mode Control of a Three-Phase AC/DC Power Converter for the Velocity Regulation of a DC Motor
Alsmadi, Yazan	Jordan University of Science and Technology
Chairez, Isaac	UPIBI-IPN
Utkin, Vadim I.	Ohio State Univ
Keywords: Application of power electronics, Control system design, Intelligent control of power systems Abstract: A DC voltage source and a DC/DC power converter can be used to control the position, speed, or torque of a DC motor. In such operational conditions, a rectifier is needed to use a DC voltage source if only a three-phase voltage source is available. The objective of this study is to replace a rectifier and DC/DC power converter by one AC/DC power converter, such that its output would be equal to the voltage needed to control a DC motor. It is assumed that the control algorithm of a DC motor is selected, which means that the desired output voltage of the AC/DC converter as a time function or function of the motor state is known. First, a sliding mode methodology is applied to control the converter’s three shoulders to make the three-phase input current track the source voltages multiplied by a time-varying gain. The gain is then selected such that the converter output voltage is equal to the desired input of the DC motor. It is shown that this condition holds if the time-varying gain satisfies a first-order differential equation, which can be implemented as part of the controller. The application of Lyapunov theory confirms that the speed regulation process has a stable equilibrium point at the origin and that the time gain variation is bounded. The power efficiency is equal to one if the gain is positive. A numerical simulation demonstrates application of the developed control methodology for both constant and time-varying angular speed reference inputs.
Paper VI163-19.2
PDF · Video · Sliding Mode Observer Based Robust Fault Reconstruction for Modular Multilevel Converter with Actuator and Sensor Fault
Zhang, Yong	Wuhan University of Science and Technology
Cheng, Xiaobin	Wuhan University of Science and Technology, School of Information
Liu, ZhenXing	Wuhan University of Science and Technology
Zheng, Ying	Huazhong University of Science and Technology
Cheng, Cheng	Huazhong University of Science and Technology
Keywords: Application of power electronics, FDI with sliding modes Abstract: In this paper, a design method of sliding mode observer (SMO) is proposed to solve the problem of robust fault reconstruction for modular multilevel converter (MMC) with actuator and sensor fault. A state space model of MMC system is established to consider simultaneously actuator fault, sensor fault and uncertainty. Based on the obtained system model, a SMO is introduced to reconstruct the fault and an augmented system is obtained. Especially, the fault can be detected and the fault dynamics can be reconstructed by controlling the sliding mode motion with the equivalent output. Moreover, the SMO gain can be designed via the semi-definite program method. Finally, the effectiveness and feasibility of this method can be verified by using a MMC simulation example.
Paper VI163-19.3
PDF · Video · Estimation of Grid Frequency in Disturbed Converter-Based Power Systems by PLL State Variable Feedback
Goldschmidt, Nico	University of Applied Sciences (HTW) Berlin, Faculty 1: School O
Schulte, Horst	HTW Berlin
Keywords: Application of power electronics, Instrumentation and control systems, Control of renewable energy resources Abstract: Fast real-time estimation of the grid frequency is essential for stable operation of renewable converter-based sources in future power systems. Therefore this paper presents a new phase-locked loop for the estimation of time-dependent frequencies in unbalanced power systems with harmonics. The proposed frequency estimation method consists of two signal processing steps: In the first step, a least mean square estimator reconstructs the fundamental sinusoidal signal from the measured three-phase grid voltage and splits it into positive, negative and zero sequence components. In the second step, the resulting first harmonic three-phase positive sequence is converted into the synchronous reference frame in the form of a phase-locked loop using a state feedback controller scheme to reconstruct the current grid frequency. Here the controller output is equivalent to the signal to be reconstructed. The feedback controller design is based on linear matrix inequalities where the requirements are explicitly considered. The capability of proposed state feedback phase-locked loop is demonstrated by full scaled electro magnetic transient simulations.
Paper VI163-19.4
PDF · Video · Robust Hinf Control for PWM Boost Converters Subject to Aging Capacitor Conditions
Magalhães, Caio	Federal University of Bahia
Ordonez, Bernardo	UFBA - Universidade Federal Da Bahia
Araújo, Humberto Xavier	UFBA
Keywords: Application of power electronics, Modeling and simulation of power systems, Condition Monitoring Abstract: Electrolytic capacitors are extensively used in DC-DC power converters and consist of a major source of concern about system reliability. Although these components are heavily affected by aging, conventional modelling and control design for converters often disregard the uncertainty on capacitor parameters. In this paper, the robust control problem for boost converters is addressed with the derivation of a more comprehensive model. Although the modelling complexity is higher, the simplicity of linear state feedback control is preserved and the synthesis algorithm is performed by a LMI-based optimization problem. Moreover, the proposed control scheme requires state estimation, which is performed online as part of an identification system. Simulation results are presented and indicate the validity of the proposed concept.
Paper VI163-19.5
PDF · Video · Non-Linear Control of Grid-Side Inverters
Schöley, Alexander	University of Rostock
Gierschner, Magdalena	University of Rostock
Jeinsch, Torsten	University of Rostock
Keywords: Control of renewable energy resources, Control system design Abstract: In this contribution the control of a grid-side inverter of a wind energy system (WES) is addressed. Unlike the well-known VOC control strategy, the proposed controller is based on a system model that does not use Park's transformation, i.e. the model is not formulated in d/q-coordinates. Therefore, the system model contains non-linearities, but the validity of the model does not rely on an accurate phase angle detection for the transformation and not on the assumption of a balanced three-phase system. The non-linearities are investigated with the stability theory of Lyapunov and the remaining linear parts can be addressed with methods form linear control theory. The presented control strategy is developed in a simulation environment and numerical simulations were performed. Results are presented that show the effectiveness of the method.
Paper VI163-19.6
PDF · Video · Auto-Tuning of PID Controller with Gain Margin Specification for Digital Voltage-Mode Buck Converter
Shehada, Ahmed	Khalifa University
Yan, Yan	Khalifa University
Beig, Abdul R. Balanthi	Khalifa University
Boiko, Igor	Khalifa University of Science and Technology
Keywords: Control system design, Application of power electronics, Modeling and simulation of power systems Abstract: This paper investigates application of an auto-tuning of a digital PID controller for a DC-DC buck converter, based on the modified relay feedback test (MRFT). Measurements of the frequency and amplitude of the oscillations produced by the MRFT are used as input to PID controller tuning rules that are proposed in this paper. These rules are coordinated with the MRFT through a certain parameter in order to allow for the specification of gain margin; mathematical proof of that is provided in the paper. Another contribution of this work is the development of the implementation of the MRFT auto-tuning method on a digitally-controlled DC-DC buck converter. A PID controller is auto-tuned and tested on a buck converter prototype, and its performance is compared to that of an optimal but non-auto-tunable controller. Results show good performance of the proposed method. A final contribution is the discussion of important practical considerations regarding the application of the MRFT-based auto-tuning to switching converters.
Paper VI163-19.7
PDF · Video · Laguerre Neural Network Driven Adaptive Control of DC-DC Step down Converter
Khan Nizami, Tousif	SRM University AP Andhra Pradesh
Chakravarty, Arghya	Indian Institute of Technology Guwahati
Keywords: Control system design, Methods based on neural networks and/or fuzzy logic for FDI Abstract: DC-DC step-down/buck converters are prominent part of DC power supply system. The dynamics of DC-DC step down converter are nonlinear in nature and are largely influenced from both parametric and external load perturbations. Under its closed loop operation, obtaining a precise output voltage tracking besides satisfactorily inductor current response is a challenging control objective. In this regard, this article proposes a novel Laguerre neural network estimation technique for the approximation of unknown and uncertain load function, followed by its subsequent compensation in the adaptive backstepping controller. A detailed design of the proposed estimator and adaptive backstepping controller along with closed loop asymptotic stability have been presented. Further, the proposed control mechanism is evaluated through extensive numerical simulations while subjecting the converter to input voltage, reference voltage and load resistance perturbations. Furthermore, the results are verified by testing the proposed controller on a laboratory prototype with DSP based TM320F240 controller board. The transient performance metrics such as settling time and peak overshoot/undershoot are evaluated and compared against adaptive backstepping control and PID control methods. Finally, the analysis of results reveals that the proposed control methodology for DC-DC step down converter offers a faster transient output voltage tracking with smooth and satisfactory inductor current response over a wide operating range.
Paper VI163-19.8
PDF · Video · Robust Feedback Linearization Control for DAB Converter Feeding a CPL
Lucas Marcillo, Kevin Eduardo	Federal University of Santa Catarina
Pagano, Daniel Juan	Federal University of Santa Catarina
Plaza Guingla, Douglas Antonio	Escuela Superior Politécnica Del Litoral (ESPOL)
Vaca-Benavides, David Alejandro	ESPOL Polytechnic University
Ríos Orellana, Sara Judith	ESPOL Polytechnic University
Keywords: Control system design, Modeling and simulation of power systems, Application of power electronics Abstract: Cascaded converters are used to satisfy the different voltage levels that loads need. Instability problems in cascaded systems may occur due to the interaction of Point-of-Load (POL) converters. POL converters exhibit the important characteristic of almost-perfect regulation at the output terminals independent of the input perturbations. However, such characteristic reflects at the input terminal as a constant power load (CPL). CPL exhibits incremental negative resistance behavior causing undesired oscillations and a high risk of instability in interconnected converters. In this paper, the cascaded converter system comprised of a Dual Active Bridge (DAB) DC-DC converter that maintains a regulated DC voltage on the intermediate bus and a POL DC-DC Buck converter that acts as a CPL. Aiming to ensure system stability and effectively mitigate oscillations effects in a cascaded system, this paper proposes a Robust Feedback Linearization Control to regulate the intermediate DC bus voltage. Simulation tests are performed by using a MATLAB/Simulink simulator to show the robustness and effectiveness of the proposed controller. The simulation results show that the proposed control approach ensures robust control performance and stability with a minor performance degradation compared to a Robust Control approach, Feedback Linearization Control approach, and Classical Control approach.
Paper VI163-19.9
PDF · Video · Stochastic Control for DC-DC Power Converters: A Generalized Minimum Variance Control Approach
Lucas Marcillo, Kevin Eduardo	Federal University of Santa Catarina
Pagano, Daniel Juan	Federal University of Santa Catarina
Plaza Guingla, Douglas Antonio	Escuela Superior Politécnica Del Litoral (ESPOL)
Vaca-Benavides, David Alejandro	ESPOL Polytechnic University
Ríos Orellana, Sara Judith	ESPOL Polytechnic University
Keywords: Control system design, Modeling and simulation of power systems, Application of power electronics Abstract: This paper proposes a Generalized Minimum Variance (GMV) controller to regulate the output of the DC-DC power converters in order to decrease the impact of the noise in the system performance. The Dual Active Bridge and the Buck converters are used to illustrate the proposed methodology. The proposed controller is designed using the stochastic augmentation methodology that provides a PID controller, in the RST structure, the ability to adequately treat noise of a stochastic nature. The GMV control reduces the variance of the control signal and in turn leads to a better output characteristic. The simulation results show that the GMV controller achieve better performance in the sense of minimum variance and energy consumption in comparison with a robust PID controller.
Paper VI163-19.10
PDF · Video · Hybrid Controller with Fuzzy Logic Technique for Three Phase Half Bridge Interleaved Buck Shunt Active Power Filter
Echalih, Salwa	TI Lab, Faculty of Sciences Ben M’sick, Hassan II University, BP
Abouloifa, Abdelmajid	EMI
Janik, Jean-Marie	Université De Caen Normandie
Lachkar, Ibtissam	EMI
Hekss, Zineb	TI Lab, Faculty of Sciences Ben M’sick, Hassan II University, BP
Chaoui, Fatima-Zahra	ENSET, Université Mohammed V
Giri, Fouad	University of Caen Normandie
Keywords: Control system design, Modeling and simulation of power systems, Application of power electronics Abstract: This paper addresses a new control of three-phase half bridge interleaved buck shunt active power filter (HBIB-SAPF). We aim for a control strategy achieving simultaneously, the two following objectives: i) compensation of harmonic currents and reactive power absorbed by nonlinear loads for satisfying a power factor correction; ii) regulation of the HBIB converter DC capacitor voltage. To meet the above objectives, the proposed controller structure consists of two loops. The inner loop is designed using a hybrid dynamical approach to model the system, the hybrid automaton is proposed to deal with the compensation topic by switching between the different operative modes, which is conditioned by some invariance and transition conditions. The outer loop is built up based on fuzzy logic control (FLC), applied to regulate the DC bus voltage of three-phase HBIB-SAPF. It is confirmed, via simulation results in Matlab/ SimPowerSystems & Stateflow toolbox that the proposed controller actually achieves the objectives it is designed for.
Paper VI163-19.11
PDF · Video · Suboptimal Multirate MPC for Five-Level Inverters
Ordonez, Joaquin G.	University of Seville
Gordillo, Francisco	Universidad De Sevilla
Montero-Robina, Pablo	Universidad De Sevilla
Limon, Daniel	Universidad De Sevilla
Keywords: Control system design, Modeling and simulation of power systems, Application of power electronics Abstract: The application of multilevel converters to renewable energy systems is a growing topic due to their advantages in energy efficiency. Regarding its control, model predictive control (MPC) has become very appealing due to its natural consideration of discrete inputs, its optimization capability, and the present-day availability of powerful processing hardware. The main drawback of MPC compared to other control techniques in this field is that the control input is held constant during the sampling period, and it is usually difficult or even impossible to reduce this sampling period because of hardware limitations. For this reason, a multirate MPC algorithm is proposed, which allows to change the control input several times within the sampling period. The optimization problem is simplified and made suboptimal to substantially decrease computational burden. This approach is tested in simulation on a three-phase, five-level diode-clamped converter (DCC) operating in inverted mode with a three-phase resistive load. Results show significant reduction in harmonic distortion at the cost of an increase in the number of commutations with respect to a standard MPC operating at the same sampling period.
Paper VI163-19.12
PDF · Video · An Interval Arithmetic Approach for Multilevel Converter Harmonic Minimization Using Parseval's Theorem
Gennat, Marc	Hochschule Niederrhein University of Applied Science
Tibken, Bernd	Univ of Wuppertal
Keywords: Parametric optimization, Power systems, Application of nonlinear analysis and design Abstract: Multilevel converters are used for DC/AC power supply conversion, which is often applied in electric vehicle (EV) motor drives. AC conversion is done by a stepped output voltage, which provides a near-sinusoidal voltage with its fundamental frequency, but contains some higher harmonics. The elimination of several harmonics is fully implemented and well described in numerous publications, see Chiasson et al. (2003, 2004, 2005); Li et al. (2010); Tarisciotti et al. (2014), and Majed et al. (2014). In these papers the first set of undesired harmonics was eliminated, which in general was done by solving an equivalent system of equations using different methods such as resultants, Newton-Raphson (Chiasson et al. (2003)) and Optimal Minimization of Total Harmonic Distortion (OMTHD) technique, see Li et al. (2010). Higher harmonics stayed unrecognized to these optimization algorithms and delivered an undesired power spectrum to the total harmonic distortion (THD) of AC conversion. This paper presents a novel approach to the global THD-optimization of three-phase systems taking into account all harmonics up to infinity. This global optimization is implemented using interval arithmetic, see Hansen and Walster (2003), which neither need a convex objective function nor continuous-differentiable function. Interval arithmetic computes guaranteed intervals containing the global minima. The optimum is computed with an algebraic objective function, which is derived from Parseval's theorem on a 2 pi periodic function.
Paper VI163-19.13
PDF · Video · Real-Time Solution to Quadratically Constrained Quadratic Programs for Predictive Converter Control
Chen, Zhe	Ecole Polytechnique Federale De Lausanne
Verschueren, Robin	ABB Switzerland Ltd
Almer, Stefan	ABB Switzerland Ltd
Banjac, Goran	ETH Zurich
Keywords: Real time optimization and control, Application of power electronics, Modeling and simulation of power systems Abstract: This paper considers the real-time implementation of MPC tailored to voltage source converters with inductive-capacitive filter. Previous work has shown that the nonlinear and non-convex MPC problem can be equivalently formulated as a convex quadratically constrained quadratic program (QCQP). We develop two tailored algorithms based on the OSQP and HPIPM solvers to efficiently solve this QCQP. As the aforementioned solvers do not support quadratic constraints, we extend them so that they can solve QCQPs. We provide numerical comparison between the proposed methods and state-of-the-art solvers and show that our solvers are suitable for embedded applications.

VI163-20
Stability of Power Systems	Regular Session
Chair: Muenz, Ulrich	Siemens
Co-Chair: Weber, Harald	University of Rostock
Paper VI163-20.1
PDF · Video · Voltage Stabilization of Dc/dc Converter-Driven Constant Power Loads Via Feeding-Back the Output Measured Current
Papageorgiou, Panos	University of Patras
Alexandridis, Antonis	University of Patras, Power Systems, Greece
Keywords: Application of power electronics, Power systems stability, Control system design Abstract: A new approach and a novel solution to the voltage control problem of a dc/dc boost converter feeding an arbitrary constant power load (CPL) is developed. Particularly, as CPLs exhibit negative incremental resistance, a fact that in combination with the nonlinear nature of a converter/CPL system creates ad hoc stability problems, a nonlinear control design is proposed with main purposes: i) to be effective on regulating the output voltage regardless of the power absorbed, ii) to be easily implemented as a feedback loop from measurable states and outputs. In the feedback loop the measurable current at the power load side is fed back diminishing the need to apply any adaptation or other complicated mechanism for estimating the power absorbed by the CPL. Hence, the proposed controller analysis is based on the complete closed-loop nonlinear model instead of using standard linearized techniques and asymptotic stability is proven by applying suitable Lyapunov methods. This design approach extends the controller validity in a wide range while in practice it can be easily realized. The stable and good performance of the controller is finally evaluated by simulations taken with various CPL levels.
Paper VI163-20.2
PDF · Video · Video Based Combustion State Identification for Municipal Solid Waste Incineration
Zhou, Chenchen	Zhejiang University
Cao, Yi	Zhejiang University
Yang, Shuang-Hua	Loughborough University
Keywords: Control of renewable energy resources, Constraint and security monitoring and control, Power systems stability Abstract: As a means of secondary utilization of resources, waste incineration power generation has received more and more attention in recent years. However, due to various uncertainties, municipal solid waste(MSW) combustion is unstable. Owing to the large time-delay from the combustion state to conventional process measurements, it is difficult to reflect the combustion state of the incinerator. This paper uses a combustion video stream to identify the combustion state in real-time. The PCA-k-means clustering method is proposed to cluster different combustion states to distinguish abnormal flames from normal ones, which do not need any operators' attention. Based on the clustering, alarms on abnormal combustion states can be implemented to alert an operator to adjust incinerator operation conditions so that the desired combustion state can be achieved.
Paper VI163-20.3
PDF · Video · Self Tuning Wide Area Damping Control for Distributed Power Systems
Nayak, Abhishek	Indian Institute of Technology, Delhi
Mishra, Sukumar	Indian Institute of Technology Delhi
Keywords: Control system design, Intelligent control of power systems, Dynamic interaction of power plants Abstract: Damping of low-frequency inter-area oscillations in a power system has been the main concern for ascertaining the small-signal stability. Much of these efforts had been paid on designing damping controller with controller parameters obtained by offline analysis using a linearized model of the power system around a most probable operating point. A modern power system is however subjected to frequent changes in operating points due to load, renewable penetration and topology variations. An adaptive controller has the advantage of flexibility in getting the controller parameters auto-tunned online thus can be used for different operating conditions. This paper presents a WADC controller using a self tunning control (STC) strategy. The evaluation of the designed controller under various conditions has been carried out with renewable integrated IEEE 11 bus and IEEE 39 bus test systems. From the results, it is found that the proposed WADC can provide improved damping on inter-area oscillations under variable operating conditions.
Paper VI163-20.4
PDF · Video · Robust Adaptation in Dynamically Switching Load Frequency Control
Tao, Tian	Delft University of Technology
Roy, Spandan	Delft University of Technology (TU Delft)
Yuan, Shuai	Delft University of Technology
Baldi, Simone	Southeast University
Keywords: Control system design, Power systems stability, Design of fault tolerant/reliable systems Abstract: In recent years, heuristics for adaptive solutions to load frequency control (LFC) in power systems have been proposed that include adapting the LFC targets or adapting the participation factor for the resources. However, stability guarantees for these adaptation ideas are missing, especially in the presence of switching/evolving topologies of the power system. In today's smart grids, switching topologies often arise from reconfiguration and resilience against faults or from switching among different control areas in order to dampen oscillations and face cyber attacks. This work proposes a novel LFC framework in which adaptation and switching topologies are combined in a provably stable way.
Paper VI163-20.5
PDF · Video · Design of Scalable Controllers for Power Systems
Izumi, Shinsaku	Okayama Prefectural University
Nishijima, Kensuke	Okayama Prefectural University
Xin, Xin	Okayama Prefectural University
Keywords: Control system design, Power systems stability, Optimal operation and control of power systems Abstract: This paper studies scalable control of power systems, i.e., control with the constraint that controllers of all generators are the same. This control framework is useful to reduce the cost of constructing large-scale power systems because we can obtain controllers of all generators merely by designing one controller. The problem addressed here is to find the same controllers stabilizing an equilibrium point of the resulting feedback system and improving the performance in terms of the time response. As a solution to this problem, we present controllers to uniformly increase the damping forces of generators. We then show that an equilibrium point of the resulting feedback system is stable under certain conditions. In addition, we present a design method of the controller gain for improving the performance of the resulting feedback system in terms of the time response.
Paper VI163-20.6
PDF · Video · Frequency and Voltage Control Schemes for Three-Phase Grid-Forming Inverters
Ojo, Yemi	University of Cambridge
Benmiloud, Mohammed	University of Amar Telidji, LACoSERE Laboratory
Lestas, Ioannis	University of Cambridge,
Keywords: Control system design, Power systems stability, Smart grids Abstract: Grid-forming inverters play an important role in supporting power systems with low rotational inertia. Their frequency and voltage control policies must guarantee a synchronised operation, accurate power sharing amongst inverters, and a good transient response. Simultaneously achieving the latter two requirements is in general a non-trivial problem and existing schemes in the literature often focus on one of these two aspects. In this paper, we propose a simple frequency controller that uses the inverter output current as feedback to adapt its frequency, and also propose controllers for the regulation of the DC and AC voltages. We show that the proposed control architectures achieve both power sharing without a communication link, and desirable passivity properties that can enhance the dynamic performance. Closed loop stability of the grid-forming inverter with a dynamic load is also proven and simulations on advanced models are carried out to validate the results.
Paper VI163-20.7
PDF · Video · Active Power Regulation of a Storage Power Plant (SPP) with Voltage Angle Control As Ancillary Service
Gerdun, Paul	University of Rostock
Ahmed, Nayeemuddin	University of Rostock
Weber, Harald	University of Rostock
Keywords: Modeling and simulation of power systems, Power systems stability, Control of renewable energy resources Abstract: Electrical Energy Storage (EES) plays an increasingly important role to balance the intermittent power generation and demand, thus ensuring a more reliable network. An example of such an EES is the Storage Power Plant (SPP). It has been proved in previous studies that the SPP not only improves the power supply security but also reduces redispatch costs. However, its protection features against overcurrent and exceeding of its generation limit or storage capacity have not been discussed yet. In reality, such events can occur, leading to unexpected grid failures as a worst case scenario. Thus, the aim of this paper is to exhibit the behavior of a controller model which has been implemented in the SPP to protect the power plant during such situations. In this investigation, once the SPP's active power output is about to surpass its limit, the power plant automatically switches to a different mode of operation at the threshold value to prevent this from happening. In this manner, the SPP can protect itself autonomously and also helps to create a more robust system.
Paper VI163-20.8
PDF · Video · A Cascade Structure of Damped-SOGI to Identify Multimode Low-Frequency Oscillations
Mansouri, Mohammad	University of Calgary
Westwick, David	University of Calgary
Knight, Andrew M.	University of Alberta
Keywords: Modeling and simulation of power systems, Power systems stability, Dynamic interaction of power plants Abstract: The on-line estimation of low-frequency oscillations in an interconnected power system has attracted much attention as this provides vital information about the stability condition of the power system. In this paper, a measurement-based structure for estimation of the frequency, magnitude, and damping of multimode oscillations is proposed. The method can be applied to the Phasor Measurement Unit (PMU) to extract further information about the power system. The proposed method is derived by applying modifications to the parallel structure of an existing method called Damped Second Order Generalized Integrator (Damped-SOGI). The paper details the proposed cascade structure and presents simulation results to confirm the analytical derivations and the desired performance of the proposed method.
Paper VI163-20.9
PDF · Video · Contingency-Based Voltage Stability Monitoring Via Neural Network with Multi-Level Feature Fusion
Bai, Xiwei	Institute of Automation, Chinese Academy of Sciences
Tan, Jie	Institute of Automation, Chinese Academy of Sciences
Keywords: Power systems stability, Constraint and security monitoring and control, Artificial intelligence Abstract: To monitor the voltage stability state of complex power grid, a four-category stability classification problem that incorporates a set of serious contingencies is posed. Quick decision-making and high accuracy are critical for the safety operation of power system. However, this problem involves feature of different types, levels and dimensions and is hard to be handled by the traditional classifier. This paper utilizes the deep learning technique and proposes a multi-level deep neural network (ML-DNN) that achieves feature fusion of the electrical parameter measurements, topology and contingency information. Experiments are implemented on IEEE-39 system, the ML-DNN performs better in four main evaluation indices comparing with five existing models, which demonstrates its advantage for online voltage stability monitoring.
Paper VI163-20.10
PDF · Video · An Optimal Active Power Scheduling Strategy with Renewable Energy Based on Distributed Consensus Algorithms
Zhang, Hui	Hohai University
Shi, Linjun	Hohai University
Hua, Guanghui	UIUC
Lee, Kwang Y.	Baylor University
Keywords: Power systems stability, Control of renewable energy resources, Control of distributed systems Abstract: Aiming at the influence of the uncertainty of renewable energy generation on the power distribution of smart grid, a distributed optimal scheduling strategy for smart grid energy storage units based on consensus algorithm was proposed. This method does not rely on the central controller, but through the local communication between the energy storage units, according to their own information and acquired neighbor information to adjust the deviation between the actual and planed power in real time. In addition, in order to verify that the algorithm can optimize the network loss, MATPOWER is used to calculate the network loss before and after optimization. The system simulation results show that the proposed distributed scheduling strategy can ensure that all storage units converge to the same optimal value, and make the power grid run more economically.
Paper VI163-20.11
PDF · Video · Dual-Stage Control Structure for Multilevel Voltage Source Inverters
Nery, Eduardo Gabe	Universidade Federal Do Rio Grande Do Sul
Araujo Pimentel, Guilherme	Pontifícia Universidade Católica Do Rio Grande Do Sul
Rohr, Eduardo R.	University of Newcastle
Salton, Aurelio Tergolina	Universidade Federal Do Rio Grande Do Sul (UFRGS)
Keywords: Power systems stability, Control system design Abstract: This work proposes an alternative for total harmonic distortion (THD) attenuation in power inverters by combining two different circuit stages. The Macro stage comprises of a Neutral-Point-Clamped (NPC) multilevel inverter operating in high voltage and low switching frequency. The Micro stage is a two-level three-phase inverter, which is faster and more accurate due to its higher frequency and limited voltage. In this dual-stage approach, the opposite characteristics of the converters lead the Micro stage to correct the distortions of the Macro. It is possible to work with small values of filtering components, lower than the ones needed in a one-stage approach. This way, the presented proposal aims to reduce the physical size of the converter and its costs. The NPC inverter works in open loop with its switching signals generated by optimized pulse patterns (OPP). For correct THD filtering, a resonant control strategy with a Notch filter is designed in the frequency domain, as well as a feedforward structure designed in time domain. Simulation results show that the proposed system keeps voltage THD in acceptable levels for IEEE Standards.
Paper VI163-20.12
PDF · Video · Controller Tuning in Power Systems Using Singular Value Optimization
Mesanovic, Amer	Otto-von-Guericke-Universität Magdeburg
Muenz, Ulrich	Siemens
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Power systems stability, Control system design, Control of renewable energy resources Abstract: As the share of renewable generation in large power systems continues to increase, the operation of power systems becomes increasingly challenging. The constantly shifting mix of renewable and conventional generation leads to largely changing dynamics, increasing the risk of blackouts. We propose to retune the parameters of the already present controllers in the power systems to account for the seemingly changing operating conditions. To this end, we present an approach for fast and computationally efficient tuning of parameters of structured controllers. The goal of the tuning is to shift system poles to a specified region in the complex plane, e.g. for stabilization or oscillation damping. The approach exploits singular value optimization in the frequency domain, which enables scaling to large systems and is not limited to power systems. The efficiency of the approach is shown on three systems of increasing size with multiple initial parameterizations.
Paper VI163-20.13
PDF · Video · Switching Method Based Load Frequency Control for Power System with Energy-Limited DoS Attacks
Shang-Guan, Xingchen	China University of Geosciences
Jin, Li	China University of Geosciences
He, Yong	China University of Geosciences
Zhang, Chuan-Ke	China University of Geosciences
Jiang, Lin	The University of Liverpool
Spencer, Joseph William	University of Liverpool
Wu, Min	China University of Geosciences
Keywords: Power systems stability, Control system design, Design of fault tolerant/reliable systems Abstract: A load frequency control (LFC) scheme for modern power systems employs an open communication network to transmit control/measurement signals. The usage of the open communication network in power system makes the LFC scheme more vulnerable to communication network attacks, for example a denial-of-service (DoS) attack. This attack will prevent a certain amount of transmission of the signals so as to degrade the performance of LFC scheme, or even to lead to instability of power system. Therefore, this paper concerns LFC scheme for single-area power system with energy-limited DoS attack based on switching method. Compared with the latest schemes only considering duration of a DoS attacks, the proposed LFC takes fully into account both the duration and attack frequency of the DoS attack. A switching LFC model for a single-area power system is firstly constructed based on the characteristic of periodical sampling and DoS attacks. Then, an exponential stability criterion is developed in terms of the duration and frequency of a DoS attack. Next, a feasible controller of LFC scheme is derived by solving linear matrix inequalities in the criterion. Finally, a detailed design algorithm of LFC scheme is presented for a known DoS attack or an unknown DoS attack. The effectiveness of the proposed LFC scheme is evaluated on a single-area power system under DoS attacks. The proposed LFC scheme is compared with a robust LFC scheme and an event-triggered H_infty LFC scheme. The obtained contrasting results demonstrate that the proposed LFC scheme can defend DoS attacks with limited energy, and can perform better control effect in the presence of load fluctuations.
Paper VI163-20.14
PDF · Video · Analysis of a Bilinear Model of an Electric Power System Using Spectral Decompositions of Lyapunov Functions
Iskakov, Alexey	V.A.Trapeznikov Institute of Control Sciences, Moscow
Yadykin, Igor	V.A. Trapeznikov Institute of Control Sciences, Russian Academy
Keywords: Power systems stability, Dynamic interaction of power plants, Optimal operation and control of power systems Abstract: In this paper, the spectral decompositions of Lyapunov functions are applied for the first time to the analysis of the behavior of a bilinear model of a two-area electric power system. In contrast to the technique of normal forms and modal series methods, we consider the spectral decomposition not for the dynamics of state variables, but for Lyapunov functions, which characterize the L2-norms of variables or signals in the time domain. The solution of the generalized Lyapunov equation for a bilinear system is represented as the sum of Hermitian matrices corresponding to individual eigenvalues of the system or their pairwise combinations. An iterative algorithm for calculating spectral terms is developed for stable bilinear systems. In a test experiment for the purpose of transient stability analysis, we evaluate the value of individual eigenmodes and their pairwise combinations depending on the magnitude of bilinear terms. The obtained results are consistent with an intuitive interpretation derived from the model equations and eigenvalue analysis. The spectral decompositions of Lyapunov functions allowed us to indicate the range of applicability of linear model and to reveal dominant eigenmodes in the analysis of transient stability of electric power system.
Paper VI163-20.15
PDF · Video · Impact of Current Limitation of Grid-Forming Voltage Source Converters on Power System Stability
Schöll, Christian	University of Stuttgart, Institute of Combustion and Power Plant
Lens, Hendrik	University of Stuttgart
Keywords: Power systems stability, Modeling and simulation of power systems, Control of renewable energy resources Abstract: Grid-forming voltage source converters (VSC) have important characteristics of synchronous generators (SG). These include the provision of inertia and, in particular, voltage source behavior. These properties are required to make interconnected power systems with up to 100 % converter based generation possible. However, grid-forming VSC can not replace an important feature of SG: overcurrent capability. This property of SG contributes to power system stability. In the case of severe disturbances, SG may initially be overloaded before the load is gradually shared with other feed-ins. Due to the risk of damage, VSC have an overcurrent protection. However, most grid-forming VSC control concepts do not incorporate a sophisticated overcurrent limitation. This paper shows, by means of simulations, that current limiting of grid-forming VSC can lead to significant power system stability issues due to unsuccessful load sharing between other feed-ins. In addition, the paper shows, that with an increasing share of constant power loads, these issues can occur sooner.
Paper VI163-20.16
PDF · Video · Admittance Matrix Computation and Stability Analysis of Droop Controlled DC Micro-Grids with CPL
Braitor, Andrei-Constantin	The University of Sheffield
Konstantopoulos, George	University of Sheffield
Kadirkamanathan, Visakan	The University of Sheffield
Keywords: Power systems stability, Modeling and simulation of power systems, Control system design Abstract: In this paper, an analytical method of computing the admittance matrix is introduced that facilitates the stability analysis of DC micro-grid systems, in presence of constant power loads (CPLs). As one of the most common nonlinear loads, CPLs could yield instability in DC micro grids; an effect referred to as ’negative impedance instability’. The proposed method is particularly useful when a typical controller (droop control, voltage regulation) is designed to control the DC bus voltage of the micro-grid, as it allows the factorisation of the impedance matrix using singular matrices. In doing so, the closed-loop stability proof can be more easily approached, by isolating the singularities and, then, employing straightforward linear algebra tools to arrive at the stability conditions. In order to validate the proposed approach, compute the admittance matrix and test stability conditions, a DC microgrid with n DC/DC power converters connected to a CPL is considered. Simulation results are also displayed to demonstrate the proper operation of the DC micro-grid control and design framework.
Paper VI163-20.17
PDF · Video · Control Limitations Due to Zero Dynamics in a Single-Machine Infinite Bus Network
Björk, Joakim	KTH Royal Institute of Technology
Johansson, Karl H.	Royal Institute of Technology
Keywords: Power systems stability, Optimal operation and control of power systems, Control system design Abstract: In this work, fundamental control limitations for rotor angle stability are considered. Limitations are identified by characterizing open-loop transfer function zeros for input-output combinations of certain power system configurations. Of particular interest are non-minimum phase (NMP) zeros that limit the achievable performance of the closed-loop system. By studying a single-machine infinite bus power system model, analytic conditions for the presence of NMP zeros are derived. They are shown to be closely linked to the destabilizing effect of automatic voltage regulators (AVRs). Depending on the control loop, it is found that NMP zeros may persist in the system even if the closed-loop system is stabilized through feedback control. A simulation study shows that NMP zeros introduced by AVR limit the achievable performance and stabilization using feedback control.
Paper VI163-20.18
PDF · Video · Damping of Interarea Modes Using a GMVC-Based WAPSS
Trentini Preuss, Rodrigo	Federal Institute of Santa Catarina
Kutzner, Ruediger	Fachhochschule Hannover
Garcia Bartsch, Arthur	Federal Institute of Santa Catarina
Baasch Raizer, Anna Karolina	Federal Institute of Santa Catarina
Keywords: Power systems stability, Optimal operation and control of power systems, Modeling and simulation of power systems Abstract: This paper presents the implementation of a GMVC-based WAPSS to damp the interarea modes of power systems. The choise for the GMVC to tackle this problem lies on the fact that it can be used to compensate the time delay due to the latency of the transmission system in a more natural way than other controllers. The paper shows that it is possible to improve system's closed-loop stability since its behavior is the same as if the time delay is not regarded. Simulation results with Kundur's System prove that a latency of 1 second at a conventional WAPSS might lead system's power to oscillate for 50 seconds for a short-circuit at the transmission line, whereas the oscillation decreases to only 5 seconds if the GMVC-based WAPSS is implemented.
Paper VI163-20.19
PDF · Video · A Frequency-Shaped Controller for Damping Inter-Area Oscillations in Power Systems
Wilches-Bernal, Felipe	Sandia National Laboratories
Schoenwald, David	Sandia National Laboratories
Pierre, Brian	Sandia National Laboratories
Byrne, Raymond H.	Sandia National Labs
Keywords: Power systems stability, Smart grids, Optimal operation and control of power systems Abstract: This paper discusses how to design an inter-area oscillations damping controller using a frequency-shaped optimal output feedback control approach. This control approach was chosen because inter-area oscillations occur at a particular frequency range, from 0.2 to 1 Hz, which is the interval the control action must be prioritized. This paper shows that using only the filter for the system states can sufficiently damp the system modes. In addition, the paper shows that the filter for the input can be adjusted to provide primary frequency regulation to the system with no effect to the desired damping control action. Time domain simulations of a power system with a set of controllable power injection devices are presented to show the effectiveness of the designed controller.
Paper VI163-20.20
PDF · Video · A Modified PFC Rectifier Based EV Charger Employing CC/CV Mode of Charging
Tiwary, Anyuti	Thapar Institute of Engineering and Technology
Singh, Mukesh	Thapar Institute of Engineering and Technology
Keywords: Smart grids, Application of power electronics, Real time simulation and dispatching Abstract: Automobile industry has displayed an inclination towards Electric Vehicles (EVs). However, EVs charging throws inevitable challenges due to inclusion of non-linear charger circuitry. The conventionally utilized AC-DC rectification in charger poses ruinous effects to Grid and EV structure in the form of harmonics interference and obnoxious spikes in current. Thus, repercussions of elevated THD can be witnessed in poor efficiency and deterioration of EV charger. Furthermore, harmonics in input inductor current produce harmonics in rectifiers output voltage. This can lead to DC link voltage fluctuation and adversely affect DC/DC converter functioning. Henceforth, a Power Factor Correction (PFC) rectifier based charger has been proposed that eliminates unwanted harmonics from input current and reduces THD. Moreover, harmonics in rectifier's output voltage are reduced and constant DC link voltage is obtained. Sinusoidal input current is maintained through Critical Conduction Mode (CrCM) and hysteresis current control application. These are achieved using inner current and outer voltage control loop method. The former produces sinusoidal current wave in phase with input voltage to improve power factor. Whereas, latter helps in achieving constant DC link voltage. Hence, THD factor of 1.30% and power factor of 0.9998 are recorded. In addition, model inculcates CC/CV charging algorithm to control overcharging of battery. Here, battery charges at Constant Current (CC) initially. Once, maximum voltage is reached, charging occurs at Constant Voltage (CV). It is governed by two isolated PI controllers. The collaborated work of PFC and CC/CV helps in recording model's efficiency of 96.8%. Furthermore, a 2 kW charger prototype is analysed using real time simulation and validated through Hardware-in-loop (HIL) in OPAL-RT.
Paper VI163-20.21
PDF · Video · A Blockchain Based Electric Vehicle Smart Charging System with Flexibility
Okwuibe, Godwin	Oli Systems GmbH, Stuttgart
Li, Zeguang	Albert-Ludwigs-Universität Freiburg
Brenner, Thomas Johannes Konrad	OLI Systems GmbH
Langniss, Ole	OLI Systems GmbH
Keywords: Smart grids, Power systems stability, Control of renewable energy resources Abstract: The increase in development of electric vehicle(EV) will have a strong impact on the power distribution grid if adequate care is not taken on the high power demand required for charging EV. Also, there is need to create a business platform to attract investors and business owners into the business of EV charging station to accommodate the new EV's that will be developed in future. If this is not done, there is no doubt that in few years, EV owners will be faced with the problems of unavailability of charging stations and congestion in grid sequel to simultaneous charging of many EV's. This work proposes a smart EV charging infrastructure based on blockchain platform. With the charging demand (kWh) and time provided by the EV user, the EV load flexibility is determined and utilized through smart charging to achieve a stable grid. EV owners and charging stations are linked through the platform thereby reducing the actors in EV charging ecosystem from 6 to 4. Flexibility (power and time) in charging of EV is traded within the blockchain platform. By this, many investors will be attracted into the business of EV charging station and through flexible offers, EV loads are shifted from the peak load hours. Consequently, the simulations shows that the acceptance rate of the EV users increased by more than 50% when our smart charging system was adopted compared to the normal charging scenario.
Paper VI163-20.22
PDF · Video · Visual-Detection Based Fruit Fly Optimization Algorithm for Robust Analysis of Integrated Energy Systems
Hou, Weizhen	North China Electric Power University
Li, Jiayu	North China Electric Power University
Xu, Jing	North China Electric Power University
Lee, Kwang Y.	Baylor University
Huang, Yu	North China Electric Power University
Keywords: Smart grids, Control of renewable energy resources, Power systems stability Abstract: In this paper, a visual-detection (VD)-based fruit fly optimization algorithm (FOA) is proposed for solving a robust analysis problem of integrated energy systems (IES) with energy storage based on the information gap decision theory (IGDT). In the searching phase, the VD-based decision delay and visual feature detection mechanisms are incorporated within the FOA. By using the decision delay mechanism, different convergence problems of calculation results in several set delay iterations are analyzed, and the preservation strategy, visual feature detection strategy, and reset strategy are adopted to solve different convergence problems, where standard test functions are also adopted to test the proposed algorithm. The proposed VD-FOA is superior to the basic FOA and is applied to solve the IGDT-based robust analysis problem of IES with energy storage. The experimental results show the applicability and effectiveness of the proposed algorithm.
Paper VI163-20.23
PDF · Video · Generalized Persistent Fault Detection in Distribution Systems Using Network Flow Theory
Greber, Márton	University of Pannonia
Fodor, Attila	University of Pannonia
Magyar, Attila	University of Pannonia
Keywords: Smart grids, Modeling and simulation of power systems, Parameter estimation based methods for FDI Abstract: Persistent faults are steady state anomalies with a magnitude which does not necessary trigger general protective gear. It is present in various types of distribution networks, as leak in pipe networks or as high-impedance fault in electric systems. As smart meters come into general use, distribution systems are upgraded to have advanced metering infrastructure which can be used for diagnostic purposes. Different kind of detection methods are presented in different physical domains therefore comparison is cumbersome. The main achievement of the presented work is the formulation of an abstract system description, in order to tackle problems from various domains on a common ground. The notions of the well established general network theory are being used as a solid foundation. In this framework a general extension of flow networks is presented for distribution systems with measurement data available. Detecting faults at metered points is tackled in the literature, this problem is translated into the proposed representation. On the other hand a novel problem is described, the fault at unknown location between two metered points. The applicability of the abstract description to specialized distribution systems is presented through a simple case study.
Paper VI163-20.24
PDF · Video · Cyber Security of Electric Networks with Energy Storages
Kolosok, Irina	Melentiev Energy Systems Institute of Siberian Branch of the Rus
Korkina, Elena	Melentiev Energy Systems Institute of Siberian Branch of the Rus
Tomin, Nikita	Energy Systems Institute
Keywords: Smart grids Abstract: Modern Energy Power Systems (EPS) are characterized by a rather high share of distributed generation, renewable energy sources (RES) and energy storage systems (ESS) operating under the control of smart devices. For transition to a qualitatively new level of EPS control, the developed countries create Smart Grids. An effect of sudden changes of loads, power flows in the lines, and changes in the generation, as well as other unexpected factors can negatively affect on stability and reliability of state of EPS as well as lower EPS flexibility that is one of the most relevant features of future energy systems. Use of ESS is one of the recognized options of maintaining the energy system flexibility. At the same time executing energy storages at an energy object and, moreover, their coordination using Internet-technologies globally increase cyber vulnerability of electric network. At this paper different aspects of cyber security of electric networks with energy storage units incorporated into them are shown and ways of their cyber resilience are considered. By arranging PMUs in power system nodes using ESS, awareness of the absence of cyber attacks can be increased.

VI164
Power and Process System - Fault Detection, Supervision and Safety of Technical Process
VI164-01 Analysis of Reliability and Safety   Regular Session, 6 papers
VI164-02 Fault Detection and Applications   Regular Session, 19 papers
VI164-03 Fault Tolerant Control of Technical Processes   Regular Session, 5 papers

VI164-01
Analysis of Reliability and Safety	Regular Session
Chair: Dong, Zhe	Tsinghua University
Co-Chair: Jia, Qing-Shan	Tsinghua University
Paper VI164-01.1
PDF · Video · Hidden Markov Model Based Approach for Alarm Rationalization
Ariamuthu Venkidasalapathy, Joshiba	Texas A&M University
Kravaris, Costas	Texas A&M University
Keywords: Analysis of reliability and safety, Computational methods for FDI, Statistical methods/signal analysis for FDI Abstract: Alarm rationalization is a key element in ISA 18.2 alarm management lifecycle. During an abnormal event, alarms are generated in the control room to alert the operator of the affected regions in the process. An important objective of rationalization is to guide the operator troubleshoot quickly and help take necessary correction actions to restore normal operation. In this paper, the idea of representing the fault propagation path by the sequence of alarms generated by it, is explored. A model-based approach based on Hidden Markov Model (HMM) is proposed to predict the most likely cause of alarms using the alarm sequence generated. The probabilistic framework of HMM paves way to account for stochastic features of real plant operations that may arise due to random noises in sensors as well as the effect of fault magnitudes on sequences. The approach was applied to an industrial case study: Vinyl Acetate Monomer production process. The results show that the proposed approach was successful in predicting the probable cause of alarms generated with high accuracy. The model was able to predict the cause with reasonable accuracy even when tested with short alarm sub-sequences. This allows for early identification of faults, providing more time to the operator.
Paper VI164-01.2
PDF · Video · Reserve Balancing in a Microgrid System for Safety Analysis
Kiebler, Clemens	Technische Universität Chemnitz
Prodan, Ionela	INP Grenoble
Petzke, Felix	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Analysis of reliability and safety, Model predictive and optimization-based control Abstract: This work presents a robust MPC (Model Predictive Control) approach for reserve balancing in DC microgrid systems under uncertainties like wind power and energy price variations and different types of fault events. The robust MPC algorithm considers a variable-length prediction horizon which accounts for forecasts in energy price and renewable power over one day. Furthermore, a storage system is used to increase the utility of the demands and minimize the energy costs. The algorithm is tested for multiple fault types which affect the system (line and loss of power faults).
Paper VI164-01.3
PDF · Video · Online Reliability Assessment of Passive Nonlinear Systems Based on Extended State-Observer with Application to Nuclear Reactors
Dong, Zhe	Tsinghua University
Li, Bowen	Tsinghua University
Guo, Zhiwu	State Key Laboratory of Nuclear Power Safety Monitoring Technol
Guo, Chao	Tsinghua University
Huang, Xiaojin	Tsinghua University
Keywords: Analysis of reliability and safety, Monitoring and performance assessment, Monitoring of product quality and control performance Abstract: Online reliability assessment based on system model and operational data is crucial for all the safety critical systems. Since system reliability can be calculated directly from failure-rate, the central in online reliability assessment is the determination of failure-rate. In fact, the deviation of actual re-sponses from its expectation can be utilized for disturbance observation which can further determine the failure-rate. In this paper, an extended state observer (ESO) is proposed for general nonlinear dissipative systems, which provides globally bounded observations for not only state-vector but also total disturbance and its differentiation. By assuming that the failure-rate is given by the estimated differentiation of total disturbance, the reliability can be evaluated. This ESO-based online reliability assessment method is then applied to a nuclear heating reactor, and simulation results show the feasibility and effectiveness.
Paper VI164-01.4
PDF · Video · Toward HAZOP 4.0 Approach for Managing the Complexities of the Hazard and Operability of an Industrial Polymerization Reactor
Mokhtarname, Reyhane	Shiraz University
Safavi, Ali Akbar	Shiraz University
Urbas, Leon	Technische Universität Dresden
Salimi, Fabienne-Fariba	ADEPP Academy
Zerafat, Mohammad mahdi	Faculty of Advanced Technologies, Shiraz University, Shiraz, Ira
Harasi, Nasser	Advanced Control Laboratory, School of Electrical and Computer E
Keywords: Analysis of reliability and safety, Process modeling and identification, Industrial applications of process control Abstract: Conventional HAZOP is a collaborative and multidisciplinary activity to identify the hazards associated to operability of the chemical processes. Then the consequences and required safeguards of each potential deviation or failure are assessed qualitatively one by one. It is performed with the assumption of "one failure at the time" for the process parameters. Furthermore, "domino effects" are avoided to keep the HAZOP brainstorming sessions systematic and effective. Therefore, the quality and outcomes of HAZOP study is relatively subjective and depends on the experience and competency of the HAZOP team. This simplified approach cannot fully cover the hazard identification and risk assessment of the complex processes such as polymerization. Furthermore, the incident investigations show that almost all major accidents have occurred due to multiple failures or domino effects. This paper aims at developing a practical methodology in the context of "Industry 4.0" and particularly illustrate how dynamic simulation liberates the HAZOP team from the simplification assumptions such as one failure at the time or neglecting the domino effects during the lifecycle of the complex processes. An industrial styrene bulk free radical polymerization process has been chosen as the case study to depict the applicability of the proposed method. In continuation of this research, the dynamic simulation integrated with Artificial Intelligence (AI) algorithms and Multivariable Process Monitoring (MPM) together with virtual collaboration tools will be invoked towards a more practical and effective HAZOP 4.0 platform. Such a platform can be the foundation of the further Process Safety Management (PSM) elements such as "Operating manuals", "Training and Competency management", "Condition monitoring and predictive maintenance", "Management of Change", "Pre-Start-up Safety Review", etc.
Paper VI164-01.5
PDF · Video · An SW-ELM Based Remaining Useful Life Prognostic Approach for Aircraft Engines
Peng, Dingzhou	Harbin Institute of Technology
Yin, Shen	Harbin Institute of Technology
Li, Kuan	Harbin Institute of Technology
Luo, Hao	Harbin Institute of Technology
Keywords: Diagnosis, Aerospace Abstract: With the rapid development of prognostics and health management (PHM), the prognostic of the remaining useful life (RUL) is gradually being used for performance management and optimization. The aerospace industry is particularly in need of this, for instance, the remaining life expectancy of aircraft engines is of great significance to guarantee the safety and reliability. However, it is hard to establish the physical model of aircraft engines with the complex degradation process, which motivates the data-driven solution to RUL prediction. In this paper, a data-driven RUL prognostic approach is proposed for aircraft engines. Key performance indicators are extracted from sensor variables through principal component analysis. The summation wavelet-extreme learning machine is used to predict the KPIs' degradation process by iterative method, and then KPIs' degradation states are determined by subtractive-maximum entropy fuzzy clustering to calculate the RUL of engines. To validate the prediction model, aircraft engine degradation data are used for model simulation. Compared with other algorithms, the proposed method delivers superior prediction performance.
Paper VI164-01.6
PDF · Video · Predictive Maintenance of VRLA Batteries in UPS towards Reliable Data Centers (I)
Tang, Jing-Xian	Tsinghua University
Du, Jin-Hong	The University of Chicago
Lin, Yiting	Tencent Inc
Jia, Qing-Shan	Tsinghua University
Keywords: Data-Driven Decision Making, Energy and Distribution Management Systems Abstract: The reliability of data centers can be severely affected when battery failure occurs in the Uninterruptible Power Supply (UPS). Thus it has become a central issue for the industry to discover failure-impending batteries in UPS. In this paper, we consider this important problem and present a data-driven method for predictive battery maintenance. The major contributions are as follows.First, we develop a changepoint detection technique for effcient data labeling. Second, new features are designed to fully utilize the dataset. Third, we build a predictive classiffication model which can discriminate between healthy and failure-impending batteries. Our method has been built and evaluated on 209,912,615 records from Tencent data center involving nearly 300 batteries monitored over 2 years. The experiment on test set shows that our method is able to predict battery replacement with 98% accuracy and averagely 15 days in advance, which outperforms the previous maintenance policy by more than 8%.

VI164-02
Fault Detection and Applications	Regular Session
Chair: Polycarpou, Marios M.	University of Cyprus
Co-Chair: Mevel, Laurent	INRIA
Paper VI164-02.1
PDF · Video · Distributed Active Faults Diagnosis for Systems with Conditionally Dependent Faults
Straka, Ondrej	University of West Bohemia
Puncochar, Ivo	University of West Bohemia
Keywords: Active Fault Diagnosis, Distributed Fault Diagnosis, Filtering and change detection Abstract: The paper deals with active fault diagnosis of stochastic large scale systems for the cases when the fault in one subsystem may change the probability of occurrence of faults in other subsystems. The multiple model framework is considered and each subsystem is represented by a set of models describing fault-free and faulty behavior. The transitions between them are characterized probabilistically. The paper proposes two active fault diagnosis algorithms, a decentralized one and a distributed one. Their performance is compared in a numerical example.
Paper VI164-02.2
PDF · Video · Causal Network Construction Based on Convergent Cross Mapping (CCM) for Alarm System Root Cause Tracing of Nonlinear Industrial Process
Tian, Chang	Zhejiang University
Zhao, Chunhui	Zhejiang University
Fan, Haidong	Zhejiang Energy Group Research and Development
Zhang, ZhenWei	Zhejiang Energy Group Research Institute
Keywords: AI methods for FDI, Data mining and multivariate statistics, Applications of FDI and FTC Abstract: In terms of an alarm system, the propagation of a fault is identified as the main reason for low efficiency and the leading cause of dramatic industrial accidents. Thus, tracing the root causes of faulty conditions that lead to alarm floods is necessary. For root cause tracing, a widely accepted method is to characterize the process by causality at first and then trace the root causes. This work focuses on the former part. The conventional techniques to deal with causal analysis of industrial processes have difficulty in handling the nonlinearity of variables, obtaining accurate probability density and time lag, etc. In this work, a novel causal network construction method based on convergent cross mapping (CCM) that accurately describe process causality was proposed to deal with the above problems. First, the original monitoring variables were determined by a maximum Lyapunov method to determine whether they were chaotic time series, which aims to judge whether the application conditions of CCM can be satisfied. Then, some characteristic variables are selected from original variables through data preprocessing and descending dimension methods, which are defined as nodes that constitute the causal network. Second, the CCM-based methods are used to identify the causal direction and indirect causal relationship between variables, so as to construct the structure of the causal network. Since the CCM based on deterministic systems theory, it can handle nonlinearity and does not rely on the sample distribution. Finally, the weight of the edges in the graph is calculated to obtain the causal network which describes the process causality and serves as the basis for subsequent root causes tracing of alarms. The effectiveness of the proposed method is illustrated via a real industrial case study.
Paper VI164-02.3
PDF · Video · Fault Diagnosis Integrating Physical Insights into a Data-Driven Classifier
Atoui, Mohamed Amine	ISTIA - University of Angers
Cohen, Achraf	University of Angers
Keywords: AI methods for FDI, Statistical methods/signal analysis for FDI, Applications of FDI and FTC Abstract: The main goal of this paper is to present a new method for fault detection and isolation with a Bayesian network (BN). This method combines model-based and data-driven frameworks to detect and diagnose single, multiple and unknown faults. We propose an original BN structure with new decision rules. These rules are constructed to take advantage of the prior model knowledge and the available data. Our network presents new perspective to detect unknown fault and outperforms some recent work proposed in Bayesian networks literature. The performance of the method is illustrated on a heating water process simulating several scenarios of operating conditions.
Paper VI164-02.4
PDF · Video · Modular Distributed Fault Diagnosis for Adaptive Structures Using Local Models
Gienger, Andreas	University of Stuttgart
Schaut, Stefan	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Tarin, Cristina	University of Stuttgart
Keywords: Applications of FDI and FTC, Distributed Fault Diagnosis, Statistical methods/signal analysis for FDI Abstract: Adaptivity has become a promising concept in civil engineering to improve the load-bearing behavior of buildings and to reduce material consumption. However, the integrated actuators and sensors increase the complexity and adversely affect the reliability making a fault diagnosis for actuator and sensor faults necessary. In this paper, the distributed fault diagnosis of an adaptive high-rise truss structure, which is characterized by a modular design, is investigated. Based on local models and the local measurement information of hydraulic actuators and strain gages, a distributed fault diagnosis scheme is proposed for the diagnosis of actuator and sensor faults. Since the local models do not have information about the interconnection to other modules, the model-based residual is uncertain and faults in the other module can affect the local residual. For this reason, an effective online estimation of the probability density function and the Kullback-Leibler divergence of the residual is presented for change detection considering the stochastic uncertainties. Moreover, the selected sensor layout of the adaptive structure allows the isolation of the investigated actuator faults such that fault propagation paths of the distributed system are analyzed and sensor faults are isolated by communicating the detected changes in the modules. The effectiveness of the approach is illustrated in a simulation study.
Paper VI164-02.5
PDF · Video · Efficient Design of Fault Detection Architectures for Power Networks by Using Game Theory
Saracho, Daniel	University of Seville
Muros, Francisco Javier	University of Seville
Maestre, Jose M.	University of Seville
Keywords: Computational methods for FDI, Reconfigurable control, sensor and actuator faults, Fault accommodation and Reconfiguration strategies Abstract: In this paper, a ranking of the best locations to install remote control transformation centers (RCTCs) in distribution power lines is obtained by using the Shapley value of a cooperative game. The characteristic function of the game is based on both supply quality and economic indicators, which are relevant aspects regarding the operation and viability of electricity corporations. An academic example based on real data taken from a Spanish electricity company is considered to illustrate the feasibility of the proposed approach.
Paper VI164-02.6
PDF · Video · Condition Monitoring for Single-Rotor Wind Turbine Load Sensors in the Full-Load Region
Enevoldsen, Thomas	Technical University of Denmark
Galeazzi, Roberto	Technical University of Denmark
Papageorgiou, Dimitrios	Technical University of Denmark
Jeppesen, Christian	Aalborg University
Keywords: Condition Monitoring, Filtering and change detection, Statistical methods/signal analysis for FDI Abstract: Incipient faults on blade load sensors can impede the sound performance of a wind turbine,leading to increasing loads over time and severe blade degradation. As such, knowledge of the blade load sensors’ health is essential for ensuring effective load reduction by means of individual pitch control. This paper presents a condition monitoring strategy for the blade load sensors based on estimation of the loads acting on the rotor blades in the full-load region. Fault detection is achieved via appropriate residual generators, the statistical properties of which are used to design change detectors robust against measurement noise and wind field stochasticity. Specifically, a Generalized Likelihood Ratio Test for the t-LocationScale distribution is developed for ensuring robust detection of sensor blade faults. The proposed method is evaluated in a high-fidelity simulator under non-uniform wind scenarios. The simulation results show that detection of multiplicative faults on the blade load sensors is achieved even in absence of knowledge of the local wind speed.
Paper VI164-02.7
PDF · Video · Wear Detection for Progressing Cavity Pumps with System Identification Methods
Müller, Jens	Ruhr-Universität Bochum
Kouhi, Yashar	Ruhr Universität Bochum
Leonow, Sebastian	Ruhr University Bochum
Monnigmann, Martin	Ruhr-Universität Bochum
Keywords: Condition Monitoring, Signal and identification-based methods, Applications of FDI and FTC Abstract: We present a model-based approach for a non-invasive online wear detection for progressing cavity pumps. The approach is based on a model of the rotor displacement. All unknown model parameters can be determined from measured data with a recursive-least-squares algorithm, which can efficiently be run on an embedded device. The identified model parameters provide information about the internal wear. Without the model-based approach, wear can only be analyzed after disassembling the pump. We evaluate the proposed approach in a laboratory test setup with an undersize rotor, which simulates a worn pump. The results show the proposed approach can reliably monitor wear.
Paper VI164-02.8
PDF · Video · A Machine Learning Approach to Fault Detection in Transformers by Using Vibration Data
Tavakoli, A.H.	Politecnico Di Milano
De Maria, Letizia	RSE S.p.A
Valecillos, B.	Trafoexpert GmbH
Bartalesi, D.	RSE S.p.A
Garatti, Simone	Politecnico Di Milano
Bittanti, Sergio	Politecnico Di Milano
Keywords: Condition Monitoring, Signal and identification-based methods, Statistical methods/signal analysis for FDI Abstract: Transformer Vibration Technique is considered an effective method to monitor structural elements of transformers, in particular, to detect loose or deformed windings. As it is well known, vibrations vary with the sensor location on the transformer tank, which makes the number and the placement of sensors critical aspects for fault detection. In this paper, we investigate this issue by analyzing vibration spectra collected from various sensors installed on the tank of a typical oil filled power transformer operating under two limit cases, namely absence or presence of clamping looseness on windings. Support Vector Machines (SVM) are employed and an extensive analysis is performed to understand the informativeness of data corresponding to various sensors so as to figure out the appropriate number of sensors and their best location. This way fault detection is eventually achieved with a reduced and optimized number of sensors, resulting in a significant saving of time and costs.
Paper VI164-02.9
PDF · Video · Sensor Bias Fault Diagnosis for a Class of Nonlinear Uncertain Hybrid Systems
Heracleous, Constantinos	University of Cyprus
Keliris, Christodoulos	University of Cyprus
Panayiotou, Christos	Univ of Cyprus
Polycarpou, Marios M.	University of Cyprus
Keywords: FDI for hybrid systems Abstract: This paper presents a sensor bias fault diagnosis approach for a class of hybrid systems with nonlinear uncertain discrete-time dynamics, measurement noise, and autonomous and controlled mode transitions. The proposed approach uses an observer based on a modified hybrid automaton framework and a fault detection scheme that employs a filtering method tighter mode-dependent thresholds for the detection of sensor faults (even with small magnitude). An autonomous guard events identification (AGEI) module is also developed and linked with both the fault detection scheme and the hybrid observer to eliminate any false alarms due to autonomous mode transitions and allow effective mode estimation. Finally, an adaptive sensor fault estimation scheme is included, which is activated once a fault is detected to isolate and estimate the sensor bias fault magnitude.
Paper VI164-02.10
PDF · Video · Fault Detection for Linear Parameter Varying Systems under Changes in the Process Noise Covariance
Viefhues, Eva	BAM Federal Institute of Materials Research and Testing
Döhler, Michael	Inria
Hille, Falk	BAM Federal Institute for Materials Research and Testing
Mevel, Laurent	INRIA
Keywords: FDI for linear systems, Parameter estimation based methods for FDI, Structural analysis and residual evaluation methods Abstract: Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models - each estimated from data measured in a reference state - are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then conflicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
Paper VI164-02.11
PDF · Video · Exergy Graph-Based Fault Detection and Isolation of a Gas-To-Liquids Process
Greyling, Sarita	North-West University Potchefstroom
van Schoor, George	North-West University
Uren, Kenneth Richard	North-West University
Marais, Henri-Jean	North-West University
Keywords: FDI for nonlinear Systems, Computational methods for FDI, Applications of FDI and FTC Abstract: With the sheer size of modern process plants, the Fault Detection and Isolation (FDI) field continues to gain popularity. FDI is a sophisticated concept which aims to detect and isolate anomalies that occur within a plant to avoid losses of personnel, damages to the environment, and financial implications. It does so in a way which is more direct, efficient and safer than what human operators are capable of. One approach to FDI is to consider the exergy characterisation of a system. By describing the exergy of the system units and streams, in this case a gas-to-liquids (GTL) process plant, the various process variables are encapsulated under a universal energy-domain parameter. The advantage of this being that it can describe the physical states as well as the chemical characteristics of the process. Previous work which utilised exergy characterisation along with a fixed-threshold approach showed promise. This study however, shows that the approach falls short when presented with 3 % faults. These results motivated the investigation of utilising attributed graphs, which package exergy data into a framework that preserves structural information of the plant. The usefulness of finding similarities (called graph matching) between the graphs constructed of operational conditions and pre-collected fault conditions to detect and isolate faulty conditions, is demonstrated. The technique performs well when considering fault magnitudes bigger than 8 % but deteriorates when applied to smaller, 3 % faults. The poor performance could be ascribed to the graph matching aspect, which is described by a single distance value that discards dimensionality. Future work will therefore look into the graph matching technique specifically, aiming to retain more informative dimensions.
Paper VI164-02.12
PDF · Video · Enhanced Anomaly Detector for Nonlinear Cyber-Physical Systems against Stealthy Integrity Attacks
Zhang, Kangkang	Nanjing University of Aeronautics and Astronautics
Polycarpou, Marios M.	University of Cyprus
Parisini, Thomas	Imperial College & Univ. of Trieste
Keywords: FDI for nonlinear Systems, Filtering and change detection, Analysis of reliability and safety Abstract: The detection of stealthy integrity attacks for nonlinear cyber-physical systems is a great challenge for the research community. This paper proposes a backward-in-time detection methodology to enhance the anomaly detector against stealthy integrity attacks for a class of nonlinear cyber-physical systems. It uses the virtual value of the state at a time instant prior to the occurrence time of the attacks for detecting stealthy attacks. The definition of stealthy integrity attacks is formulated in the context of nonlinear plants such that they are undetectable with respect to traditional anomaly detectors. A H_infty fixed-point smoother is developed for estimating the analytical virtual values of the states at a prior time to the attack occurrence time, and then, the backward-in-time detection schemes are proposed based on the smoother. Based on the prior estimates, attack residual generation and threshold generation schemes are designed. Finally, a simulation is presented to illustrate the effectiveness of the enhanced anomaly detector.
Paper VI164-02.13
PDF · Video · Ellipsoid Bundle and Its Application to Set-Membership Estimation
Tang, Wentao	Harbin Institute of Technology
Zhang, Qinghua	INRIA
Wang, Zhenhua	Harbin Institute of Technology
Shen, Yi	Harbin Institute of Technology
Keywords: Filtering and estimation for FDI, Observer based and parity space based methods for FDI Abstract: This paper studies set-membership estimation for discrete linear time-varying systems subject to unknown disturbance and noise, which are bounded by ellipsoids. To improve the existing ellipsoid-based set-membership estimation methods, we propose a new set representation tool, called ellipsoid bundle, which combines the advantages of ellipsoids and zonotopes for uncertainty set representation and computation. Then, ellipsoidal bundles are used to design a new set-membership estimation method.
Paper VI164-02.14
PDF · Video · Robust Fault Detection of Nonlinear Uncertain Systems with Event-Triggered Communication
Zhao, Dong	University of Cyprus
Polycarpou, Marios M.	University of Cyprus
Keywords: Methods based on neural networks and/or fuzzy logic for FDI, FDI for nonlinear Systems, FDI and FTC for networked systems Abstract: The robust fault detection problem for a class of nonlinear uncertain systems with event-triggered measurement communication is addressed in this study. The proposed event-triggered robust fault detection scheme has two steps. First, with the event-triggered measurement, an adaptive approximator is proposed to learn the unknown modeling uncertainty online. Second, after the learning procedure, an event-triggered residual generator is designed by integrating the adaptive approximator with the residual signal for fault detection. The adaptive threshold for fault detection decision is derived by taking the event-triggered scheme into consideration. The performance of the event-triggered fault detection system is rigorously analyzed by characterizing the event-triggered sampling error, including the stability of the adaptive approximation and the fault detectability.
Paper VI164-02.15
PDF · Video · Fault Identification in HVDC Grids Using a Transient Parametric Model
Verrax, Paul	Supergrid Institute
Bertinato, Alberto	Supergrid Institute
Kieffer, Michel	CNRS - CentraleSupélec - Université Paris-Sud, Institut
Raison, Bertrand	INPG
Keywords: Parameter estimation based methods for FDI, Modeling and simulation of power systems, Signal and identification-based methods Abstract: This paper presents a novel single-ended fault identification algorithm for meshed High Voltage Direct Current grids. This algorithm can be used in the context of fully-selective fault-clearing strategies. Once a fault is suspected, using a parametric model describing the voltage and current evolution just after the fault occurrence, a maximum-likelihood estimate of the fault distance and impedance is evaluated. The presence of the fault is then confirmed depending on the size of the confidence region of the obtained estimate. The approach is evaluated on a simulated three-node meshed grid. The current and voltage need to be observed during less than 0.2 ms to get an accurate estimate of the fault characteristics and to identify consistently the faulty line.
Paper VI164-02.16
PDF · Video · A Novel Dynamic Baysian Canonical Correlation Analysis Method for Fault Detection
Yu, Jiaxin	Zhejiang University
Yang, Zeyu	Zhejiang University
Zhou, Le	Zhejiang University of Science & Technology
Ye, Lingjian	Ningbo Institute of Technology, Zhejiang University
Song, Zhihuan	Zhejiang University
Keywords: Process performance monitoring/statistical process control, Parameter estimation based methods for FDI Abstract: In the field of Multivariate Statistical Process Monitoring (MSPM), process dynamics has always been the focus. Besides, considering the uncertainty in chemical processes, latent variable models are extended to the probabilistic framework, in which maximum likelihood estimation with expectation maximization (EM) algorithm is adopted for parameter learning. However, the modelling performance is restricted owing to the reason that these models either neglect the static characteristics reflecting process structure or suffer from over fitting and local optimum. To tackle these issues, a dynamic Baysian canonical correlation analysis (DBCCA) model is developed through combining the consideration of process dynamics with the variational CCA and utilized for fault detection. More specifically, both static structural characteristics and process dynamics can be simultaneously captured in DBCCA model. In essence, the variational Bayesian approach renders effects of regularization, alleviating the dilemma in traditional maximum likelihood estimation methods by nature. The effectiveness of proposed method is testified on the well-known Tennessee Eastman (TE) benchmark, where improvements are attained.
Paper VI164-02.17
PDF · Video · Exergy-Based Fault Detection on the Tennessee Eastman Process
Vosloo, Johandri	North-West University
Uren, Kenneth Richard	North-West University
van Schoor, George	North-West University
Auret, Lidia	Stone Three Digital
Marais, Henri-Jean	North-West University
Keywords: Statistical methods/signal analysis for FDI, Applications of FDI and FTC Abstract: The exergy-based fault detection method has not yet been applied to a complex industrial system that adequately represents a dynamically changing process. One such system, the Tennessee Eastman process, is commonly used as a benchmark for fault detection methods. In this paper, an exergy-based fault detection approach is applied to the Tennessee Eastman process. This is done to investigate the feasibility of using this approach when confronted with noisy sensor data and control loops masking faulty behaviour. An exergy characterisation was performed on stream data obtained from the Tennessee Eastman process. The exergy characterisation included a new approach to calculate the standard chemical exergy of unknown components. For fault detection, threshold limits were determined for the exergy characterisation when normal operating conditions are assumed. The threshold limits were calculated following the upper and lower control limit determination of the Shewhart control chart. The results showed that this method could quantify both the physical state as well as the chemical features of the process and that 17 out of the 20 considered faults could be detected. This shows that the exergy-based method could be adequately applied to the Tennessee Eastman process.
Paper VI164-02.18
PDF · Video · FDI Study for a Wave Energy Converter by Structural Analysis
Gonzalez E., Alejandro G.	Universidad Nacional Autonoma De Máxico
Verde, Cristina	Inst. De Ingenieria, UNAM
Maya-Ortiz, Paul	Universidad Nacional Autonoma De Mexico
Keywords: Structural analysis and residual evaluation methods, Computational methods for FDI, Process control applications Abstract: This paper presents a fault diagnosis study for a wave energy converter by using structural analysis (SA) as the main tool. An Archimedes wave swing-based converter is considered as a case study with a detailed model taken from a real case. Thus, one looks for robust residuals for the irregular wave effects and sensitivity to fault detection. The faults considered for the device are as follows: central tank perforation, brakes damage, position and speed sensor faults, as well as an actuator fault. The transient response of the residuals to these faults is simulated by MATLAB/Simulink and demonstrates the potentiality of the analysis.
Paper VI164-02.19
PDF · Video · Clustering of Redundant Parameters for Fault Isolation with Gaussian Residuals
Mendler, Alexander	University of British Columbia
Döhler, Michael	Inria
Ventura, Carlos E.	Univ of British Columbia
Mevel, Laurent	INRIA
Keywords: Structural analysis and residual evaluation methods, Statistical methods/signal analysis for FDI, Computational methods for FDI Abstract: Fault detection and isolation in stochastic systems is typically model-based, meaning fault-indicating residuals are generated based on measurements and compared to equivalent mathematical system models. The residuals often exhibit Gaussian properties or can be transformed into a standard Gaussian framework by means of the asymptotic local approach. The effectiveness of the fault diagnosis depends on the model quality, but an increasing number of model parameters also leads to redundancies which, in turn, can distort the fault isolation. This occurs, for example, in structural engineering, where residuals are generated by comparing structural vibrations to the output of digital twins. This article proposes a framework to find the optimal parameter clusters for such problems. It explains how the optimal solution is a compromise, because with an increasing number of clusters, the fault isolation resolution increases, but the detectability in each cluster decreases, and the number of false alarms changes. To assess these factors during the clustering process, criteria for the minimum detectable change and the false-alarm susceptibility are introduced and evaluated in an optimization scheme.

VI164-03
Fault Tolerant Control of Technical Processes	Regular Session
Chair: El-Farra, Nael H.	University of California, Davis
Co-Chair: Yang, Qinmin	Zhejiang University
Paper VI164-03.1
PDF · Video · Fault-Tolerant Control of Degrading Systems with On-Policy Reinforcement Learning
Ahmed, Ibrahim	Vanderbilt University
Quiñones-Grueiro, Marcos	Universidad Tecnológica De La Habana José Antonio Echeverría (CU
Biswas, Gautam	Vanderbilt University
Keywords: AI methods for FDI, Fault diagnosis and fault tolerant control, Neural networks in process control Abstract: We propose a novel adaptive reinforcement learning control approach for fault tolerant control of degrading systems that is not preceded by a fault detection and diagnosis step. Therefore, a priori knowledge of faults that may occur in the system is not required. The adaptive scheme combines online and offline learning of the on-policy control method to improve exploration and sample efficiency, while guaranteeing stable learning. The offline learning phase is performed using a data-driven model of the system, which is frequently updated to track the system's operating conditions. We conduct experiments on an aircraft fuel transfer system to demonstrate the effectiveness of our approach.
Paper VI164-03.2
PDF · Video · Adaptive Fuzzy Output-Constrained Control of Uncertain MISO Nonlinear Systems with Actuator Faults
Ruan, Zhengwei	Zhejiang University
Yang, Qinmin	Zhejiang University
Keywords: Design of fault tolerant/reliable systems Abstract: This paper presents a novel adaptive fuzzy fault-tolerant controller for a class of uncertain multi-input single-output (MISO) nonlinear systems subject to actuator faults with user-defined time-varying asymmetric output constraints. The highlight of the proposed method is that it can tolerate the partial and total loss of effectiveness faults without the need for additional fault detection and isolation mechanism, as well as remain the system output within the predesigned time-varying output constraints during the system operation. To achieve the new results, an error transformation strategy is implemented to convert the original constrained system to an unconstrained one. For the transformed system, an effective switching function scheme is developed to search for the desired working mode by observing a switching performance index in which the impact of faulty actuators on the system can be weakened automatically. Furthermore, it is proved that the proposed adaptive fuzzy actuator fault compensation scheme can guarantee that the output is confined within the preselected bounds and all the closed-loop signals are bounded. Finally, numerical analysis confirms the merits of the proposed controller.
Paper VI164-03.3
PDF · Video · Design of an Integrated Actuator Fault-Tolerant Control under Robust Performance Requirements
Buciakowski, Mariusz	University of Zielona Gora
Witczak, Marcin	University of Zielona Gora
Pazera, Marcin	University of Zielona Gora
Keywords: Design of fault tolerant/reliable systems, FDI for linear systems, Filtering and estimation for FDI Abstract: The paper concerns a development of an integrated design of fault estimation and control scheme within an integrated actuator fault-tolerant control framework. The integrated design boils down to avoiding a standard three-step fault diagnosis (detection, isolation, identification) and replacing it by a fault estimation. Subsequently, the inaccuracies caused by fault estimation are taken into account while designing fault-tolerant controller. Contrarily to the usual framework, which extends the set of disturbances/noise by such inaccuracies, they are taken into account individually in such a way as to achieve a well balanced final control effect. Finally, a complete fault tolerant design procedure is provided along with its convergence analysis. The last part of the paper shows the performance of the proposed approach using a DC-servo motor benchmark example.
Paper VI164-03.4
PDF · Video · Stackelberg Differential Game-Based Optimal Fault Estimation and Accommodation for Continuous-Time Linear Systems
Xu, Yuhang	Nanjing University of Aeronautics and Astronautics
Yang, Hao	Nanjing University of Aeronautics and Astronautics
Jiang, Bin	Nanjing University of Aeronautics and Astronautics
Polycarpou, Marios M.	University of Cyprus
Keywords: Fault accommodation and Reconfiguration strategies, Distributed Fault-tolerant Control, Design of fault tolerant/reliable systems Abstract: This paper deals with the optimal fault estimation and accommodation problem for a class of linear systems in the framework of Stackelberg differential game theory. In this framework, the observer plays the role of the follower, while the system plays the role of the leader in making sequential decisions. A dual controller approach is used to design an auxiliary controller for the observer such that it can non-cooperate with the controller of the system to achieve the Stackelberg equilibrium. To achieve the online updating of the fault-tolerant controller, an adaptive dynamic programming methodology is used by establishing two critic neural networks for the observer and system respectively. Finally, a simulation is presented to illustrate the efficiency and applicability of the theoretical results.
Paper VI164-03.5
PDF · Video · Performance-Based Fault Mitigation in Sampled-Data Process Systems with Sensor Faults and Measurement Delays
Allen, James	University of California, Davis
El-Farra, Nael H.	University of California, Davis
Keywords: Fault accommodation and Reconfiguration strategies, Reconfigurable control, sensor and actuator faults, Design of fault tolerant/reliable systems Abstract: The objective of this work is to provide systematic tools for the analysis and mitigation of sensor faults in sampled-data processes with discretely-sampled and delayed state measurements. The emphasis is on determining the effects of varying process and controller parameters, including faults, sampling period, delay, plant-model mismatch and controller gain, on the stability and performance characteristics of the closed-loop system, and providing insight into how these effects can be counteracted through the use of active fault accommodation measures. The developed insights and methods are applied to a representative chemical process system with sampled and delayed state measurements. The stability of the closed-loop system is first characterized as a function of the sampling rate, the measurement delay, the fault magnitude, the fault accommodation measures, and the plant-model mismatch. The faults assessed have the form of diminished or hyperactive measurements of the system states. As a primary accommodation measure for these faults, the location of the closed-loop poles are adjusted to achieve stability during faulty operation. A performance metric that captures the closed-loop system's disturbance recovery behavior is chosen and parameterized in the same manner as the stability of the system, and is used to inform the fault accommodation decision-making process further. The explicit characterization of the stability and performance regions offer insight into the operational robustness and ranges of tolerable sensor faults that can be accommodated; and these are discussed with some simulation results for context.

VI171
Transportation and Vehicle Systems - Automotive Control
VI171-01 Electric Vehicle Propulsion and Control   Invited Session, 4 papers
VI171-02 Future Automotive Drives and the Role of Automatic Control   Invited Session, 5 papers
VI171-03 Eco-Driving: Energy Efficient Driving by Optimizing the Vehicle Speed   Open Invited Session, 7 papers
VI171-04 Adaptive and Robust Control of Automotive Systems   Regular Session, 7 papers
VI171-05 Automotive System Identification and Modelling   Regular Session, 12 papers
VI171-06 Engine Modelling and Control   Regular Session, 14 papers
VI171-07 Hybrid, Electric, and Solar Vehicles   Regular Session, 30 papers
VI171-08 Modeling, Supervision, and Control of Automotive Systems   Regular Session, 12 papers
VI171-09 Nonlinear and Optimal Control for Automotive Systems   Regular Session, 10 papers
VI171-10 Vehicle Dynamics and Control   Regular Session, 13 papers

VI171-01
Electric Vehicle Propulsion and Control	Invited Session
Chair: Ghanes, Malek	Centrale Nantes
Co-Chair: Di Gennaro, Stefano	Univ. Di L'Aquila
Organizer: Ghanes, Malek	Centrale Nantes
Paper VI171-01.1
PDF · Video · A New Approach on Stator Flux Estimation of IPMSMs Considering Magnetic and Cross-Coupling Saturations (I)
Taherzadeh, Mehdi	Ecole Central of Nantes, LS2N
Hamida, Assaad	Ecole Centrale De Nantes
Ghanes, Malek	Centrale Nantes
Koteich, Mohamad	Renault Group
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling, Electric and solar vehicles Abstract: This paper deals with estimating the stator flux of interior permanent magnet synchronous machines (IPMSMs) for hybrid electric vehicles (EHV) applications. The magnetic uncertainties due to the magnetic saturation are considered as new terms on the current-flux model of the machine. Considering the new model, an appropriate observer based on extended Kalman like algorithm is proposed to observe those terms. The observed terms are then used on the flux estimator to take into account the effect of magnetic saturation. The observability and the stability of the observer for the proposed system are studied. The simulation and experimental results are presented to illustrate the capacities of the proposed method.
Paper VI171-01.2
PDF · Video · Optimization of EV-Fast Charging Station Placement for Grid Support (I)
Gao, Xiang	Kiel University
Brueske, Sebastian	Kiel University
Andresen, Markus	Kiel University
Liserre, Marco	Kiel University
Keywords: Electric and solar vehicles Abstract: Electric vehicle charging stations are essential for the proceeding electrification of transportation. In particular, fast charging infrastructures cause high power demands and challenge the hosting capacity of already highly loaded distribution grids. For maximizing the grid’s hosting capacity, the charging infrastructure can provide grid voltage support or mitigation of current violation of devices such as transformers. Both grid support functionalities are dependent on the placement of charging stations in the grid. This work investigates the impact of charging stations’ location on the potential of these functionalities. The theoretical basis of the functionalities is introduced and an algorithm for optimized placement of fast charging stations (FCS) in the grid is introduced to maximize the hosting capacity for home charging facilities (HCFs).
Paper VI171-01.3
PDF · Video · Power Management in Serial Hybrid Electric Vehicle: A Singular Perturbation Approach (I)
Rouquet, Sebastien	Centrale Nantes
Ghanes, Malek	Centrale Nantes
Barbot, Jean Pierre	ENSEA
Merienne, Ludovic	Renault
Keywords: Hybrid and alternative drive vehicles, Engine modelling and control, Modeling, supervision, control and diagnosis of automotive systems Abstract: In this paper, a control based on singular perturbation approach is designed to solve the problem of power management for a serial hybrid electric vehicle. In this case, the power supply system consists of an Internal Combustion Engine (ICE) mechanically bound to a Permanent Magnet Synchronous Machine (PMSM) through a flywheel. Both sources are torque-controlled and connected to the traction motor by simple (without battery) DC link. The contribution of this paper is to apply the singular perturbation approach to design a control, which takes into account the different dynamic of the considered power topology. The proposed strategy is based on two-closed loops cascade control (fast and slow), which allows to impose the constraints of slower (faster respectively) ICE torque dynamics (PMSM current dynamics respectively) and to protect the power devices.
Paper VI171-01.4
PDF · Video · Integrated Active Control of Electric Vehicles (I)
Acosta Lua, Cuauhtemoc	Centro Universitario De La Ciénega, Universidad De Guadalajara
Castillo-Toledo, Bernardino	CINVESTAV-GDL, Mexico
Di Gennaro, Stefano	Univ. Di L'Aquila
Keywords: Vehicle dynamic systems, Control architectures in automotive control, Automotive system identification and modelling Abstract: This work describes how it is possible to integrate active chassis control actions in an electric vehicle. A vehicle with Active Front Steering (AFS) is considered, which imposes an incremental steer angle to the front wheels. Using Permanent Magnet Synchronous Motors (PMSMs) as powertrain, fitting on the left/right wheel axle shafts, it is possible to impose not only a desired longitudinal traction, but also an appropriate active yaw torque, so mimicking a classic Rear Torque Vectoring (RTV). The AFS, along with the RTV, allow imposing a desired behavior for the active chassis control of the vehicle, so improving its safety.

VI171-02
Future Automotive Drives and the Role of Automatic Control	Invited Session
Chair: Isermann, Rolf	University of Technology Darmstadt
Co-Chair: Eriksson, Lars	Linköping University
Organizer: Isermann, Rolf	University of Technology Darmstadt
Paper VI171-02.1
PDF · Video · An Artificial-Intelligence-Based Method to Automatically Create Interpretable Models from Data Targeting Embedded Control Applications (I)
Buchner, Jens S.	ETAS GmbH
Boblest, Sebastian	ETAS GmbH
Engel, Patrick	ETAS GmbH
Junginger, Andrej	ETAS GmbH
Ulmer, Holger	ETAS GmbH
Keywords: Nonlinear and optimal automotive control, Automotive system identification and modelling, Modeling, supervision, control and diagnosis of automotive systems Abstract: The development of new automotive drivetrain layouts requires modeling of the involved components to allow for ideal control strategies. The creation of these models is both costly and challenging, specifically because interpretability, accuracy, and computational effort need to be balanced. In this study, a method is put forward which supports experts in the modeling process and in making an educated choice to balance these constraints. The method is based on the artificial intelligence technique of genetic programming. By solving a symbolic regression problem, it automatically identifies equation-based models from data. To address possible system complexities, data-based expressions like curves and maps can additionally be employed for the model identification. The performance of the method is demonstrated based on two examples: 1. Identification of a pure equation based model, demonstrating the benefit of interpretability. 2. Creation of a hybrid-model, combining a base equation with data-based expressions. Possible applications of the method are model creation, system identification, structural optimization, and model reduction. The existing implementation in ETAS ASCMO-MOCA also offers a high efficiency increase by combining and automating the two procedural steps of embedded function engineering and calibration.
Paper VI171-02.2
PDF · Video · Smart and Hybrid Battery Balancing for Electric Vehicles (I)
de Castro, Ricardo	German Aerospace Center (DLR)
Araújo, Rui Esteves	University of Porto - Faculty of Engineering
Varela Barreras, Jorge	Imperial College London
Pinto, Cláudio	Continental Engineering Services, Lousado, Portugal
Keywords: Electric and solar vehicles Abstract: Battery packs of electric vehicles are prone to capacity, thermal, and aging imbalances in their cells, which limit power delivery to the vehicle. Spurred by this issue, we propose a new class of battery balancing systems, called hybrid battery balancing, capable of simultaneously equalizing battery capacity and temperature while enabling hybridization with additional storage systems, such as supercapacitors. Our research departs from the current research paradigm, which regards battery equalization and hybridization as two independent functions performed by two separated power converters. In contrast, our concept integrates these two functions into a single system, paving the way for a lower cost of power conversion in hybrid energy storage units. In exchange for reduced hardware costs, this integration of functions poses challenges to the design and control of the hybrid system, such as simultaneously coordinating a large number of power converters, enforcing actuation and safety constraints and making trade-offs between multiple technical and economic objectives. To handle these challenges, we developed constrained and hierarchical optimal control frameworks that rely on convex formulations as a means to obtain computationally efficient control algorithms. Through validation in small scale prototypes, we have demonstrated that this hybrid balancing concept can significantly decrease energy losses and battery stress while increasing a vehicle’s range as compared to conventional balancing methods.
Paper VI171-02.3
PDF · Video · Optimization Method for the Energy and Emissions Management of a Hybrid Electric Vehicle with an Exhaust Aftertreatment System (I)
Ritzmann, Johannes	ETH Zürich
Lins, Georg	ETH Zürich
Onder, Christopher Harald	Swiss Federal Institute of Technology Zurich (ETH Zürich)
Keywords: Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control, Modeling, supervision, control and diagnosis of automotive systems Abstract: This paper presents a real-time optimization method to compute the fuel-optimal torque split, gear selection and engine on/off command for a Diesel hybrid electric vehicle equipped with an exhaust aftertreatment system. We aim to minimize the amount of fuel consumed, while achieving a charge-sustaining operation and keeping the tailpipe NO x emissions below the legislative limit. We simplify the full vehicle model to facilitate the formulation of a mixed-integer convex problem which is then solved using the proposed iterative convex optimization (ICO) algorithm. We validate the result by comparing it to the globally optimal solution computed using dynamic programming (DP). For the simple model, the ICO algorithm finds the same solution as the DP benchmark. The computation time was reduced from one week for the DP benchmark to 49s for the ICO solution. By comparing the DP solution obtained on the full model with the ICO solution evaluated on the full model, we observe an offset in the solution due to model mismatch, but find that the ICO algorithm captures the qualitative trends of the optimal solution. The proposed algorithm is capable of solving the energy and emissions management problem in real-time, forming the basis for online optimal control.
Paper VI171-02.4
PDF · Video · Future Heavy Commercial Vehicle Drives: Opportunities with Hydrocarbon and Renewable Fuels and Control Challenges (I)
Eriksson, Lars	Linköping University
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Hybrid and alternative drive vehicles, General automobile/road-environment strategies Abstract: Control systems play a fundamental role in today’s vehicles and are necessary for achieving clean and efficient propulsion of vehicles. In particular, they are critical for achieving the emission legislations, without the onboard control systems the legislations on low emissions could not be achieved and we wouldn’t be allowed to drive cars and trucks on the road. Commercial vehicles are efficient and need a lot of energy for propulsion which means that there are great challenges in the future when we need to replace the Diesel fuel. The presentation will look at different options for the replacement and discuss how control will continue to play a key role for the development of future clean commercial vehicles. New fuels open up new possibilities for combustion control giving cleaner engine exhaust emissions. Furthermore, the impact of hybridization and electrification of long haul trucks have on fuel economy and emissions from trucks will be discussed, in this application there is a particularly important interplay between the vehicle and the control system that manages the energy conversion and the emission abatement.
Paper VI171-02.5
PDF · Video · Perspectives for the Future of Automotive Powertrains (I)
Isermann, Rolf	University of Technology Darmstadt
Keywords: Hybrid and alternative drive vehicles, Fuel cells for Automotive Applications, Electric and solar vehicles Abstract: Based on recent publications and conferences an overview is compiled for the kind of applied automotive drives in the foreseeable future, especially with regard to the use of renewable, regenerative energies. The contribution begins with a summary of liquid and gaseous fossil and synthetic fuels, including e-fuels and bio-fuels. Then the CO2-legislations for 2030 are considered and their consequences for combustion engines. Some properties of battery-electric drives, different hybrid drives and fuel-cell drives are discussed. This allows to compare their energy consumption, emissions, driving ranges, charging or tanking facilities. Then a forecast is derived for the used powertrains in 2030. The contribution serves as introduction to the invited session on "Future automotive drives and the role of automatic control".

VI171-03
Eco-Driving: Energy Efficient Driving by Optimizing the Vehicle Speed	Open Invited Session
Chair: Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Co-Chair: Sciarretta, Antonio	IFP
Organizer: Sciarretta, Antonio	IFP
Organizer: Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Paper VI171-03.1
PDF · Video · Optimal Freewheeling Control of a Heavy-Duty Vehicle Using Mixed Integer Quadratic Programming (I)
Held, Manne	KTH Royal Institute of Technology
Flärdh, Oscar	Scania CV AB
Roos, Fredrik	Scania CV AB
Mårtensson, Jonas	KTH Royal Institute of Technology
Keywords: Nonlinear and optimal automotive control, Autonomous Vehicles, Intelligent driver aids Abstract: Improving the powertrain control of heavy-duty vehicles can be an efficient way to reduce the fuel consumption and thereby reduce both the operating cost and the environmental impact. One way of doing so is by using information about the upcoming driving conditions, known as look-ahead information, in order to coast in gear or to use freewheeling. Controllers using such techniques today mainly exist for vehicles in highway driving. This paper therefore targets how such control can be applied to vehicles with more variations in their velocity. The driving mission of such a vehicle is here formulated as an optimal control problem. The control variables are the tractive force, the braking force, and a Boolean variable representing closed or open powertrain. The problem is solved by a model predictive controller, which at each iteration solves a mixed integer quadratic program. The fuel consumption is compared for four different control policies: a benchmark following the reference of the driving cycle, look-ahead control without freewheeling, freewheeling with the engine idling, and freewheeling with the engine turned off. Simulations on a driving cycle with a varying velocity profile show the potential of saving 11%, 19%, and 23% respectively for the control policies compared with the benchmark, in all cases without increasing the trip time.
Paper VI171-03.2
PDF · Video · Eco-Driving for Energy Efficient Cornering of Electric Vehicles in Urban Scenarios (I)
Padilla, G. P. (Paul)	Eindhoven University of Technology
Pelosi, Carmine	Eindhoven University of Technology
Beckers, Camiel	Eindhoven University of Technology
Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control, Intelligent driver aids Abstract: In this paper, we propose a model for eco-driving that considers cornering effects. The proposed model purely relies on the geometric configuration of the vehicle and road. Consequently, we propose an eco-driving optimal control problem formulation that is suitable for both straight and curved trajectories in urban scenarios. Moreover, it can be applied for vehicles with front wheel drive (FWD) or rear wheel drive (RWD). We use a case study for an electric vehicle executing cornering maneuvers to validate the proposed approach with a high fidelity vehicle model. Results show an approximated improvement of 8% in energy savings with respect to traditional eco-driving strategies, especially in trajectories with large curvatures.
Paper VI171-03.3
PDF · Video · Information and Collaboration Levels in Vehicular Strings: A Comparative Study (I)
Dollar, Robert Austin	Clemson University
Sciarretta, Antonio	IFP
Vahidi, Ardalan	Clemson Univ
Keywords: Multi-vehicle systems, Trajectory and Path Planning, Nonlinear and optimal automotive control Abstract: The potential safety, productivity, and energy benefits of automated vehicles have driven a surge of research interest in their algorithms. Even within single-lane driving, control engineers now have a profusion of approaches available to them. Algorithm classes include classical controllers, receding horizon controllers, and constrained eco-driving formulae based on Pontryagin's Minimum Principle. Differing connectivity architectures and collaboration levels further differentiate algorithms from one another. This study evaluated six controllers in two drive cycle-based scenarios using an electric powertrain model for energy analysis. Individual-vehicle and string performance were examined, including string stability and length. Algorithms with greater access to information generally performed best. Although collaboration affected energy use only slightly, it made a greater impact on string length.
Paper VI171-03.4
PDF · Video · Real-Time Driving Mode Advice for Eco-Driving Using MPC (I)
Chen, Yutao	Eindhoven University of Technology
Lazar, Mircea	Eindhoven Univ. of Technology
Keywords: Intelligent driver aids, Control architectures in automotive control, Nonlinear and optimal automotive control Abstract: This paper proposes an on-line advice eco-driving assistance system (EDAS) for providing the optimal velocity profile to improve fuel economy. The EDAS employs a driver-in-the-loop (DIL) framework, where an adviser is designed to provide high-level driving mode suggestions while the low-level control commands such as throttle and brake, are left to the driver to implement. A simplified dynamic model is developed in the adviser excluding continuous-time control variables such as the engine torque and engine brake torque. The adviser employs an event-triggered model predictive control (MPC) algorithm to provide suggestions in real-time using predictive road and traffic information. On-line computational cost for the MPC has been significantly reduced using an efficient mixed-integer optimal control (MIOC) algorithm. To demonstrate the efficiency and effectiveness of the proposed EDAS, a numerical study and a simulation using measured data from a real-life driving test is conducted. Comparisons are made between the proposed EDAS and an eco-driving controller considering both high and low level control inputs without a driver.
Paper VI171-03.5
PDF · Video · A Look-Ahead Car Following Scheme for Efficient Driving on Urban Roads (I)
Kamal, Md Abdus Samad	Gunma University
Hashikura, Kotaro	Gunma University
Hayakawa, Tomohisa	Tokyo Institute of Technology
Ogitsu, Takeki	Gunma University
Yamada, Kou	Gunma Univ
Imura, Jun-ichi	Tokyo Institute of Technology
Keywords: Motion control, Nonlinear and optimal automotive control, General automobile/road-environment strategies Abstract: For safe and efficient driving of a vehicle on urban roads, it is essential to analyze the trends of the vehicles ahead to take early measures in changing traffic situations. Existing efficient driving systems based on optimal car following compute the vehicle control input by solving an optimization problem over a prediction horizon, and at the expense of large computation cost, they provide significant improvement in traffic flows and fuel consumption. This paper proposes a look-ahead car following scheme, which can take anticipatory driving decisions with negligible computation cost, for efficient driving of a vehicle. Specifically, at first, the distinctive features of an optimal car following scheme over traditional car following of a human driver are investigated. Then, based on the features observed, a look-ahead car following scheme is formulated that can partly reflect the desired driving characteristics of the optimal car following scheme. The proposed scheme extends a traditional car following model by incorporating the predicted state of the preceding vehicle in a restricted look-ahead horizon. Finally, the proposed look-ahead car following scheme is evaluated in typical urban traffic scenarios, and the observed driving characteristics and performances are compared.
Paper VI171-03.6
PDF · Video · Receding Horizon Reference Governor for Implementable and Optimal Powertrain-Aware Eco-Driving (I)
Shen, Daliang	Argonne National Laboratory
Han, Jihun	Argonne National Laboratory
Jeong, Jongryeol	Argonne National Laboratory
Karbowski, Dominik	Argonne National Laboratory
Rousseau, Aymeric	Argonne National Laboratory
Keywords: Nonlinear and optimal automotive control, Autonomous Vehicles, Trajectory and Path Planning Abstract: This paper presents an adaptive, two-level control structure that makes it possible to implement a numerical optimization algorithm for eco-driving in real time. The reference governor in the higher level is characterized by a low, flexible sampling rate and adopts a receding horizon for preview and optimization. The optimization algorithm thereby finds the energy-minimizing solution, based on Pontryagin's minimum principle (PMP), for traveling the selected route segments without colliding with the preceding vehicle. The tracking control in the lower level compensates for errors due to modeling inaccuracies and unmodeled disturbances. The hierarchical structure can accommodate different types of numerical solvers and control schemes that apply to various vehicle powertrain configurations. A large-scale simulation study using real-world route data with high-fidelity powertrain models validates the proposed control structure and its online implementation.
Paper VI171-03.7
PDF · Video · Dual Stage Multilevel Control for Heavy Duty Vehicles under Different Traffic Conditions (I)
Polverino, Pierpaolo	University of Salerno
Arsie, Ivan	University of Naples
Pianese, Cesare	University of Salerno
Keywords: Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control Abstract: The present paper details a performance analysis made through model-based simulation of a dual stage multi-level control algorithm applied to heavy duty vehicles that accounts for traffic information. Such work exploits a control algorithm at different level of traffic congestion. In the two stages control, the first level entails a supervisory optimizer, which evaluates the optimal speed and gear shifting profile according to road and vehicle information to minimize fuel consumption; the second level is an actuator control that computes the powertrain signals to be applied to the engine actuators to comply with the indications given by the supervisory control. The advancement brought by the present work resides in the introduction of speed constraints related to different traffic levels: i) free flow, ii) free flow/conditioned, iii) conditioned and iv) congested. To each state, a maximum limiting speed is associated and several scenarios are investigated in simulated environment. All the results are compared to a conventional Cruise Controller to assess the achievements in terms of fuel consumption reduction, assessing that the proposed control strategy ensures an average reduction about 3.5% over all the investigated conditions.

VI171-04
Adaptive and Robust Control of Automotive Systems	Regular Session
Chair: del Re, Luigi	Johannes Kepler University
Co-Chair: Shafai, Bahram	Northeastern Univ
Paper VI171-04.1
PDF · Video · Combined Cooperative Adaptive Cruise Control Using Collective Initial Excitation Based Distributed Parameter Estimator
Garg, Tushar	Indraprastha Institute of Information Technology Delhi
Roy, Sayan Basu	Indraprastha Institute of Information Technology Delhi
Keywords: Adaptive and robust control of automotive systems, Cooperative control, Decentralized Control and Systems Abstract: In cooperative adaptive cruise control (CACC), autonomous vehicles are grouped into a string of platoon and, the main objective is to automatically adapt their speed using on-board sensors and communication with the preceding vehicle to maintain a desired inter-vehicle distance. Cruise control is achieved in the presence of parametric uncertainty in the vehicle dynamics using principles of adaptive control. This work proposes a novel combined CACC strategy for an uncertain homogeneous platoon with guaranteed parameter convergence and asymptotic string stability. A novel distributed consensus-based parameter estimator is proposed in conjunction with a model reference adaptive control (MRAC) algorithm using a direct control-gain update law. The algorithm ensures exponential parameter estimation error convergence to zero as well as asymptotic convergence of tracking-error to zero. Conventional CACC protocols require a condition of the persistence of excitation (PE) for parameter convergence, which is required for better transient performance in converging to a string stable configuration. The PE condition is highly restrictive in the context of cruise control since velocity profiles which are demanded in the platoon model do not typically satisfy the PE condition. In contrast, the proposed scheme can ensure parameter convergence under a significantly milder condition, coined as collective initial excitation (C-IE). The C-IE condition is an extension of the concept of initial excitation (IE), which is recently proposed in the context of adaptive control of the single-agent system. Unlike IE, the C-IE condition caters to distributed estimation in the context of multi-agent systems. As far as the authors are aware, this is the first work on the CACC framework, which ensures exponential convergence of parameter estimation error of each vehicle under the mild condition of C-IE, which further leads to asymptotic convergence of the entire vehicle platoon to a string stable configuration. Simulation study dictates that the proposed CACC architecture outperforms the existing CACC algorithms in terms of tracking and estimation performance.
Paper VI171-04.2
PDF · Video · Adaptive Model Predictive Control of Combustion in Flex Fuel Heavy Duty Compression-Ignition Engine
Li, Xiufei	Lund University
Tunestal, Per	Lund University, Faculty of Engineering
Johansson, Rolf	Lund University
Keywords: Adaptive and robust control of automotive systems, Engine modelling and control Abstract: Flex-fuel engines can operate on different fuels, from fossil fuel to renewable fuel and their mixture. With the assumption that fuel species is unknown in advance, the mutative fuel properties give rise to an interesting control problem. Since the combustion phasing and ignition delay in the combustion process are intimately coupled, the fuel injection system and air system need to be combined for performance. In this work, an adaptive Model Predictive Control (MPC) approach is proposed to control the combustion process in a multi-cylinder heavy duty compression-ignition (CI) engine. MPC is a suitable design for this multiple inputs/outputs system with actuator constraints, and adaptivity is the solvent for the unknown mutative fuel properties. The combustion timing and ignition delay are extracted from cooled in-cylinder pressure sensors and simultaneously controlled by manipulating injection timings, the intake oxygen concentration, and intake pressure using an exhaust-gas recirculation (EGR) system and a variable-geometry turbocharger (VGT). Diesel, gasoline/n-heptane mixture, and ethanol/n-heptane mixture are used in the experiments. The method is validated in fuel transitions from diesel to gasoline mixture and from gasoline mixture to ethanol mixture.
Paper VI171-04.3
PDF · Video · Self-Tuning NMPC of an Engine Air Path
Mendoza Zapata, Emmanuel David	Universidad De Piura
Schrangl, Patrick	Johannes Kepler University Linz
Ipanaqué, William	Piura University
del Re, Luigi	Johannes Kepler University
Keywords: Adaptive and robust control of automotive systems, Nonlinear and optimal automotive control, Engine modelling and control Abstract: Many automotive systems such as engines have manufacturing tolerances or change over time. This limits the performance of controllers tuned for the nominal case. A robust controller can not always overcome this performance gap. Against this background, in this work, we propose a self-tuning control strategy for an engine air path model obtained from data of a real engine and show its benefits setting. The self-tuning control consists of an online parameter estimation algorithm for polynomial non-linear autoregressive with exogenous input (PNARX) models and a nonlinear model predictive controller (NMPC) implemented by the continuation/generalized minimum residual (C/GMRES) algorithm. In a first step design of experiments (DOE) is utilized to identify a PNARX model offline from measurements performed on an engine test bed. A tracking NMPC is designed for this model and applied in simulation on the identified model. The control performance is assessed for the case of a wrong initial guess. It is shown that the resulting performance gap can be overcome by the online parameter estimation of a k-step prediction model with directional forgetting. An improved closed loop control performance of the air path model confirms the approach.
Paper VI171-04.4
PDF · Video · Adaptive Control of a Vehicular Platoon with Unknown Parameters and Input Variations
Aghababa, Mohammad Pourmahmood	Urmia University of Technology
Saif, Mehrdad	University of Windsor
Shafai, Bahram	Northeastern Univ
Keywords: Adaptive and robust control of automotive systems, Nonlinear and optimal automotive control, Intelligent transportation systems Abstract: An efficient switching adaptive control algorithm for automating connected vehicles in a rigid platoon pattern is proposed here. A second-order nonlinear model for the follower vehicles running on the highways is adopted and it is assumed that the parameters of the vehicles's model, including the mass, aerodynamic drag and tire drag, are fully unknown and their values cannot be used in arriving at the control laws. Furthermore, some uncertainties and external perturbations are added to the model to consider the eects of always present modeling errors, un-modeled dynamics and external time varying perturbations on the vehicles. Besides, control input variations are inserted into the nonlinear model of the platoon to represent actuator uctuations. Subsequently, a robust adaptive control scheme is established so that the asymptotic stability of each vehicle in the platoon is guaranteed, and this is demonstrated using the Lyapunov stability criterion. A novel spacing error variable is also introduced to achieve the global string stability for the whole platoon. Following a comprehensive mathematical analysis, a computer simulation example is presented to illustrated the effectiveness as well as the performance of the proposed control system.
Paper VI171-04.5
PDF · Video · Uncertainties Investigation and Mu-Synthesis Control Design for a Full Car with Series Active Variable Geometry Suspension
Feng, Zilin	Imperial College London
Yu, Min	Imperial College London
Cheng, Cheng	Huazhong University of Science and Technology
Evangelou, Simos	Imperial College
Jaimoukha, Imad M.	Imperial College London
Dini, Daniele	Imperial College London
Keywords: Adaptive and robust control of automotive systems, Vehicle dynamic systems, Modeling, supervision, control and diagnosis of automotive systems Abstract: Linear robust control schemes, for example the H infinity control, are commonly utilized in the control design of an active suspension system, with a linearized and time-invariant state-space model of the system adopted. However, the vehicle parameter uncertainties are mainly ignored and their effect on the control robustness is not investigated. In this paper, a mu-synthesis-based control scheme is synthesized for a full car with the recently introduced Series Active Variable Geometry Suspension (SAVGS), to mainly enhance the ride comfort and road holding performance, with two significant practical uncertainties in the sprung mass and the suspension damping taken into account. Numerical simulations with a high fidelity nonlinear vehicle model are performed, with the cases of the fixed and swept values of the sprung mass tested, to assess the control robustness and performance of the developed scheme against the passive suspension as well as the H-infinity-controlled SAVGS. The proposed mu-synthesis control scheme is proved to be more effective for realistic applications as it is capable of maintaining the suspension performance improvement regardless of variations of system parameters associated with the uncertainties, while the H infinity control performance tends to deteriorate when a notable deviation from the nominal values occurs.
Paper VI171-04.6
PDF · Video · A Centralized Multilayer LPV/H∞ Control Architecture for Vehicle’s Global Chassis Control, and Comparison with a Decentralized Architecture
Hamdan, Ali	University of Technology of Compiegne UTC
Chokor, Abbas	Universite De Technologie De Compiegne
Talj, Reine	Heudiasyc, University of Technology of Compiegne
Doumiati, Moustapha	ESEO Angers
Keywords: Control architectures in automotive control, Adaptive and robust control of automotive systems, Vehicle dynamic systems Abstract: This paper deals with the development of Global Chassis Controller where the Active Front steering, Direct Yaw Control and Active Suspensions, are coordinated together in the aim to improve the overall vehicle performance i.e maneuverability, lateral stability and rollover avoidance. The main contribution of this work is the integration of the Active suspension system (AS) in a centralized multilayer control architecture to control the roll angle. A polytopic approach is used to find the LPV/H∞ controller where an offline Linear Matrix Inequality (LMI) optimal solver is used to realize the optimality of this controller. The different layers of this architecture are detailed. The proposed LPV/H∞ controller is validated by simulation using Matlab/Simulink, and a comparison is done with a decentralized architecture that has been developed in the laboratory, to show the difference in behavior and performance of both strategies of control and the effectiveness of centralized one on the rollover avoidance.
Paper VI171-04.7
PDF · Video · LPV-Based Control for Automated Driving Using Data-Driven Methods
Fényes, Dániel	Institute for Computer Science and Control (SZTAKI)
Nemeth, Balazs	MTA SZTAKI
Gaspar, Peter	SZTAKI
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling, Adaptive and robust control of automotive systems Abstract: This paper presents a novel data-driven modeling approach and control design for automated driving purposes. The control-oriented polytopic model is identified using machine-learning algorithm in a Linear Parameter Varying (LPV) structure. The control of the automated driving is designed based on LPV control synthesis method, with which the performances of the system are guaranteed. Through the automated driving system the steering intervention is performed, while the maximization of the longitudinal velocity in a predicted safety region is achieved. The operation and the effectiveness of the proposed control system is demonstrated through a comprehensive simulation example using the high- delity simulation software CarSim.

VI171-05
Automotive System Identification and Modelling	Regular Session
Chair: Basset, Michel	Université De Haute-Alsace
Co-Chair: Jain, Tushar	Indian Institute of Technology Mandi
Paper VI171-05.1
PDF · Video · On Vehicle Pitch Estimation Via Solid-State LIDAR
Selmanaj, Donald	Polytechnic University of Tirana
Corno, Matteo	Politecnico Di Milano
Panzani, Giulio	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Automotive sensors and actuators, Automotive system identification and modelling, Vehicle dynamic systems Abstract: Solid-state LIDAR technology has recently emerged, allowing for smaller and more affordable devices. In the present work, we investigate the possibility of using a vehicle mounted solid-state LIDAR to estimate the vehicle pitch and heave dynamics. We present and compare two approaches: a model-based estimation and a data driven algorithm. The algorithms are tested on an instrumented vehicle. The experimental results show that the data-driven approach outperforms the model-based estimation in estimating pitch caused both by accelerations and braking and by road disturbances.
Paper VI171-05.2
PDF · Video · Parameter Identification for Nonlinear Models from a State-Space Approach
Matz, Jules	Université De Haute-Alsace
Birouche, Abderazik	Université of Haute Alsace
Mourllion, Benjamin	UHA
Bouziani, Fethi	INPG
Basset, Michel	Université De Haute-Alsace
Keywords: Automotive system identification and modelling Abstract: A new approach to parameter estimation of dynamical models is proposed. Its objective is to approximate at best the different dynamics of the system, instead of approximating at best the system output in time. This leads to a weighting of the error depending on the samples location in the state-space and input space. A possible implementation is proposed and applied for estimating the parameters of a two degrees of freedom vehicle dynamics model. The proposed approach is shown to better approximate the fast transient dynamics, at the cost of a degraded performance on steady-states.
Paper VI171-05.3
PDF · Video · A Kinematic Parameter Estimator Applied to a Bi-Directional Vehicle
Lucet, Eric	CEA
Micaelli, Alain	CEA
Keywords: Automotive system identification and modelling, Autonomous Mobile Robots Abstract: This paper deals with the online estimation of the geometric and kinematic parameters of a wheeled mobile robot, with the objective of its precise navigation. To do this, the implementation of an algorithm for estimating these parameters is proposed. It is based on a quadratic criterion to be minimized, which is a function of the difference between the measured and estimated robot pose. The estimator inputs external measurements of robot positions and speeds and proprioceptive inertial and odometer measurements, and outputs an estimate of model parameters. Its expression does not depend on the position of the robot relative to the path to be followed and its possible tracking errors, nor on the speed of the tracking. The experimental implementation carried out on a real bi-directional container truck under realistic operating conditions has shown its performance.
Paper VI171-05.4
PDF · Video · Extended Kalman Filter Based Estimation of the State of Charge of Lithium-Ion Cells Using a Switched Model
Routh, Bikky	Indian Institute of Technology Kharagpur
Mitra, Desham	Indian Institute of Technology, Kharagpur, India
Patra, Amit	Indian Institute of Technology Kharagpur
Mukhopadhyay, Siddhartha	IIT KGP
Keywords: Automotive system identification and modelling, Health monitoring and diagnosis, Kalman filtering techniques in automotive control Abstract: The State of Charge (SoC) is one of the important quantities estimated by the Battery Management System (BMS) of Lithium-ion cells. However, the hysteresis effect and flat SoC-OCV nature of Lithium Iron Phosphate (LFP) battery complicate the SoC estimation. This paper proposes a novel switched model to successfully capture the hysteresis phenomena and enhance the accuracy of SoC estimation of LFP cells. The model is switched between charge and discharge modes, where the current direction decides the mode. The model parameters are functions of SoC and the switched mode. The parameters are estimated from Pulse Charge Data (PCD) and Pulse Discharge Data (PDD) using a Successive Recursive Least Square (SRLS) technique. The SRLS algorithm ensures sufficiency of excitation by capturing only the transient response of each pulse. Using the proposed model, SoC estimation is carried out using the Extended Kalman Filter (EKF). The proposed approach is validated by a real drive cycle data which is widely used to test vehicle performance. The study has been carried out on LFP pouch cell with a nominal capacity of 20Ah and a nominal voltage of 3.3V and experiments are performed using the Biologic (BCS-815) battery testing equipment.
Paper VI171-05.5
PDF · Video · A Machine Learning Method for Vehicle Classification by Inductive Waveform Analysis
Roth Vasconcellos, Bruno	Pontifícia Universidade Católica Do Paraná
Rudek, Marcelo	Pontifical Catholic University of Parana - PUCPR/PPGEPS
de Souza, Marcelo	FISCALTECH
Keywords: Automotive system identification and modelling, Integrated traffic management, Information processing and decision support Abstract: The classification of vehicles is a matter of importance for traffic control and management, helping with traffic surveillance as well as in statistical data collection. Among the several vehicular classification techniques, the most popular uses inductive loop sensors, because they achieve high accuracy rate at low cost. This paper proposes 5 different vehicle classification models by inductive waveform analysis: KNN, SVC, Decision Tree, Random Forest, and Voting Classifier. A brief introduction to the mathematical basis of these models and the main forms of vehicle detection are also presented. The obtained results reached an accuracy of 94% and showed how inductive waveform analysis is still a valid option for vehicle classification.
Paper VI171-05.6
PDF · Video · Online Traction Parameter Identification and Mapping
Kobelski, Alexander	Technische Universität Chemnitz
Osinenko, Pavel	Skoltech Institute of Science and Technology
Streif, Stefan	Technische Universität Chemnitz
Keywords: Automotive system identification and modelling, Kalman filtering techniques in automotive control, Vehicle dynamic systems Abstract: Fuel consumption of heavy-duty vehicles such as tractors, bulldozers etc. is comparably high due to their scope of operation. The operation settings are usually fixed and not tuned to the environmental factors, such as ground conditions. Yet exactly the ground-to-propelling-unit properties are decisive in energy efficiency. Optimizing the latter would require a means of identifying those properties. This is the central matter of the current study. More specifically, the goal is to estimate the ground conditions from the available measurements, such as drive train signals, and to establish a map of those. The ground condition parameters are estimated using an adaptive unscented Kalman filter. A case study is provided with the actual and estimated ground condition maps. Such a mapping can be seen as a crucial milestone in optimal operation control of heavy-duty vehicles.
Paper VI171-05.7
PDF · Video · Online Bayesian Tire-Friction Learning by Gaussian-Process State-Space Models
Berntorp, Karl	Mitsubishi Electric Research Labs
Keywords: Automotive system identification and modelling, Learning and adaptation in autonomous vehicles Abstract: The friction dependence between tire and road is highly nonlinear and varies heavily between different surfaces. The tire friction is important for real-time vehicle control, but difficult to learn with automotive-grade sensors as they only provide indirect measurements based on sensing parts of the vehicle state. In this paper we leverage recent advances in particle filtering and Gaussian Processes (GPs), to provide an online method for jointly estimating the vehicle state and subsequently identifying the tire friction as a function of the wheel slip. The unknown function mapping the wheel slip to tire friction is modeled as a GP that is included in a dynamic vehicle model relating the GP to the vehicle state.We illustrate the efficacy of the method using synthetic data on a snow-covered road.
Paper VI171-05.8
PDF · Video · A Novel Strategy for High-Performance Vehicle Lateral Motion Control
Yin, Xiuxun	Continental Teves AG & Co. OHG
Eckert, Alfred	Systems & Technology, Continental Chassis & Safety Division
Keywords: Automotive system identification and modelling, Nonlinear and optimal automotive control, Vehicle dynamic systems Abstract: Abstract: This paper presents a new design strategy for vehicle lateral motion control. In particular, the controller design problem for vehicle path following is considered. A new kind of full error-state dynamic equation incorporating more significant error states is introduced, which describes vehicle lateral dynamics with respect to the desired path, even without the curvature of the desired path acting as disturbance at the input. Thus, the feedback and the feedforward controller can be designed straightforwardly. A novel solution is provided to extract the desired feedforward steering command and the desired reference states from the varying curvature of the desired path. Simulation results demonstrate the efficiency, high performance and robustness of the developed control strategy.
Paper VI171-05.9
PDF · Video · Instantaneous Gearshift Model Based on Gear-Dependent Angular Momentum
Tebaldi, Davide	Univ. of Modena and Reggio Emilia
Zanasi, Roberto	Univ of Modena and Reggio Emilia
Keywords: Automotive system identification and modelling, Simulation, Vehicle dynamic systems Abstract: The paper presents a new gearbox dynamic model for the effective simulation of simultaneous multi-clutches lock/unlock, by exploiting the Power-Oriented Graphs (POG) modeling technique. The generalized structure of the proposed model allows to simulate various gearbox configurations, which may foresee a change in terms of equivalent moment of inertia on the primary or secondary shaft, depending on the internal clutches configuration being function of the currently engaged gear. The peculiarity of the model lies in the instantaneous engagement of the new gear by skipping the slipping transient related to change of the internal clutches configuration, while preserving the natural loss of energy associated to it. The effectiveness of the presented gearbox model is finally tested and compared with classical gearbox modeling solutions with the aid of some simulation results.
Paper VI171-05.10
PDF · Video · Resource Efficient Classification of Road Conditions through CNN Pruning
Fink, Daniel	Leibniz University Hanover
Busch, Alexander	Leibniz University Hanover, Institute of Mechatronic Systems
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: General automobile/road-environment strategies, Automotive system identification and modelling Abstract: Towards autonomous driving, advanced driver assistance systems increasingly undertake basic driving tasks by replacing human assessment and interactions, when controlling the vehicle. The performance of these systems is directly related to knowledge of the vehicle's state and influential parameters. In this respect, the road condition has a major influence on the tires' traction and thus significantly affects the behavior of the vehicle. Therefore, a prediction of the upcoming road condition can improve the performance of the assistance systems which leads to an increased driving safety and comfort. The presented work aims to classify the road surface as well as its weather-related condition, based on images of the front camera view, using deep convolutional neural networks. In order to take computational limitations of vehicle control units into account, a pruning approach is investigated to reduce the network complexity.
Paper VI171-05.11
PDF · Video · A Novel State and Parameter Estimation Algorithm for Spark Ignition Engine
Singh, Vyoma	IIT Mandi
Pal, Birupaksha	Researcher
Jain, Tushar	Indian Institute of Technology Mandi
Keywords: Kalman filtering techniques in automotive control, Automotive system identification and modelling, Engine modelling and control Abstract: The engine control and estimation problem is an important area of research in the automotive industry. Researchers have been working to make the vehicles more efficient and economically friendly while producing lesser pollutants. To reduce emissions, the air-fuel ratio must be controlled to a specific value. The requirement of air-fuel ratio improvement has increased the need for the investigation of engine dynamical models and their parameter estimation. Some of the main parameters affecting the air-fuel ratio are the throttle discharge coefficient, thermal efficiency and volumetric efficiency. The precise values of these parameters are essential for accurate control of the air-fuel ratio of the engine. Under steady state, these parameters are constant but in the long run due to wear and tear of the engine and various uncertainties, their value may change. The main challenges are how to obtain the information of parameters and that of the states under the influence of process noise, measurement noise and parameter uncertainty, which are essential elements to develop an effective control strategy. In this work, the problem of physical parameter estimation of the nonlinear system comprising a throttle, intake manifold, engine speed dynamics and fuel system altogether with unknown states have been considered. A novel method with a unique combination of Unscented Kalman Filter and Recursive Least Squares with forgetting factor for estimation of parameters and states of spark ignition engines has been developed. Simulation results are provided for state and parameter estimation for spark ignition engine model.
Paper VI171-05.12
PDF · Video · Simulation Environment for Analysis and Controller Design of Diesel Engines
Nguyen, Khac Hoang	Aalto University School of Electrical Engineering
Modabberian, Amin	Aalto University
Zenger, Kai	Aalto University School of Electrical Engineering
Storm, Xiaoguo	Vaasa University
Hyvönen, Jari	Engine Research and Technology Development at Wärtsilä Marine So
Keywords: Data-based control, Parametric optimization, Model validation Abstract: Novel combustion concepts and multi injection cylinderwise control methods are needed in large marine diesel engines for increased performance and to reduce the green house gas emissions. Even though diesel technology in cars might be reducing there is no replacement of dual fuel diesel technology in large marine engines to be seen in the near future. The paper discusses a rapid grey-box modelling technique, which can be used to predict cylinder pressure and heat release in engine cylinders. The model can be used to design effective cylinder-wise control algorithms which increase the engine performance and save fuel under constraint of emissions.

VI171-06
Engine Modelling and Control	Regular Session
Chair: Koch, Charles Robert	University of Alberta
Co-Chair: Suzuki, Masayasu	Utsunomiya University
Paper VI171-06.1
PDF · Video · Support Vector Machine for a Diesel Engine Performance and NOx Emission Control-Oriented Model
Aliramezani, Masoud	University of Alberta
Norouzi Yengeje, Armin	University of Alberta
Koch, Charles Robert	University of Alberta
Keywords: Engine modelling and control Abstract: A control oriented diesel engine NOx emission and Break Mean Effective Pressure (BMEP) model is developed using Support Vector Machine (SVM). Steady state experimental data from a medium duty diesel engine is used to develop BMEP and NOx emission model using Support Vector Machine (SVM). The engine speed, the amount of injected fuel and the injection rail pressure are used as input variables to predict the steady state engine NOx emission and BMEP. The steady state model results were then implemented in the control oriented model. A fast response electrochemical NOx sensor is used to experimentally study the engine transient NOx emission and to verify the transient response of the control oriented model. The results show that the SVM algorithm is capable of accurately learning the engine BMEP and NOx which improves the accuracy of the control oriented model compared to a conventional regression algorithm (trust-region) used in the literature. The control oriented model results closely match the experiments in both transient and steady state conditions with a root mean square error of 0.26 (bar) and 10 (ppm) for BMEP and NOx respectively.
Paper VI171-06.2
PDF · Video · Co-Simulation of Multi-Domain Engine and Its Integrated Control for Transient Driving Cycles
Picerno, Mario	RWTH Aachen University
Lee, Sung-Yong	VKA RWTH Aachen
Schaub, Joschka	FEV Europe GmbH
Ehrly, Markus	FEV Europe GmbH
Millo, Federico	Politecnico Di Torino
Scassa, Mauro	FEV Italia S.r.l
Andert, Jakob	RWTH Aachen University
Keywords: Engine modelling and control Abstract: Virtualization of powertrain components allows the front-loading of conventional vehicle calibration and validation tasks to Model-in-the-Loop (MiL) and Hardware-in-the-Loop (HiL) simulations. This approach is based on the utilization of highly accurate physics-based powertrain models that enable a seamless system validation using virtual testing methods in order to ensure cost-effective powertrain development by reducing hardware tests. Proper modelling methods target the optimum between parametrization effort, model accuracy and required computing power to grant the real-time (RT) capability of the simulation, which is mandatory for HiL simulation. In this paper two validated modelling approaches and their implementation into a MiL environment are introduced and discussed. The approaches are the MATLAB/Simulink based Mean Value Engine Model (MVEM) and the Fast-Running Modelling (FRM) of GT-Power. After the models integration in a Simulink frame, the responses of a model-based control unit with the two simulation models were evaluated using real experimental data. In transient cycles, the controller showed a different reaction to the feedback signals of the two engine models. The purposes of the conducted investigation are mainly to evaluate strong and weak points of both approaches and to propose the best-practice modelling approaches for virtual calibration and validation. A comparative rating shows the main advantage of the MVEM in the flexibility for HiL-based systems and the model training effort for the FRM.
Paper VI171-06.3
PDF · Video · A Heuristic Engine and EATS Supervisory Control Scheme for Heavy-Duty Vehicles
Tiberi, Ubaldo	Volvo Group Trucks Technology
Gelso, Esteban R.	Volvo Group Trucks Technology
Keywords: Engine modelling and control Abstract: In this paper we present a heuristic supervisory control scheme for jointly controlling the engine and the after-treatment system (EATS) in heavy-duty vehicles. The proposed controller aims at fulfilling emission legislation constraints without penalizing the fluid consumption and the delivered torque. Compared to existing methods, the proposed control scheme is computationally efficient since it does not require the online execution of iterative algorithms as it is typically done for this class of problems. Moreover, it does not require an accurate model identification of the system nor it requires highly skilled personnel for calibrating its parameters, which are two aspects very appealing in an industrial setting. The effectiveness of the proposed approach is evaluated through simulations where a comparison with existing methods is also performed.
Paper VI171-06.4
PDF · Video · Scheduling Parameter Reduction of Diesel Engine Air Path LPV Model by PCA and Autoencoder-Based Method
Hirata, Mitsuo	Utsunomiya University
Asahi, Teruhiko	Utsunomiya University
Shiraishi, Tatsuya	Utsunomiya University
Suzuki, Masayasu	Utsunomiya University
Keywords: Engine modelling and control, Adaptive and robust control of automotive systems, Automotive system identification and modelling Abstract: This study presents a method to reduce the number of scheduling variables in a linear parameter-varying (LPV) model of a diesel engine air path system. The reduction of these scheduling variables is very important because it exponentially decreases the computational complexity for the gain-scheduled LPV controller synthesis. Principal component analysis (PCA) and autoencoder (AE) based neural networks are applied to the LPV diesel engine's air path model, and the relationship between the accuracy of the reproduced scheduling variables and the number of the reduced scheduling parameters is evaluated via conduction of numerical simulations.
Paper VI171-06.5
PDF · Video · Predictive In-Cycle Closed-Loop Combustion Control with Pilot-Main Injections
Jorques Moreno, Carlos	Scania CV AB
Stenlaas, Ola	Scania CV AB
Tunestal, Per	Lund University, Faculty of Engineering
Keywords: Engine modelling and control, Adaptive and robust control of automotive systems, Control architectures in automotive control Abstract: This paper studies the use of predictive in-cycle close-loop combustion control to reduce the stochastic cyclic variations of diesel combustion. The combustion metrics that fully define the pressure trace with a pilot-main injection i.e. pilot and main start of combustion, burned pilot mass, and engine load are used as the set-point reference. These metrics are in-cycle predicted by calibrated models as functions of the current cylinder state, estimated by in-cylinder pressure measurements. The proposed approach uses four individual controllers for the set-point error minimization, which respectively regulate the injection's timing and duration of the pilot-main injection. The controllers are implemented in a FPGA and tested in a Scania D13 engine. The steady-state error reduction, disturbance rejection and transient response are discussed. The results confirm the error reduction in both, cycle-to-cycle and cylinder-to-cylinder variations. The error dispersion, measured by the 95% confidence interval, was reduced between 25% and 75% for all the controlled parameters. By on-line adaptation, the controllers are robust against model uncertainties and fuel types.
Paper VI171-06.6
PDF · Video · Frequency Response Based Multivariable Feedback Control Design for Transient RCCI Engine Operation
Verhaegh, Jan	TNO Automotive
Kupper, Frank	TNO Automotive
Willems, Frank	Eindhoven University of Technology
Keywords: Engine modelling and control, Automotive system identification and modelling, Control architectures in automotive control Abstract: Reactivity Controlled Compression Ignition (RCCI) is a high efficient, pre-mixed combustion concept, which is characterized by controlled auto-ignition. RCCI control has to guarantee stable and safe operation for varying operating conditions. Research concentrated on next-cycle fuel path control, so far. However, a crucial step towards on-road implementation is accurate control of both air and fuel path, especially during transients. In this work, a systematic, frequency domain-based design method is presented for coordinated air-fuel path control. Starting from MIMO system identification using Frequency Response Functions, cylinder individual combustion models are developed. Based on these models, a static decoupling matrix and five SISO PI controllers are designed. The followed method allows to analyze and guarantee local robust stability, disturbance rejection and reference tracking properties. For transients, the controller is scheduled as a function of engine speed and torque. The potential of the designed MIMO controller is demonstrated on a six-cylinder Diesel-E85 RCCI engine. This controller shows good reference tracking for engine speed-load variations. Furthermore, it enables safe RCCI operation towards higher loads compared to open-loop control strategies.
Paper VI171-06.7
PDF · Video · Development and Identification of a Control Oriented Model of NOx Storage Catalyst for Automotive Application
D'Aniello, Federica	University of Salerno
Arsie, Ivan	University of Naples "Parthenope"
Pianese, Cesare	University of Salerno
De Cesare, Matteo	Magneti Marelli SpA
Keywords: Engine modelling and control, Automotive system identification and modelling, Modeling, supervision, control and diagnosis of automotive systems Abstract: The NOx Storage Catalyst is currently envisaged to be implemented in light-duty passenger cars for nitrogen oxides reduction, in order to comply with strict emission legislation targets. Since robustness and durability of the engine and emission control system is the first priority in automotive application, to satisfy the need of robust on-board real time monitoring, diagnosis and control, computing ecient methods are needed. In this framework, a control oriented model that describes the dynamics of the main physical-chemical processes within the NSC catalyst, while still maintaining affordable computational burden, has been developed and validated. Model calibration has been performed, for light-duty application, along the NEDC test cycle, by using a statistical-based sub-optimal procedure, based on a parametric analysis which allows identifying the more suitable section of NEDC cycle for model identication, without the need to perform cost- and time- expensive experiments on the engine test bench. The procedure also accounts for missing information and sensors inaccuracies. The great potential of this methodology is the possibility to adopt not optimal designed tests for model parameters identication. The proposed methodology is proven to be effective for real time control strategy, directly embedded in ECU, and provide a sub-optimal but effective strategy for complex models calibration.
Paper VI171-06.8
PDF · Video · Tuning of Model Predictive Engine Controllers Over Transient Drive Cycles
Maass, Alejandro I.	The University of Melbourne
Manzie, Chris	The University of Melbourne
Shames, Iman	University of Melbourne
Chin, Robert	The University of Melbourne & University of Birmingham
Nesic, Dragan	Univ of Melbourne
Ulapane, Nalika	University of Melbourne
Nakada, Hayato	Toyota Motor Corporation
Keywords: Engine modelling and control, Control architectures in automotive control Abstract: A framework for tuning the parameters of model predictive controllers (MPCs) based on gradient-free optimisation (GFO) is proposed. Efficient calibration of MPCs is often a difficult task given the large number of tuning parameters and their non-intuitive correlation with the output response. We propose an efficient and systematic framework for the tuning of MPC parameters that can be implemented iteratively within the closed-loop setting. The performance of the proposed GFO-based algorithm is evaluated through its application to air-path control for diesel engines over simulations and experiments. We illustrate that the tuned parameters provide satisfactory tracking of reference trajectories over engine drive cycles with only a few iterations. Thereby, we extend existing MPC tuning approaches that calibrate parameters using step responses on the fuel rate and engine speed onto tuning over a full drive cycle response.
Paper VI171-06.9
PDF · Video · A Switching System Oriented Modeling and Control Strategy for Idle Speed Control of a Hybrid Powertrain
Obergfell, Micha Sebastian	University of Duisburg-Essen
Ding, Steven X.	Univ of Duisburg-Essen
Wobbe, Frank	IAV GmbH
Goletz, Christoph-Marian	IAV GmbH
Folkers, Michael	IAV GmbH
Rabba, Heiko	IAV GmbH
Keywords: Engine modelling and control, Hybrid and alternative drive vehicles Abstract: The market development of partially electrified powertrains in passenger cars motivates the re-consideration of the idle speed control problem. In this paper, a switching system model is first developed to unite the main discrete-event characteristics of the combustion engine and time-continuous characteristics of the electric motor. The presented model is classified as a discrete-time switching system model with linear subsystems. Based on this description, we further perform a model-based controller design using the lifting technique. Although the optimality property of the controller is bound to the assumption of constant turning speed, it still provides several useful properties. These are the inherent control allocation between electric and combustion engine, the consideration of the discontinuous behavior, and the discrete-time description basis which is important for implementation in a common controller architecture.
Paper VI171-06.10
PDF · Video · Development of an Integrated Control Strategy for Engine and SCR System Based on Effective EGR Rate
D'Aniello, Federica	University of Salerno
Arsie, Ivan	University of Naples
Pianese, Cesare	University of Salerno
Stola, Federico	Marelli Europe - Powertrain
Keywords: Engine modelling and control, Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling Abstract: The introduction of actual and upcoming emission standards, move the industrial attentions from laboratory towards real-world emission performance, In-Service Conformity testing (ISC) and life-time periods. Besides advanced air management, fuel injection pattern optimization and after treatment systems, the goal to realize optimal and robust powertrain setting under varying operating conditions, while ensuring the proper operation of ATs, is challenging and require a massive calibration effort. To accomplish this task, the present research deals with supervisory controller for the integrated engine-SCR system, also referred in literature as EGR-SCR balancing. The goal is to comply with NOx emissions limit and, at the same time, to minimize global costs over transient operating conditions. The potential of this IEM strategy is demonstrated for a typical type-approval test case. The optimization identififies the effective EGR actuation, based on the actual powertrain state, engine settings and ATs performances. The resulting control strategy optimizes the overall performance.
Paper VI171-06.11
PDF · Video · Model Based Control with Online Automatic Adaptation by Neural Network for Advanced Diesel Combustion
Cao, Jianan	The University of Tokyo
Kim, Jihoon	The University of Tokyo
Takahashi, Motoki	The University of Tokyo
Yamasaki, Yudai	The University of Tokyo
Keywords: Engine modelling and control, Neural networks Abstract: Control-oriented models based on physics have been proposed as an alternative to conventional control methods to improve engine performance under real driving conditions including various transient condition. Even if models were built based on physical rules, there are still parameters existing in equations and it is desirable to adapt the parameters in real time according to driving condition. Therefore, the authors developed an online automatic adaptation method for model-based control of diesel engines, which is based on neural networks. The predictive accuracy of the adapted model has been evaluated by simulation, and the performance of the feed-forward controller based on the model is evaluated by experiment under actual engine.
Paper VI171-06.12
PDF · Video · Hybrid Model Predictive Control of a Variable Displacement Engine Mode Management
Majecki, Pawel	Univ of Strathclyde
Grimble, Michael	University of Strathclyde, Industrial Control Centre
Haskara, Ibrahim	GM Research & Development
Chang, ChenFang	GM R&D Center
Keywords: Engine modelling and control, Nonlinear and optimal automotive control, Control architectures in automotive control Abstract: The use of Hybrid Predictive Control for model-based propulsion control applications is considered. A Variable Displacement Engine (VDE) control problem is considered, involving both continuous-time dynamics and discrete control actions in the form of activating/deactivating the engine cylinders. Hybrid Model Predictive Control is one of the most successful hybrid control schemes and builds upon predictive control methods developed for engine torque management. The ways in which preview information can be used to improve controller performance are considered, as well as simplifications to the hybrid control algorithms to reduce the computational burden. Several hybrid control design approaches are compared using a simulation of a VDE engine. The aim is to optimize the total system behaviour to provide good torque tracking, reduced fuel consumption and smooth cylinder switching. The main contribution is the demonstration that hybrid predictive control can provide a practical solution to an engine control application with the potential to enhance performance and with options to reduce complexity.
Paper VI171-06.13
PDF · Video · Engine-Based Input-Output Linearization for Traction Control Systems
Reichensdörfer, Elias Jeremias Virgil	Technical University of Munich, BMW Group
Odenthal, Dirk	BMW Group
Wollherr, Dirk	Technical University of Munich
Keywords: Engine modelling and control, Vehicle dynamic systems, Nonlinear and optimal automotive control Abstract: Engine-based traction control marks a paradigm shift for electronic stability systems in the automotive industry. It enables traction control systems with higher bandwidth and performance by an architectural change. As a new approach, only few work exists that considers analytic control design for engine-based traction control. This paper extends our recent work on input-output linearization for engine-based traction control. Global, exponential stability for arbitrary vehicle parameters and time-varying road adhesion coefficients is shown for the first time. Experiments in a test vehicle compare the proposed design with different traction control systems. It is shown that on the considered maneuver, the control design achieves superior tracking performance, disturbance attenuation and damping of drivetrain oscillations.
Paper VI171-06.14
PDF · Video · Design of a Neural Virtual Sensor for the Air and Charging System in a Diesel Engine
Alfieri, Vincenzo	General Motors Global Propulsion Systems
Pedicini, Carmen	University of Sannio
Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Keywords: Modeling, supervision, control and diagnosis of automotive systems, System integration and supervision, Automotive sensors and actuators Abstract: The main objective of this work is to design a virtual sensor capable of estimating variables that are unmeasurable on-line in the air and charging subsystem of a Diesel engine. In order to achieve this objective, a data-driven approach is pursued. In particular, we show that combining high-gain observers and feed-forward neural networks, it is possible to design an observer for the air and charging system of a Diesel engine on the basis of data acquired via a test bench. The performance of this observer is evaluated in a real experimental setting.

VI171-07
Hybrid, Electric, and Solar Vehicles	Regular Session
Chair: Borrelli, Francesco	University of California
Co-Chair: Rinderknecht, Stephan	Technische Universitaet Darmstadt
Paper VI171-07.1
PDF · Video · Global Sensitivity Analysis on the Torque Accuracy of the Powertrain in Electric Vehicles
Braband, Matthias	University of Applied Sciences Trier
Adams, Michael	University of Applied Sciences Trier
Wilhelmi, Andreas	Hofer Eds GmbH
Scherer, Matthias	University of Applied Sciences Trier
Keywords: Automotive system identification and modelling, Modeling, supervision, control and diagnosis of automotive systems, Electric and solar vehicles Abstract: Electric drive systems are increasingly used in automobiles. However, the com- bination of comfort, dynamics and safety requirements places high demands on the torque accuracy. The complex interplay of battery, inverter and electrical machine causes a lot of system uncertainties based on parameter fluctuations and measurement errors that influence the system performance. These influences on the closed loop torque control are analyzed and quantified using a variance based sensitivity analysis. This method enables to connect the variance of the torque accuracy with the parameters causing this variance. Moreover, it quantifies the influences of the parameters independent of the complexity of the analyzed system. In addition, two methods to ensure convergence of the variance based sensitivity measures are proposed. The results of the analysis are presented for static working points of an battery electric drive system.
Paper VI171-07.2
PDF · Video · In-Vehicle System Identificatin of an Induction Motor Loss Model
Rolle, Bernhard	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Automotive system identification and modelling, Modeling, supervision, control and diagnosis of automotive systems, Electric and solar vehicles Abstract: The influence of induction motor model parameter deviations on field-oriented control performance has been widely investigated. Various methods have been introduced to track variations of magnetic and resistive parameters of the so called T-equivalent circuit model. Online methods on embedded systems exist and are successfully used in modern motor controls. For the use in vehicle propulsion control systems and particularly supervisory controls, however, state-of-the-art identification methods may not be applied directly, due to restricted communication interfaces or a limited amount of available measurements at sampling frequencies above the required rates. To cope with these limitations, a moddeling approach is introduced which is based on the equivalent flat system representation of the induction motor, stationary operation conditions, and the incorporation of the vehicle specific field-oriented control strategy. The inclusion of the control strategy allows for derivation of least-square error formulations which are used to identify a selection of induction motor model parameters from low frequency vehicle measurements. An experimental study demonstrates the accuracy of the proposed method and shows how effectively the introduced model can reproduce the measurment of the rms phase current and electric power.
Paper VI171-07.3
PDF · Video · Glocal Traction Control for In-Wheel-Motor Electric Vehicles - a Passivity Approach
Nguyen, Binh Minh	The University of Tokyo
Tsumura, Koji	The University of Tokyo
Hara, Shinji	Tokyo Institute of Technology
Keywords: Control architectures in automotive control, Vehicle dynamic systems, Electric and solar vehicles Abstract: Although traction control of in-wheel-motor electric vehicles (IWM-EVs) has been studied for years, we still face the essential theoretical issue: How to assure the stability of the overall system while attaining both global and local control performances? This issue has been neglected by almost the works in the literature. The main reason is due to the nonlinearity and complexity in vehicle dynamics, especially the vehicle driven by multi-actuators. A new traction method is proposed in this paper in the glocal (global/local) framework to overcome this problem. The command to each local IWM includes two signals: (i) the local signal through anti-slip control in the lower-layer, and (ii) the global signal distributed from the driver or the upper-layer controller that managing the average wheel velocity. Stability of the whole system is guaranteed based on the fundamental passivity theory. The effectiveness of the proposed approach is verified by using Carsim/Matlab co-simulator.
Paper VI171-07.4
PDF · Video · Control Allocation for Hybrid Braking Considering Dynamic Battery Behaviour
Lupberger, Stefan	University of Kaiserslautern
Degel, Wolfgang	Technische Universität Kaiserslautern
Odenthal, Dirk	BMW Group
Bajcinca, Naim	University of Kaiserslautern
Keywords: Electric and solar vehicles, Control architectures in automotive control, Vehicle dynamic systems Abstract: This work deals with the problem of maximizing energy recovery while optimizing braking capability of high-performance electric vehicles under given actuator constraints. A scalable, real-time capable concept using a complementary filter with an additional daisy chain for the control allocation between hydraulic brakes and electric motors is proposed. Furthermore, a model inversion approach that derives necessary battery limits while trying to decouple the wheel speed control loop from the protection loop of a modern battery management system is described. The hybrid braking control architecture is studied in simulation and validated in a prototype electric vehicle by highly dynamical driving manoeuvres.
Paper VI171-07.5
PDF · Video · Disturbance Observer Based Constrained Resonant Control of SRM Integrated EV Drive in Vehicle-To-Home (V2H) Operation
Saeed, Junaid	RMIT University
Wang, Liuping	RMIT University
Fernando, Nuwantha	RMIT University
Keywords: Electric and solar vehicles, Control of systems in vehicles, Control architectures in automotive control Abstract: This paper presents a disturbance observer based constrained resonant control strategy for a switched reluctance motor (SRM) integrated electric vehicle (EV) drive in vehicle-to-home (V2H) mode of operation. First, a full-order large-signal model of the integrated drive is developed using averaged modeling technique. Then, a fixed switching frequency disturbance estimation based constrained resonant control with an intrinsic anti-windup mechanism is proposed to achieve a 50Hz sinusoidal voltage at the inverter output. It is shown through simulation studies that the proposed control scheme achieves excellent reference tracking and disturbance rejection with different linear and non-linear load types.
Paper VI171-07.6
PDF · Video · On the Real Range-Need of Electric Cars: A Telematic-Box Data-Driven Analysis
Savaia, Gianluca	Politecnico Di Milano
Formentin, Simone	Politecnico Di Milano
Strada, Silvia	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Electric and solar vehicles, Information processing and decision support, Human factors in vehicular system Abstract: Electric vehicles represent an effective weapon against pollution and global warming. In the last years, there has been an increasing effort by scientists, carmakers and governments to encourage the use of electric alternatives to conventional cars. Nevertheless, the market share of electric vehicles was still less than 2% in 2017, the main reason being the perception that battery ranges and infrastructures are not yet ready to satisfy the drivers' needs. In this paper, we exploit a massive dataset of 35M trips for over 60k vehicles in a metropolitan city of Italy, to show instead that electric vehicles are already a feasible solution. Specifically, we show that, even if no public infrastructure is available, only 4% of existing vehicles cannot be turned into an equivalent electric car.
Paper VI171-07.7
PDF · Video · Towards Optimal Planning of EV Charging Stations under Grid Constraints
Chen, Zhongqi	Zhejiang University
Li, Chao	Zhejiang University
Chen, Xiaofei	Zhejiang University
Yang, Qinmin	Zhejiang University
Keywords: Electric and solar vehicles, Modeling and simulation of transportation systems, Intelligent transportation systems Abstract: At present, the public charging network can not fully satisfy the charging demands of electric vehicles (EVs), which hinders the further development of EVs. In fact, as the key roles of charging service market, the operators need to plan charging stations properly to improve the profit while ensuring qualified charging service. Meanwhile, as the power supplier, the grid requires the charging stations to be deployed properly to lower the generation cost while ensuring safe and stable grid operation. This paper aims to plan the EV charging station (CS) network to improve the comprehensive profit by taking both the operator and the grid into consideration. Firstly, the Voronoi diagram method is used to divide the area to be planned based on the candidate set. Then, a mathematical profit maximization model with electric physical constraints is designed to distribute appropriate capacities for each candidate EV CS locations. The generalized Benders decomposition algorithm is applied to obtain the optimal solution. Finally, the simulation results demonstrate the effectiveness of the proposed algorithm based on a case study which consists of a 56-node distribution system and Xiamen traffic network system.
Paper VI171-07.8
PDF · Video · Model Predictive Energy Control Including Mechanical Fatigue Life of a Two-Motor Multi-Speed Electric Vehicle
Tao, Yikai	Technical University of Darmstadt
Schoeneberger, Daniel	Technical University of Darmstadt
Rinderknecht, Stephan	Technische Universitaet Darmstadt
Morhard, Bernd	Technical University of Munich
Schweigert, Daniel	Technical University of Munich
Gerlach, Martin	Leibniz University Hannover
Obernolte, Urs	Lenze
Keywords: Electric and solar vehicles, Nonlinear and optimal automotive control, Hybrid and alternative drive vehicles Abstract: Over the last three decades, energy management strategies considering minimum energy consumption have been extensively studied in the field of automotive engineering. On the contrary, the fatigue life of mechanical parts in powertrains is rarely considered. This paper addresses a Real-time-oriented Multi-Objective Energy Management Strategy aimed at both the energy consumption and the fatigue life of mechanical parts in the powertrain of a Battery Electric Vehicle (BEV) with an innovative Two-Motor Multi-Speed Hyper-High-Speed Powertrain. This strategy is based on Model Predictive Control (MPC), while Dynamic Programming (DP) is embedded to solve the non-linear optimal control problem in the prediction horizon. The online simulation results show that this MPC-based strategy prolongs the service life of the powertrain with a minor sacrifice in energy consumption, and that this strategy achieves a sub-optimal result close to the offline optimal result from DP. Moreover, the result from MPC-based strategy approaches the optimal result with prolonging prediction horizon.
Paper VI171-07.9
PDF · Video · Effect of Uncertainty in SOC Estimation on the Performance of Energy Management for HEVs
Ghosh, Susenjit	Indian Institute of Technology Kharagpur
Biswas, Dhrupad	Indian Institute of Technology, Kharagpur, India
Mitra, Desham	Indian Institute of Technology, Kharagpur, India
Sengupta, Somnath	IIT Kharargpur
Mukhopadhyay, Siddhartha	IIT KGP
Keywords: Hybrid and alternative drive vehicles, Automatic control, optimization, real-time operations in transportation, Kalman filtering techniques in automotive control Abstract: Existing energy management strategies of HEVs do not consider the inaccuracy of SOC estimation during optimal control formulation. In this paper, the importance and effect of considering this discrepancy in SOC values are analyzed and a mathematical relationship has been established. A sensitivity-based approach is adopted to analyze the problem. Finally, it is demonstrated through theoretical justifications and realistic simulation results that without incorporation of this discrepancy, not only does this lead to exceeding safe boundary conditions for battery but it also substantially affects fuel economy/energy consumption.
Paper VI171-07.10
PDF · Video · Predictive Hybrid Powertrain Energy Management with Asynchronous Cloud Update
Deng, Junpeng	Johannes Kepler University Linz
del Re, Luigi	Johannes Kepler University
Jones, Stephen	AVL List GmbH
Keywords: Hybrid and alternative drive vehicles, Control architectures in automotive control, Nonlinear and optimal automotive control Abstract: The optimal energy management of a hybrid powertrain has the task to provide the required traction power combining both power sources in the best way. This can be achieved well if the future drive cycle is known/precomputed. However, both speed and traction power requirement may deviate from the expected ones due to many factors, like traffic, weather etc. Against this background, it might be sensible to recompute them whenever needed to keep using the latest future information. Unfortunately, this computation is typically too slow for real time use. In this paper we propose a control structure in which the real time task is solved by a predictive controller which tracks the optimal reference from the cloud, and requests an update of the reference regularly. The update can integrate new information from V2X. This asynchronous operation allows recovering most of the performance of the perfect prediction, while removing tight constraints on the offline computation and copes better with interruptions in communications to the cloud.
Paper VI171-07.11
PDF · Video · On Weighing the Conflicting Cost Functions for Optimal Energy Management of Electrified Powertrain
Zhao, Mingjie	Beijing Institute of Technology
Zhao, Tong	The Ohio State University
Liu, Qiongqiong	Huai’an Vocational College of Information Technology
Ahmed, Qadeer	The Ohio State University
Rizzoni, Giorgio	Ohio State Univ
Keywords: Hybrid and alternative drive vehicles, Modeling, supervision, control and diagnosis of automotive systems Abstract: Besides fuel economy, gear shifting and engine start-stop frequency in the optimal energy management for hybrid electric vehicles (HEVs) will also influence the overall performance and drivability. However, such drivability concerns will also impact the vehicle’s energy efficiency. To solve this conflicting optimization problem, this paper aims to find the proper weighing of the conflicting costs to achieve a right balance based on sensitivity analysis. The problem is formulated by expanding the conventional cost function with additional penalty items for gear shifting and engine start-stop, and a range extended hybrid delivery truck is modeled as a case study. Dynamic programming (DP) algorithm is applied to guarantee all the comparisons are under the same benchmark, and a split-DP solution is carried out to accelerate the searching process. Analytical fitting and trend analysis methods are used to find the proper penalty factors. Eventually, a comprehensive comparison among optimized, experiential and none penalty factors is shown, indicating that such appropriate weighing can significantly improve drivability with only 0.2% more fuel cost.
Paper VI171-07.12
PDF · Video · Online Optimal Mode Control for Plug-In Hybrid Vehicles Based on Driving Routes
Watanabe, Ryunosuke	Tokyo Institute of Technology
Yoshioka, Hiroto	NSK Ltd
Ibuki, Tatsuya	Tokyo Institute of Technology
Sakayanagi, Yoshihiro	Toyota Motor Corporation / Tokyo Institute of Technology
Sampei, Mitsuji	Tokyo Inst. of Tech
Keywords: Hybrid and alternative drive vehicles, Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control Abstract: This paper proposes an online optimal mode control method to minimize fuel consumption for plug-in hybrid vehicles (PHVs) considering two drive modes: electric vehicle (EV) and hybrid vehicle (HV) modes. The proposed method predicts fuel and electricity consumption of PHVs based mainly on a driving-route model that considers road grades and vehicle speed distributions. The driving-route model is estimated with terrain maps and historical driving data on a planned route. In this work, two energy consumption maps are built for the EV and HV modes of the PHVs. The driving-route model and energy consumption maps lead to the formulation of an integer linear programming problem by regarding the two drive modes as binary variables. A detailed vehicle simulator, called ADVISOR, demonstrates that the proposed method improves fuel efficiency over that of a conventional method.
Paper VI171-07.13
PDF · Video · The Influence of Mode Change Penalties on the Comparison of Hybrid Drivetrain Topologies
van Harselaar, Wilco	Daimler AG
Brouwer, Markus	Daimler AG
Rinderknecht, Stephan	Technische Universitaet Darmstadt
Hofman, Theo	Technische Universiteit Eindhoven
Keywords: Hybrid and alternative drive vehicles, Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control Abstract: Hybrid drivetrains are systems with complex behavior of which finding the optimal design is a problem with a large design space. To assess a design on efficiency over a driving cycle, a control strategy is needed. Introducing mode change and engine start penalties in the optimization of the control increases the accuracy of the results at the cost of increased computation time. Yet, due to the large design space of the design problem, computation time is critical. In this work, an extensive case study is presented to analyze the influence of penalizing mode changes and engine starts on the comparison of hybrid drivetrain topologies. Eight different drivetrain topologies are considered, including parallel, series-parallel, and multi-mode powersplit topologies. For these topologies, the control is optimized over two driving cycles using dynamic programming with and without penalties. The introduction of mode change and engine start penalties reduces the number of mode changes by a factor of three to five, and the number of engine starts by approximately a factor of three. Yet, the influence on the fuel consumption comparison between the topologies is small: the largest change in relative fuel consumption is 0.36 percentage points, with the average absolute change over both cycles being 0.15 percentage points. The computation time is increased by approximately a factor of 26 due to the introduction of the penalties. Therefore, in the context of the system level design of hybrid drivetrains, it can be argued that the additional computation time outweighs the minor increase in accuracy provided by mode change penalties.
Paper VI171-07.14
PDF · Video · Optimized Design of Multi-Speed Transmissions for Parallel Hybrid Electric Vehicles
Li, Xuefang	Sun Yat-Sen University
Chen, Boli	University College London
Evangelou, Simos	Imperial College
Keywords: Hybrid and alternative drive vehicles, Modeling, supervision, control and diagnosis of automotive systems, Vehicle dynamic systems Abstract: In this paper, the optimal design of a multi-speed transmission system in terms of gear ratio, number of gears and gear shifting strategy is investigated for a parallel hybrid electric vehicle. The design procedure starts with the optimization of the transmission configuration to identify the optimal gear ratios for a specified number of gears. In order to avoid solving a complex co-optimization problem that involves numerous control variables for hybrid powertrain energy management (EM), gear ratios and gear shifting, the gear ratio optimization is properly decoupled from the co-optimization problem, while the optimal gear shifting strategy for the optimized gear ratios are determined jointly with the powertrain EM. The separation of the co-optimization makes it possible to solve individual problems by dynamic programming (DP), which guarantees global optimality. To show the impact of optimally designed and controlled transmission on fuel savings, the fuel economy solution of the proposed scheme is compared with the traditional EM and gear shifting optimization method that applies non-optimized gear ratios. Simulation examples verify the effectiveness of the proposed methodology and show the fuel savings incurred by the configuration optimization of the multi-speed transmission system.
Paper VI171-07.15
PDF · Video · Forecasting ECMS for Hybrid Electric Vehicles
Kuchly, Jean	PRISME
Nelson-Gruel, Dominique	University of Orleans
Charlet, Alain	Univ. Orléans
Simon, Antoine	Groupe PSA
Jaine, Thierry	Groupe PSA
Nouillant, Cédric	PSA Peugeot Citroen
Chamaillard, Yann	PRISME
Keywords: Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control Abstract: This paper aims to propose a real-time suitable method to tackle the problem of energy and pollutant management of Hybrid Electric Vehicles. Methods proposed in the literature often limit the underlying optimal control problem to single-instant optimizations (Paganelli, 2002) due to the difficulty of taking future into account and to onboard limited computational resources. The point of the present paper is to propose an online oriented method based on a long-term vehicle speed prediction, using cartographic information such as speed limitation, road curvature, traffic and road signs. Pontryagin Maximum Principle applied on the predicted vehicle speed signal allows to convert the optimal control problem into a root-finding problem. This problem is solved using a Pegasus algorithm supplied by a black-box method, allowing high computational efficiency. The results are near-optimal and significantly better than classical methods: in the real-driving trip used in this paper, forecasting-ECMS showed a consumption 1.1% better and NOx emissions 4.4% better than a SOC-feedback adaptive-ECMS.
Paper VI171-07.16
PDF · Video · Optimal Vehicle Following Strategy for Joint Velocity and Energy Management Control of Series Hybrid Electric Vehicles
Pan, Xiao	Imperial College London
Chen, Boli	University College London
Evangelou, Simos	Imperial College
Keywords: Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control, Automatic control, optimization, real-time operations in transportation Abstract: Recent advances in information and communication technologies present opportunities to optimally control the driving speed and powertrain energy management of vehicles under dynamic traffic circumstances. This paper addresses the energy-efficient car following problem of a series hybrid electric vehicle (HEV) by an enhanced adaptive cruise control (EACC) method. EACC is based on a nonlinear model predictive control framework, in which the behaviour of the lead vehicle is forecast by a neural network predictor trained by common test cycles. With the real-time predicted reference speed, EACC simultaneously optimizes the velocity and energy source power split of the ego HEV, while keeping the inter-vehicular distance within the desired range. The performance of EACC is benchmarked against a practical adaptive cruise control (ACC) that performs drafting and an impractical optimal control (OC) solved throughout the entire journey. Numerical examples show that the EACC can effectively close the gap between ACC and OC in terms of optimality with a remarkable fuel saving over ACC, while the computational load of EACC is comparable to ACC, which is much more efficient than the OC. Further design insight of the methodology is also provided by an investigation into the influence of the prediction horizon.
Paper VI171-07.17
PDF · Video · Multi-Layer Predictive Energy Management System for Battery Electric Vehicles
Medina, Robinson	TNO
Parfant, Angelko Godfried Petrus	TNO
Pham, T.H.	TNO Powetrains, Powertrains Department, P.O. Box 756, 5700 AT, H
Wilkins, Steven	TNO Powetrains, Powertrains Department, P.O. Box 756, 5700 AT, H
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Electric and solar vehicles, Guidance, navigation and control of vehicles Abstract: Range anxiety is one of the barriers for the customer acceptance of Battery Electric Vehicles (BEVs). To cope with this limitation, this paper presents a Predictive Energy Management System (PEMS) that can reduce total battery energy consumption by using available up-coming route information such as traffic flow, speed limits and road slope. The developed PEMS contains two optimization layers: the first layer generates a speed profile for the upcoming route that minimizes driving energy, while simultaneously controlling the average driving speed; the second layer reduces the energy consumption of the Heating, Ventilation, and Air Conditioning (HVAC) system, while guaranteeing driver thermal comfort. The proposed PEMS results in an algorithm capable of running in real time, due to the use of simplified vehicle and powertrain component models. Simulation results show potential energy savings of 7.1% compared to a baseline strategy, i.e. a non-predictive energy management system.
Paper VI171-07.18
PDF · Video · A Computationally Efficient Predictive Cruise Control for Automated Electric Vehicles
Dong, Shiying	Jilin University
Gao, Bingzhao	Jilin University
Liu, Qifang	Jilin University
Liu, Jiaqi	Jilin University
Chen, Hong	Jilin Univ, Campus NanLing
Keywords: Nonlinear and optimal automotive control, Autonomous Vehicles, Electric and solar vehicles Abstract: This paper proposes an energy-efficient predictive cruise control (PCC) system to cope with range anxiety of automated electric vehicles. The proposed approach is formulated as an optimal control problem to realize better energy efficiency and ensure safe inter-vehicle distance. To improve computational efficiency, a fast algorithm combining Gauss pseudospectral method (GPM) and moving horizon control (MHC) is introduced to solve this nonlinear optimal problem. The comparative simulation results reveal that the energy economy of the PCC system is improved about 4.1%, and its computation time is reduced compared with the Euler method while ensuing the same accuracy.
Paper VI171-07.19
PDF · Video · Decentralized Optimal Powertrain Control for Connected Hybrid Electric Vehicles in Merging Scenario
Xu, Fuguo	Sophia University
Shen, Tielong	Sophia University
Zhang, Jiangyan	Dalian Minzu University
Keywords: Nonlinear and optimal automotive control, Electric and solar vehicles, Decentralized Control and Systems Abstract: This extended abstract mainly deals with the optimal merging problem for connected hybrid electric vehicles (HEVs), a real-time decentralized optimization strategy is proposed to minimize traveling time and energy consumption for HEVs. Both vehicle dynamics and powertrain operation are optimized simultaneously to achieve the global energy efficiency improvement. A case study is conducted in a multi-vehicle-controllable traffic-in-the-loop powertrain platform to verify the effectiveness of proposed decentralized optimization strategy.
Paper VI171-07.20
PDF · Video · Hierarchical Control of Electric Bus Lines
Lacombe, Remi	Chalmers University of Technology
Gros, Sebastien	NTNU
Murgovski, Nikolce	Chalmers University of Technology
Kulcsar, Balazs	Chalmers University of Technology
Keywords: Nonlinear and optimal automotive control, Modeling and simulation of transportation systems, Electric and solar vehicles Abstract: In this paper, we propose a hierarchical control strategy for a line of electric buses with the double objective of minimizing energy consumption and providing regular service to the passengers. The state-space model for the buses is formulated in space rather than in time, which alleviates the need for integer decision variables to capture their behavior at bus stops. This enables us to first assemble a fully-centralized multi-objective line problem in the continuous nonlinear optimization framework. It is then reassembled into a hierarchical structure with two levels of control in order to improve on scalability and reliability. This new supervisory structure consists of a centralized line level controller which handles the time headway regularity of the buses, and of decentralized bus level controllers which simultaneously manage the energy consumption of each individual bus. Our method demonstrates good battery energy savings and regularity performances when compared to a classical holding strategy.
Paper VI171-07.21
PDF · Video · An Internal Model Approach to Robust Current Control of IPMSM Drives with Respect to Unknown and Varying Inductances
Metzkow, René	Brandenburgische Technische Universität Cottbus-Senftenberg
Rueda-Escobedo, Juan G.	Brandenburg University of Technology Cottbus-Senftenberg
Doering, Daniela	Brandenburg University of Technology Cottbus - Senftenberg
Schiffer, Johannes	Brandenburg University of Technology
Keywords: Adaptive and robust control of automotive systems, Hybrid and alternative drive vehicles, Engine modelling and control Abstract: Interior permanent magnet synchronous machines (IPMSMs) are well-suited for high-performance applications, such as traction drives in hybrid and electric vehicles. Yet a major challenge to fully exploit their potential is the fact that their self and cross-coupling inductances vary significantly across the operation range. In addition, this variation is difficult to characterize and complicates the design of provably stabilizing and robust controls. Motivated by this, by using an IPMSM model with current dependant inductances together with the internal model principle, a nonlinear current control scheme is derived that renders the equilibrium point of the closed-loop system exponentially stable. Both the control and the stability result only require the knowledge of an upper bound of the gradient of the inductances as well as lower and upper bounds on the inductance values themselves, while their actual evolution can be completely unknown. This is a major advantage compared to existing (PI-based) current control approaches, as it makes costly practices to determine the inductance variations unnecessary. The efficacy of the proposed control scheme is demonstrated in a simulation example.
Paper VI171-07.22
PDF · Video · Model Predictive Controller Development for Controlling Actuators of Automated Manual Transmission
Lakhera, Siddharth	Indian Institute of Technology, Kharagpur
Sengupta, Somnath	IIT Kharargpur
Singh, Vimlendu	Indian Institute of Technology Kharagpur
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Hybrid and alternative drive vehicles, Control architectures in automotive control Abstract: Automotive transmission technology is evolving rapidly to match up with the growing need of increased power transfer efficiency, tractive demands and powertrain electrification. In this, Automated Manual Transmission (AMT) systems have made their way to the global market as popular choice by automotive industry. AMT applications have grown substantially in Hybrid Electric Vehicles, where hybrid controller decides optimum gear ratio and the gearshift needs to be automated. Advanced model-based predictive techniques for AMT supervisory controllers have allowed complex clutch control, gear shift control and optimal gear-ratio selection. However, the AMT’s lower level actuator control is usually done with the help of simple linear controllers like PID. This work aims to evaluate the performance of the AMT system when using a Model Predictive Controller (MPC) for controlling generic AMT actuators. This generic AMT and its control system are modeled and implemented within a HEV vehicle closed loop system model. For gearshift control problem, MPC controller is developed and implemented as actuator controller within the AMT control system framework. A simple PID based actuator controller is also developed to serve as benchmark. The comparative performance of the developed MPC and PID based controllers are evaluated by simulating them during gear-shift operation under a realistic drive cycle. Finally, suitability of MPC for the AMT actuator controller is illustrated through the obtained results.
Paper VI171-07.23
PDF · Video · Closed-Loop Battery Aging Management for Electric Vehicles
Pozzato, Gabriele	Politecnico Di Milano
Corno, Matteo	Politecnico Di Milano
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Hybrid and alternative drive vehicles, Nonlinear and optimal automotive control Abstract: In this work, a closed-loop battery aging management strategy for electric vehicles is proposed. The aging management strategy, following the model predictive control rationale, optimizes a cost function accounting for aging and vehicle performance online. The proposed formulation is based on a closed-loop term which aims at tracking a user defined aging profile. A thorough simulation study validates the approach and verifies its robustness against model uncertainties and anomalous aging phenomena.
Paper VI171-07.24
PDF · Video · Energy Management of Heavy-Duty Fuel Cell Electric Vehicles: Model Predictive Control for Fuel Consumption and Lifetime Optimization
Ferrara, Alessandro	TU Wien
Okoli, Michael	TU Wien
Jakubek, Stefan M.	Technical Univ. of Vienna/Austria
Hametner, Christoph	Vienna University of Technology
Keywords: Nonlinear and optimal automotive control, Control architectures in automotive control, Fuel cells for Automotive Applications Abstract: This paper investigates the application of a simple but effective model predictive control concept for the fuel consumption and system lifetime optimization of a heavy-duty fuel cell electric vehicle. Energy management strategies primarily help extend the fuel cell lifetime by limiting shutdowns, transients and high-power operations to avoid detrimental conditions. In this framework, the proposed online control scheme determines a significant reduction of the average fuel cell power change rate and a small fuel consumption increment with respect to the control law that minimizes the fuel consumption, computed offline through the Pontryagin’s minimum principle. These results refer to the real-world driving mission of a road freight vehicle, including the elevation gradient of the road, which highly affects the load request in downhill and uphill sections. However, this preliminary study does not include a speed prediction model, but it assumes that the speed is known without uncertainties over a relatively short time horizon.
Paper VI171-07.25
PDF · Video · On Strict Dissipativity of Systems Modeled by Convex Difference Inclusions: Theory and Application to Hybrid Electric Vehicles
Pozzato, Gabriele	Politecnico Di Milano
Muller, Matthias A.	Leibniz University Hannover
Formentin, Simone	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Nonlinear and optimal automotive control, Automatic control, optimization, real-time operations in transportation Abstract: In this paper, strict dissipativity conditions are derived for the optimal steady-state operation of dynamical systems described by convex difference inclusions. This result guarantees convergence to a neighborhood of the optimal steady-state for the closed-loop system resulting from the application of economic model predictive control schemes. The validity of the results is shown in a simulation environment considering the problem of the optimal power split in hybrid electric vehicles.
Paper VI171-07.26
PDF · Video · Traffic-Aware Vehicle Energy Management Strategies Via Scenario-Based Optimization
Wulf Ribelles, L.Alfredo	Université D’Orléans
Padilla, G. P. (Paul)	Eindhoven University of Technology
Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Keywords: Nonlinear and optimal automotive control, Hybrid and alternative drive vehicles, Mission planning and decision making Abstract: This paper explores the development of traffic-aware energy management strategies by means of scenario-based optimization. This is motivated by that fact that real driving conditions are subject to uncertainty, thereby making the real-time optimization of the energy consumption of a vehicle to be a challenging problem. In order to deal with this situation, we employ the current framework of complete vehicle energy management in a receding horizon fashion, in which we consider random constraints representing realizations of exogenous signals, i.e., the uncertain driving conditions. Additionally, we study three methods for velocity prediction in energy management strategies, i.e., a method based on (average) traffic information, a method based on Gaussian process regression, and a method that combines both. The proposed strategy is tested with real traffic data using a case study of the power split in a series-hybrid electric vehicle. The behavior of the battery, control inputs and fuel consumption generated with the resulting strategies are compared against the optimal solution from an offline benchmark and a situation with perfect prediction of the future, For the considered case, the use of a Gaussian process regression and the traffic speed achieves near optimal fuel consumption.
Paper VI171-07.27
PDF · Video · Data-Driven Energy Management Strategy for Plug-In Hybrid Electric Vehicles with Real-World Trip Information
Choi, Yongkeun	University of California, Berkeley
Guanetti, Jacopo	University of California Berkeley
Moura, Scott	UC Berkeley
Borrelli, Francesco	University of California
Keywords: Nonlinear and optimal automotive control, Intelligent driver aids, Hybrid and alternative drive vehicles Abstract: This paper presents a data-driven supervisory energy management strategy (EMS) for plug-in hybrid electric vehicles which leverages Vehicle-to-Cloud connectivity to increase energy efficiency by learning control policies from completed trips. The proposed EMS consists of two layers, a cloud layer and an on-board layer. The cloud layer has two main tasks: the first task is to learn EMS policy parameters from historical trip data, and the second task is to provide the policy parameters along a certain route requested from the vehicle. The on-board layer receives the learned policy parameters from the cloud layer and computes a real-time solution to the powertrain energy management problem, using a model predictive control scheme. The proposed EMS is evaluated on more than 3000 miles (48 independent driving cycles) of real-world trip data, collected along three commuting routes in California. For the routes, the proposed algorithm shows 3.3%, 7.3%, and 6.5% improvement in average MPGe when compared to a baseline EMS.
Paper VI171-07.28
PDF · Video · Lithium Battery Model Development and Application in Simulation of the Energy Consumption of Electric Bus Running
Xie, Feng	IFAK (Institute of Automation and Communication, Magdeburg, Germ
Czogalla, Olaf	Institute of Automation and Communication IFAK Magdeburg
Naumann, Sebastian	Institut F. Automation U. Kommunikation
Keywords: Simulation, Modeling and simulation of transportation systems Abstract: Battery electric buses take an increasingly larger market share and attract much attention from bus fleet operators to undercut urban emissions limits. But meanwhile it also becomes a challenge to operators to determine the required battery capacity to be sufficient for the specific transport operations. The deployment planning includes to select appropriate bus model specifications, battery characteristics, charging parameters, timetable schedules and further dependencies under the aspect of ownership costs. Regarding battery characteristics however, most electrochemical battery models focus more on the internal structure, which have a worse compatibility on a system level. This paper aims to build up a lithium-battery model based on the third-Thevenin equivalent circuit, considering both complexity and accuracy. Firstly, this battery model is implemented with lookup tables to represent the values of each circuit component, which results in a mean error of 1.98 mV or 0.06%, compared with the original measurement data. Then a general control model of electric vehicles is introduced to cooperate with this battery model in a system, combined by the current flowing between these two models. Finally a simulation is proceeded, employing the real data from Solaris® Urbino 12 Electric Bus, which provides a reliable SOC estimation for the full day operation.
Paper VI171-07.29
PDF · Video · An Artificial Potential Function for Battery Life Optimization in Car-Following System
Liu, Bo	Central South University
Yang, Yingze	Central South University
Liao, Hongtao	Central South University
Zhang, Rui	Central South University
Chen, Bin	Central South University
Gao, Kai	Changsha University of Science & Technology
Zhou, Feng	Changsha University of Science & Technology
Liu, Weirong	Central South University
Huang, Zhiwu	Central South University
Peng, Jun	Central South University
Keywords: Automatic control, optimization, real-time operations in transportation, Nonlinear and optimal automotive control, Modeling, supervision, control and diagnosis of automotive systems Abstract: For a pure electric car-following system, if the auto-following vehicle acts in an aggressive following manner, battery life fades evidently, since overcharging or over-discharging damage the cell irreversibly. In this regard, this paper proposed an artificial potential function for battery life extension. First, the electric vehicle physical model and an empirical lithium-ion battery model have established form real-world data measurement. The physical layer models car-following dynamics and the battery model describes the energy consumption. Second, with the perceptive of the battery life in a loss-minimal, optimize manner, the controller mathematically computes the optimal acceleration/deceleration value with the Lagrange multipliers method. Then using the Matlab curve fitting tool toolbox to fusion optimal acceleration data with potential function, thus the acceleration consistent rule is realized through the consistency of an artificial potential function. Finally, the control strategy is validated through a simulation test in Matlab/Simulink, and the results show that the proposed control strategy extends battery life while keeping good tracking ability.
Paper VI171-07.30
PDF · Video · An Eco-Routing Algorithm for HEVs under Traffic Conditions
Le Rhun, Arthur	Inria Saclay and CMAP Ecole Polytechnique
Bonnans, Joseph Frédéric	Inria-Saclay and CMAP
De Nunzio, Giovanni	IFP Energies Nouvelles
Leroy, Thomas	IFP Energies Nouvelles
Martinon, Pierre	Inria
Keywords: Intelligent driver aids, Hybrid and alternative drive vehicles, Engine modelling and control Abstract: In a previous work, a bi-level optimization approach was presented for the energy management of Hybrid Electric Vehicles (HEVs), using a statistical model for traffic conditions. The present work is an extension of this framework to the eco-routing problem. The optimal trajectory is computed as the shortest path on a weighted graph whose nodes are (position, state of charge) pairs for the vehicle. The edge costs are provided by cost maps from an offline optimization at the lower level of small road segments. The error due to the discretization of the state of charge is proven to be linear if the cost maps are Lipschitz. The classical A* algorithm is used to solve the problem, with a heuristic based on a lower bound of the energy needed to complete the travel. The eco-routing method is compared to the fastest-path strategy by numerical simulations on a simple synthetic road network.

VI171-08
Modeling, Supervision, and Control of Automotive Systems	Regular Session
Chair: Hohmann, Soeren	KIT
Co-Chair: Abel, Dirk	RWTH-Aachen University
Paper VI171-08.1
PDF · Video · Coordinated AFS and DYC for Autonomous Vehicle Steerability and Stability Enhancement
Khelladi, Faïza Enfel	Université De Haute Alsace
Orjuela, Rodolfo	IRIMAS
Basset, Michel	Université De Haute-Alsace
Keywords: Control architectures in automotive control, Modeling, supervision, control and diagnosis of automotive systems, Vehicle dynamic systems Abstract: In this paper, the hierarchical yaw stability control architecture is introduced. This approach coordinates two controllers, namely the steerability and the stability controllers improving respectively the handling performance and the lateral stability. Thus, each controller has a control domain, a control objective, and its own active system. The coordination of these controllers is made by means of a supervisor that gives activation functions to prioritize each controller according to the detected situation whether it is critical or not. Using the same controllers, two supervisors are investigated. On one hand, the sideslip angle - sideslip rate phase plan, and the simplified yaw rate - sideslip angle phase plan on the other hand. Finally, simulation results are given to show the effectiveness of the proposed approach.
Paper VI171-08.2
PDF · Video · Real-Time Classification of Road Type and Condition in Passenger Vehicles
Beilfuss, Tim	Leibniz University Hannover, Institute of Mechatronic Systems
Kortmann, Karl-Philipp	Leibniz University Hannover
Wielitzka, Mark	Leibniz University Hanover
Hansen, Christian	Leibniz University Hannover, Institute of Mechatronic Systems
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Intelligent driver aids, Automotive sensors and actuators, Map building Abstract: Modern vehicles are equipped with numerous sensors and hence offer an increasing degree of environmental perception. In this work, a method is presented that is able to classify different road types and their conditions based on standard vehicle sensors. Therefore, training and validation data on two routes in urban traffic and on federal highways was gathered using a Volkswagen Golf GTE Plug-In Hybrid. The method uses features based on both frequency and time domain extended with a physical vehicle sub-model. For the classification a decision tree model is trained offline and implemented for online use on target hardware commonly used in modern vehicles. A Bayesian and Markov based filter is used to smooth the output and increase the accuracy of the classification. Since the method is based on sensors that are available in modern vehicles, there is no need for additional hardware, reducing the effort required for implementation. Results show promising classification performance, especially for classifying cobblestone. The three classes of good, medium and bad asphalt labeled relatively precise despite very similar characteristics. Possible applications of the approach could be to adapt vehicles suspension and driving dynamics, to parameterize driver assistance systems, or to update road maps according to their current condition.
Paper VI171-08.3
PDF · Video · Set-Membership Switched Observers Based on Interval Characterization of the Estimation Error
Ifqir, Sara	IBISC Laboratory, Evry Val d'Essonne University
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Ichalal, Dalil	IBISC-Lab, Evry Val d'Essonne University
Ait Oufroukh, Naima	IBISC
Mammar, Said	University Evry Val D'Essonne
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Automatic control, optimization, real-time operations in transportation, Simulation Abstract: This paper presents a new set-membership estimation methodology for uncertain switched LPV discrete-time systems subject to unknown inputs, unmeasurable time-varying parameters and measurement noise. The proposed approach provides a guaranteed interval that is constructed as the sum of punctual state estimation and its corresponding estimation error limits. First, a punctual switched unknown input observer, robust against unknown inputs and time-varying uncertainties, is constructed. The proposed switched observer design is based on the solution of an optimization problem in terms of LMIs. Then, an outer-approximation of the enclosure set of state estimation error is computed using the admissible bounds of state and uncertainties. Application to vehicle state estimation is provided to show the design procedure and the flexibility of the proposed scheme. Comparison to real data demonstrates the accuracy and effectiveness of the obtained results.
Paper VI171-08.4
PDF · Video · Highway Entrance Merging Assistant for Minimal Traffic Disturbance
Assadi, Amin	Johannes Kepler University Linz
Meier, Florian	Johannes Kepler University Linz
del Re, Luigi	Johannes Kepler University
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Autonomous Vehicles, Motion control Abstract: Merging of traffic flows is a potentially dangerous situation frequently associated with important impacts on traffic fluidity. This paper examines the possibility of improving merging from an entrance of a highway by adapting the speed of the incoming vehicles reducing as much as possible the need for actions by the drivers on the main lane. Multi-layer traffic models are used to describe and simulate the interactions between drivers. A predictive controller is then designed to minimize the probability that the vehicles on the incoming roads need to change the speed or the lane. The proposed approach is shown to strongly enhance traffic fluidity for a wide range of traffic densities on the main flow without compromising safety.
Paper VI171-08.5
PDF · Video · Experimental Verification of a Control System for Autonomous Navigation
Szűcs, Benedek	Institute for Computer Science and Control
Kisari, Adam	Institute for Computer Science and Control
Kőrös, Péter	Research Center of Vehicle Industry, Széchenyi István University
Pup, Dániel	Research Center of Vehicle Industry, Széchenyi István University
Rödönyi, Gábor	Institute for Computer Science and Control
Soumelidis, Alexandros	Institute for Computer Science and Control
Bokor, Jozsef	Hungarian Academy of Sciences
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Control architectures in automotive control, Autonomous Vehicles Abstract: A flexible architecture is developed with the purpose of supporting education and research on the field of autonomous vehicles. A pure electric vehicle is equipped with on-board computational units, sensors and actuator interfaces. This paper presents the current status of the control system and its validation by means of navigation experiments. With the cascade control architecture, problems of actuator dead-zone, sensor offset errors, path tracking and redesign for obstacle avoidance are addressed.
Paper VI171-08.6
PDF · Video · Trajectory Optimization for Falsification: A Case Study of Vehicle Rollover Test Generation Based on Black-Box Models
Tang, Sunbochen	University of Michigan
Li, Nan	University of Michigan
Kolmanovsky, Ilya V.	University of Michigan
Girard, Anouck	University of Michigan, Ann Arbor
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Safety Abstract: In this paper, we consider optimization of trajectories for automotive vehicle rollover testing. In particular, worst-case trajectories that are most likely to cause rollover accidents are determined through trajectory optimization. Our approach combines online local-model identification and gradient-based input update, and can be applied to black-box type models, e.g., a high-fidelity vehicle dynamics model given as a simulation code and not as an explicit set of equations. With our approach, a library of worst-case trajectories corresponding to different operating conditions (e.g., vehicle mass, road surface conditions, etc.) can be constructed and subsequently used in hardware tests.
Paper VI171-08.7
PDF · Video · Optimal Sliding Mode Control Method for Active Suspension Control
Bayar, Kerem	Middle East Technical University
Sadeghi Khaneghah, Farshid	Middle East Technical University
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control, Vehicle dynamic systems Abstract: A non-linear quarter car vehicle model is used in this study, for developing an active suspension control algorithm. The control method used is optimal sliding mode control, along with feedback linearization for compensating the nonlinear aspects of the plant. In addition to the work in recent literature that applies these control methods, estimation of the static suspension deflection; i.e. vehicle sprung mass is performed. Through simulation results, it is shown that correct information of vehicle sprung mass, compared to taking it as a constant parameter in control design, improves the performance of the controller. This in turn, reduces the sprung mass acceleration level, and enhances ride comfort.
Paper VI171-08.8
PDF · Video · Intrinsic Differences between Backward and Forward Vehicle Simulation Models
Pettersson, Pär	Chalmers University of Technology
Jacobson, Bengt	Chalmers University of Technology
Bruzelius, Fredrik	Chalmers Univ of Technology
Johannesson, Pär	RISE Research Institutes of Sweden
Fast, Lars	RISE Research Institutes of Sweden
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Simulation, General automobile/road-environment strategies Abstract: Two common methods for predicting the energy usage in vehicles through mathematical simulation, the `backward' and the `forward' schemes, are discussed and compared in terms of the longitudinal vehicle behaviour they predict. In the backward scheme, the input driving cycle is initially assumed to be followed perfectly and therefore the vehicle speed is not a dynamic state. In the forward scheme, a driver model controls the vehicle in an attempt to follow the input driving cycle, and the vehicle speed is intrinsically a dynamic state. A theoretical study is made with a simple mathematical vehicle model, where it is shown that the two methods neither predict the same expected energy use nor energy variation. Next, the simulation model that is used for the co rating of heavy-duty trucks in Europe, VECTO, is used as an example of the backward method, and an equivalent implementation in a forward scheme is attempted. Two numerical experiments are made with these models: a detailed study of the longitudinal vehicle behaviour on a reference mission; and a study of the predicted co emissions on a family of stochastically generated missions. The conclusion is that the backward method is easier to use but the forward method has a greater potential to predict realistic behaviour.
Paper VI171-08.9
PDF · Video · Data-Driven On-Line Load Monitoring in Garbage Trucks
Breschi, Valentina	Politecnico Di Milano
Formentin, Simone	Politecnico Di Milano
Todeschini, Davide	Politecnico Di Milano
Cologni, Alberto Luigi	Università Degli Studi Di Bergamo
Savaresi, Sergio	Politecnico Di Milano
Keywords: Modeling, supervision, control and diagnosis of automotive systems, System integration and supervision Abstract: The payload of garbage trucks may vary substantially over the time, affecting both the vehicle performance and driving safety. Information on the load in real-time could thus play a key role for monitoring and diagnostics. Unfortunately, physical sensors directly measuring the vehicle mass are usually too costly for commercial trucks, while the correlation between consecutive values of the load is not considered by most of existing approaches for mass estimation. Since this correlation characterizes load variations in garbage trucks, this paper proposes an ad-hoc approach for payload estimation, which relies on inertial sensors only. To minimize the tuning effort, we introduce a strategy to automatically select the key tunable parameters of the estimator. The effectiveness of the proposed approach is demonstrated on experimental data collected on a real truck.
Paper VI171-08.10
PDF · Video · Neural Observer for Nonlinear State and Input Estimation in a Truck-Semitrailer Combination
Jahn, Tim	Leibniz Universität Hannover
Ziaukas, Zygimantas	Leibniz Universität Hannover
Kobler, Jan-Philipp	BPW Bergische Achsen KG
Wielitzka, Mark	Leibniz University Hanover
Ortmaier, Tobias	Gottfried Wilhelm Leibniz Universität Hannover
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Vehicle dynamic systems, Automotive system identification and modelling Abstract: Driver assistance systems have become an indispensable part of today’s vehicle technology. Especially in the commercial vehicle sector, the challenges in obtaining information increase with rising system complexity. Compared to trucks, trailers for commercial vehicle combinations are sparsely equipped with electronic components. This leads to difficulties in implementation of intelligent systems for the trailer as necessary information is not provided. Reasons for this can be an insufficient sensor equipment due to uneconomical costs or a missing communication channel between the two vehicle units, preventing the transmission of required truck related information to the trailer. A possible model-based method to obtain unmeasured states is the Extended Kalman Filter. However, this approach requires elaborate preliminary work steps of high complexity and a sophisticated domain knowledge. Alternatively, this paper proposes the applicability of Neural Networks for estimating the required state and input variables, namely the articulation angle and the truck’s steering angle. Two different network types are used: the Feedforward Neural Network and the Nonlinear Autoregressive Exogenous Neural Network. The measured input variables for the networks, in accordance with the inputs of the Extended Kalman Filter in a previous publication, are merely trailer yaw rate and longitudinal speed. In conclusion, a comparison between the results of the Neural Networks and those of the Extended Kalman Filter is drawn.
Paper VI171-08.11
PDF · Video · Semi-Active Suspension Control Design Via Bayesian Optimization
Savaia, Gianluca	Politecnico Di Milano
Formentin, Simone	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Vehicle dynamic systems, Information processing and decision support Abstract: The fine tuning of semi-active suspension control systems for road vehicles is usually a costly and burdensome task, needing control expertise and many hours of professional driving. In this paper, we propose a data-driven tuning method enabling the automatic calibration of the parameters of the suspension controller using a small number of experiments and exploiting Bayesian Optimization tools. The effectiveness of the proposed approach is validated on a commercial multi-body simulator. As a side contribution, the approach is shown to be robust with respect to variations of the testing conditions.
Paper VI171-08.12
PDF · Video · Tracking a Reference Damping Force in a Magneto-Rheological Damper for Automotive Applications
Savaia, Gianluca	Politecnico Di Milano
Panzani, Giulio	Politecnico Di Milano
Corno, Matteo	Politecnico Di Milano
Sinigaglia, Andrea	Altran
Savaresi, Sergio	Politecnico Di Milano
Keywords: Automotive sensors and actuators, Modeling, supervision, control and diagnosis of automotive systems, Control architectures in automotive control Abstract: Magneto-rheological dampers are gaining a lot of attention in the automotive industry and they show many advantages over their hydraulic counterpart. However, they are characterised by a highly nonlinear damping characteristics which may not be desired. In this paper, the authors present a control scheme which gives the possibility to track any reference damping force in a magneto-rheological damper. The main assumption of this research is the actual force exerted by the damper is not available for measurement, since such a sensor could not be installed onto a commercial vehicle. The control of this device is particularly challenging because of a singularity point in the origin which has significant repercussions on performance if not considered. The authors propose a novel closed-loop technique which is compared against an industrial solution based on an open-loop scheme, proving the former to be superior via a qualitative and quantitative analysis.

VI171-09
Nonlinear and Optimal Control for Automotive Systems	Regular Session
Chair: Sename, Olivier	Grenoble Institute of Technology / GIPSA-Lab
Co-Chair: Zaccarian, Luca	LAAS-CNRS and University of Trento
Paper VI171-09.1
PDF · Video · NMPC for Racing Using a Singularity-Free Path-Parametric Model with Obstacle Avoidance
Kloeser, Daniel	University of Freiburg
Schoels, Tobias	University of Freiburg
Sartor, Tommaso	University of Freiburg
Zanelli, Andrea	University of Freiburg
Frison, Gianluca	University of Freiburg
Diehl, Moritz	University of Freiburg
Keywords: Nonlinear and optimal automotive control Abstract: This work presents the real-time control of 1:43 scale autonomous race cars using nonlinear model predictive control based on a singularity-free prediction model. This model allows the car to drive at both low and high speeds and in stop-and-go maneuvers. Additional constraints are imposed in the optimal control problem to ensure the validity of the model assumptions. Moreover, the control scheme is capable of avoiding obstacles online. The experimental results show that the proposed method converges to nearly time-optimal behavior by maximizing the progress on the track and achieves competitive lap time results.
Paper VI171-09.2
PDF · Video · Contingent Nonlinear Model Predictive Control for Collision Imminent Steering in Uncertain Environments
Dallas, James	University of Michigan
Wurts, John	University of Michigan
Stein, Jeffrey L.	Univ. of Michigan
Ersal, Tulga	University of Michigan
Keywords: Nonlinear and optimal automotive control, Adaptive and robust control of automotive systems, Automotive system identification and modelling Abstract: A novel uncertainty based contingent model predictive control algorithm is presented for autonomous vehicles operating in uncertain environments. Nominal model predictive control relies on a model to predict future states over a horizon and hence requires accurate models and parameterization. In application, environmental conditions and parameters may be unknown or varying, posing robustness issues for model predictive control. This work presents a new selectively robust adaptive model predictive control algorithm that is applied to collision imminent steering controllers for automotive safety. In this context, uncertainties in the road coefficient of friction are estimated using unscented Kalman filtering and the controller is updated based upon the estimated uncertainties. The utility of the uncertainty based controller is demonstrated in a collision imminent steering scenario and compared to nominal deterministic model predictive control, as well as a baseline adaptive scheme. The results suggest the uncertainty based controller can improve the robustness of model predictive control by nearly 50% for deterministic model predictive control and over 10% for the baseline adaptive scheme.
Paper VI171-09.3
PDF · Video · Nonconvex Consensus ADMM for Cooperative Lane Change Maneuvers of Connected Automated Vehicles
Katriniok, Alexander	Ford Research & Innovation Center (RIC)
Keywords: Nonlinear and optimal automotive control, Automatic control, optimization, real-time operations in transportation, Multi-vehicle systems Abstract: Connected and automated vehicles (CAVs) offer huge potential to improve the performance of automated vehicles (AVs) without communication capabilities, especially in situations when the vehicles (or agents) need to be cooperative to accomplish their maneuver. Lane change maneuvers in dense traffic, e.g., are very challenging for non-connected AVs. To alleviate this problem, we propose a holistic distributed lane change control scheme for CAVs which relies on vehicle-to-vehicle communication. The originally centralized optimal control problem is embedded into a consensus-based Alternating Direction Method of Multipliers framework to solve it in a distributed receding horizon fashion. Although agent dynamics render the underlying optimal control problem nonconvex, we propose a problem reformulation that allows to derive convergence guarantees. In the distributed setting, every agent needs to solve a nonlinear program (NLP) locally. To obtain a real-time solution of the local NLPs, we utilize the optimization engine OpEn which implements the proximal averaged Newton method for optimal control (PANOC). Simulation results prove the efficacy and real-time capability of our approach.
Paper VI171-09.4
PDF · Video · Safety-Extended Explicit MPC for Autonomous Truck Platooning on Varying Road Conditions
Schirrer, Alexander	Vienna University of Technology
HaniŠ, TomáŠ	CTU in Prague, Faculty of ElectricalEngineering, Departmentfor Co
Klauco, Martin	Slovak University of Technology in Bratislava
Thormann, Sebastian	Technische Universität Wien
Hromcik, Martin	Czech Technical Univ
Jakubek, Stefan M.	Technical Univ. of Vienna/Austria
Keywords: Nonlinear and optimal automotive control, Control architectures in automotive control, Vehicle dynamic systems Abstract: Automotive platooning can significantly improve traffic safety and efficiency, but many control challenges need to be solved to function properly under realistic driving conditions. This paper proposes a novel multi-rate explicit model-predictive controller (eMPC) for safe autonomous distributed vehicle platooning in varying road friction conditions. A safety-augmented distributed predictive control formulation ensures safe vehicle spacing versus emergency braking of preceding vehicles given current friction estimates. This complex control problem is carefully formulated into an efficiently parametrized optimization problem realized as eMPC. The resulting platoon shows excellent performance in a complex vehicle dynamics co-simulation validation with low communication and computation demands.
Paper VI171-09.5
PDF · Video · Co-Design of a Continuously Variable Transmission Using Sequential Quadratic Programming-Based Control Optimization
Fahdzyana, Chyannie	Eindhoven University of Technology
Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Hofman, Theo	Technische Universiteit Eindhoven
Keywords: Nonlinear and optimal automotive control, Control of systems in vehicles Abstract: For systems with nonlinear dynamics, Dynamic Programming for control is commonly considered in the framework of integrated plant and control system design. Despite its popularity, this control strategy can run into some computational issues as the performance is dependent on the state and input discretization. In this paper, we propose a Sequential Quadratic Programming-based control optimization strategy for integrated system design, where both the plant and control are optimized for the case study of a continuously variable transmission. The proposed plant and control design problem will be solved using a nested strategy.
Paper VI171-09.6
PDF · Video · Modelling Human Driving Behavior for Multi-Mode Constrained Model Predictive Control of Mixed Traffic at Unsignalized Intersections
Bethge, Johanna	Otto-von-Guericke-Universität Magdeburg
Morabito, Bruno	Otto-von-Guericke-Universität Magdeburg
Rewald, Hannes	Otto-von-Guericke-Universität Magdeburg
Ahsan, Adil	Otto-von-Guericke-Universität Magdeburg
Sorgatz, Stephan	Volkswagen Aktiengesellschaft
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Nonlinear and optimal automotive control, Learning and adaptation in autonomous vehicles, Trajectory Tracking and Path Following Abstract: Safety of autonomous cars at intersections with mixed traffic, i.e. including human drivers and autonomous cars, is still challenging. In this paper, we propose a unifying approach fusing a learning algorithm, i.e. neural network regression to model the human drivers behaviour, and model predictive control with multi-mode dynamic constraints to control the ego vehicle. As a simulation example, we consider a single autonomous car on an unsignalized intersection, which gives right-of-way to a human-driven vehicle. We show how human driving behavior can be modeled based on real data and implemented in the proposed predictive control approach by dynamically changing the constraints of the optimization problem.
Paper VI171-09.7
PDF · Video · An LMI-Based Approach for the Control of Semi-Active Magnetorheological Suspensions
Begnis, Ruben	Università Degli Studi Di Trento
Panzani, Giulio	Politecnico Di Milano
Brentari, Mirko	University of Trento
Zaccarian, Luca	LAAS-CNRS and University of Trento
Keywords: Nonlinear and optimal automotive control, Vehicle dynamic systems, Automotive sensors and actuators Abstract: We address modeling and control of semi-active suspensions based on magnetorheological (MR) fluids. We first introduce a saturation-based model of the underlying nonlinear phenomena, and combine the MR suspension with a quarter car model whose parameters resemble a SUV-like vehicle. Then we present simulation results to test the passenger comfort arising from the passive configuration (namely holding the input constant over the whole simulation) and the use of the Skyhook controller (which is adapted from its typical use in electrohydraulic suspensions). Finally, we propose LMI-based control designs exploiting an approximated model and typical generalized sector conditions for saturation nonlinearities. The simulation results show the advantages of the proposed design.
Paper VI171-09.8
PDF · Video · GPU Based Stochastic Parameterized NMPC Scheme for Control of Semi-Active Suspension System for Half Car Vehicle
Murali Madhavan Rathai, Karthik	GIPSA Lab - University of Grenoble, Alpes, Grenoble, France
Alamir, Mazen	Gipsa-Lab (CNRS-University of Grenoble)
Sename, Olivier	Grenoble Institute of Technology / GIPSA-Lab
Keywords: Nonlinear and optimal automotive control, Vehicle dynamic systems, Control architectures in automotive control Abstract: Control of complex systems with inherent randomness in process dynamics poses a serious concern for control engineers, especially in situations where performance and constraint satisfaction are highly demanded. In this paper, we propose a real time (RT) scenario based stochastic parameterized NMPC (SS-pNMPC) scheme for control of semi-active (SA) system for a half car vehicle. The method utilizes graphic processing unit (GPU) to generate several RT scenarios of the random road profile for each parameterized input and through Monte-Carlo (MC) simulations, the expected objective function along with a probabilistic constraint violation certificate are numerically obtained. The optimal input is elicited by finding the input either with minimum expected objective or with the lowest probabilistic constraint violation certificate. The method was implemented on NVIDIA Jetson embedded boards and also, tested in MATLAB/Simulink environment for different ISO road profiles and the simulation results exhibits better performance of the proposed method in comparison to passive systems.
Paper VI171-09.9
PDF · Video · Real-Time Optimized Model Predictive Control of an Active Roll Stabilization System with Actuator Limitations
Nareyko, Georgi	Dr. Ing. H.c. F. Porsche AG
Biemelt, Patrick	University of Paderborn
Traechtler, Ansgar	University of Paderborn
Keywords: Vehicle dynamic systems, Nonlinear and optimal automotive control, Automotive sensors and actuators Abstract: Active roll stabilization systems are used to improve both the ride dynamics and ride comfort. For that, the measureable information about road disturbance should be used to calculate the control variable for the actuators at the front and rear axle. Even without previewed disturbance information the whole car dynamics can be modelled and provide future states of the controlled system which consequently can be regarded in the calculation in advance. By the framework of a Model Predictive Control, the actuator limitations can be included. Additionally, the movement of the car body and each wheel is regarded, so that an optimal allocation of the control variables on both actuators takes place. With both aspects, namely the actuator limitations and the optimization itself, a high potential for ride comfort improvement is generated.
Paper VI171-09.10
PDF · Video · Practical Method to Complete Learning Model Predictive Control with Generalization Capability
Török, Ferenc	Technische Universität München
Peni, Tamas	Institute for Computer Science and Control (SZTAKI)
Keywords: Autonomous Vehicles, Learning and adaptation in autonomous vehicles, Nonlinear and optimal automotive control Abstract: The paper presents a practical method to complete Learning Model Predictive Control (LMPC) with generalization capability. LMPC has been developed by F. Borrelli and his co-authors for systems performing iterative tasks. The method is based on saving the state trajectories of successful runs and using this database to improve the control performance in the future iterations. When the controller faces a new task, the database is cleared and the learning phase starts over. This paper addresses the question of how a general knowledge base can be built to warm start the learning process. As a potential solution, a practical method is proposed. The algorithm is tailored specifically to the autonomous racing application, but the concept can be extended to a wider class of control problems. The procedure includes the construction of special teaching tracks, on which the trajectory database is generated and a multi-step migration procedure for transferring the learned trajectories onto any new track. The efficiency of the method is demonstrated by numerical simulations.

VI171-10
Vehicle Dynamics and Control	Regular Session
Chair: Eriksson, Lars	Linköping University
Co-Chair: Di Gennaro, Stefano	Univ. Di L'Aquila
Paper VI171-10.1
PDF · Video · Sum of Squares Approach for Ground Vehicle Lateral Control under Tire Saturation Forces
Ribeiro, Alexandre Monteiro	Unicamp
Fioravanti, André R.	Unicamp
Moutinho, Alexandra	IDMEC/LAETA, Instituto Superior Técnico, Universidade De Lisboa
Paiva, Ely	UNICAMP
Keywords: Nonlinear and optimal automotive control, Vehicle dynamic systems Abstract: This work presents the stability analysis and design of a lateral controller for a nonlinear ground vehicle applying the concept of polynomial sum of squares relaxations. The system is approximated by a polynomial vector field that describes the lateral vehicle dynamics. The resulting polynomial system falls on a class of non-affine in input system, which makes the control synthesis more involved. This issue is circumvented by an input-affine approximation, simplifying the stability analysis and the design procedure of a polynomial state-feedback controller able to enlarge the region of attraction (RoA). We also compare the estimated region of attraction with the standard LQR optimal controller.
Paper VI171-10.2
PDF · Video · Test Methodology for the Vehicle-Tire Handling Performance Evaluation: Objectification of Driver's Subjective Assessment
Pagliarecci, Nico	Goodyear Dunlop Luxembourg, Universite De Haute Alsace
Zimmer, Francois	Goodyear/Dunlop Luxemburg
Birouche, Abderazik	Université of Haute Alsace
Basset, Michel	Université De Haute-Alsace
Keywords: Vehicle dynamic systems Abstract: In the context of vehicle-tire handling performance evaluation, subjective closed loop and objective open loop vehicle dynamics tests have been carried out in linear domain to get insights on the driver's testing strategy. Experimental tests' data analysis showed that vehicle responses have a big effect on the driver's steering input and, therefore, on the subjective rating. In this paper, a clustering method developed by the test driver is used to group, categorize and differentiate specific vehicle-tire handling behaviors. This method allowed to study the correlation between objective measurements and subjective evaluation of the vehicle response. Data analysis highlighted objective metrics that can explain the variance of the driver's subjective rating. The handling performance classification developed by the driver can be retrieved with the objective metrics previously mentioned.
Paper VI171-10.3
PDF · Video · Experimental Validation of a Hierarchical Suspension Control Via MR Damper
Savaia, Gianluca	Politecnico Di Milano
Corno, Matteo	Politecnico Di Milano
Panzani, Giulio	Politecnico Di Milano
Sinigaglia, Andrea	Automobili Lamborghini
Savaresi, Sergio	Politecnico Di Milano
Keywords: Vehicle dynamic systems, Control architectures in automotive control, Automotive sensors and actuators Abstract: The suspension system has the most significant impact on vehicle dynamics, comfort and stability; these aspects are conflicting and the objective of an automatic control is to find a compromise. In this paper, the authors present an approach for the control of the vertical dynamics consisting of two layers: a low-level controller which fully exploits the properties of the magneto-rheological damper technology, and a high-level controller based upon a linearized skyhook for the full body control. The controller is experimentally validated on an actual vehicle and compared against an existing commercial solution.
Paper VI171-10.4
PDF · Video · Multi-Modes Control for Semi-Active Suspension Systems
Bel Haj Frej, Ghazi	University of Bordeaux, France
Moreau, Xavier	University of Bordeaux, France
Hamrouni, Emna	IMS - Univ. Bordeaux
Benine Neto, André	IMS Laboratory
Hernette, Vincent	PSA Peugeot Citroen
Keywords: Vehicle dynamic systems, Control architectures in automotive control, Modeling, supervision, control and diagnosis of automotive systems Abstract: The aim of this work is to design and analyze multi-modes semi-active suspension using a Continuously Variable Damper (CVD). A modeling approach for the CVD is presented, and three suspension modes are developed. The studied damper can achieve different suspension modes by controlling the actuation force, which makes its damping adjustment more efficient. By applying an appropriate control strategy to the damper based on minimizing the quadratic gap between the control actuation force for each mode and a control target, satisfaction of both ride comfort and driving safety can be realized. The control target is synthesized using CRONE-SkyHook approach. Performances of the proposed method are validated through a speed bump profile and a real measured road profile.
Paper VI171-10.5
PDF · Video · A Comparison of Optimal Gear Shifts for Stiff and Flexible Driveshafts During Accelerations
Ekberg, Kristoffer	Linköping University
Eriksson, Lars	Linköping University
Keywords: Vehicle dynamic systems, Engine modelling and control Abstract: Reducing the fuel consumption is important and much development work is on engine optimization for best stationary fuel consumption. Here, a solution is developed for the transient operation to get fuel optimal accelerations, considering the actuation of fuel injection, wastegate control and gear utilization. The transient acceleration scenario studied is; a truck is approaching a red light at slow rolling speed, the light turns green and the truck shall be accelerated to 50 km/h with minimum fuel. Optimal control is used to find the fuel optimal control strategies. By using a dynamic engine model, taking the turbocharger dynamics into consideration, the engine air fuel ratio is taken into account. The differences and similarities between a stiff and flexible driveline model, are analyzed. The results show that the most dominating effect is the turbocharger dynamics of the engine. The two drivelines have similar gear changing strategies while the finer details differ due to the additional degrees of freedom that are present in the flexible driveline.
Paper VI171-10.6
PDF · Video · Active Attitude Control of Ground Vehicles with Partially Unknown Model
Bianchi, Domenico	University of L'Aquila
Borri, Alessandro	Istituto Di Analisi Dei Sistemi Ed Informatica "A. Ruberti" (IAS
Di Benedetto, M. Domenica	Univ of L'Aquila
Di Gennaro, Stefano	Univ. Di L'Aquila
Keywords: Vehicle dynamic systems, Intelligent transportation systems Abstract: We present a novel solution to the attitude control problem of ground vehicles by means of the Active Front Steering (AFS) system. The classical feedback linearization method is often used to track a reference yaw dynamics while guaranteeing vehicle stability and handling performance, but it is difficult to apply because it relies on the exact knowledge of the nonlinearities of the vehicle, in particular the tire model. In this work, the unknown nonlinearities are real-time learnt on the basis of the universal approximation property, widely used in the area of neural networks. With this approximation method, the Uniform Ultimate Boundedness (UUB) property with respect to tracking and estimation errors can be formally proven. Preliminary simulation results show good tracking capabilities when model and parameters are affected by uncertainties, also in presence of actuator saturation.
Paper VI171-10.7
PDF · Video · Rack Force Estimation for Driving on Uneven Road Surfaces
Bhardwaj, Akshay	University of Michigan Ann Arbor
Slavin, Daniel	Ford Motor Company
Walsh, John	Ford Motor Company
Freudenberg, James S.	Univ. of Michigan
Gillespie, Brent	Univ of Michigan
Keywords: Vehicle dynamic systems, Modeling, supervision, control and diagnosis of automotive systems, Automotive system identification and modelling Abstract: The force transmitted from the front tires and tie rods to the steering rack of a vehicle, called the rack force, significantly influences the torque experienced by a driver at the steering wheel. As a result, estimates of rack force are used in a wide variety of advanced driver assist systems. Existing methods for producing rack force estimates are either susceptible to steering system disturbances or are only applicable for driving on roads with low frequency profile variations such as road slopes. In this paper we present a model that can produce disturbance-free rack force estimates for driving on roads with high frequency profile variations, such as road cleats and potholes, in addition to roads with low frequency profile variations. We validate the estimation accuracy of our model by presenting results from two driving experiments that were performed on test tracks with known low and high frequency road profile variations. We further demonstrate the merits of our model relative to the existing models by comparing the various estimates to rack force measurements obtained using a sensor mounted in the test vehicle.
Paper VI171-10.8
PDF · Video · String Stability of Homogenous Vehicle Platoons Based on Cooperative Extended State Observers
Liu, Anquan	Shanghai University
Li, Tao	East China Normal University
Gu, Yu	East China Normal University
Dai, Haohui	East China Normal University
Keywords: Vehicle dynamic systems, Modeling, supervision, control and diagnosis of automotive systems, Intelligent driver aids Abstract: We study platoon control of homogeneous vehicles with linear third-order longitudinal dynamics with the constant time headway (CTH) policy. In order to ensure string stability with a small time headway, a distributed control law based on extended state observers is proposed. The controller of each follower vehicle only depends on its own velocity, acceleration, inter-vehicle distance and velocity difference with respect to its immediate predecessor. First, a dynamic model based on velocity differences between adjacent vehicles is established. Then cooperative extended state observers are designed to estimate the acceleration differences between adjacent vehicles, based on which distributed cooperative controllers are designed. By analyzing the transfer function of inter-vehicle distances errors, the sufficient conditions to ensure string stability are presented. It is shown that for any given positive time headway, the parameters of distributed cooperative state observers and controllers can be properly designed so that the inter-vehicle distance errors are not amplified during the backward propagation along the platoon. The effectiveness of the cooperative control law is demonstrated by simulations.
Paper VI171-10.9
PDF · Video · Model Predictive Control of Half-Car Active Suspension Systems Using Particle Swarm Optimisation
Pedro, Jimoh O.	University of the Witwatersrand
Nhlapo, Sakhile M. S.	University of Witwatersrand
Mpanza, Lindokuhle Justice	University of the Witwatersrand
Keywords: Vehicle dynamic systems, Modeling, supervision, control and diagnosis of automotive systems, Nonlinear and optimal automotive control Abstract: This paper presents the design of a particle swarm-optimised model predictive controller (MPC) for a half-car nonlinear electrohydraulic suspension system as it traverses a deterministic road disturbance. The particle swarm optimisation (PSO) algorithm uses an objective function which is based on conflicting active vehicle suspension system (AVSS) design specifications such as: ride comfort, road holding, road handling, suspension travel and power consumption. An inner-loop PID-based force feedback control is incorporated in the design to ensure good force tracking. The half-car model is composed of nonlinear suspensions and actuator dynamics. Simulation results demonstrate the superior performance of the proposed control scheme over the passive vehicle suspension system (PVSS) and the non-optimised MPC in rejecting the deterministic road disturbance.
Paper VI171-10.10
PDF · Video · On Optimal Control of Multichamber Suspensions
Dattilo, Stefano	Politecnico Di Milano
Panzani, Giulio	Politecnico Di Milano
Corno, Matteo	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Vehicle dynamic systems, Nonlinear and optimal automotive control Abstract: This paper deals with the technological analysis, and optimal control of multichamber suspensions for automotive applications. Multichamber suspensions are composed by a variable damping shock absorber and an air-spring equipped with at least an auxiliary volume. The auxiliary volume is connected to the air-spring main chamber through a two-state valve. This configuration allows for a rapid change of both the damping and the stiffness of the suspension. The first goal of this paper is to model and analyze the behaviour of the suspension, the second goal is to investigate the potential benefit of this architecture from the comfort point of view. To this aim, the paper proposes an optimal benchmark controller and tests it in simulation showing comfort improvements up to 16% with respect to state-of-the-art solution of a passive soft spring and semi-active damping control.
Paper VI171-10.11
PDF · Video · Two Degrees of Freedom Slip Controller with Lateral Torque Distribution
Degel, Wolfgang	Technische Universität Kaiserslautern
Lupberger, Stefan	University of Kaiserslautern
Odenthal, Dirk	BMW Group
Bajcinca, Naim	University of Kaiserslautern
Keywords: Vehicle dynamic systems, Nonlinear and optimal automotive control, Modeling, supervision, control and diagnosis of automotive systems Abstract: Current slip control systems focus on vehicles with single-axle drive or all-wheel drive. This work presents a new two degrees of freedom slip controller affecting the average wheel speed and the wheel speed difference between the left and right wheel of a driven axle. The approach is applicable for electronically controlled limited-slip differentials and individually controllable brake actuators. The control design is performed with input-output linearization and global stability in the sense of Lyapunov is proven for the zero dynamics. The proposed control system is evaluated in a prototype vehicle and fulfills the task of traction control.
Paper VI171-10.12
PDF · Video · Optimal Tyre Management of a Formula One Car
West, Wilhelm Joachim	University of Pretoria
Limebeer, David	Oxford University, Engineering Science Department
Keywords: Vehicle dynamic systems, Nonlinear and optimal automotive control, Simulation Abstract: Optimal control calculations are used to study the effect of tyre wear on race car performance. This is achieved by solving a minimum lap time optimal control problem over multiple laps using a dynamical model of a Formula One car. A previously developed thermodynamic model is enhanced by adding an additional state for the carcass temperature of the tyres. The tyre grip is modelled as a function of the tyres' wear and temperature. Grip reduces when tyres get worn, or the tyres are not operated within their optimal temperature window. Overheating the tyres can accelerate wear, which in turn, degrades performance. The optimal control problem solver needs to `manage' the state of tyres throughout a race (not just a single lap) to ensure that optimal race performance is achieved. At some point during a race a pit stop may be required to change worn tyres so that tyre grip can be restored. It is essential to understand the wear characteristics of various tyre compounds in order to determine the point when the time needed for a pit stop is justified in terms of subsequent racing performance.
Paper VI171-10.13
PDF · Video · Moment Propagation of Discrete-Time Stochastic Polynomial Systems Using Truncated Carleman Linearization
Pruekprasert, Sasinee	National Institute of Informatics
Takisaka, Toru	National Institute of Informatics
Eberhart, Clovis	National Institute of Informatics
Cetinkaya, Ahmet	National Institute of Informatics
Dubut, Jeremy	National Institute of Informatics
Keywords: Safety, Simulation, Vehicle dynamic systems Abstract: We propose a method to compute an approximation of the moments of a discrete-time stochastic polynomial system. We use the Carleman linearization technique to transform this finite-dimensional polynomial system into an infinite-dimensional linear one. After taking expectation and truncating the induced deterministic dynamics, we obtain a finite-dimensional linear deterministic system, which we then use to iteratively compute approximations of the moments of the original polynomial system at different time steps. We provide upper bounds on the approximation error for each moment and show that, for large enough truncation limits, the proposed method precisely computes moments for sufficiently small degrees and numbers of time steps. We use our proposed method for safety analysis to compute bounds on the probability of the system state being outside a given safety region. Finally, we illustrate our results on two concrete examples, a stochastic logistic map and a vehicle dynamics under stochastic disturbance.

VI172
Transportation and Vehicle Systems - Marine Systems
VI172-01 Advances in Surface Vessels Autonomy   Invited Session, 10 papers
VI172-03 Marine Robotics: A New Wave of Autonomous Systems   Open Invited Session, 16 papers
VI172-04 Marine Systems Guidance and Control   Regular Session, 12 papers

VI172-01
Advances in Surface Vessels Autonomy	Invited Session
Chair: Reppa, Vasso	Delft University of Technology
Co-Chair: Galeazzi, Roberto	Technical University of Denmark
Organizer: Reppa, Vasso	Delft University of Technology
Organizer: Galeazzi, Roberto	Technical University of Denmark
Organizer: Negenborn, Rudy	Delft University of Technology
Organizer: Blanke, Mogens	Technical University of Denmark
Paper VI172-01.1
PDF · Video · Cooperative Control of Autonomous Tugs for Ship Towing (I)
Du, Zhe	TU Delft
Reppa, Vasso	Delft University of Technology
Negenborn, Rudy	Delft University of Technology
Keywords: Autonomous surface vehicles, Cooperative control, Control architectures in marine systems Abstract: Autonomous surface vehicles (ASVs) are seeing a significant development over the last decade. In recent years, their commercial applications are attracting the attention of many companies. One of the promising subjects is to develop autonomous tugs for ship berthing. This paper focuses on the cooperative control of autonomous tugs for ship towing in a berthing scenario. We propose a multi-layer optimal control strategy for a two-tug towing system to guarantee a ship reaching a desired position with a desired heading and velocity. In the higher layer supervisory control, an optimal control method is used to allocate towing forces and determine towing angles. With the help of these results and geometry relationships, the reference trajectories of the two autonomous tugs can be calculated online. Based on the reference trajectories, the trajectory tracking, which is in the lower layer, is addressed. Simulation results indicate that two autonomous tugs can cooperatively tow the unpowered ship to a desired position with a desired heading and velocity.
Paper VI172-01.2
PDF · Video · Low Altitude Georeferencing for Imaging Sensors in Maritime Tracking (I)
Helgesen, øystein Kaarstad	Norwegian University of Science and Technology
Brekke, Edmund F.	Norwegian Univ. of Science and Tech
Stahl, Annette	Norwegian University of Science and Technology
Engelhardtsen, øystein	DNV-GL
Keywords: Autonomous surface vehicles, Sensing, Marine system navigation, guidance and control Abstract: This paper presents a method for georeferencing low-altitude camera sensors, both infrared and electro-optical, in a maritime context. Accurate georeferencing require very high precision for the object pixel coordinates due to sensor resolution. To achieve this we refine the bounding boxes provided by an SSD object detector using the Sobel operator and the Hough transform. Using real world data this method is applied in a maritime tracking system based on the Joint Integrated Probabilistic Data Association method and compared to radar tracking. The georeferenced cameras surpassed radar performance in several of the benchmarks and maintained tracks with greater reliability at the cost of reduced position accuracy.
Paper VI172-01.3
PDF · Video · Robust and Reliable Multi-Sensor Navigation Filter for Maritime Application (I)
Gehrt, Jan-Jöran	RWTH Aachen University
Liu, Shuchen	RWTH Aachen University
Nitsch, Maximilian	RWTH Aachen University
Bruhn, Wilko	Raytheon Anschütz GmbH
Rohde, Sven	Raytheon Anschütz GmbH
Zweigel, René	RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Kalman filtering techniques in marine systems control, Marine system navigation, guidance and control, Autonomous surface vehicles Abstract: This publication describes the further development of a navigation concept especially designed for maritime application and its recent integration on the research ship DENEB of the German Federal Maritime and Hydrographic Agency (BSH). The proposed navigation concept consists of a tightly-coupled navigation filter, which bases on quantities of an inertial measurement unit (IMU), is aided by a Doppler velocity log (DVL), and Global Navigation Satellite System (GNSS) dual constellation signals of two antennas. Integrity monitoring with fault detection and exclusion (FDE), ensures the reliability of the GNSS observables. A new approach for integrating low quality and biased DVL data without endangering the state estimation accuracy and preciseness, but enhancing it's robustness is introduced. A new integration of real-time sea level data from an online service in the filter improves robustness in addition. The navigation system is evaluated in an extensive measurement campaign with DENEB in harbor of Rostock, Germany. Basically, two different advantages of the proposed navigation concept are investigated. Firstly, evaluation proves that integration of the low quality and biased data of the vessels DVL is possible without lowering the navigation filter accuracy significantly. Secondly, the robustness of the concept against sensor failure is shown. Therefore, by means of post-processing the recorded data, GNSS and DVL outage is investigated. Evaluation verifies, that the multi-sensor fusion and the integration of real-time sea level data improves the robustness of the navigation solution and therefore is qualied for autonomous application.
Paper VI172-01.4
PDF · Video · Trajectory Planning and Control for Automatic Docking of ASVs with Full-Scale Experiments (I)
Bitar, Glenn Ivan	Norwegian University of Science and Technology
Martinsen, Andreas Bell	NTNU
Lekkas, Anastasios M.	Norwegian University of Science and Technology
Breivik, Morten	Norwegian University of Science and Technology
Keywords: Autonomous surface vehicles, Trajectory and Path Planning, Nonlinear and optimal marine system control Abstract: We propose a method for performing automatic docking of a small autonomous surface vehicle (ASV) by interconnecting an optimization-based trajectory planner with a dynamic positioning (DP) controller for trajectory tracking. The trajectory planner provides collision-free trajectories by considering a map with static obstacles, and produces feasible trajectories through inclusion of a mathematical model of the ASV and its actuators. The DP controller tracks the time-parametrized position, velocity and acceleration produced by the trajectory planner using proportional-integral-derivative feedback with velocity and acceleration feed forward. The method’s performance is tested on a small ASV in confined waters in Trondheim, Norway. The ASV performs collision-free docking maneuvers with respect to static obstacles when tracking the generated reference trajectories and achieves successful docking.
Paper VI172-01.5
PDF · Video · Automated Maneuvering in Confined Waters Using Parameter Space Model and Model-Based Control (I)
Kurowski, Martin	University of Rostock
Schubert, Agnes	University of Rostock
Jeinsch, Torsten	University of Rostock
Keywords: Marine system identification and modelling, Adaptive and robust control in marine system, Control architectures in marine systems Abstract: The paper discusses methods to increase the level of automation in ship handling towards a possible autonomous operation. The focus is on maneuvering situations in confined waters within the velocity range between dynamic positioning and transiting. While performant automation solutions exist for specialized vessels, standard ships are operated manually in maneuvering situations. In this context, one challenge is to adapt a model for controller design of maneuvering vessels. It is a cumbersome task to parameterize the common hydrodynamical oriented models, especially for maneuvering standard ships. Therefore, a more experimental approach has been chosen to decrease the complexity of the model structure. In that way, the applied motion model is highly abstracted and has a minimal number of parameters which are mapped in parameter spaces. For motion control, a cascaded structure integrating a velocity and a maneuver control system has been designed. The low-level part consists of a model-based feedforward control applying the parameter space model implicitly. Further a simple decentralized multi-variable feedback controller is used. Here, a robust approach has been applied for controller parameterization by assigning a specific parameter space to each defined operation range. The methods are verified and validated with two demonstrators. Firstly a passenger vessel is used in a ship handling simulator and secondly real world experiments are performed applying an unmanned surface vehicle. The objective of these trials is automated maneuvering in the port of Rostock.
Paper VI172-01.6
PDF · Video · COLREGs-Based Situation Awareness for Marine Vessels - a Discrete Event Systems Approach (I)
Hansen, Peter Nicholas	Technical University of Denmark
Papageorgiou, Dimitrios	Technical University of Denmark
Blanke, Mogens	Technical University of Denmark
Galeazzi, Roberto	Technical University of Denmark
Lützen, Marie	Svendborg International Maritime Academy
Mogensen, John	Svendborg International Maritime Academy
Bennedsen, Mette	Svendborg International Maritime Academy
Hansen, Dorte Olbæk	Svendborg International Maritime Academy
Keywords: Decision support systems in marine systems, Autonomous surface vehicles, Marine system navigation, guidance and control Abstract: Autonomy at different levels is envisaged to provide decision support, to enable navigation with temporally unattended bridge or have the navigator placed remotely, being able to take command if required. For this purpose, methods for computer-based situation awareness are needed to avoid risks of collision. Correct interpretation of a situation is crucial, and all navigation decisions must be based on the COLREGs. This paper presents a discrete-event-systems-based framework that facilitates autonomous interpretation of the situation in which the own ship is. This can be used for COLREGs-compliant decision planning when all vessels navigate according to the rules. The proposed framework comprises a set of coupled finite-state deterministic automata and segregates situation understanding from anticipation. The suggested formalism is analysed with respect to avoidance of deadlocks and shows how synchronisation of vessel-specific automata modules is achieved. Simulations illustrate the concept using realistic scenarios.
Paper VI172-01.7
PDF · Video · On Collision Risk Assessment for Autonomous Ships Using Scenario-Based MPC (I)
Tengesdal, Trym	Norwegian University of Science and Technology
Brekke, Edmund F.	Norwegian Univ. of Science and Tech
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Autonomous surface vehicles, Marine system navigation, guidance and control Abstract: Collision Avoidance (COLAV) for autonomous ships is challenging since it relies on track estimates of nearby obstacles which are inherently uncertain in both state and intent. This uncertainty must be accounted for in the COLAV system in order to ensure both safe and efficient operation of the vessel in accordance with the traffic rules. Here, a COLAV system built on the Scenario-based Model Predictive Control (SB-MPC) with dynamic probabilistic risk treatment is presented. The system estimates the probability of collision with all nearby obstacles using a combination of Monte Carlo simulation (MCS) and a Kalman Filter (KF), taking the uncertainty in both position and velocity into account. A probabilistic collision cost is then used in the MPC to penalize risk-taking maneuvers. Simulation results show that the proposed method may provide increased robustness due to increased situational awareness, while also being able to efficiently follow the nominal path and adhere to the traffic rules.
Paper VI172-01.8
PDF · Video · Vision-Based Object Tracking in Marine Environments Using Features from Neural Network Detections (I)
Schöller, Frederik Emil Thorsson	DTU
Blanke, Mogens	Technical University of Denmark
Plenge-Feidenhans'l, Martin	DTU
Nalpantidis, Lazaros	DTU - Technical University of Denmark
Keywords: Autonomous surface vehicles, Neural networks, Robot Navigation, Programming and Vision Abstract: Autonomous decision support is desired to enable navigation with a temporally unattended bridge or to have the vessel navigated remotely. In order to have safe navigation, it is crucial to correctly interpret the current situation given any scenario. Proper perception of the surrounding environment is essential for good situational awareness. This paper suggests a method for tracking objects that have been detected by a neural network. The method utilises features that have been computed during the detection step, thereby ensuring good features that are representative for the given objects while saving the time it would take to compute new features. The suggested method is evaluated on data acquired in Danish near-coastal waters. Evaluation shows that the tracking method is able to track the detections well with few switches of object identity. The method is shown to outperform a similar tracking algorithm, while keeping the speed needed for real-time applications.
Paper VI172-01.9
PDF · Video · Risk-Based Model Predictive Control for Autonomous Ship Emergency Management (I)
Blindheim, Simon André Johnsen	Norwegian University of Science and Technology
Gros, Sebastien	NTNU
Johansen, Tor Arne	Norwegian University of Science and Technology
Keywords: Autonomous surface vehicles, Mission planning and decision making, Nonlinear and optimal marine system control Abstract: Control for semi- and fully-autonomous ships is a broad and complex field. Making autonomous high-level decisions in place of the captain is considered difficult, partly due to the risks and uncertainties involved. Though human operators located in onshore control centers are still needed for safety and regulatory reasons, there is a growing demand for complex decisions to be made by the onboard control system itself, both during normal operations and extraordinary circumstances. Model predictive control (MPC) is a promising approach to tackle this problem. In this paper, a dynamic risk-based decision-making algorithm is constructed through the use of heuristic objectives, capable of planning suitable vessel trajectories in emergency situations. Nonlinear programming using the direct multiple-shooting method implemented with the CasADi framework is considered, and the resulting control performance of several emergency scenarios is analyzed using simulation. The developed algorithm proved capable of both generating suitable trajectories below a certain risk threshold, and to engage the safety systems appropriately. It is concluded that MPC with independent risk cost terms is a promising method for autonomous ship trajectory planning and emergency management.
Paper VI172-01.10
PDF · Video · Model Predictive Trajectory Tracking Control and Thrust Allocation for Autonomous Vessels (I)
Haseltalab, Ali	Delft University of Technology
Garofano, Vittorio	Delft University of Technology
van Pampus, Maurits	Delft University of Technology
Negenborn, Rudy	Delft University of Technology
Keywords: Autonomous surface vehicles, Nonlinear and optimal marine system control, Control architectures in marine systems Abstract: The maneuvering control of autonomous vessels has been under extensive investigations by academic and industrial communities since it is one of the primary steps towards enabling unmanned shipping. In this paper, a model predictive control (MPC) approach is presented for trajectory tracking control of vessels which takes into account the thrust allocation (TA) problem in the presence of rotatable thrusters. In this approach, the TA problem is formulated over a finite horizon and solved with regard to the power consumption, changes in the angle and speed of actuators, and the operating constraints. In the proposed control approach, several linearization techniques have been employed to enable the adoption of quadratic programming approaches for solving the MPC's and TA's optimization problems. The performance of the proposed approach is evaluated through several simulation experiments using a replica vessel model.

VI172-03
Marine Robotics: A New Wave of Autonomous Systems	Open Invited Session
Chair: Bibuli, Marco	CNR-INM
Co-Chair: Galeazzi, Roberto	Technical University of Denmark
Organizer: Bibuli, Marco	CNR-INM
Organizer: Zereik, Enrica	Cnr - Inm
Organizer: Pascoal, Antonio M.	Instituto Superior Técnico (IST-ID) VAT 509830072
Organizer: Sousa, Joao	Fac. Engenharia Universidade Do Porto
Organizer: Galeazzi, Roberto	Technical University of Denmark
Paper VI172-03.1
PDF · Video · A Complete Process for Shipborne Sea-Ice Field Analysis Using Machine Vision (I)
Sandru, Andrei	Aalto University
Hyyti, Heikki Sakari	Finnish Geospatial Research Institute (FGI), National Land Surve
Visala, Arto	Aalto University, ELEC School
Kujala, Pentti	Aalto University
Keywords: Robot Navigation, Programming and Vision, Decision support systems in marine systems, Sensor integration and perception Abstract: A sensor instrumentation and an automated process are proposed for sea-ice field analysis using ship mounted machine vision cameras with the help of inertial and satellite positioning sensors. The proposed process enables automated acquisition of sea-ice concentration, floes size and distribution. The process contains pre-processing steps such as sensor calibration, distortion removal, orthorectification of image data, and data extraction steps such as sea-ice floe clustering, detection, and analysis. In addition, we improve the state of the art of floe clustering and detection, by using an enhanced version of the k-means algorithm and the blue color channel for increased contrast in ice detection. Comparing to manual visual observations, the proposed method gives significantly more detailed and frequent data about the size and distribution of individual floes. Through our initial experiments in pack ice conditions, the proposed system has proved to be able to segment most of the individual floes and estimate their size and area.
Paper VI172-03.2
PDF · Video · Deep Learning Based Segmentation of Fish in Noisy Forward Looking MBES Images (I)
Christensen, Jesper	Technical University of Denmark, ATLAS MARIDAN ApS
Mogensen, Lars V.	ATLAS MARIDAN ApS
Ravn, Ole	Technical University of Denmark
Keywords: Neural networks, Autonomous underwater vehicles, Marine system navigation, guidance and control Abstract: In this work, we investigate a Deep Learning (DL) approach to fish segmentation in a small dataset of noisy low-resolution images generated by a forward-looking multibeam echosounder (MBES). We build on recent advances in DL and Convolutional Neural Networks (CNNs) for semantic segmentation and demonstrate an end-to-end approach for a fish/non-fish probability prediction for all range-azimuth positions projected by an imaging sonar. We use self-collected datasets from the Danish Sound and the Faroe Islands to train and test our model and present techniques to obtain satisfying performance and generalization even with a low-volume dataset. We show that our model proves the desired performance and has learned to harness the importance of semantic context and take this into account to separate noise and non-targets from real targets. Furthermore, we present techniques to deploy models on low-cost embedded platforms to obtain higher performance fit for edge environments -- where compute and power are restricted by size/cost -- for testing and prototyping.
Paper VI172-03.3
PDF · Video · Cooperative Navigation Based on Bearing and Range Measurements to Different Vehicles (I)
Santos, David	Instituto Superior Técnico, Universidade De Lisboa
Batista, Pedro	Instituto Superior Técnico, Universidade Técnica De Lisboa
Keywords: Autonomous underwater vehicles, Kalman filtering techniques in marine systems control, Marine system navigation, guidance and control Abstract: This paper presents a navigation solution for a vehicle operating in cooperation with two other. The vehicle is assumed to measure bearing to one of the aiding vehicles and range to the other. An observer with globally exponentially stable error dynamics is designed by obtaining an equivalent observable linear time-varying system using an artificial output and state augmentation. The observer relies on local measurements, as well as limited communication between the vehicles. Simulations are performed to assess the proposed solution.
Paper VI172-03.4
PDF · Video · Saliency and Anomaly: Transition of Concepts from Natural Images to Side-Scan Sonar Images (I)
Kapetanović, Nadir	University of Zagreb Faculty of Electrical Engineering and Compu
Miskovic, Nikola	University of Zagreb Faculty of Electrical Engineering and Compu
Tahirovic, Adnan	Politecnico Di Milano, University of Sarajevo
Keywords: Autonomous underwater vehicles, Sensors and actuators, Decision support systems in marine systems Abstract: An AUV or a multi-AUV systems performing autonomous seafloor exploration missions with a side-scan sonar need to perceive their environment in order to replan the mission if they detect interesting objects in sensor data. Several anomalous/salient object detection methods mostly used for natural images are here applied to sonar images. All methods were firstly benchmarked on a 1500 simulated side-scan sonar images dataset. Precision-recall and processing time analysis was conducted in order to choose the best suited method in such controlled conditions. The performance of the best performing anomaly detection method was then validated on a 350 real side-scan sonar images dataset. This method was then implemented and optimized for the computer onboard an AUV. It turned out to be fast enough for online processing of large volumes of sonar data.
Paper VI172-03.5
PDF · Video · Cloud-Based Remote Control Framework for Unmanned Surface Vehicles (I)
Wang, Zhao	Huazhong University of Science and Technology
Yang, Shaolong	Huazhong University of Science and Technology
Xiang, Xianbo	Huazhong University of Science and Technology
Vasilijevic, Antonio	University of Zagreb
Miskovic, Nikola	University of Zagreb
Nad, Dula	University of Zagreb
Keywords: Unmanned marine vehicles, Autonomous surface vehicles, Decentralized Control and Systems Abstract: This paper proposes a cloud-based mission control framework for a fleet of unmanned vehicles. The framework enables easy, timely and prioritized remote access to fleet operations regardless of operator location. By leveraging cloud-based technologies the framework accomplishes scalable monitoring, remote control, data acquisition and sharing. While the front-end is applicable across mobile robotic systems, the back-end presented in this paper provides integration with the Robot Operating System (ROS); thus, enabling integration of various marine robotic agents based on the same robot framework. The proposed framework operation is demonstrated on the H2OmniX unmanned surface vehicles during trials in Biograd na Moru, Croatia.
Paper VI172-03.6
PDF · Video · 2D Forward Looking SONAR in Underwater Navigation Aiding: An AUKF-Based Strategy for AUVs (I)
Franchi, Matteo	University of Florence
Ridolfi, Alessandro	University of Florence
Zacchini, Leonardo	University of Florence
Keywords: Marine system navigation, guidance and control, Autonomous underwater vehicles, Kalman filtering techniques in marine systems control Abstract: This paper proposes an underwater navigation system where linear speed estimations, obtained with a 2D Forward-Looking SONAR (FLS), are integrated within a navigation filter and this solution is shown to work satisfyingly in the absence of Doppler Velocity Log (DVL) readings. Both to provide a better description of the system, which is a dynamic entity in a dynamic environment and to characterize FLS measurements, an Adaptive Unscented Kalman Filter (AUKF)-based estimator is here proposed. The solution has been tested and validated offline making use of navigation data obtained during sea trials performed in July 2018 with FeelHippo AUV at the basin of the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE), La Spezia (Italy).
Paper VI172-03.7
PDF · Video · A Preliminary Experiment Combining Marine Robotics and Citizenship Engagement Using Imitation Learning (I)
Odetti, Angelo	CNR
Bibuli, Marco	CNR-INM
Bruzzone, Gabriele	CNR-ISSIA
Cervellera, Cristiano	National Research Council
Ferretti, Roberta	CNR-INM
Gaggero, Mauro	National Research Council of Italy
Zereik, Enrica	Cnr - Inm
Caccia, Massimo	CNR-INM
Keywords: Autonomous surface vehicles, Neural networks, Marine system navigation, guidance and control Abstract: In this paper, we describe a preliminary experiment of citizenship engagement in the context of marine robotics using imitation learning to train a controller that mimics human behavior. The experiment has been carried out during the Festival della Comunicazione in Camogli, Italy, in September 2019. In more detail, citizens have been asked to piloting a small, light, and safe autonomous surface vehicle in front of a crowded public beach with the goal of performing an S-shaped path. The trajectories and controls performed by non-expert human operators have been recorded with the aim of training an imitation system that, after collecting a sufficient number of trajectories and controls pairs, has been able to drive the vehicle without human intervention. To learn the human behavior, echo state networks have been employed as approximating architectures. The resulting controller turned out to be very effective in performing successfully the considered experiment with a reduced amount of training trajectories by imitating the human behavior also in unknown situations. The success of this experiment may pave the way to new research processes where citizens are actively engaged.
Paper VI172-03.8
PDF · Video · Experimental Evaluation of Outliers Filtering Techniques in Networked Acoustic Localisation Systems (I)
Fenucci, Davide	National Oceanography Centre
Munafo, Andrea	National Oceanography Centre
Keywords: Kalman filtering techniques in marine systems control, Acoustic-Based Networked Control and Navigation, Autonomous underwater vehicles Abstract: Localisation-aware underwater networks are gaining increasing attention in the marine robotics community thanks to their ability of providing navigational services. This can be beneficial in a number of applications, as for instance to support the navigation of Autonomous Underwater Vehicles (AUVs) when traditional aiding systems are impractical or not cost effective. However, the unreliability of the acoustic channel, together with the additional overhead and constraints introduced by the network itself, result in localisation measurements that are intrinsically sporadic. This makes the outlier filtering problem of localisation measurements obtained through networked underwater systems particularly important and challenging. This paper uses experimental data to compare the integration of two different outlier filtering methodologies in an existing network-aided AUV navigation filter. The first method aims at pre-filtering the measurements to identify and discard potential outliers before they are fused in the navigation filter. The second one modifies the correction step of the Kalman filter to integrate measurements in an outlier-robust way. Results show that when the navigation filter is made outlier-robust the navigation performance increases and the system becomes less sensitive to tuning, a key characteristic for fielded systems.
Paper VI172-03.9
PDF · Video · Deep Learning for On-Board AUV Automatic Target Recognition for Optical and Acoustic Imagery (I)
Zacchini, Leonardo	University of Florence
Ridolfi, Alessandro	University of Florence
Topini, Alberto	University of Florence
Secciani, Nicola	University of Florence
Bucci, Alessandro	University of Florence
Topini, Edoardo	University of Florence
Allotta, Benedetto	Univ of Florence
Keywords: Sensing, Autonomous underwater vehicles, Neural networks Abstract: In the widespread field of underwater robotics applications, the demand for increasingly intelligent vehicles is leading to the development of Autonomous Underwater Vehicles(AUVs) with the capability of understanding and engaging the surrounding environment. Consequently, to push the boundaries of cutting-edge smart AUVs, the automatic recognition of targets is becoming one of the most investigated topics and Deep Learning-based strategies have shown astonishing results. In the context of this work, two different neural network architectures, based on the Single Shot Multibox Detector (SSD) and on the Faster Region-based Convolutional Neural Network (Faster R-CNN), have been trained and validated, respectively, on optical and acoustic datasets. In particular, the models have been trained with the images acquired by FeelHippo AUV during the European Robotics League (ERL) competition, which took place in La Spezia, Italy, in July 2018. The proposed ATR strategy has then been validated with FeelHippo AUV in an on-board post-processing stage by exploiting the images provided by both a 2D Forward Looking Sonar (FLS) as well as an IP camera mounted on-board on the vehicle.
Paper VI172-03.10
PDF · Video · Probabilistic Intent Inference for Predicting the Compliance with COLREGs between Two Surface Ships (I)
Cho, Yonghoon	KAIST
Kim, Jonghwi	KAIST
Kim, Jinwhan	KAIST
Keywords: Autonomous surface vehicles, Unmanned marine vehicles, Marine system navigation, guidance and control Abstract: The international regulations for preventing collisions at sea (COLREGs) are the rules of the road for marine surface vessels. However, certain ships fail to comply with COLREGs and their non-compliance poses a greater danger to the maritime safety. This study proposes a probabilistic model for intent inference of ship maneuvers which consist of an intent model, a dynamics model, and a measurement model. An algorithm based on the proposed graphical model is implemented to infer and predict the ship’s intent of non-compliance/compliance with COLREGs, which enables making proper decisions for collision avoidance maneuvers even when the opponent ship violates the marine traffic rules. In order to demonstrate the feasibility of the proposed algorithm, the results of extensive traffic simulations are presented and discussed.
Paper VI172-03.11
PDF · Video · A New Virtual Reality Interface for Underwater Intervention Missions (I)
de la Cruz Soler, Marcos	Jaume I University
Casañ, Gustavo	Jaume I University
Sanz, P.J.	Univ of Jaume I
Marin, Raul	Universitat Jaume I
Keywords: Man-machine interfaces, Teleoperation, Unmanned marine vehicles Abstract: Nowadays, most underwater intervention missions are developed through the well-known work-class ROVs (Remote Operated Vehicles), equipped with teleoperated arms under human supervision. Thus, despite the appearance on the market of the first prototypes of the so-called I-AUV (Autonomous Underwater Vehicles for Intervention), the most mature technology associated with ROVs continues to be trusted. In order to fill the gap between ROVs and incipient I-AUVs technology, new research is under progress in our laboratory. In particular, new HRI (Human Robot Interaction) capabilities are being tested inside a three-year Spanish coordinated project focused on cooperative underwater intervention missions. In this work new results are presented concerning a new user interface which includes immersion capabilities through Virtual Reality (VR) technology. It is worth noting that a new HRI module has been demonstrated, through a pilot study, in which the users had to solve some specific tasks, with minimum guidance and instructions, following simple Problem Based Learning (PBL) scheme. Finally, it is noticeable that, although this is only a work in progress, the obtained results are promising concerning friendly and intuitive characteristics of the developed HRI module. Thus, some critical aspects, like complexity fall, training time and cognitive fatigue of the ROV pilot, seem more affordable now.
Paper VI172-03.12
PDF · Video · The Value Function As a Decision Support Tool in Unmanned Vehicle Operations (I)
Aguiar, Miguel Campos Pinto Coelho	Faculty of Engineering (FEUP), University of Porto
Sousa, Joao	Fac. Engenharia Universidade Do Porto
Dias, João Miguel	NMEC-CESAM, DFis, University of Aveiro
Silva, Jorge Estrela	Instituto Superior De Engenharia Do Porto
Mendes, Renato	NMEC-CESAM, DFis, University of Aveiro and CIIMAR, University Of
Ribeiro, Américo S.	NMEC-CESAM, DFis, University of Aveiro
Keywords: Unmanned marine vehicles, Decision support systems in marine systems, Nonlinear and optimal marine system control Abstract: General problems of optimal trajectory generation and of optimal space-time rendezvous for autonomous underwater vehicles affected by time-varying fluid flows are formulated and solved in the framework of dynamic programming. The optimal solutions include optimal trajectories, as well as departure times and positions. The approach consists in using the principle of optimality (PO) to embed, for example, an optimal time to reach a target problem from some fixed position and time into a more general problem of finding the optimal time to reach a target from any point and time. The solution of this general problem is given by the value function, the solution of a Hamilton-Jacobi-Bellman equation (HJBE) which expresses the PO in an infinitesimal form. The HJBE is solved using an efficient parallel numerical solver. The problems of interest are solved either by minimizing the value function over one or more variables (e.g., time) or by using level sets of the value function to coordinate departure times for multiple vehicles to rendezvous at a given target. The paper presents a description and an illustration of the approach and briefly discusses how value-function-based calculations provide a very effective way to solve complex motion planning and coordination problems. The discussion is aided by examples modeling real operational scenarios using current velocity forecasts from a state-of-the-art model of the Sado river estuary in Portugal.
Paper VI172-03.13
PDF · Video · Collision Avoidance Systems for Maritime Autonomous Surface Ships Considering Uncertainty in Ship Dynamics (I)
Huang, Yamin	Delft University of Technology
Chen, Linying	Delft University of Technology
Negenborn, Rudy	Delft University of Technology
van Gelder, P.H.A.J.M.	Delft University of Technology
Keywords: Autonomous surface vehicles, Genetic algorithms in marine systems, Trajectory and Path Planning Abstract: Many Collision Avoidance Systems (CAS) for autonomous ships usually presume that a ship’s dynamics are completely known in advance. However, precise parameters for ships in different operating conditions are, in fact, uncertain and unknown. The parameter identification of ship dynamics is challenging and time-consuming. Thus, uncertainties in the ship dynamic model are inevitable, which can lead to errors between real trajectories and predicted trajectories. These errors might result in an unexpected collision between ships. Therefore, it is necessary to consider tracking errors in the CAS, which is missing in most existing CAS. This article proposes a way to incorporate the errors in CAS. Specifically, a Velocity Obstacle (VO) algorithm is employed to find collision-free velocities with estimated tracking errors. Firstly, the ship is assumed to be a "black box" whose inputs and outputs are observable, while the internal workings are unknown. Secondly, parameters optimization of a PID controller are employed to determine the best feedback gains for tracking given trajectories; Thirdly, the maximal tracking errors for controlling the ship to arbitrary velocities are estimated. Finally, the maximal error is added to the safety distance and the VO algorithm is employed to find a collision-free solution. The proposed Unknown-Dynamics CAS (UD-CAS) can support the upgrade of existing conventional ships to Type I-III maritime autonomous surface ship.
Paper VI172-03.14
PDF · Video · Range-Based Navigation and Target Localization: Observability Analysis and Guidelines for Motion Planning (I)
Nguyen, Hung	Instituto Superior Técnico
Pascoal, Antonio M.	Instituto Superior Técnico (IST-ID)
Keywords: Marine system navigation, guidance and control, Acoustic-Based Networked Control and Navigation, Localization Abstract: This paper addresses the problem of target localization with a single or multiple mobile trackers using range measurements from the trackers to the target. We consider three scenarios: i) the target is fixed, ii) the target's velocity vector is unknown but constant, and iii) the target's acceleration vector is unknown but constant. The main contributions of the paper are twofold: i) we derive a set of necessary and sufficient conditions on the motion of the trackers under which the target's state, that might include the target's position, velocity and acceleration vectors is globally observable, and ii) we show how the conditions derived lend themselves to an intuitive geometric interpretation that yields valuable guidelines to plan the tracker's motion. Numerical simulations are included to confirm the conditions derived.
Paper VI172-03.15
PDF · Video · A Path-Velocity Decomposition Approach to Collision Avoidance for Autonomous Passenger Ferries in Confined Waters (I)
Thyri, Emil	NTNU
Breivik, Morten	Norwegian University of Science and Technology
Lekkas, Anastasios M.	Norwegian University of Science and Technology
Keywords: Trajectory and Path Planning, Autonomous Vehicles, Marine system navigation, guidance and control Abstract: A deliberate collision avoidance system for autonomous surface vehicles operating in confined waters with high traffic is presented. The approach focuses on dynamic obstacles, by assuming a predefined set of paths that are collision-free with respect to static obstacles. Hence, the collision avoidance problem is reduced to a velocity planning problem, which is solved by first transforming all dynamic obstacles to a path-time space and subsequently constructing a conditioned visibility graph and traversing it with Dijkstra’s algorithm. The performance of this approach is demonstrated via both simulations and full-scale sea trials in Trondheim harbor with the NTNU milliAmpere ferry prototype together with virtual dynamic obstacles.
Paper VI172-03.16
PDF · Video · Outlier Robust State Estimation through Smoothing on a Sliding Window (I)
De Palma, Daniela	University of Salento
Indiveri, Giovanni	University of Genova
Keywords: Kalman filtering techniques in marine systems control, Marine system navigation, guidance and control, Marine system identification and modelling Abstract: Measurement outliers can severely impact on the performance of conventional state estimators. The design of state estimators exhibiting enhanced robustness to measurement outliers is of interest in many areas of systems and control engineering. In marine robotics applications the issue is particularly relevant for navigation and model identification tasks exploiting acoustic based positioning and velocity sensors that are subject to relatively high rates of outliers. A sliding window state estimator is designed by minimizing the Least Median of Squares cost function evaluated by running a Rauch-Tung-Striebel smoother on the current window. The resulting estimator is tested on Doppler Velocity Log navigation data acquired on an underwater robot. Although these are only preliminary results, they confirm that the approach can be successfully used online.

VI172-04
Marine Systems Guidance and Control	Regular Session
Chair: Reppa, Vasso	Delft University of Technology
Co-Chair: Batista, Pedro	Instituto Superior Técnico, Universidade Técnica De Lisboa
Paper VI172-04.1
PDF · Video · Synthesis of an Attitude Control System for Unmanned Underwater Vehicle Using H-Infinity Approach
Gavrilina, Ekaterina	Bauman Moscow State Technical University
Chestnov, Vladimir	V.A.Trapeznikov Institute of Control Science of Russian Academy
Keywords: Adaptive and robust control in marine system, Marine system navigation, guidance and control, Unmanned marine vehicles Abstract: Recently problems requiring control unmanned underwater vehicles (UUV) at large angles of inclination (pitch and roll), become more frequent. Traditional attitude control systems use Euler angles. However, the performance of traditional systems decreases with the increasing of the tilt angles, which delays their use for new tasks. To solve this problem, stability analysis of the UUV’s attitude control system according to the generalized Nyquist stability criterion is carried out. The analyses showed that the stability of the system depends on the UUV inclination along the roll. However, at large angles of inclination, the roll channel is subject to perturbations from the yaw and pitch channels. The roll control system synthesis is solved as the H-infinity-optimization problem with the requirements of low sensitivity to perturbations from other channels. The simulation results on the full non-linear UUV Aqua-MO model confirmed the efficiency of the approach in question and demonstrated the best quality in comparison with PD controller. The obtained stability condition and synthesis approach allow to expand the working angles and improve the quality of the existing UUV control systems. These results are useful for the development of new systems as well.
Paper VI172-04.2
PDF · Video · The Method of Path Planning for AUV-Group Moving in Desired Formation in Unknown Environment with Obstacles
Filaretov, Vladimir	Institute of Automation and Control Processes
Yukhimets, Dmitry	Institute of Automation and Conrtol Processes FEB RAS
Keywords: Autonomous underwater vehicles, Cooperative control, Trajectory and Path Planning Abstract: The paper proposes a new method for trajectory formation of the AUVs group in "leader-follower" mode in the given formation in the unknown environment containing obstacles. In this mode, the AUV-leader defines the motion trajectory at the safe distance from the detected obstacles in accordance with the given mission. The AUVs-followers follow the leader and during obstacles avoidance they move along set in advance trajectories within the formation to ensure the safe distance between the AUVs-followers. In addition, the motion of the AUVs-followers along the predetermined trajectories allows to avoid additional data exchange between the AUVs with a view to match their positions.
Paper VI172-04.3
PDF · Video · Visual Loop Detection in Underwater Robotics: An Unsupervised Deep Learning Approach
Burguera, Antoni	University of the Balearic Island
Bonin-Font, Francisco Jesus	University of the Balearic Islands
Keywords: Autonomous underwater vehicles, Localization, Neural networks Abstract: This paper presents a novel Deep Neural Network aimed at fast and robust visual loop detection targeted to underwater images. In order to help the proposed network to learn the features that define loop closings, a global image descriptor built upon clusters of local SIFT descriptors is proposed. Also, a method allowing unsupervised training is presented, eliminating the need for a hand-labelled ground truth. Once trained, the Neural Network builds two descriptors of an image that can be easily compared to other image descriptors to ascertain if they close a loop or not. The experimental results, performed using real data gathered in coastal areas of Mallorca (Spain), show the validity of our proposal and favourably compares it to previously existing methods.
Paper VI172-04.4
PDF · Video · Navigation and Source Localization Based on Single Pseudo-Ranges with an Unknown Multiplicative Factor
Batista, Pedro	Instituto Superior Técnico, Universidade Técnica De Lisboa
Keywords: Kalman filtering techniques in marine systems control, Marine system navigation, guidance and control, Autonomous underwater vehicles Abstract: This paper presents a novel estimation solution for the problems of navigation and source localization based on pseudo-range measurements to a single pinger. In particular, the distance measurements are assumed to be corrupted by an unknown multiplicative factor, which is explicitly taken into consideration in the design. First, the equivalence between the problems of navigation and source localization is established, as well as cooperative navigation of two vehicles in tandem. Then, an augmented system is derived and its observability is carefully studied. The analysis is constructive, in the sense that the means to design an observer for the new system dynamics with globally exponentially stable error dynamics are readily available, resorting to linear systems theory. Moreover, the new augmented system is shown to be equivalent to the original one. Finally, simulations results are presented and discussed to assess the performance of the proposed solution in the presence of sensor noise.
Paper VI172-04.5
PDF · Video · Enhanced Cooperative Single-Range Underwater Navigation Based on Optimal Trajectories
Rúa, Santiago	Universidad Nacional Abierta Y a Distancia
Crasta, Naveen	Candela Speed Boat AB
Vasquez, Rafael E.	Universidad Pontificia Bolivariana
Pascoal, Antonio M.	Instituto Superior Técnico (IST-ID) VAT 509830072
Keywords: Marine system navigation, guidance and control, Acoustic-Based Networked Control and Navigation, Cooperative control Abstract: This work addresses the observability analysis for a cooperative range-based navigation system based on the optimization of an index. A nonlinear model is first defined in order to describe the motion of the vehicle and a mobile beacon. Then, the Fisher Information Matrix is introduced to explain how it is related with the observability problem. A unconstrained optimization problem is formulated in order to find the best sequence of actions for the beacon to ensure observability in the system; the unconstrained problem does not take into account physical limitation of the vehicle and beacon. Then, four different scenarios are solved using different constraints; we show that, when the beacon is rotating with variable angular velocity we get a better strategy than rotating with constant velocity, despite that in both scenarios the system is observable. Finally, we show that increasing the energy provided to rotate the beacon does not improve further the observability of the system. These results are important from a theoretical and practical point of view, since they represent a strategy to plan the motion of the beacon to guarantee observability in the system.
Paper VI172-04.6
PDF · Video · Velocity Estimation and Robust Non-Linear Path Following Control of Autonomous Surface Vehicles
Bejarano Pellicer, Guillermo	University Loyola Andalusia
N-Yo, Sufiyan	Loyola University Andalusia, Seville
Keywords: Marine system navigation, guidance and control, Autonomous surface vehicles, Adaptive and robust control in marine system Abstract: This work addresses the problem of non-linear path following control for under-actuated autonomous surface vehicles in the horizontal plane. The presence of multiple unknowns is considered, including unmodelled hydrodynamics, internal parametric model uncertainties, and unmeasurable disturbances due to wind, waves, and ocean currents, whereas the surge, sway, and yaw velocities are also considered to be unmeasured. Firstly, a non-linear extended state observer is applied to recover the unmeasured velocities and estimate the lumped generalised disturbances, that include all unknown terms previously detailed. Secondly, regarding the path following control, a surge-guided line-of-sight guidance law is applied to simultaneously compute the surge and heading/yaw references, while a simplified robust-adaptive backstepping control strategy is proposed. The effectiveness and robustness of the proposed estimation and control strategy is verified in simulation considering challenging disturbance and current profiles.
Paper VI172-04.7
PDF · Video · 3D Formation Control of Multiple Torpedo-Type Underactuated AUVs
Li, Ji-Hong	Korea Institute of Robot and Convergence
Park, Daegil	Korea Institute of Robot Convergence(KIRO)
Kang, Hyungjoo	Korea Institute of Robot and Convergence
Cho, Gun Rae	Korea Institute of Robot and Convergence
Keywords: Marine system navigation, guidance and control, Autonomous underwater vehicles, Coordinated control Abstract: This paper considers the formation problem for a group of torpedo-type AUVs (autonomous underwater vehicles). For each vehicle, there are only three control inputs available for the vehicle's 6-DOF motion in the water. So this is a typical underactuated system. For these underactuated multi-agent system, we propose a sort of virtual structure based formation scheme. Virtual structure is a graph with each node taken as virtual leader for each specific agent vehicle. And for the vehicle's motion control, a sort of path following scheme is used to force the vehicle to follow the virtual leader's trajectory. Proposed formation scheme can guarantee the exponential following in the spherical coordinate frame, and some of simulation studies are carried out to demonstrated this kind of following performance.
Paper VI172-04.8
PDF · Video · Flatness-Based MPC for Underactuated Surface Vessels in Confined Areas
Helling, Simon	Kiel University, Automatic Control Chair
Lutz, Max	Kiel University
Meurer, Thomas	Christian-Albrechts-University Kiel
Keywords: Marine system navigation, guidance and control, Nonlinear and optimal marine system control, Trajectory and Path Planning Abstract: A two-phase model predictive controller (MPC) is proposed for underactuated surface vessel operation in confined environments. For general driving maneuvers (phase one) the ship’s geometry is not considered explicitly while in more restricted areas (stage two) which occur, e.g., in mooring maneuvers, the ship’s geometry is approximated to ensure collision avoidance. To remove the dynamical constraint in the problem setup, the differential flatness of the fully actuated system is exploited and the flat outputs are parameterized using B- spline functions. Underactuated behavior is retained by means of inequality constraints that are imposed on the non-controllable input. In an effort to solve the MPC, a static nonlinear optimization problem is formulated and feasibility w.r.t. obstacles and actuator constraints is ensured at collocation points. Static obstacles are considered as constructive solid geometry functions in the MPC which also takes into account disturbances induced by wind.
Paper VI172-04.9
PDF · Video · Towards Control of Autonomous Surface Vehicles in Rough Seas
McCullough, Daniel Roger	University of Sheffield
Jones, Bryn L.	University of Sheffield
Gonzalez Villarreal, Oscar Julian	University of Sheffield
Rossiter, J. Anthony	Univ of Sheffield
Keywords: Nonlinear and optimal marine system control, Autonomous surface vehicles Abstract: This paper addresses the problem of controlling an Autonomous Surface Vehicle (ASV) in rough sea-states, with a view towards minimising wave-induced forces, whilst maintaining headway. This is a challenging control application since, and as is derived in the paper, the interaction between the vessel and the wave disturbance is nonlinear and coupled. This subsequently motivates the novel application of the Real Time Iteration Scheme (RTI) for Nonlinear Model Predictive Control (NMPC) of the ASV. Analysis of the resulting control signal provides an important insight into the role of the wave encounter frequency. Specifically, by actuating at twice the average wave encounter frequency, the nonlinear controller is able to reduce the wave forces, compared to an open-loop controller that achieves the same average velocity.
Paper VI172-04.10
PDF · Video · Nonlinear MPC for Combined Motion Control and Thrust Allocation of Ships
Bärlund, Alexander	ABB Industrial Automation
Linder, Jonas	Abb Corporate Research
Feyzmahdavian, Hamid Reza	ABB Corporate Research
Lundh, Michael	ABB AB, Corporate Research
Tervo, Kalevi	ABB Oy, Marine
Keywords: Nonlinear and optimal marine system control, Control architectures in marine systems, Autonomous surface vehicles Abstract: For future autonomous marine vessels, better understanding of the ship's behavior and control performance will be essential. Traditional motion control systems for ships decouple the problem into high-level motion control of the ship and thrust allocation to achieve the desired control action through the available actuators. The benefit is a segmented software, aiding in development and commissioning. The drawback of this decoupling is that the high-level controller at best has an approximate model of the capabilities in the thruster system. This typically leads to a mismatch between desired and achieved force especially when the control becomes aggressive. In this paper, a model predictive controller is proposed to solve both tasks simultaneously and overcome this drawback. The controller is based on a low-speed ship and thruster model and the resulting optimization problem is solved using the ACADO toolkit. A simulation study of a supply vessel with only two thrusters is presented to investigate the behavior of the proposed controller close to the boundary of low-speed maneuvering. The results show that there are benefits to incorporating the proposed controller.
Paper VI172-04.11
PDF · Video · Backstepping Control of Heavy Lift Operations with Crane Vessel
Ye, Jun	Delft University of Technology
Reppa, Vasso	Delft University of Technology
Negenborn, Rudy	Delft University of Technology
Keywords: Nonlinear and optimal marine system control, Control architectures in marine systems, Decision support systems in marine systems Abstract: Offshore structures with large mass are installed and removed by heavy lift vessels. During offshore constructions, two safety-critical interconnected operations take place, the dynamic positioning of the vessel and the lifting of the heavy structure by an immovable boom crane on the vessel. Existing studies on offshore boom crane control either neglect the structure (load) dynamics in sway and the vessel movement, or consider the boom angle of the crane controllable. In this paper, we present a control scheme for underactuated offshore structure, taking into consideration the impact of the dynamic positioning of the vessel on three degrees of freedom physical load model. The proposed control scheme is designed following a backstepping approach using command filters to generate virtual control signals and their derivatives avoiding the analytic differentiation. Simulation results are obtained by applying the control scheme in a dynamic positioned vessel-load model showing that the controller is able to stablize the load position during the vessel dynamic positioning.
Paper VI172-04.12
PDF · Video · Transient Energy Management Controller for Hybrid Diesel-Electric Marine Propulsion Plants Using Nonlinear MPC
Planakis, Nikolaos	National Technical University of Athens
Karystinos, Vasileios	National Technical University of Athens
Papalambrou, George	National Technical University of Athens
Kyrtatos, N.P.	National Technical University of Athens
Keywords: Nonlinear and optimal marine system control, Marine system identification and modelling, Hybrid and alternative drive vehicles Abstract: A Nonlinear Model Predictive Control (NMPC) scheme is proposed for the optimal transient power-split problem of a hybrid diesel-electric marine propulsion plant. The NMPC scheme directly controls the torque output of the diesel engine and the electric motor generator ensuring that certain constraints concerning the engine overloading are applied. In this way, fuel consumption and NOx emissions can be reduced. The modeling for the controller design was based on experimental data gathered from the hybrid plant and on first principles for the diesel engine behavior and battery charging. The controller was experimentally tested in real-time operation. Results showed that controller rejected successfully load disturbances and maintained the desired rotational speed of the powertrain as well as the desirable state of charge in battery within limits.

VI173
Transportation and Vehicle Systems - Aerospace
VI173-01 Application of Vision Information in On-Board Aircraft Systems for Civil Aviation Safety   Open Invited Session, 5 papers
VI173-02 Guidance, Navigation, and Control in Aerospace   Regular Session, 29 papers

VI173-01
Application of Vision Information in On-Board Aircraft Systems for Civil Aviation Safety	Open Invited Session
Chair: Bauer, Peter	Institute for Computer Science and Control
Co-Chair: Watanabe, Yoko	ONERA/DCSD
Organizer: Watanabe, Yoko	ONERA/DCSD
Organizer: Burlion, Laurent	Rutgers
Organizer: Bauer, Peter	Institute for Computer Science and Control
Paper VI173-01.1
PDF · Video · Aircraft Vision-Based Landing Using Robust Extended Command Governors (I)
Burlion, Laurent	Rutgers
Kolmanovsky, Ilya V.	University of Michigan
Keywords: Guidance, navigation and control of vehicles, Avionics and on-board equipments, Modeling and simulation of transportation systems Abstract: We propose a novel vision-based constrained control solution to execute aircraft landing on an unknown runway. The method is based on an extended command governor which is tailored for a specific class of constrained linear systems with a single uncertain modeling parameter. The computational burden is reduced by exploiting a robust strongly returnable set in place of a robust invariant set and computing this set through the use of a binomial expansion. Numerical results illustrate the ability to 'safely' align the aircraft with the runway while satisfying the specified terminal constraints to execute the flare. Here the terminal constraints are efficiently handled by transforming them into time-varying constraints.
Paper VI173-01.2
PDF · Video · Voting-Based Fault Detection for Aircraft Position Measurements with Dissimilar Observations (I)
Gróf, Tamás	Institute for Computer Science and Control
Bauer, Peter	Institute for Computer Science and Control
Keywords: Health monitoring and diagnosis, Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Robot Navigation, Programming and Vision Abstract: In this article a fault detection algorithm for aircraft position measurements is proposed using redundant sensor information during landing scenarios. This work was developed in the framework of the VISION EU H2020 research project. The aircraft's position can be determined via instrumental landing system, GPS and camera measurements. Considering these three sources a two out of three voting logic can be developed. After transforming the measured data sets to a common format two different methods are constructed to execute voting. The first is simple and well known thresholding where the measured position values are compared pairwise and threshold violations registered. As dissimilar data noise strengths can make thresholding unreliable the second method proposed by the authors is supplemented with an additional statistical evaluation where the measurements undergo a two-sample Z-test. Both methods were evaluated off-line with Monte-Carlo computer simulation. The tests showed that the proposed statistical method outperforms the straightforward thresholding approach.
Paper VI173-01.3
PDF · Video · Vision-Integrated Navigation and Integrity Monitoring for Aircraft Final Approach (I)
Watanabe, Yoko	ONERA/DCSD
Keywords: Decision making and autonomy, sensor data fusion, Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Safety Abstract: This paper proposes a tightly-integrated Vision/GNSS navigation system for aircraft final approach. It consists of: i) a Kalman filter-based state estimator which handles time-delayed vision measurements by using image-trigger signals of camera device, and ii) an integrity monitoring (IM) function for sensor fault detection and Protection Level calculation. The integrity monitoring function is founded on a batch-realization of Kalman filter. The paper introduces an IM reset mechanism which re-initializes a fault detector regularly without relying on the current state estimation result, in order to remove an influence of past undetected faults on the newly reset detector. The proposed navigation system is tested on real sensor measurements, acquired onboard an unmanned aircraft in flight, with simulated GNSS faults. The test results show an improvement in fault detectability as well as in navigation performance by adding onboard vision information to classical aircraft navigation system.
Paper VI173-01.4
PDF · Video · Improvements and Detailed Evaluation of Ground Obstacle Position, Size and Orientation Estimation (I)
Bauer, Peter	Institute for Computer Science and Control
Keywords: Decision making and autonomy, sensor data fusion, Safety, Localization Abstract: This paper improves and evaluates in detail a previous work of the author dealing with position, size and orientation estimation of fixed ground obstacles in aircraft sense and avoid. The improvement is the better conditioning of the system of equations by the shift of one known variable. Detailed evaluation means Monte-Carlo simulation and comparison of the disc and line-based parameter estimation methods considering also non-straight own aircraft trajectories. This is the focal point of the article as only straight trajectory results were compared until now. The mean estimation errors (in percentages) and their standard deviations with the two different methods are compared. Finally, the line-based method was better applicable for rectangular objects as expected.
Paper VI173-01.5
PDF · Video · Infrared and Visible Airborne Targets ImageFusion with Applications to Sense and Avoid (I)
Zhang, Zhouyu	NUAA
Zhang, Youmin	Concordia University
Yunfeng, Cao	NUAA
Meng, Ding	NUAA
Keywords: Autonomous systems, Guidance, navigation and control of vehicles, Autonomous Vehicles Abstract: Machine vision has revealed great potential in recent years for Sense and Avoid (SAA) ability of Unmanned Aerial Vehicle (UAV). However, the target perception capability of machine vision largely depends on illumination, which restricts UAV to move safely in dark environment. Since images acquired by infrared and visible sensors are complementary in most cases, enhancing image qualities in dark environments by fusion of infrared and visible images is a promising solution. By considering the difficulties of image fusion for airborne targets, a Convolutional Sparse Representation (CSR) based infrared and visible airborne targets image fusion algorithm is proposed in this paper for enhancing SAA capability of UAV in dark environments, which contains three parts: image decomposition, image transformation and image reconstruction. A series of registered infrared and visible images containing airborne targets are selected to evaluate the algorithm proposed in this paper. Simulation results demonstrate the algorithm proposed in this paper effectively increases image qualities in dark environments. In the aspects of fusion metrics, the algorithm proposed in this paper can achieve favorable performance against other image fusion algorithms.

VI173-02
Guidance, Navigation, and Control in Aerospace	Regular Session
Chair: Tsourdos, Antonios	Cranfield University
Co-Chair: Nebylov, Alexander	State University of Aerospace Instrumentation
Paper VI173-02.1
PDF · Video · UAV Collision Avoidance Considering No-Fly-Zones
Lee, Hae-In	Cranfield University
Shin, Hyo-Sang	Cranfield University
Tsourdos, Antonios	Cranfield University
Keywords: Autonomous systems, Guidance, navigation and control of vehicles Abstract: This paper proposes a collision avoidance algorithm that ensures minimum separation between the vehicles considering multiple no-fly-zones. The proposed algorithm aims to provide a practical and efficient tactical de-confliction solution for Unmanned Aerial Vehicles (UAVs). The main idea is to utilise the differential geometry concept that computes the minimum heading angle change to avoid the obstacles, and to expand its applicability to polygonal obstacles. This paper validates the minimum separation and efficiency of the proposed algorithm both analytically and numerically.
Paper VI173-02.2
PDF · Video · Uneven Error Ellipsoid-Based Model Predictive Control for Planetary Safe Landings
Ge, Dantong	Beijing Institute of Technology
Cui, Pingyuan	Beijing Institute of Technology
Zhu, Shengying	Institute of Deep Space Exploration, School of Aerospace Enginee
Liang, Zixuan	Beijing Institute of Technology
Keywords: Autonomous systems, Guidance, navigation and control of vehicles, Decision making and autonomy, sensor data fusion Abstract: Considering the impact of both position and velocity estimate errors on hazard avoidance, this paper proposes an uneven error ellipsoid-based model predictive control for planetary landing missions. The uneven error ellipsoid model not only takes into account system position uncertainty at the moment, but also reflects how fast the system is approaching the nearby hazard in the position space. By repetitively computing the current space margin and the most dangerous direction, the system quantifies the threat posed by the environment as the lander descends to the surface. In order to perform a safe and precise landing, we apply model predictive control during descent and incorporate a hazard avoidance performance index into the problem. Then, we validate the proposed method in a Bennu-based asteroid landing scenario and demonstrate its effectiveness of improving landing safety.
Paper VI173-02.3
PDF · Video · ICL-Based Adaptive Switching Control Strategy for Aircraft Following Change in System Dynamics
Licitra, Ryan	University of Florida
Nivison, Scott	Air Force Research Laboratory
Doucette, Emily	Air Force Research Laboratory
Keywords: Control of systems in vehicles, Autonomous systems, Flight dynamics identification, formation flying Abstract: This paper investigates a switching control strategy for a fixed-wing flight vehicle subject to a dramatic change in dynamics. When a system-altering fault occurs, the vehicle switches from a fixed-gain, model-based controller to an adaptive control strategy that uses recorded data to identify the current system online. The adaptive controller employs a data-driven integral concurrent learning scheme to estimate the mass properties, as well as lift and drag coefficients online in an effort to match the faulted system as closely as possible with cataloged flight conditions. Stability is proven to be preserved even through failed attempts to switch from the adaptive controller back to a model-based controller, as long as the developed dwell-time and finite excitation conditions for the adaptive subsystem are satisfied.
Paper VI173-02.4
PDF · Video · Minimization of the Absolute Altitude of a Low-Flying Vehicle Due to the Desire to Smoothly Bend Around the Low-Frequency Components of the Sea Waves Ordinate
Nebylov, Alexander	State University of Aerospace Instrumentation
Knyazhskiy, Alexander	State University of Aerospace Instrumentation
Nebylov, Vladimir	State University of Aerospace Instrumentation
Keywords: Control of systems in vehicles, Guidance, navigation and control of vehicles, Modeling and simulation of transportation systems Abstract: The method for minimizing the altitude of a low-flying vehicle moving near the disturbed sea surface is proposed. The altitude is minimized due to the desire to go around the low-frequency components of sea waves, primarily due to the natural property of self-stabilization inherent in non-displacement vessels and wing in ground effect vehicles. It is possible to increase the efficiency of minimizing the altitude using the elevator and flaps. It is shown in the work that this control method is quite effective for small maneuverable vehicles with a wave emotion score above 4 points. In relation to wing in ground effect vehicles, this method of movement allows to save fuel by increasing the aerodynamic quality of wing in ground effect vehicles with the decrease in altitude.
Paper VI173-02.5
PDF · Video · Hybrid Control Trajectory Optimization for Air-Breathing Hypersonic Vehicle
Song, Jaebong	KAIST
Choi, Han-Lim	KAIST
Keywords: Control of systems in vehicles, Guidance, navigation and control of vehicles, Space exploration and transportation Abstract: Trajectory optimization problem for air-breathing hypersonic vehicle is addressed in this paper. The engine of hypersonic vehicle is assumed as a dual-mode scramjet engine which can be operated as a ramjet and scramjet for wide range of flight Mach number. Boost-skipping trajectory was proposed for range maximization of hypersonic vehicle, and based on this trajectory, flight modes of dual-mode scramjet are divided into three modes, which are ram mode, scram mode, non-powered mode. Hypersonic vehicle was modelled with consideration of changes of physical quantities over mode transition. To deal with discrete mode changes as well as continuous control, hybrid optimal control method is applied to this problem. Simulation results demonstrate that the optimized trajectory with hybrid control has better performance compared to cyclic mode transition trajectory. Also, a vehicle which imitates the characteristics of dual-mode scramjet vehicle is implemented to optimize the trajectory. The results suggest that the hybrid optimal control can be applied to the trajectory optimization of a dual-mode scramjet vehicle considering the mode transition in infinite time horizon.
Paper VI173-02.6
PDF · Video · A Comparison of Model-Based and Black-Box Methods for Speed Estimation in Aircraft
Papa, Gianluca	Politecnico Di Milano
Tanelli, Mara	Politecnico Di Milano
Panzani, Giulio	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Control of systems in vehicles, Vehicle dynamic systems Abstract: The anti-skid control system in aircraft is conned to the landing-gear subsystem, and, for safety reasons, it must rely on local signals only. Therefore, it can use only two measurements: the wheel speed and the pilot braking pressure request. Therefore, the antiskid control logics are generally wheel deceleration-based, as the slip cannot be computed since the aircraft speed is not available. The vehicle speed estimation is commonly done in automotive systems, made possible also by the presence of additional sensors usually coming from an Inertial Measurement Unit (IMU). This work explores how the aircraft speed can be estimated using only the landing gear signals, and if the resulting estimate can be accurate enough to be used in closed-loop with a slip-based anti-skid controller. To do so, two estimation approaches are considered: a sliding-mode model-based one, and a black-box approach grounded on recurrent neural networks. Experimental results are shown, witnessing the potential of blackbox approaches.
Paper VI173-02.7
PDF · Video · Nonlinear Cascade Control for a Quadrotor Transporting a Slung Load
Zong-yang, Lv	Dalian University of Technology
Wu, Yuhu	Dalian University of Technology
Xia, Weiguo	Dalian University of Technology
Wang, Wei	Dalian University of Technology
Keywords: Control of systems in vehicles, Vehicle dynamic systems, Modeling and simulation of transportation systems Abstract: This paper focuses on the motion control problem for a quadrotor with a cable-suspended payload (QCSP). A dynamical model of a QCSP is proposed by the Lagrangian approach. The air resistance of the payload are considered in the model building. Based on such a dynamical model, a novel nonlinear three-loop cascade controller is proposed to realize accurate and stable velocity control for the payload of a QCSP, and the exponential stability of the whole system is proved. Numerical simulations implemented in a Matlab/SimMechanics environment demonstrate the effectiveness of the designed controller and the proposed model.
Paper VI173-02.8
PDF · Video · Threshold Bundle-Based Task Allocation for Multiple Aerial Robots
Li, Teng	Cranfield University
Shin, Hyo-Sang	Cranfield University
Tsourdos, Antonios	Cranfield University
Keywords: Decision making and autonomy, sensor data fusion, Autonomous systems, Mission control and operations Abstract: This paper focuses on the large-scale task allocation problem for multiple Unmanned Aerial Vehicles (UAVs). One of the great challenges with task allocation is the NP-hardness for both computation and communication. This paper proposes an efficient decentralised task allocation algorithm for multiple UAVs to handle the NP-hardness while providing an optimality bound of solution quality. The proposed algorithm can reduce computational and communicating complexity by introducing a decreasing threshold and building task bundles based on the sequential greedy algorithm. The performance of the proposed algorithm is examined through Monte-Carlo simulations of a multi-target surveillance mission. Simulation results demonstrate that the proposed algorithm achieves similar solution quality compared with benchmark task allocation algorithms but consumes much less running time and consensus steps.
Paper VI173-02.9
PDF · Video · Distributed Formation Tracking for Multiple Quadrotor Helicopters
He, Changran	Chinese University of Hong Kong
Huang, Jie	The Chinese University of Hong Kong
Keywords: Flight dynamics identification, formation flying, Control of systems in vehicles, Cooperative control Abstract: In this paper, we study the leader-following formation tracking problem for multiple quadrotor helicopters over static and connected communication networks via the distributed observer approach. With the virtual leader system being modeled by a linear exosystem, we develop a distributed control law that can accomplish the formation tracking for a large class of leader's trajectories.
Paper VI173-02.10
PDF · Video · Fault Detection, Isolation and Adaptive Augmentation for Incremental Backstepping Flight Control
Ignatyev, Dmitry	Cranfield University
Shin, Hyo-Sang	Cranfield University
Tsourdos, Antonios	Cranfield University
Keywords: Flight dynamics identification, formation flying, Guidance, navigation and control of vehicles, Health monitoring and diagnosis Abstract: Uncertainties caused by unforeseen malfunctions of the actuator or changes in aircraft behavior could lead to aircraft loss of control during flight. The paper presents a Two-Layer Framework (TLF) augmenting Incremental Backstepping (IBKS) control algorithm designed for an aircraft. IBKS uses angular accelerations and current control deflections to reduce the dependency on the dynamics model. Nevertheless, knowledge of the control effectiveness is still required for proper tracking performance and stability guarantee and becomes essential in a case of failure. The proposed TLF is designed to detect possible problems such as a failure or presence of unknown actuator dynamics and to adapt the control effectiveness. At the first layer, the system performs detection and isolation of possible failures. After a problem being detected and isolated, the algorithm initiates the second-layer adaptation of the individual effectiveness of the failed control effector. For some critical scenarios, when the input-affine property of the IBKS is violated, e.g., for a combination of multiple failures, the IBKS could lose stability. Meanwhile, the proposed TLF-IBKS algorithm has improved tracking and stability performance.
Paper VI173-02.11
PDF · Video · Experimental Comparison of Nonlinear Guidance Laws for Unmanned Aircraft
Sedlmair, Nicolas	Hamburg University of Technology
Theis, Julian	Hamburg University of Technology
Thielecke, Frank	Hamburg University of Technology
Keywords: Guidance, navigation and control of vehicles Abstract: Two aircraft guidance algorithms from the literature, the Non-Linear Guidance Law (NLGL) and the Nonlinear Differential Geometric Path-Following Guidance Law (NDGPFG), are assessed using a 25 kg unmanned aerobatic aircraft. The paper provides experimental results of the first flight test with the NDGPF. Prior to the real world application, a simulation study is performed to mitigate the risk. For both guidance laws, tracking performance is investigated on a purely kinematic model with unlimited control bandwidth first. Both laws provide superb tracking and the NDGPFG achieves exact path-following, i.,e. zero track error. In a second simulation, a high-fidelity model of the aircraft is used. This model includes parasitic dynamics and hence has a finite control bandwidth. In contrast to the results with the purely kinematic model, neither of the algorithms achieves exact path-following with the high-fidelity model. Nevertheless, both guidance laws provide good tracking performance and prove feasible in varying environmental conditions. This observation is finally confirmed in the flight test experiment.
Paper VI173-02.12
PDF · Video · Quaternion-Based Generalized Super-Twisting Algorithm for Spacecraft Attitude Control
Kristiansen, Bjørn Andreas	NTNU Norwegian University of Science and Technology
Groette, Mariusz Eivind	Norwegian University of Science and Technology
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Keywords: Guidance, navigation and control of vehicles Abstract: A second-order sliding mode control, the generalized super-twisting algorithm (GSTA), is used for attitude control of a spacecraft actuated by reaction wheels for pointing and a slewing maneuver. Magnetorquers are used for reaction wheel momentum dumping. Simulation results are based on a typical CubeSat. The results produced by using the GSTA are compared to sliding mode control (SMC) and a proportional–derivative (PD) controller. The simulation shows that the GSTA performs better than the SMC for the pointing and slewing maneuvers when it comes to settling time and accuracy due to reduced chattering. Compared to the PD controller, the GSTA performs similarly under the chosen conditions, with a shorter settling time for pointing, and longer settling time for slewing. The GSTA applies a torque to the reaction wheels with lower spikes and less chattering than the PD controller.
Paper VI173-02.13
PDF · Video · Spacecraft Attitude and Angular Rate Tracking Using Reaction Wheels and Magnetorquers
Groette, Mariusz Eivind	Norwegian University of Science and Technology
Gravdahl, Jan Tommy	Norwegian University of Science and Technology (NTNU)
Johansen, Tor Arne	Norwegian University of Science and Technology
Larsen, Jesper Abildgaard	Aalborg University
Vidal, Edgard Martinez	NanoAvionics
Surma, Egidijus	NanoAvionics
Keywords: Guidance, navigation and control of vehicles Abstract: Spacecraft remote sensing applications may require slew maneuvers that prioritize small ground track errors during imaging, low power consumption and quick settling time. This paper investigates attitude control with a time-varying reference for a spacecraft model actuated by reaction wheels and magnetorquers, showing (a) an analytical solution for obtaining the required reaction wheel momentum reference in a rotational maneuver; and (b) the conditions for asymptotic convergence of attitude and angular rate tracking using a quaternion-based nonlinear control law; and (c) simulation results for a 6U CubeSat in Low-Earth-Orbit performing fixed-vector pointing and slew maneuvers. In particular, if a remote sensing spacecraft shall execute a short slew maneuver and the collection of data is not required to follow a fixed ground track, then utilizing the reference quaternion propagated from initial condition may be preferred. Based on the simulated single-axis slew maneuvers, better attitude tracking performance may be achieved when the magnetorquers are actively managing the reaction wheel momentum, but decreasing their effects in the transient period may result in quicker settling time depending on chosen error tolerances.
Paper VI173-02.14
PDF · Video · Nonlinear Dynamic Inversion Autopilot Design for Dual-Spin Guided Projectiles
Tipan Rivera, Steven Patricio	Cranfield University
Thai, Sovanna	French-German Research Institute of Saint-Louis (ISL)
Proff, Michael	ISL - French German Research Institute of Saint-Louis
Theodoulis, Spilios	ISL
Keywords: Guidance, navigation and control of vehicles, Autonomous systems, Control of systems in vehicles Abstract: This paper deals with the autopilot design for a 155-mm dual-spin projectile equipped with a course correction fuze (CCF). This class of projectiles is subject to high nonlinearities and to strongly coupled dynamics between its pitch and yaw channels. To overcome these difficulties a Nonlinear Dynamic Inversion (NDI) based autopilot is proposed. This autopilot possesses a cascade structure where an inner loop linearises the nonlinear system dynamics and an outer loop enables to impose the desired system closed-loop dynamics. The configuration of a dual-spin projectile requires the development of two separate control loops, one for the roll channel and another for the pitch/yaw channels. The pitch/yaw controller is developed under a Time Scale Separation (TSS) scheme. This not only helps to accelerate the design of the control laws but also to achieve a satisfactory level of robustness. The autopilots are also validated with a nonlinear 7-DOF simulation.
Paper VI173-02.15
PDF · Video · Hardware-In-The-Loop Evaluation of a Robust C* Control Law on MuPAL-Alpha Research Aircraft
Takase, Ryoichi	The University of Tokyo
Marcos, Andres	University of Bristol
Sato, Masayuki	Japan Aerospace Exploration Agency
Suzuki, Shinji	The University of Tokuo
Keywords: Guidance, navigation and control of vehicles, Avionics and on-board equipments Abstract: This article presents the design and evaluation of a robust C* control law through Hardware-In-the-Loop Simulation (HILS) of JAXA's research aircraft called Multi-Purpose Aviation Laboratory (MuPAL-alpha). The C* control law, which is a widely used flight control architecture in aviation industries, is designed using structured H-infinity synthesis. This design method provides robustness of the controller for flight condition changes and uncertainties associated with the dynamics of MuPAL-alpha. HILS tests allow on-ground evaluation of controllers using actual actuators. The HILS results show that the designed controller adequately tracks pilot commands in the presence of airspeed variation, uncertainties in the modeling of the onboard actuators, and wind gust.
Paper VI173-02.16
PDF · Video · LIDAR-Based Gust Alleviation Control System: Obtained Results and Flight Demonstration Plan
Hamada, Yoshiro	Japan Aerospace Exploration Agency
Kikuchi, Ryota	Japan Aerospace Exploration Agency
Inokuchi, Hamaki	Japan Aerospace Exploration Agency
Keywords: Guidance, navigation and control of vehicles, Avionics and on-board equipments Abstract: This paper presents a flight demonstration project for LIDAR-based gust alleviation control currently planned in Japan. The onboard coherent Doppler LIDAR has already been developed and validated by flight experiments. The wind velocity estimation algorithm has also been developed which can estimate two-dimensional distribution of wind field between two laser beams of the LIDAR system. These components are to be incorporated with the preview control law which utilizes the estimated wind velocities in front of the aircraft, and to be validated in the flight demonstration. This paper shows the results obtained so far and introduces the flight demonstration under planning.
Paper VI173-02.17
PDF · Video · Asymmetric Barrier Lyapunov Function Based Practical Fixed-Time Control of Vertical Take-Off/ Vertical Landing Reusable Launch Vehicles with Partial State Constraints
Ju, Xiaozhe	Harbin Institute of Technology
Wang, Feng	Harbin Institute Technology, Harbin,
Wei, Changzhu	Harbin Institute of Technology
Zhang, Liang	Sun Yat-Sen University
Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles, Autonomous systems Abstract: In order to stabilize the vertical take-off/ vertical landing reusable vehicles in aerodynamic guidance phase against complex disturbances and partial state constraints, an asymmetric logarithm-type barrier function and asymmetric double-exponential-type barrier function are proposed, where the latter is smooth with respect to system states and has a higher application value compared with the logarithm-type one. Based on the barrier functions and practical fixed-time control theory, two practical fixed-time control law are derived to drive the attitude orders tracking errors to a small neighborhood of the origin within a fixed time and ensure the attitude constraints unviolated. Simulation results demonstrate the efficiency of the controllers.
Paper VI173-02.18
PDF · Video · Design of a Steering Law for Control Moment Gyro Clusters Based on a Set of Initial Positions
Dubois, Louis	CNES
Evain, Hélène	CNES
Meyniel, Vincent	CNES
Alazard, Daniel	Université De Toulouse - ISAE
Rognant, Mathieu	ONERA
Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles, Autonomous systems Abstract: This paper addresses the issue of controlling a spacecraft with a redundant pyramidal Control Moment Gyro (CMG) cluster. A rapid analysis of the mathematical problem to steer the attitude control system is carried out with a focus on how to use the redundancy to start the attitude maneuvers in optimal conditions. A set of initial positions that ensures no singularity is encountered during an unidirectional maneuver is defined thanks to the study of the topology of the cluster and simulations. The desired initial position is derived onboard the spacecraft from the direction of the maneuver. After reaching this position without creating torque errors thanks to the null-motion trajectories, the Moore-Penrose steering law is used. The cases of a pyramidal six-CMG cluster without CMG failures and with two failures are studied. Finally, simulations show the characteristics of the designed steering laws.
Paper VI173-02.19
PDF · Video · Attitude Tracking Control for Spacecraft with Fixed-Time Convergence
Chen, Wei	Beihang University
Liu, Mingmin	Shanghai Aerospace Control Technology Institute
Hu, Qinglei	Beihang University
Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles, Mission control and operations Abstract: This work mainly discusses the attitude tracking issue of spacecraft which ensures fixed-time convergence property. To achieve this, the attitude tracking dynamics model is first established. Then a novel sliding manifold is constructed based on the presented sufficient conditions of fixed-time stability. Moreover, a sliding mode controller is developed to ensure fixed-time convergence. Also, the closed-loop fixed-time stability of the whole system is proven to be guaranteed based on Lyapunov stability theory. Finally, the simulation results are provided to verify the superior performance of the designed controller.
Paper VI173-02.20
PDF · Video · Actor-Critic-Based Optimal Adaptive Control Design for Morphing Aircraft
Lee, Hanna	Seoul National University
Kim, Seong-hun	Seoul National University
Kim, Youdan	Seoul National University
Keywords: Guidance, navigation and control of vehicles, Learning and adaptation in autonomous vehicles, Navigation, Guidance and Control Abstract: An online actor-critic-based control design strategy is proposed for a variable span and sweep morphing wing aircraft considering the morphing parameters as control effectors, which makes the system non-affine in control. By adopting the dynamic property of the morphing system, the augmented morphing aircraft system is formulated to be affine in control input. Through the online actor-critic-based control design for the augmented system, the proposed method has an advantage in terms of control design for the non-affine complex system with uncertainty, because the time-varying internal dynamic model caused by the morphing system is not required. From the augmented dynamic model, the control input frequency constraints of the morphing system, which are generally considered slow can also be addressed. Numerical simulation is performed to demonstrate the effectiveness of the proposed scheme.
Paper VI173-02.21
PDF · Video · Robust Fuzzy Attitude Stabilization of Networked Spacecraft under Actuator Saturation and Persistent Disturbance
Xu, Shidong	Nanjing University of Aeronautics and Astronautics
Huang, Zheng	Nanjing University of Aeronautics and Astronautics
Keywords: Guidance, navigation and control of vehicles, Navigation, Guidance and Control, Mission control and operations Abstract: This paper is concerned with event-triggered robust attitude control of networked spacecraft with actuator saturation and persistent bounded disturbance via Takagi-Sugeno (T-S) fuzzy approach. Based on aperiodic sampling, a discrete-time event-triggered scheme avoiding Zeno phenomenon naturally is adopted to reduce communication burden within network. Based on the T-S fuzzy model of spacecraft, an event-triggered fuzzy controller subject to saturation constraint is established to perform robust attitude stabilization of spacecraft. Furthermore, in comparison with the most often used H_infty performance, L_infty-gain performance is employed to handle the persistent bounded disturbances. By virtue of convex optimization method, the problem of controller synthesis is formulated in terms of a set of linear matrix inequalities (LMIs). Finally, simulation results are provided to prove the effectiveness of the fuzzy control scheme.
Paper VI173-02.22
PDF · Video · A Generalized Control Law for Uniform, Global and Exponential Magnetic Detumbling of Rigid Spacecraft
Petit, Nicolas	MINES ParisTech
Sarras, Ioannis	ONERA-The French Aerospace Lab
Keywords: Micro-nano-aerospace vehicles/satellites, Guidance, navigation and control of vehicles, Autonomous systems Abstract: The problem of magnetic detumbling, also known as magnetic momentum unloading, is considered. The objective is to stabilize a rigid spacecraft angular velocity to zero only through magnetic actuation, i.e. magneto-torquers. We propose a generalized control law that is uniformly, globally exponentially stabilizing (UGES) and show that the celebrated b-dot law is one particular case of this law. Furthermore, we provide an explicit (time-varying) strict Lyapunov function to establish the stability claim.
Paper VI173-02.23
PDF · Video · Predictive Pursuit-Evasion Game Control Method for Approaching Space Non-Cooperative Target
Chai, Yuan	Northwestern Polytechnical University
Luo, Jianjun	Northwestern Polytechnical University
Wang, Mingming	Northwestern Polytechnical University
Yu, Min	Northwestern Polytechnical University
Keywords: Control of systems in vehicles, Trajectory Tracking and Path Following, Automatic control, optimization, real-time operations in transportation Abstract: This paper designs the predictive pursuit-evasion game-based orbit control method for the chasing spacecraft to approach a space uncooperative maneuvering target. Firstly, the trajectory planning algorithm combines RRT* and cubic splines to generate a feasible reference trajectory in the relative motion space for the chaser, which enables to deal with the boundary constraints and avoid collisions with the attachments of target. Then, based on the dynamics model, input constrains and objective functions, the pursuit-evasion game model between the target and the chaser is formulated, in which each one acts independently to satisfy its own objective function. With the game formulation, a predictive pursuit-evasion game controller for the chaser is designed to track reference trajectory. Under the frame of model predictive control, the multiple objective constraint optimization can be transferred into to quadratic programming problem to handle input constraints. By predicting opponent's best move and changing its optimal strategy for its benefit iteratively, the saddle points of the game can be obtained without opponent's maneuvering. Numerical simulations verify the effectiveness of the predictive pursuit-evasion game control method for approaching an uncooperative target.
Paper VI173-02.24
PDF · Video · Are External Magnetic Disturbances Suppressed by Magnetometer Noise When Estimating a Nanosatellite’s Rotational Motion?
Cilden-Guler, Demet	Istanbul Technical University
Kaymaz, Zerefsan	Istanbul Technical University
Hajiyev, Chingiz	Istanbul Technical Univ
Keywords: Micro-nano-aerospace vehicles/satellites, Decision making and autonomy, sensor data fusion, Flight dynamics identification, formation flying Abstract: In this study, a three-axis magnetometer based attitude estimation algorithm that includes external magnetic field model is presented. The magnetic fields from the external sources are considered in the geomagnetic field model used in the attitude estimation algorithm and not treated as error sources on the magnetometer. By this way, it was aimed to model the magnetometer better by taking into account the effects of the space environment and perform a higher accuracy in the estimation of the rotational motion of the satellite. However, a problem arose such that the magnetometer sensor noise levels used in the attitude estimations appear to mask the effects of the external magnetic field. The fact that with the developing technologies in micro-electro-mechanical systems, the magnetometer noise might be keep decreasing, led us to investigate the magnitude of the noise level that would suppress the external field.
Paper VI173-02.25
PDF · Video · Design of Satellite Maneuvers for Inertia Parameter Estimation
Nainer, Carlo	University of Lorraine
Gilson, Marion	University of Lorraine
Garnier, Hugues	University of Lorraine
Pittet, Christelle	CNES
Evain, Hélène	CNES
Keywords: Micro-nano-aerospace vehicles/satellites, Flight dynamics identification, formation flying, Guidance, navigation and control of vehicles Abstract: This paper addresses the design of satellite maneuvers for the inertia estimation. The experiment design is an important step in system identification, since the choice of the excitation signal has a great influence on the precision of the parameter estimates. In order to design an optimal maneuver, the proposed method uses a cubic B-spline representation of the trajectory. The optimized maneuver is obtained through minimization of a functional based on the Fisher information matrix. The optimization process considers the physical constraints due to the saturation of the actuators. The effectiveness of the generated trajectory is evaluated via Monte Carlo simulations using the model of a satellite-type platform. Moreover, the optimized maneuver has been also tested on a real platform in a zero-gravity experiment where, due to the limited duration of the tests, the achievement of the maximum excitation is of great importance.
Paper VI173-02.26
PDF · Video · Utilisation of the Controllable Inertial Morphing for Providing Spacecraft with Acrobatic Attitude Capabilities
Trivailo, Pavel	RMIT Univ
Rittweger, Andreas	German Aerospace Center, Institute of Space Systems
Theil, Stephan	German Aerospace Center, Institute of Space Systems
Keywords: Modeling and simulation of transportation systems, Guidance, navigation and control of vehicles, Space exploration and transportation Abstract: The paper is exploring a new method of controlling of the attitude dynamics of the spacecraft with non-zero angular momentum, using deliberately applied changes to the spacecraft inertial properties, called inertial morphing (IM). This method does not employ classical gyroscopic devices, nevertheless it enables the spacecraft to perform various acrobatics manoeuvres, allowing interchanges between stable and unstable states. In one case scenario, it enables transformation of the stable spin into unstable flipping motion and establishment of the desired periods of the flips at various stages of the procedure. Special consideration is given to the selection of the controllable morphed parameters to impose the desired periods and patterns of the acrobatics. This paper exploits use of the unstable flipping motions of the systems and due to established mini-max relationships for the flipping periods, enables selection of the system parameters, maximizing or minimizing the values of the periods for faster (more agile) maneuvers. In the other scenario, IM is used to transfer the regular spin about one body axis into the regular spin about another nominated body axis. Numerous illustration cases are presented and application of the new enhanced capabilities are discussed in detail. For example, paper presents a scenario of the reconfiguration of the articulated spacecraft with its segments being inverted during the acrobatic procedure in the desired way, which may open new possibilities during the spacecraft operation, including re-boost and landing.
Paper VI173-02.27
PDF · Video · Tracking Neighboring Quasi-Satellite Orbits Around Phobos
Muralidharan, Vivek	Purdue University
Weiss, Avishai	University of Michigan
Kalabic, Uros V.	Mitsubishi Electric Research Laboratories (MERL)
Keywords: Space exploration and transportation, Guidance, navigation and control of vehicles Abstract: We consider the orbital maintenance problem on a quasi-satellite orbit about the Martian moon, Phobos. The orbit is computed using a high-fidelity ephemeris model so that the major sources of disturbances are due to measurement error. Two types of orbit maintenance schemes are considered. The first is based on asymptotically tracking the desired trajectory and the second is based on stabilizing to the manifold of trajectories that share the same Jacobi constant as the reference trajectory. The latter can be done because trajectories with the same Jacobi constant are in the neighborhood of one another. The results show that the trajectory-tracking scheme has lower fuel consumption when tracking must be precise and that the approach of stabilizing to a manifold has better fuel consumption at the expense of tracking.
Paper VI173-02.28
PDF · Video · Spacecraft INS/CNS/Pulsar Integrated Positioning Navigation and Timing
Nebylov, Alexander	State University of Aerospace Instrumentation
Benzerrouk, Hamza	ECOLE DE TECHNOLOGIE SUPERIEURE ETS Montreal, QC, CANADA
Nebylov, Vladimir	State University of Aerospace Instrumentation
Keywords: Kalman filtering techniques in automotive control, Autonomous systems, Navigation Abstract: In this paper, novel algorithms of information fusion between Pulsars timing, ranging and positioning with orbital dynamical model of explorer spacecraft, all combined with inertial navigation systems are demonstrated. Pulsar/CNS were recently investigated using multiple variant of nonlinear filtering approaches. However, due to the coloured measurement noise and Shot noise from pulsars time of arrival measurement, robust nonlinear filters are derived based on Gauss Quadrature /Cubature Kalman approximations in the Gaussian sum framework . Clear improvement are demonstrated based on Crab pulsar data and simulation of these novel robust filtering approaches against non linearity and also against non Gaussian coloured measurement noises.
Paper VI173-02.29
PDF · Video · Pilot Assessment of Fault-Tolerant PID Flight Controller for Elevator Efficiency Reduction Via Hardware-In-The-Loop Simulations
Sato, Masayuki	Japan Aerospace Exploration Agency
Takase, Ryoichi	The University of Tokyo
Suzuki, Shinji	The University of Tokuo
Keywords: Navigation, Guidance and Control, Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles, Man-in-the-loop systems Abstract: This note presents the pilot assessment of a Fault-Tolerant Control (FTC) law for elevator efficiency reduction via Hardware-In-the-Loop Simulations (HILS) with a research airplane MuPAL-alpha. The FTC is supposed to be a PID controller from the viewpoint of the practicality and applicability, viz., conventional Stability/Control Augmentation System (S/CAS) structure is adopted. The PID-FTC is designed with the consideration of onboard actuator uncertainties as well as the possible loss of efficiency (from 0% loss up to 80% loss) in the framework of H_infty control with hinfstruct command implemented in Matlab. In HILS, the pilot is required to have steady climb and descent under the condition that the elevator efficiency is gradually reduced in a software level. HILS results indicate that the designed PID-FTC works well when the elevator efficiency decreases even under wind gust conditions.

VI174
Transportation and Vehicle Systems - Transportation Systems
VI174-01 Control in Transportation Systems   Regular Session, 6 papers
VI174-02 Intelligent Transportation Systems   Regular Session, 17 papers

VI174-01
Control in Transportation Systems	Regular Session
Chair: Timotheou, Stelios	University of Cyprus
Co-Chair: Qin, Bin	Hunan University of Technology
Paper VI174-01.1
PDF · Video · Traffic Control on Freeways Using Variable Speed Limits
Dörschel, Lorenz	RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Integrated traffic management Abstract: A new practical oriented feedback control structure for traffic control on freeways using variable speed limits is presented. Therefore, a simple controller structure which satisfies legal and operator demands for a single road is derived from system analysis of a macroscopic traffic model. Furthermore, this road-controller is accompanied with a sequence control and a road-network-controller. In contrast to existing work, novel control variables are used within controller design and tuning guidelines for non-control-engineers are given. The proposed control structure is investigated in simulations, which have been validated using experimental data from the German autobahn.
Paper VI174-01.2
PDF · Video · Unscented Stochastic Model Predictive Perimeter Control of Uncertain Two-Regions Urban Traffic
Harati, Ehsan	University of Cyprus, KIOS Research and Innovation Centre of Exc
Timotheou, Stelios	University of Cyprus
Panayiotou, Christos	Univ of Cyprus
Keywords: Integrated traffic management, Adaptive and robust control of automotive systems, Nonlinear and optimal automotive control Abstract: In this article, Stochastic Model Predictive Control (SMPC) is employed for optimal perimeter control of traffic flow with uncertain Macroscopic Fundamental Diagram (MFD), traffic accumulation and traffic demand of two regions. Two regions urban traffic networks are described through the MFD. The MFD is a fundamental relation between average flow (production) and density (accumulation) in urban regions. Although the MFD is often assumed as a simple deterministic curve, possible heterogeneity in urban regions results in large scattering of the MFD pattern. Traffic accumulation is considered uncertain due to limited sources of measurements. Moreover, traffic demand is based on the stochastic nature of drivers. The stochastic uncertainty is modeled through appropriate probability distribution functions for MFD, traffic accumulation and demand. Simulation results show the superiority of the proposed method compared to deterministic MPC in the presence of model mismatch.
Paper VI174-01.3
PDF · Video · Control of Traffic Light Timing Using Decentralized Deep Reinforcement Learning
Maske, Harshal	University of Illinois, Urbana Champaign
Chu, Tianshu	Uhana Inc
Kalabic, Uros V.	Mitsubishi Electric Research Laboratories (MERL)
Keywords: Integrated traffic management, Automatic control, optimization, real-time operations in transportation, Intelligent transportation systems Abstract: In this work, we introduce a scalable, decentralized deep reinforcement learning (DRL) scheme for controlling traffic signalization. The work builds on previous results using multi-agent DRL, with a new state representation and reward definitions. The state representation is a coarse image of traffic and the definitions of reward functions are tested based on the simulated Monaco SUMO Traffic (MoST) scenario. Based on extensive numerical experimentation, we have found the most appropriate choice of the reward function is related to minimizing the average amount of time vehicles spent in the network, but with various modifications that improve the learning process. The resulting algorithm performs better than the previous one on which it is based and markedly better than a non-learning based, greedy policy.
Paper VI174-01.4
PDF · Video · Emergency-Induced Effects on High-Speed Railway Networks: A Complex Network Theory's Perspective
Ma, Junfeng	Central South University, School of Automation,
Ma, Shan	Central South University
Peng, Tao	Central South University
Gui, Weihua	Central South University
Keywords: Modeling and simulation of transportation systems, Safety, Information processing and decision support Abstract: In this paper, we analyze the characteristics of high-speed railway networks in the presence of emergencies from a complex network theory's perspective. First, we represent the railway network by a graph where the nodes denote stations and the edges denote train flows. For a railway network system, the punctuality of trains and the number of trains running through stations are the two main factors for evaluating emergency-induced effects. We thus assign each edge of the graph a weight which is determined by these two key quantities. Then we propose a method to estimate the delay of trains and some metrics are introduced to analyze the properties of the railway network under disruptive events. These metrics may be also used to quantify the influences of the emergencies. Finally, examples are provided to illustrate the developed theory.
Paper VI174-01.5
PDF · Video · Scheduling Algorithm Supporting V2X Communications Based on NOMA Access
Bouhamed, Emna	Enet'com
Marouane, Hend	Enet'com
Aladin, Trabelsi	National School of Electronics and Telecommunications (ENET'COM)
Zerai, Faouzi	Enet'com
Keywords: Safety, Intelligent transportation systems, Automatic control, optimization, real-time operations in transportation Abstract: 5G network must support a large number of Vehicle-to-Everything (V2X) connections with high throughput and low latency.The existing resource allocation scheme based on orthogonal multiple access (OMA) seems to be unsuitable for dense network due to the limitation of the spectral bandwidth and the available resources. This work, presents a new scheduling algorithm scheme called SAVCN (Scheduling Algorithm for V2X Communication based on NOMA), for 5G network. In non-orthogonal multiple access (NOMA) scheme, the same resource can be shared by several transmitters. The proposed algorithm improves network performances in terms of Quality of Service (QoS), throughput, fairness and error rate. In fact SAVCN allocate efficiently the available resource blocks (RBs) in order to maximize the system throughput by taking into account the minimal distance between transmitters and receivers. It maximizes also the number of served V2X users and minimizesthe bit error rate. Simulation results indicate promising performance for SAVCN.
Paper VI174-01.6
PDF · Video · Ultracapacitor Energy Storage Systems Based on Dynamic Setting and Coordinated Control for Urban Trains
Wang, Xin	Hunan University of Technology
Luo, Yingbing	Hunan University of Technology
Qin, Bin	Hunan University of Technology
Peng, Junming	Hunan University of Technology
Zhou, Yu	Hunan University of Technology
Sun, Zhongcan	Hunan University of Technology
Keywords: Control system design Abstract: The supply voltage of traction systems fluctuates frequently due to acceleration and braking during urban rail train running process. In order to achieve better performance for ultracapacitor energy storage systems, a bilateral ultracapacitor energy storage system structure is adopted, and a method based on dynamic setting and coordination is proposed, in which the charge and discharge voltage thresholds of ultracapacitors are dynamically set and the energy flows are coordinated controlled between the bilateral ultracapacitor energy storage systems. The simulation results show that the proposed control strategy can achieve good energy-saving effect and stabilize the traction network voltage under the premise of balanced use of the ultracapacitor energy storage systems.

VI174-02
Intelligent Transportation Systems	Regular Session
Chair: Sacone, Simona	Univ of Genova
Co-Chair: Fatahi Valilai, Omid	Jacobs University Bremen GGmbH
Paper VI174-02.1
PDF · Video · Vehicle Emission Control on Road with Temporal Traffic Information Using Deep Reinforcement Learning
Xu, Zhenyi	University of Science and Technology of China
Cao, Yang	Univercity of Science and Technology of China
Kang, Yu	University of Science and Technology of China
Zhao, Zhenyi	University of Science and Technology of China
Keywords: Intelligent transportation systems Abstract: The increased vehicle usage significantly aggravate the urban air pollution, which have great impact on the public health. Therefore, it is necessary to make proper traffic control policies and reduce traffic emissions. However, it is difficult to establish control strategies based on modeling methods, and carry out online control based on historical traffic information for the complex time-varying characteristics of emissions. In this paper, we present a deep reinforcement learning emission control strategy, which automatically learns the optimal traffic flow and speed limits to reduce traffic emission on the target road segment based on the temporal traffic information. The proposed approach is evaluated on real world vehicle emission data in Hefei. And the results demonstrate the effectiveness of the proposed approach against baseline methods.
Paper VI174-02.2
PDF · Video · Altruistic Control of Connected Automated Vehicles in Mixed-Autonomy Multi-Lane Highway Traffic
Keskin, Musa Furkan	Chalmers University of Technology
Peng, Bile	Chalmers University of Technology
Kulcsar, Balazs	Chalmers University of Technology
Wymeersch, Henk	Department of Signals and Systems, Chalmers University of Techno
Keywords: Intelligent transportation systems, Autonomous Vehicles, Motion control Abstract: We consider the problem of altruistic control of connected automated vehicles (CAVs) on mixed-autonomy multi-lane highways to mitigate moving traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. In order to efficiently solve the resulting non-convex mixed-integer nonlinear programming (MINLP) problem, we decompose it into three non-convex subproblems, each of which can be transformed into a convex quadratic program via penalty based reformulation of the optimal velocity with relative velocity (OVRV) car-following model. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies on both single- and multi-lane roads.
Paper VI174-02.3
PDF · Video · Collision Risk Assessment Based on Line of Sight
Kumari, Simran	Indian Institute of Technology, Kharagpur
Ghosh, Susenjit	Indian Institute of Technology Kharagpur
Mitra, Desham	Indian Institute of Technology, Kharagpur, India
Sengupta, Somnath	IIT Kharargpur
Mukhopadhyay, Siddhartha	IIT KGP
Keywords: Intelligent transportation systems, Decision making and autonomy, sensor data fusion, Information processing and decision support Abstract: Collision avoidance of vehicles is an essential safety feature of modern-day vehicles. The widely used Time to Collision (TTC) approach for collision risk assessment provides a false alarm in many situations like road turning, traffic intersection, and near-miss. Therefore, this risk assessment approach cannot be applied to many realistic scenarios where knowledge of future trajectory plays an important role in collision risk assessment. After evaluating conventionally used techniques, this paper proposes a novel probabilistic approach of collision risk assessment utilizing Line of Sight (LOS) concept for front-to-front end forward-collision situation. This approach does not require high computational power during online execution and is expected to reduce false alarm rates to a significant level. For the implementation of this approach, a large number of forward-collision scenarios are generated, and various motion parameters are characterized. Further, Bayesian learning is used to update the risk at every sampling instant for each scenario followed by a risk threshold generation based on Receiver Operating Characteristic (ROC) plot. Finally, a decision is made by predicting the collision risk at certain distances and then comparing them with the threshold of risk. Simulations using relevant industry-standard software and realistic assumptions have been performed, which produces results ensuring the effectiveness of the proposed methodology.
Paper VI174-02.4
PDF · Video · Pareto-Improving Pricing Schemes for Route Assignment of Heterogeneous Users
Papadopoulos, Aristotelis Angelos	University of Southern California
Kordonis, Ioannis	CentraleSupléc
Dessouky, Maged	University of Southern California
Ioannou, Petros A.	University of Southern California
Keywords: Intelligent transportation systems, Freight transportation Abstract: Traffic congestion constitutes a major problem in commercial areas having negative effects on travel times, fuel consumption and other operational costs. Additionally, the continuously increasing use of GPS technologies has made drivers to make routing decisions in an effort to minimize their own individual travel time which is known to lead to an inefficient road usage. In this paper, we propose a novel pricing scheme to alleviate traffic congestion by controlling the freight routing decisions through a coordination mechanism. The proposed mechanism asks the truck drivers to declare their Origin-Destination (OD) pair and their individual Value Of Time (VOT) and guarantees that every participant truck driver will be better-off compared to the User Equilibrium (UE) by providing them individual incentives to truthfully declare their VOT while leading to a budget balanced on average mechanism. The optimum route assignment and the resulting pricing scheme can be calculated by solving a nonconvex optimization problem. To reduce the dimensionality of the problem, we propose a second pricing scheme and we prove that satisfies the aforementioned characteristics. Finally, the evaluation of our approach using the Sioux Falls network shows that the proposed pricing schemes can make the network approach the System Optimum (SO) solution.
Paper VI174-02.5
PDF · Video · Real-Time Multiple Model Joint Estimation for an Urban Traffic Junction Subject to Jump Dynamics
Chetcuti Zammit, Luana	University of Malta
Fabri, Simon G.	Univ of Malta
Scerri, Kenneth M.	University of Malta
Keywords: Intelligent transportation systems, Modeling and simulation of transportation systems Abstract: Traffic conditions in signalized junctions are highly dynamic and may be subject to abrupt changes due to unanticipated traffic incidents or network obstructions. These abrupt changing conditions are represented as different regimes or modes where each mode is represented by its own distinct model, forming a set of multiple models. At any instance in time, only one model of the set has the potential of representing the physical system dynamics at that time. However the dynamics may arbitrarily jump over to a different regime when an abnormal condition arises. Furthermore, it might be impossible to identify these models a priori. Hence, a multiple model approach is developed to self-detect these abrupt changes, identify which member of the set best represents the actual system and automatically self-configure and add a new model to the set when a previously unmodelled regime arises. This approach makes use of a real-time joint (dual) estimation algorithm to estimate traffic state variables such as queue lengths and traffic flow, as well as model parameters such as turning ratios, saturation flow values and noise covariance resulting from unmodelled dynamics and measurement errors. The proposed algorithm is validated through simulations on signalized 3-arm and 4-arm junctions with typical day-to-day traffic conditions including several network irregularities occuring at different times of the day such as arm closures as a result of traffic incidents. This work is aimed to form part of adaptive control loops for traffic light systems that are able to autonomously adjust to changing traffic conditions so as to ensure efficient vehicle flows.
Paper VI174-02.6
PDF · Video · Front Tracking Transition System Model with Controlled Moving Bottlenecks and Probabilistic Traffic Breakdowns
Cicic, Mladen	KTH Royal Institute of Technology
Mikolasek, Igor	CDV - Transport Research Centre
Johansson, Karl H.	Royal Institute of Technology
Keywords: Intelligent transportation systems, Modeling and simulation of transportation systems, Integrated traffic management Abstract: Cell-based approximations of PDE traffic models are widely used for traffic prediction and control. However, in order to represent the traffic state with good resolution, cell-based models often require a short cell length, which results in a very large number of states. We propose a new transition system traffic model, based on the front tracking method for solving the LWR PDE model. Assuming piecewise-linear flux function and piecewise-constant initial conditions, this model gives an exact solution. Furthermore, it is easier to extend, has fewer states and, although its dynamics are intrinsically hybrid, is faster to simulate than an equivalent cell-based approximation. The model is extended to enable handling moving bottlenecks as well as probabilistic traffic breakdowns and capacity drops at static bottlenecks. A control strategy that utilizes controlled moving bottlenecks for bottleneck decongestion is described and tested in simulation. It is shown that we are able to keep the static bottleneck in free flow by creating controlled moving bottlenecks at specific instances along on the road, and using them to regulate the incoming traffic flow.
Paper VI174-02.7
PDF · Video · Queue Discharge-Based Emergency Vehicle Traffic Signal Preemption
Obrusnik, Vit	Czech Technical University in Prague
Herman, Ivo	Herman Electronics
Hurak, Zdenek	Czech Technical University in Prague
Keywords: Intelligent transportation systems, Modeling and simulation of transportation systems, Safety Abstract: In this paper, we document a novel method for emergency vehicle preemption at an intersection controlled by traffic lights. The method relies on wireless vehicle-to-infrastructure (V2I) communication between the emergency vehicle and the traffic lights controller, availability of an accurate estimate of the number of vehicles in the queue, and a mathematical model of dynamics of discharging of the queue. Unlike some occasionally deployed methods that trigger the preemption the instant that the emergency vehicle appears at a prespecified distance from the intersection, the proposed method adapts the activation moment to the actual traffic conditions so that the preemption is as short as possible, thus reducing the impact on the other traffic. The method has been finetuned using numerical simulations in SUMO simulator and experimentally verified in real urban traffic.
Paper VI174-02.8
PDF · Video · Network-Level Optimal Control for Public Bus Operation
Varga, Balazs	Budapest University of Technology and Economics
Peni, Tamas	Institute for Computer Science and Control (SZTAKI)
Kulcsar, Balazs	Chalmers University of Technology
Tettamanti, Tamás	Budapest University of Technology and Economics
Keywords: Modeling and simulation of transportation systems, Automatic control, optimization, real-time operations in transportation Abstract: The paper presents modeling, control and analysis of an urban public transport network. First, a centralized system description is given, built up from the dynamics of individual buses and bus stops. Aiming to minimize three conflicting goals (equidistant headways, timetable adherence, and minimizing passenger waiting times), a reference tracking model predictive controller formulated based on the piecewise-affine system model. The closed-loop system is analyzed with three methods. Numerical simulations on a simple experimental network showed that the temporal evolution of headways and passenger numbers could maintain their periodicity with the help of velocity control. With the help of randomized simulation scenarios, sensitivity of the system is analyzed. Finally, infeasible regions for the bus network control was sought using by formulating an explicit model predictive controller.
Paper VI174-02.9
PDF · Video · Flow-Based Flight Routing and Scheduling under Uncertainty
Gammana Guruge, Nadeesha Sandamali	Nanyang Technological University
Su, Rong	Nanyang Technological University
Kalupahana Liyanage, Kushan Sudheera	Nanyang Technological University
Keywords: Modeling and simulation of transportation systems, Automatic control, optimization, real-time operations in transportation, Intelligent transportation systems Abstract: To tackle the future air traffic demands and to enhance the safety of the Air Transportation System (ATS), a proper flight routing and scheduling scheme is required. This paper proposes an Air Traffic Flow Management (ATFM) model while considering the inherent uncertainties present in the ATS. The proposed model aims to reduce capacity violations and conflicts with the use of a probabilistic approach of chance constraint while minimizing adverse effects due to demand and capacity uncertainties. Further, the proposed approach uses the concept of flow-based modeling in which a set of flights are considered as a flow, to enlarge the problem space with the added feature of scalability. In the end, a flow decomposition strategy is used to obtain the individual flight information from the flow results. To the best of our knowledge, this is the first attempt to propose an ATFM model with a flow-based structure while considering both demand and capacity uncertainties. The optimization problem is formulated as an Integer Linear Programming (ILP) problem. The NP-hard nature of the overall problem is minimized by transforming the problem into a Maximum Weighted Independent Set (MWIS) finding problem.
Paper VI174-02.10
PDF · Video · Network Performance Evaluation under Disruptive Events through a Progressive Traffic Assignment Model
Siri, Enrico	University of Genova
Siri, Silvia	University of Genova
Sacone, Simona	Univ of Genova
Keywords: Modeling and simulation of transportation systems, Intelligent transportation systems, Automatic control, optimization, real-time operations in transportation Abstract: The purpose of this paper is to present an assignment model as a basis for evaluating the performance of a traffic network, capable of describing its evolution immediately after the occurrence of a disruptive event. First of all, a User-Equilibrium traffic assignment problem is solved in order to obtain an estimation of the system state before the disruption. Starting from the critical event, a Progressive Assignment procedure is performed in order to obtain reasonable traffic assignments on the network, taking into account the users' tolerance to increases in travel times as well as the inherent inertia of the system. Therefore a metric for the description of the network performance is proposed as well as implementation of the model on a test network.
Paper VI174-02.11
PDF · Video · Model-Predictive-Type Signal Control for a Burgers' Cellular Automaton Traffic Flow Model Based on Particle Swarm Optimization
Kai, Tatsuya	Tokyo University of Science
Sato, Munehiro	Tokyo University of Science
Keywords: Modeling and simulation of transportation systems, Intelligent transportation systems, Automatic control, optimization, real-time operations in transportation Abstract: This study is devoted to development of a new systematic signal control method for a traffic flow model represented by the Burgers' cellular automaton. First, it is shown that an optimal signal control problem with an objective function on the total number of traffic jam is formulated as a nonlinear integer programming problem Then, a new algorithm to solve the optimal signal control problem based on particle swarm optimization (PSO), and the method is extended to a model-predictive-type control method in order to treat inflow and outflow of cars. Some numerical simulations indicate that the new signal control method can reduce the total number of traffic jam the most in the four methods.
Paper VI174-02.12
PDF · Video · Joint Route Guidance and Demand Management Using Generalized MFDs
Menelaou, Charalampos	Univeristy of Cyprus
Timotheou, Stelios	University of Cyprus
Kolios, Panayiotis	University of Cyprus
Panayiotou, Christos	Univ of Cyprus
Keywords: Modeling and simulation of transportation systems, Intelligent transportation systems, Navigation, Guidance and Control Abstract: In this work we propose a Model Predictive Control (MPC) framework that combines multi-region route guidance with demand management at a macroscopic level. While route guidance is employed to control all vehicular routes, demand management is introduced to control the flows' departure times. In effect a portion of the demand may be instructed to wait at their origin before commercing their journey (i.e., delayed departure) and thus ensure that, when vehicles do enter the network, they will travel at free-flow conditions. We show that the resulting problem is a nonlinear optimization problem that is solved by a novel convex relaxation with tight lower bounds on the optimal solution. Extensive simulations are conducted to evaluate the performance of the proposed MPC convex optimization problem indicating the substantial performance improvements in the network utilization.
Paper VI174-02.13
PDF · Video · A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation
Siyuan, Liu	University of Chinese Academy of Sciences
Lin, Shu	University of Chinese Academy of Sciences
Wang, Yibing	Zhejiang University
De Schutter, Bart	Delft University of Technology
Lam, William H.K.	The Hong Kong Polytechnic University
Keywords: Modeling and simulation of transportation systems, Intelligent transportation systems, Simulation Abstract: In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.
Paper VI174-02.14
PDF · Video · A Novel Mathematical Model for a Cloud-Based Drone Enabled Vehicle Routing Problem Considering Multi-Echelon Supply Chain
Farajzadeh, Fatemeh	Sharif University of Technology
Moadab, Amirhossein	Sharif University of Technology
Fatahi Valilai, Omid	Jacobs University Bremen GGmbH
Houshmand, Mahmoud Houshmand	Sharif University of Technology
Keywords: Modeling and simulation of transportation systems, Transportation logistics, Navigation Abstract: In recent years, the product delivery system has faced a significant amount of changes with reducing cost and waiting time of last-mile delivery. Unmanned aerial vehicles, or drones, have the potential to deal with these issues effectively. This paper developed a novel mathematical formulation to investigate the optimum routing between various types of nodes in a multi-echelon supply chain, including third-party logistics companies (3PL), warehouses, and consumers. A conceptual model is represented in the paper to comprehend the readers better, and eventually, the novelty of the developed model is discussed further by explaining the concept of solving.
Paper VI174-02.15
PDF · Video · Dynamic Scheduling Algorithm Based on NOMA with Priority Assignment for V2X Communications
Trabelsi, Ala Din	National School of Electronics and Telecommunications (ENET'COM)
Marouane, Hend	Enet'com
Bouhamed, Emna	Enet'com
Zarai, Faouzi	Enet'com
Keywords: Safety, Intelligent transportation systems, Automatic control, optimization, real-time operations in transportation Abstract: Nowadays, heterogeneous and stringent requirements for the fifth generation (5G) mobile communication system are imposed to adapt with the fast growing usage of the mobile equipment including connected vehicles and rapid development of IoT. As a consequence, the limitation and inefficient using of the spectrum becomes a major problem to meet the demand of mobile broadband, extreme capacity and high throughput. Thus, to handle the challenges of access collisions, the scarcity of spectral efficiency due to the limited bandwidth and massive connectivity, non-orthogonal multiple access (NOMA) schemes have been introduced as a potential solution for 5G wireless networks. Accordingly, this paper presents a new optimal scheduling algorithm for V2X connections called Dynamic Scheduling Algorithm based on NOMA and Priority Assignment for vehicular Networks (DSA-PA-NOMA), which improves performances in terms of Quality of Service (QoS), throughput and bit error rate (BER). The proposed algorithm consider the traffic classification imposed by V2X exigency and taking into account the channel conditions of Vehicular User Equipment (VUE) expressed by the Signal-to-Interference-plus-Noise Ratio (SINR) value.
Paper VI174-02.16
PDF · Video · Onboard Model-Based Prediction of Tram Braking Distance
Do, Loi	Czech Technical University in Prague
Herman, Ivo	Herman Electronics
Hurak, Zdenek	Czech Technical University in Prague
Keywords: Automatic control, optimization, real-time operations in transportation, Simulation Abstract: In this paper, we document a design of a computational method for an onboard prediction of a breaking distance for a city rail vehicle---a tram. The method is based on an onboard simulation of tram braking dynamics. Inputs to this simulation are the data from a digital map and the estimated (current) position and speed, which are, in turn, estimated by combining a mathematical model of dynamics of a tram with the measurements from a GNSS/GPS receiver, an accelerometer and the data from a digital map. Experiments with real trams verify the functionality, but reliable identification of the key physical parameters turns out critically important. The proposed method provides the core functionality for a collision avoidance system based on vehicle-to-vehicle (V2V) communication.
Paper VI174-02.17
PDF · Video · Measuring Urban Sidewalk Practicability: A Sidewalk Robot Feasibility Index
Corno, Matteo	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: autonomic transport systems, Navigation, Automatic control, optimization, real-time operations in transportation Abstract: Autonomous parcel delivery is attracting a lot of interest. Terrestrial delivery drones travel at lower speeds, are smaller and lighter than passenger cars. These features make them an ideal and valuable first step and experimental sandbox toward fully autonomous vehicles. To be useful, however, small wheeled drones need to operate on parts of the roads that are reserved to pedestrians. This is a challenge by itself. Pedestrian areas are less structured than road and abide by looser rules. The best route for a delivery drone may not be the shortest path; other aspects need to be accounted for that make a route more or less practical for the specific features of the vehicle. This paper introduces a quantitative analysis of these specific issues. The paper proposes a quantitative index that asses a route practicability for a small terrestrial drone. It combines different aspects that account for sidewalk width, sidewalk surface condition, route length and the number of driveways and crosswalks present on the way. We provide the mathematical definition of the index, and use our wheeled drone prototype to show how it can be used to classify and chose the best routes among a selection. Although the index is designed for autonomous drones, given the specific dynamic features of the drone, it can also be employed as is to quantify the accessibility of different routes for disabled people.

VI175
Transportation and Vehicle Systems - Intelligent Autonomous Vehicles
VI175-01 Controls for Connected and Autonomous Vehicles   Open Invited Session, 17 papers
VI175-02 Coordination Control for Autonomous Vehicles   Regular Session, 25 papers
VI175-03 Human Vehicle Interaction   Regular Session, 8 papers
VI175-04 Mission Planning and Decision Making for Autonomous Vehicles   Regular Session, 8 papers
VI175-05 Perception for Autonomous Vehicles   Regular Session, 9 papers
VI175-06 Trajectory and Path Planning for Autonomous Vehicles   Regular Session, 26 papers
VI175-07 Trajectory Tracking and Path Following for Autonomous Vehicles   Regular Session, 13 papers

VI175-01
Controls for Connected and Autonomous Vehicles	Open Invited Session
Chair: Eriksson, Lars	Linköping University
Co-Chair: Johansson, Karl H.	Royal Institute of Technology
Organizer: Eriksson, Lars	Linköping University
Paper VI175-01.1
PDF · Video · A Dynamic Game Formulation for Cooperative Lane Change Strategies at Highway Merges (I)
Ladino, Andres	IFSTTAR
Wang, Meng	Delft University of Technology
Keywords: Intelligent transportation systems, Cooperative navigation, Navigation, Guidance and Control Abstract: A dynamic game framework is put forward to derive the system optimum strategy for a network of cooperative vehicles interacting at a merging bottleneck with simplified vehicle dynamics model. Merging vehicles minimize the distance travelled on the acceleration lane in addition to the same cost terms of the mainline vehicles, taking into account the predicted reaction of mainline vehicles to their merging actions. An optimum strategy is found by minimizing the joint cost of all interacting vehicles while respecting behavioral and physical constraints. The full dynamic game is cast as a set of sub-problems regularly expressed as standard optimal control problems that can be solved efficiently. Numerical examples show the feasibility of the approach in capturing the nature of conflict and cooperation during the merging process.
Paper VI175-01.2
PDF · Video · Adaptive Strategies to Platoon Merging with Vehicle Engine Uncertainty (I)
Jain, Vishrut	Delft University of Technology
Liu, Di	Southeast University
Baldi, Simone	Southeast University
Keywords: Autonomous Vehicles, Learning and adaptation in autonomous vehicles, Multi-vehicle systems Abstract: While several synchronization-based protocols have been provided for formation-keeping of cooperative vehicles, the problem of synchronized merging is more challenging. Challenges associated to the merging scenario include the need for establishing bidirectional interaction (in place of unidirectional look-ahead interaction), and the need for considering different engine dynamics (in place of homogeneous engine dynamics). This work shows how such challenges can be tackled via a newly proposed strategy based on adaptive control with bidirectional error: the adaptive control framework autonomously adapts to different engine dynamics, while the bidirectional error seamlessly allows the vehicle that wants to merge to interact with both the front and the rear vehicles, in a similar way as humans do.
Paper VI175-01.3
PDF · Video · Parameter Varying Approach for a Combined (Kinematic + Dynamic) Model of Autonomous Vehicles (I)
Atoui, Hussam	Grenoble-Alpes University
Sename, Olivier	Grenoble Institute of Technology / GIPSA-Lab
Alcala, Eugenio	UPC
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Keywords: Autonomous Vehicles, Trajectory Tracking and Path Following, Adaptive and robust control of automotive systems Abstract: This paper proposes a solution for the integrated longitudinal and lateral control problem of autonomous vehicles. A mixed model including kinematic and dynamic behavior of the vehicle is used to design a single controller to achieve stability and tracking performances. The proposed solution is based on the Linear Parameter Varying (LPV) control approach, where an output-feedback dynamical controller is designed based on Linear Matrix Inequalities (LMIs). The control synthesis is carried on using the gridded-based approach to reduce the conservatism. Simulation results show the stabilization of the vehicle with robustness in tracking performances, in the presence of the road friction coefficient disturbances.
Paper VI175-01.4
PDF · Video · Time-Dependent Hybrid-State A* and Optimal Control for Autonomous Vehicles in Arbitrary and Dynamic Environments (I)
Folkers, Andreas	University of Bremen
Rick, Matthias	University of Bremen
Büskens, Christof	Univ of Bremen
Keywords: Trajectory and Path Planning, Nonlinear and optimal automotive control, Navigation, Guidance and Control Abstract: The development of driving functions for autonomous vehicles in urban environments is still a challenging task. In comparison with driving on motorways, a wide variety of moving road users, such as pedestrians or cyclists, but also the strongly varying and sometimes very narrow road layout pose special challenges. The ability to make fast decisions about exact maneuvers and to execute them by applying sophisticated control commands is one of the key requirements for autonomous vehicles in such situations. In this context we present an algorithmic concept of three correlated methods. Its basis is a novel technique for the automated generation of a free-space polygon, providing a generic representation of the currently drivable area. We then develop a time-dependent hybrid-state A* algorithm as a model-based planner for the efficient and precise computation of possible driving maneuvers in arbitrary dynamic environments. While on the one hand its results can be used as a basis for making short-term decisions, we also show their applicability as an initial guess for a subsequent trajectory optimization in order to compute applicable control signals. Finally, we provide numerical results for a variety of simulated situations demonstrating the efficiency and robustness of the proposed methods.
Paper VI175-01.5
PDF · Video · Kernel Regression for Trajectory Reconstruction of Vehicles under Speed and Inter-Vehicular Distance Constraints (I)
Aubin-Frankowski, Pierre-Cyril	MINES ParisTech
Petit, Nicolas	MINES ParisTech
Szabo, Zoltan	Ecole Polytechnique
Keywords: Intelligent transportation systems, Information processing and decision support, Navigation Abstract: This work tackles the problem of reconstructing vehicle trajectories with the side information of physical constraints, such as inter-vehicular distance and speed limits. It is notoriously difficult to perform a regression while enforcing these hard constraints on time intervals. Using reproducing kernel Hilbert spaces, we propose a convex reformulation which can be directly implemented in classical solvers such as CVXGEN. Numerical experiments on a simple dataset illustrate the efficiency of the method, especially with sparse and noisy data.
Paper VI175-01.6
PDF · Video · Energy Optimal Coordination of Fully Autonomous Vehicles in Urban Intersections (I)
Pelosi, Carmine	Eindhoven University of Technology
Padilla, G. P. (Paul)	Eindhoven University of Technology
Donkers, M.C.F. (Tijs)	Eindhoven University of Technology
Keywords: Autonomous Vehicles, Intelligent transportation systems, Integrated traffic management Abstract: This paper provides a solution to conflict resolutions between Autonomous Vehicles (AV) crossing an urban intersection. The conflict resolution problem is formulated as an optimal control problem, where the objective is to minimize the energy consumption of all the vehicles, while avoiding collisions. Since the problem has a combinatorial nature, it is tackled though a sequential mixed-integer quadratically constrained programming approach. Simulation results show that since the AVs do not need to follow specific driving rules, the intersection crossing order is chosen to optimize the overall energy consumption. The research outcome underlines the benefits of moving towards fully autonomous systems which will allow for higher traffic throughput. Furthermore, the proposed formulation is the starting point for future explorations towards real-time implementation.
Paper VI175-01.7
PDF · Video · Semi-Constant Spacing Policy for Leader-Predecessor-Follower Platoon Control Via Delayed Measurements Synchronization (I)
Zhang, Yu	Tongji University
Wang, Meng	Delft University of Technology
Hu, Jia	Tongji University
Bekiaris-Liberis, Nikolaos	Technical University of Crete
Keywords: Multi-vehicle systems, Intelligent transportation systems Abstract: Constant spacing-based platooning systems cannot guarantee string stability if platoon members only use the preceding vehicle's information. To meet string stability specification, leader-predecessor-follower (LPF) platooning systems are proposed to incorporate the information of both the preceding vehicle and the platoon leader into the control loop. However, string stability of LPF platooning systems is very sensitive to communication and sensing delays. Even a delay of 5 milliseconds may render LPF platooning systems string-unstable. This paper focuses on a new approach to deal with communication and sensing delays of LPF platooning systems. A semi-constant spacing policy is introduced that synchronizes delayed measurements of system states obtained from different sources and aims at tracking the past information of the preceding vehicle to gurantee string stability. Moreover, the delay-synchronizing LPF platooning system puts the same requirements on controller parameters as the nominal LPF platooning system that is not affected by communication delays. Thus, the feedback controller parameters of the delay-synchronizing LPF platoon can be designed without considering delays.
Paper VI175-01.8
PDF · Video · A Tool to Enable FPGA-Accelerated Dynamic Programming for Energy Management of Hybrid Electric Vehicles (I)
Skarman, Frans	Linköping University
Gustafsson, Oscar	Linköping University
Jung, Daniel	Linköping University
Krysander, Mattias	Linköping University
Keywords: Nonlinear and optimal automotive control Abstract: When optimising the vehicle trajectory and powertrain energy management of hybrid electric vehicles, it is important to include look-ahead information such as road conditions and other traffic. One method for doing so is dynamic programming, but the execution time of such an algorithm on a general purpose CPU is too slow for it to be useable in real time. Significant improvements in execution time can be achieved by utilising parallel computations, for example, using a Field-Programmable Gate Array (FPGA). A tool for automatically converting a vehicle model written in C++ into code that can executed on an FPGA which can be used for dynamic programming-based control is presented in this paper. A vehicle model with a mild-hybrid powertrain is used as a case study to evaluate the developed tool and the output quality and execution time of the resulting hardware.
Paper VI175-01.9
PDF · Video · TS-MPC for Autonomous Vehicle Using a Learning Approach (I)
Alcala, Eugenio	UPC
Sename, Olivier	Grenoble Institute of Technology / GIPSA-Lab
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Quevedo, Joseba	Technical Univ of Catalonia
Keywords: Autonomous Vehicles, Motion control, Nonlinear and optimal automotive control Abstract: In this paper, the Model Predictive Control (MPC) and Moving Horizon Estimator (MHE) strategies using a data-driven approach to learn a Takagi-Sugeno (TS) representation of the vehicle dynamics are proposed to solve autonomous driving control problems in real-time. To address the TS modeling, we use the Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to obtain a set of polytopic-based linear representations as well as a set of membership functions relating in a non-linear way the different linear subsystems. The proposed control approach is provided by racing-based references of an external planner and estimations from the MHE offering a high driving performance in racing mode. The control-estimation scheme is tested in a simulated racing environment to show the potential of the presented approaches.
Paper VI175-01.10
PDF · Video · Low-Latency Robust MPC for CACC under Variable Road Geometry (I)
Lan, Jianglin	Loughborough University
Zhao, Dezong	Loughborough University
Tian, Daxin	Beihang University
Keywords: Autonomous Vehicles, Cooperative control, Nonlinear and optimal automotive control Abstract: Cooperative adaptive cruise control (CACC) has attracted much research attention, due to its great potential in improving traffic throughput, safety and energy efficiency. This paper aims to address the following problems that are rarely investigated in the literature: (i) the time delay caused by online computation of the optimal control action, and (ii) robustly stable CACC under variable road geometry. To this end, a one-step ahead robust model predictive control (MPC) is developed for achieving CACC and lane keeping (LK) of the followers in the platoon, by leveraging vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. In the proposed design, the current MPC policy is generated one-step ahead during the previous sampling period to avoids the optimization-induced time delay existing in the traditional MPC. LK control is incorporated with CACC to ensure vehicle lateral stability and vehicle following under variable road geometry. The MPC design is formulated as an easily solved linear matrix inequality (LMI) optimization problem with consideration of the control input limits and constraints on platooning errors and lateral displacement. Effectiveness of the proposed MPC and its advantages over the traditional MPC are verified by simulating a vehicle platoon on roads with time-varying bank, curvature and grade.
Paper VI175-01.11
PDF · Video · Learning to Falsify Automated Driving Vehicles with Prior Knowledge (I)
Favrin, Andrea	University of Padova
Nenchev, Vladislav	Bayerische Motoren Werke AG
Cenedese, Angelo	University of Padova
Keywords: Autonomous Vehicles, Modeling and simulation of transportation systems, Learning and adaptation in autonomous vehicles Abstract: While automated driving technology has achieved a tremendous progress, the scalable and rigorous testing and verification of safe automated and autonomous driving vehicles remain challenging. Assuming that the specification is associated with a violation metric on possible scenarios, this paper proposes a learning-based falsification framework for testing the implementation of an automated or self-driving function in simulation. Prior knowledge is incorporated to limit the scenario parameter variance and into a model-based falsifier to guide and improve the learning process. For an exemplary adaptive cruise controller, the presented framework yields non-trivial falsifying scenarios with higher reward, compared to scenarios obtained by purely learning-based or purely model-based falsification approaches.
Paper VI175-01.12
PDF · Video · Learning-Based Risk-Averse Model Predictive Control for Adaptive Cruise Control with Stochastic Driver Models (I)
Schuurmans, Mathijs	KU Leuven
Katriniok, Alexander	Ford Research & Innovation Center (RIC)
Tseng, Eric	Ford Motor Company
Patrinos, Panagiotis	KU Leuven
Keywords: Learning and adaptation in autonomous vehicles, Intelligent driver aids, Motion control Abstract: We propose a learning-based, distributionally robust model predictive control approach towards the design of adaptive cruise control (ACC) systems. We model the preceding vehicle as an autonomous stochastic system, using a hybrid model with continuous dynamics and discrete, Markovian inputs. We estimate the (unknown) transition probabilities of this model empirically using observed mode transitions and simultaneously determine sets of probability vectors (ambiguity sets) around these estimates, that contain the true transition probabilities with high confidence. We then solve a risk-averse optimal control problem that assumes the worst-case distributions in these sets. We furthermore derive a robust terminal constraint set and use it to establish recursive feasibility of the resulting MPC scheme. We validate the theoretical results and demonstrate desirable properties of the scheme through closed-loop simulations.
Paper VI175-01.13
PDF · Video · Event-Triggered Switched Pinning Control for Merging or Splitting Vehicle Platoons (I)
Wakasa, Takuma	The University of Electro-Communications
Sawada, Kenji	The University of Electro-Communications
Shin, Seiichi	The University of Electro-Communications
Keywords: Multi-vehicle systems, Automatic control, optimization, real-time operations in transportation, autonomic transport systems Abstract: This paper proposes a switched pinning control system with an event-triggering mechanism for vehicle platoons. A switched pinning control method is applied to the multi-agent systems with homogeneous spring-mass-damper sub-systems. A model predictive controller switches pinning agents via mixed-integer quadratic programming. The interval step of the switching is determined according to the convergence rate to the target values. If the convergence rate is lower than the triggering condition, the switching of the pinning agents will become more frequent. Otherwise, the switching of the pinning agents will become less frequent. This event-triggering mechanism can reduce the calculation cost of the optimization in the steady.
Paper VI175-01.14
PDF · Video · String Stable H-Infinity LPV Cooperative Adaptive Cruise Control with a Variable Time Headway (I)
Laib, Khaled	Cambridge University, Engineering Department
Sename, Olivier	Grenoble Institute of Technology / GIPSA-Lab
Dugard, Luc	Gipsa-Lab, CNRS Grenoble-INP-Université Grenoble Alpes
Keywords: Autonomous Vehicles, Cooperative control, Adaptive and robust control of automotive systems Abstract: Cooperative Adaptive Cruise Control (CACC) of vehicle platoon with a variable time headway is considered in this paper. The two main control objectives in such problems are the convergence of the intervehicle distance tracking errors towards zero and the attenuation of any disturbance propagating along the platoon. To ensure those objectives for any variable time headway, the Linear Parameters Varying (LPV) approach is used in combination with the Hinf control approach. The efficiency of the designed controller is illustrated through frequency domain analysis and time domain simulations.
Paper VI175-01.15
PDF · Video · Control of Interacting Vehicles Using Model-Predictive Control, Generalized Nash Equilibrium Problems, and Dynamic Inversion (I)
Britzelmeier, Andreas	Bundeswehr University
Gerdts, Matthias	University of the Federal Armed Forces Munich
Rottmann, Thomas	Bundeswehr University Munich
Keywords: Mission planning and decision making, Multi-vehicle systems, Trajectory Tracking and Path Following Abstract: The paper presents a control concept for interacting vehicles in a road network. The approach combines a high-level controller for the generation of collision-free trajectories and a low-level dynamic inversion controller for path tracking. The high-level controller uses model-predictive control for generalized Nash equilibrium problems, which are used to coordinate the vehicles. The control concept was implemented and validated on scale robots and experimental results are discussed.
Paper VI175-01.16
PDF · Video · Event-Triggered Add-On Safety for Connected and Automated Vehicles Using Road-Side Network Infrastructure (I)
Mamduhi, Mohammad Hossein	KTH Royal Institute of Technology
Hashemi, Ehsan	University of Waterloo
Baras, John S.	Univ. of Maryland
Johansson, Karl H.	Royal Institute of Technology
Keywords: Safety, Intelligent transportation systems, Intelligent driver aids Abstract: This paper proposes an event-triggered add-on safety mechanism to adjust the control parameters for timely braking in a networked vehicular system while maintaining maneuverability. Passenger vehicle maneuverability is significantly affected by the combined slip friction effect, in which larger longitudinal tire slips result in considerable drop in lateral tire forces. This is of higher importance when unexpected dangerous situations occur on the road and immediate actions, such as braking, need to be taken to avoid collision. Harsh braking can lead to high-slip and loss of maneuverability; hence, timely braking is essential to reduce high-slip scenarios. In addition to the vehicles own active safety systems, the proposed event-triggered add-on safety is activated upon being informed about dangers by the road-side infrastructure. The aim is to incorporate the add-on safety feature to adjust the automatic control parameters for smooth and timely braking such that a collision is avoided while vehicle’s maneuverability is maintained. We study two different wireless technologies for communication between the infrastructure and the vehicles, the Long-Term Evolution (LTE) and the fifth generation (5G) schemes. The safety advantages of the proposed framework is validated through high-fidelity software simulations.
Paper VI175-01.17
PDF · Video · From a Classic Renault Twizy towards a Low Cost Autonomous Car Prototype: A Proof of Concept
Orjuela, Rodolfo	Université De Haute-Alsace, IRIMAS UR7499
Lauffenburger, Jean-Philippe	Université De Haute-Alsace
Ledy, Jonathan	Université De Haute-Alsace
Basset, Michel	Université De Haute-Alsace
Lambert, Joel	Université De Haute-Alsace
Bresch, Didier	Université De Haute-Alsace
Bockstaller, Jean-Jacques	Université De Haute-Alsace
Keywords: Control architectures in automotive control, Automotive sensors and actuators, Intelligent driver aids Abstract: This paper shows how a conventional electric car is modified into an autonomous vehicle. The starting point to the presented developments is the Renault Twizy specially designed for urban mobility. The goal is to reuse the mechanical, electrical and electronic elements to customise this car in an autonomous electric vehicle. For that purpose, communication, actuators and sensors systems are added. The challenge here is double, on the one hand the integration challenge due to the small place offered by the Renault Twizy, and on the other hand the proposed systems must associate low cost and good performances. The proof of concept of our autonomous prototype is given through some experimental validations.

VI175-02
Coordination Control for Autonomous Vehicles	Regular Session
Chair: Mårtensson, Jonas	KTH Royal Institute of Technology
Co-Chair: Horn, Joachim	Helmut-Schmidt-University / University of the Federal Armed Forces Hamburg
Paper VI175-02.1
PDF · Video · Safe Coverage of Compact Domains for Second Order Dynamical Systems
Chacon, Juan	Simon Fraser University
Chen, Mo	Simon Fraser University
Fetecau, Razvan	Simon Fraser University
Keywords: Autonomous Mobile Robots, Decentralized Control and Systems, Safety Abstract: Autonomous systems operating in close proximity with each other to cover a specified area has many potential applications, but to achieve effective coordination, two key challenges need to be addressed: coordination and safety. For coordination, we propose a locally asymptotically stable distributed coverage controller for compact domains in the plane and homogeneous vehicles modeled with second order dynamics with bounded input forces. This control policy is based on artificial potentials designed to enforce desired vehicle-domain and inter-vehicle separations, and can be applied to arbitrary compact domains including non-convex ones. We prove, using Lyapunov theory, that certain coverage configurations are locally asymptotically stable. For safety, we utilize Hamilton-Jacobi (HJ) reachability theory to guarantee pairwise collision avoidance. Rather than computing numerical solutions of the associated HJ partial differential equation as is typically done, we derive an analytical solution for our second-order vehicle model. This provides an exact, global solution rather than an approximate, local one within some computational domain. In addition to considerably reducing collision count, the collision avoidance controller also reduces oscillatory behaviour of vehicles, helping the system reach steady state faster. We demonstrate our approach in two representative simulations involving a square domain and a non-convex moving domain.
Paper VI175-02.2
PDF · Video · Model Predictive Control for the Coordination of Autonomous Vehicles at Intersections
Mihaly, Andras	SZTAKI
Farkas, Zsofia	SZTAKI
Gaspar, Peter	SZTAKI
Keywords: Autonomous Vehicles, Automatic control, optimization, real-time operations in transportation, Multi-vehicle systems Abstract: The paper describes a method for defining the crossing order of autonomous vehicles at a non-signalized intersection. The safe passage of vehicles through the intersection is achieved by a centralized Model Predictive Control (MPC) method. The minimization of traveling time or energy consumption and the condition of collision-avoidance are incorporated in the control design. The goal of the research is to guarantee safe passage of the autonomous vehicles by taking uncertainties of position measurements into consideration. The operation of the proposed control method is demonstrated by simulation examples made in a high-accuracy simulation environment to present its efficiency.
Paper VI175-02.3
PDF · Video · Distributed Model Predictive Control for Cooperative Landing
Persson, Linnea	KTH Royal Institute of Technology
Bereza, Robert	KTH Royal Institute of Technology
Wahlberg, Bo	KTH Royal Institute of Technology
Keywords: Autonomous Vehicles, Cooperative control, Decentralized Control and Systems Abstract: We design, implement and test two control algorithms for autonomously landing a drone on an autonomous boat. The first algorithm uses distributed model predictive control (DMPC), while the second combines a cascade controller with DMPC. The algorithms are implemented on a real drone, while the boat's motion is simulated, and their performance is compared to a centralized model predictive controller. Field experiments are performed, where all algorithms show an ability to land while avoiding violation of the safety constraints. The two distributed algorithms further show the ability to use longer prediction horizons than the centralized model predictive controller, especially in the cascade case, and also demonstrate improved robustness towards breaks in communication.
Paper VI175-02.4
PDF · Video · Case Study on Communication Based Cooperative Longitudinal Vehicle Guidance
Schrödel, Frank	IAV GmbH
Voßwinkel, Rick	IAV GmbH
Ritschel, Robert	IAV GmbH
Gerwien, Maximilian	IAV GmbH
Gruschka, Erik	IAV GmbH
Schwarz, Norman	IAV GmbH
Jungmann, Alexander	IAV GmbH
Keywords: Autonomous Vehicles, In-vehicle communication networks, Motion control Abstract: An approach of a proven concept for cooperative longitudinal vehicle guidance is presented. The paper briefly describes the communication pipeline as well as the incorporated communication technology. Moreover, the used longitudinal controller, which explicitly considers the communicated states of the vehicles ahead, is addressed. Here, we are expanding a classical Adaptive Cruise Controller (ACC) to realize the cooperative longitudinal guidance functionality simply and robustly. On the one hand, the current states of the vehicle in front are transmitted and on the other hand the desired ones. Results of a real-world test campaign of platooning vehicles illustrate the effectiveness of the proposed approach.
Paper VI175-02.5
PDF · Video · Adaptive Feedforward Compensator Based on Approximated Causal Transfer Function for CACC with Communication Delay
Kim, Daejung	Hanyang University
Kim, Hyeongil	Hyundai Mobis Corporation
Lee, Seung-Hi	Hongik Univeristy
Chung, Chung Choo	Hanyang Univ
Keywords: Autonomous Vehicles, Multi-vehicle systems, Adaptive and robust control of automotive systems Abstract: In this paper, we propose an adaptive feedforward compensator using parameter estimation to compensate for the communication time delay in cooperative adaptive cruise control (CACC). When CACC uses a feedforward controller to improve tracking performance and satisfy the string stability, it should take into account the communication delay between vehicles. Pad'e approximation of the time delay can be used for the design of feedforward compensator, but there is a limitation since the approximated system becomes the non-minimum system. To cope with this inherent non-causality problem, we propose an approximated causal transfer function for the feedforward compensator. Then, we apply extended Kalman filter as one of parameter estimation methods with a nonlinear model from the state augmented by a parameter of the approximated causal transfer function. Numerical simulation results show that the proposed system not only mitigates spacing error in time-varying communication delay but also satisfies string stability in a platoon.
Paper VI175-02.6
PDF · Video · Constant Time-Headway Spacing Policy with Limited Communication Range for Discrete Time Platoon Systems
Peters, Andrés Alejandro	Universidad Tecnológica Metropolitana
Rojas, Alejandro	Universidad De Concepcion
Keywords: Autonomous Vehicles, Multi-vehicle systems, Decentralized Control and Systems Abstract: We present a study of the scaling properties of the interconnection of n agents (e.g. vehicles) through an r-lookahead network. These networks are considered as a possible implementation for vehicle platooning, although we do not make any assumptions on what the agents represent, and we assume them to be linear time invariant (LTI) discrete time systems, locally controlled by an LTI controller. In particular, we show that the r-lookahead topology gives rise to dynamics which can be studied from the roots of polynomials with transfer functions as their coefficients. Through numerical simulations, we study aspects relating the use of lookahead measurements and their effect on the value of a time headway constant needed for the scalability property known as string stability.
Paper VI175-02.7
PDF · Video · Optimal Formation of Autonomous Vehicles in Mixed Traffic Flow
Li, Keqiang	Tsinghua Univ, Beijing, China
Wang, Jiawei	Tsinghua University
Zheng, Yang	University of Oxford
Keywords: Autonomous Vehicles, Multi-vehicle systems, Modeling and simulation of transportation systems Abstract: Platooning of multiple autonomous vehicles has attracted significant attention in both academia and industry. Despite its great potential, platooning is not the only choice for the formation of autonomous vehicles in mixed traffic flow, where autonomous vehicles and human-driven vehicles (HDVs) coexist. In this paper, we investigate the optimal formation of autonomous vehicles that can achieve an optimal system-wide performance in mixed traffic flow. Specifically, we consider the optimal H2 performance of the entire traffic flow, reflecting the potential of autonomous vehicles in mitigating traffic perturbations. Then, we formulate the optimal formation problem as a set function optimization problem. Numerical results reveal two predominant optimal formations: uniform distribution and platoon formation, depending on traffic parameters. In addition, we show that 1) the prevailing platoon formation is not always the optimal choice; 2) platoon formation might be the worst choice when HDVs have a poor string stability behavior. These results suggest more opportunities for the formation of autonomous vehicles, beyond platooning, in mixed traffic flow.
Paper VI175-02.8
PDF · Video · Coordinated Lane Change in Autonomous Driving: A Computationally Aware Solution
Falsone, Alessandro	Politecnico Di Milano
Sakcak, Basak	Politecnico Di Milano
Prandini, Maria	Politecnico Di Milano
Keywords: Autonomous Vehicles, Trajectory and Path Planning, Multi-vehicle systems Abstract: This paper addresses the design of coordinated maneuvers in an autonomous driving set-up involving multiple vehicles. In particular, we consider a lane change problem where a vehicle has to merge in a platoon traveling in the adjacent lane of a two-lane one way road. We propose a cooperative solution that trades optimality for computational feasibility without simplifying the merging vehicle dynamics. The key idea is decoupling the problem into two phases: an online coordination phase where vehicles in the platoon create a gap where the merging vehicle can safely enter, and a merging phase, where the merging vehicle change lane by tracking a pre-computed optimal maneuver. A numerical case study shows the achieved trade off between performance degradation and reduction in computing time of the proposed solution.
Paper VI175-02.9
PDF · Video · Cooperative Adaptive Cruise Control of Heterogeneous Vehicle Platoons
Lefeber, Erjen	Eindhoven University of Technology
Ploeg, Jeroen	Eindhoven University of Technology
Nijmeijer, Hendrik	Eindhoven University of Technology
Keywords: Cooperative navigation, Multi-vehicle systems, Autonomous Vehicles Abstract: Road throughput can be increased by cooperative adaptive cruise control (CACC), which allows vehicles to drive at short inter-vehicle distances without compromising string stability by using wireless inter-vehicle communications. Practical application, however, may involve vehicles with different driveline dynamics, thus forming a heterogeneous platoon. This property potentially requires knowledge of other vehicle's driveline dynamics for implementation of CACC, which may not be available. As opposed to robust or adaptive approaches, the heterogeneity problem is solved here by revisiting an existing, widely adopted controller for homogeneous strings using an input-output linearization approach. As a result, a class of controllers is obtained which allows for vehicle strings that are heterogeneous with respect to driveline dynamics, without requiring knowledge of these dynamics. Furthermore, it is shown that the new controller represents a class of controllers that encompasses the original homogeneous controller. To illustrate the performance of the new controller, simulations of a heterogeneous platoon are presented and the string stability properties are assessed. From this analysis, it appears that the new controller performs at least as good as the original one, in terms of minimum string-stable time gap, settling time, and maximum jerk.
Paper VI175-02.10
PDF · Video · Comfort-Aware Cooperative Cruise Control of Multiple High-Speed Trains: An Artificial Potential Field Approach
Wang, Pingping	Central South University
Huang, Zhiwu	Central South University
Zhou, Feng	Changsha University of Science & Technology
Chen, Bin	Central South University
Wu, Yue	Central South University
Liu, Yongjie	Central South University
Li, Fei	Central South University
Peng, Jun	Central South University
Keywords: Cooperative navigation, Trajectory Tracking and Path Following, Multi-vehicle systems Abstract: In this work, the cruise control problem of multiple high-speed trains movements is investigated. Different from the classical PID control method applied in the practical highspeed train operation system, in this paper, a cooperative cruise control strategy considering both safety and passenger comfort based on layered potential function is proposed. First, the cyber-physical modeling of the high-speed trains system is presented, where the physical layer models the dynamic characteristic, and the cyber layer describes the communication topology. Second, a cooperative control algorithm based on layered potential function is designed. The underlying artificial potential function is introduced to keep a safe distance between adjacent high-speed trains, and the speed consensus rule is realized through the consensus algorithm. The hyperbolic tangent function is selected as the upper artificial potential function to ensure the acceleration of the high-speed train within a comfortable range. Finally, the stability of the control system is proved by the Lyapunov stability theorem, and simulations verify the effectiveness of the control strategy.
Paper VI175-02.11
PDF · Video · Distributed PI Control for Heterogeneous Nonlinear Platoon of Autonomous Connected Vehicles
Manfredi, Sabato	Univ of Naples Federico II
Petrillo, Alberto	University of Naples Federico II
Santini, Stefania	Univ. Di Napoli Federico II
Keywords: Decentralized Control and Systems, Autonomous Vehicles, Intelligent transportation systems Abstract: In this paper we present a distributed PI-based control law that guarantees the platoon formation to track leader velocity with a pre-xed inter-vehicular distance, when vehicles are heterogeneous in both parameters and nonlinear drivetrain dynamics. Moreover, differently from most of the approaches in the literature, the proposed PI protocol intrinsically compensates for the nonlinear, heterogeneous and uncertain drivetrain dynamics without requiring any feedforward control action. We formulate sufficient conditions for closed-loop heterogeneous non-linear vehicular network stability that can be used to tune the PI control parameters. Simulation results conrm the effectiveness of the proposed PI controller in both nominal and uncertain platooning scenario.
Paper VI175-02.12
PDF · Video · Collision-Avoiding Decentralized Control for Vehicle Platoons: A Mechanical Perspective
Calafiore, Giuseppe	Politecnico Di Torino
Possieri, Corrado	Consiglio Nazionale Delle Ricerche
Proskurnikov, Anton V.	Politecnico Di Torino
Keywords: Decentralized Control and Systems, Autonomous Vehicles, Multi-vehicle systems Abstract: A new bidirectional decentralized control algorithm for vehicle platoons is proposed, which guarantees absence of collisions between the vehicles. The algorithm exploits an elegant parallel between vehicles platoon and chains of interconnected mass-spring-damper systems and the idea of barrier certificates. Stability and robustness properties of the algorithm are examined. The results are illustrated by numerical examples, simulating different driving scenarios.
Paper VI175-02.13
PDF · Video · Platoon Control of Connected Autonomous Vehicles: A Distributed Reinforcement Learning Method by Consensus
Liu, Bo	The University of Manchester
Ding, Zhengtao	The University of Manchester
Lv, Chen	Nanyang Technological University
Keywords: Decentralized Control and Systems, Cooperative navigation, Multi-vehicle systems Abstract: This paper proposes a distributed reinforcement learning method based on deep Q-network and the consensus algorithm to deal with the multi-vehicle platoon control problem, which contains the two processes of local training and global consensus. The platooning problem is decomposed into many single-vehicle tasks based on deep Q-network, where each vehicle accumulates its experience data samples by interacting with its front and back vehicles. After initialization, all vehicles' Q-networks arefirst locally optimized based on their own experience simultaneously. The consensus algorithm is then used to make all vehicles in a decentralized platoon approach each other, where the communication is only required among directly connected vehicles. At last, the simulation study shows that the Q-networks of all vehicles reach consensusfirst and then converge to the optimum in union using the proposed distributed deep Q-networks algorithm, and all vehicles learn to form the required platoon and move forward with a roughly equal separation.
Paper VI175-02.14
PDF · Video · Game Theoretical Decision Making Approach for a Cooperative Lane Change
Hruszczak, Mark	IAV GmbH
Löwe, Brian Tewanima	Technische Universität Kaiserslautern
Schrödel, Frank	IAV GmbH
Freese, Matthias	IAV GmbH
Bajcinca, Naim	University of Kaiserslautern
Keywords: Mission planning and decision making, Autonomous Vehicles, General automobile/road-environment strategies Abstract: Recent advances in communications technology make it possible for vehicles to interact with each other and their environment. This allows for superior maneuvers, which open up a wide range of possibilities, which conventional vehicles without communication lack. To that end, this paper examines a decision making approach for an automated and cooperative lane change maneuver, which is based on the fundamentals of game theory. The decision making algorithm is realized with intuitive benefit functions, which are modelled similar to the semantic of human driving behavior. The used benefit functions can be classified into two sub-games: player against a single player and player against the totality of all players. By mapping four distinct driving maneuvers to their respective benefits, the problem of selecting the optimal maneuver can be solved using game theory methods. After the optimal driving maneuver has been identified, the cooperative lane change can be performed. The approach has been validated in a simulated highway scenario. Simulations have shown that a cooperative lane change does not have a significant negative effect on the traffic flow.
Paper VI175-02.15
PDF · Video · Carrier-Vehicle System for Delivery in City Environments
Bono Rossello, Nicolas	Université Libre De Bruxelles
Garone, Emanuele	Université Libre De Bruxelles
Keywords: Mission planning and decision making, Multi-vehicle systems, Trajectory and Path Planning Abstract: In this paper we present an extension of the carrier-vehicle problem for the case of delivery in an urban environment. The small vehicle, namely a drone, performs the delivery of goods at the customer address while the large vehicle is in charge of transporting, launching, recovering and servicing the drone. In this work it is assumed that the take-off and landing points are not at the location of the customer but fixed spots predefined by the city. In this context, the truck is allowed to advance during the drone delivery, providing a landing location closer to the following client and reducing the route completion time. The selection of these spots is restricted by the autonomy of the drone and the velocity of both vehicles. The urban environment is addressed by defining a different distance metric for the aerial and the terrestrial vehicle, respectively. The paper presents a mixed-integer linear programming formulation which allows to solve the given problem of computing the truck routes and selecting the optimal takeoff/landing spots in reasonable time. Illustrative examples of this problem and a computational analysis of the presented solution conclude the paper.
Paper VI175-02.16
PDF · Video · Combined Scheduling and Control Design for the Coordination of Automated Vehicles at Intersections
Kneissl, Maximilian	DENSO AUTOMOTIVE Deutschland GmbH
Molin, Adam	Denso International Europe
Kehr, Sebastian	DENSO AUTOMOTIVE Deutschland GmbH
Esen, Hasan	Denso International Europe
Hirche, Sandra	Technical University of Munich
Keywords: Multi-vehicle systems, Autonomous Mobile Robots, Mission planning and decision making Abstract: Solving the problem of intersection crossing for autonomous vehicles is a challenging task due to combined combinatoric and dynamical control decisions. To reduce the complexity of the computations and distribute the resulting global optimization problem, we propose a combined scheduling-control method. Thereby, in this paper, we focus on the formulation of a resource-constrained-project-scheduling problem (RCPSP) to solve the combinatoric decision, i.e. the order in which vehicles cross an intersection area in a central coordination unit. This problem considers control decisions from the vehicles, which are computed using model predictive control (MPC) laws. In turn, the resulting scheduling solution is incorporated again in local vehicle MPC problems, which negotiate among each other to find a dynamically feasible solution. This seamless combination of scheduling and control results in efficient solutions, which is illustrated using numerical simulation and the results are compared with afirst-come-first-served (FCFS) strategy.
Paper VI175-02.17
PDF · Video · Reducing Time Headway in Platoons under the MPF Topology in the Presence of Communication Delays
Abolfazli, Elham	Aalto University
Besselink, Bart	University of Groningen
Charalambous, Themistoklis	School of Engineering
Keywords: Multi-vehicle systems, Cooperative navigation, Automatic control, optimization, real-time operations in transportation Abstract: For platoons under the multiple-predecessor following (MPF) topology, communication delays can compromise both the internal stability and string stability. The most straightforward solution to guarantee stability is by increasing the time headway. On the other hand, time headway plays a significant role in road capacity and increasing its value is in contrast with the idea of platooning. In this study, internal stability and string stability of platoons suffering from communication delays are investigated and a lower bound for the time headway is proposed. Using this bound, platoons do not need to massively increase the time headway in order to compensate for the effects of communications delays. Finally, we evaluate the proposed lower bound on the time headway and the simulation results demonstrate its effectiveness.
Paper VI175-02.18
PDF · Video · Design of Adaptive Cruise Controllers for Externally Positive Vehicles
Schwab, Alexander	Ruhr-Universität Bochum
Lunze, Jan	Ruhr-Universität Bochum
Keywords: Multi-vehicle systems, Decentralized Control and Systems, Autonomous Vehicles Abstract: This paper addresses the design of adaptive cruise controllers for guaranteed collision avoidance. The design problem is solved with distributed feedback controllers which work with locally measurable quantities and, hence, do not require a centralised coordinating unit or a communication system. The design objectives are achieved by placing the closed-loop eigenvalues in a proposed set so that the controlled vehicle is asymptotically stable and satisfies a sufficient condition on external positivity.
Paper VI175-02.19
PDF · Video · Control of Heterogeneous Platoons Using a Delay-Based Spacing Policy
Horn, Joachim	Helmut-Schmidt-University / University of the Federal Armed Forc
Seeland, Felix	Helmut Schmidt University / University of the Federal Armed Forc
Miekautsch, Fritz	Helmut-Schmidt-University
Fay, Alexander	Helmut Schmidt Universitaet
Keywords: Multi-vehicle systems, Decentralized Control and Systems, Trajectory Tracking and Path Following Abstract: A control design approach for heterogeneous platoons is derived that achieves tracking of the desired delay-based spacing policy. The delay-based spacing policy induces an identical spatially varying velocity reference for all vehicles of the platoon. Thus, the control law is derived in the spatial domain. For a heterogeneous platoon, with individual dynamics of each vehicle, the first step of the control design is an individual exact linearization of each vehicle that transforms the heterogeneous platoon into a homogeneous platoon, where all vehicles have identical dynamics with respect to the new input. Then, a well-known control design for homogeneous platoons may be applied. The results are illustrated by simulations.
Paper VI175-02.20
PDF · Video · Limited Gradient Criterion for Global Source Seeking with Mobile Robots
Gronemeyer, Marcus	Helmut-Schmidt-University / University of the Federal Arms Hambu
Alpen, Mirco	Helmut-Schmidt-University
Horn, Joachim	Helmut-Schmidt-University / University of the Federal Armed Forc
Keywords: Cooperative navigation, Autonomous Mobile Robots, Mission planning and decision making Abstract: This paper presents a criterion and control scheme based on the assumption of a bound on the gradient of a field distribution which guarantees to find the global extremum of the distribution. Mobile robots move through the search space gathering information at points which are calculated as a minimization problem over part of the search space which is guaranteed to include the global extremum based on the previously gathered measurements. Position control in combination with collision avoidance drives each robot to the next position while communicating its position to the other robots. Upon arrival, the next measurement of the field distribution is performed and the next position reference is calculated by each robot until the robots narrowed the search area to a single location. Previously proposed control schemes can find single points as candidates for the global maximum but struggle to guarantee that this point is the global extremum. Simulation results with robot models show the performance in comparison to a naive approach.
Paper VI175-02.21
PDF · Video · Gap Opening Controller Design to Accommodate Merges in Cooperative Autonomous Platoons
Scholte, Wouter	Eindhoven University of Technology
Zegelaar, Peter	Ford Research Centre Aachen
Nijmeijer, Hendrik	Eindhoven Univ of Technology
Keywords: Multi-vehicle systems, Autonomous Vehicles, Decentralized Control and Systems Abstract: In this paper, a cooperative platoon-based gap opening controller is developed. The intended application is gap creation in cooperative platoons to accommodate merges with spatial restrictions. Therefore, the main objective is to execute the maneuver in a predefined time. The controller design is based on a regular cooperative adaptive cruise control algorithm with an additional feedforward term for a desired gap. Experimental validation of the controller is performed with small mobile robots. The proposed control strategy is capable of opening the gap in a predefined time. In future work, this strategy can be used in the design of a merging algorithm specifically for CACC platoons.
Paper VI175-02.22
PDF · Video · A Novel Formation Creation Algorithm for Heterogeneous Vehicles in Highway Scenarios: Assessment and Experimental Validation
Zambelli, Massimo	University of Pavia
Carulli, Paola	University of Pavia
Steinberger, Martin	Graz University of Technology
Horn, Martin	Graz University of Technology
Ferrara, Antonella	University of Pavia
Keywords: Multi-vehicle systems, Autonomous Vehicles, Intelligent transportation systems Abstract: In this paper a novel algorithm for the on-line creation of formations of heterogeneous vehicles is proposed for highway traffic scenarios. A two-step iterative distributed strategy is formulated which relies on Dynamic Programming and trajectory tracking. Only position measurements and basic communication capabilities for global coordination are required, while scalability is guaranteed by the underlying structure of the algorithm. In addition, spatial and velocity constraints are taken into account. The presented concept forms the basis for more sophisticated formation creation controllers. Results obtained in experiments with automated small-scale trucks show the underlying validity and practical feasibility of the algorithm.
Paper VI175-02.23
PDF · Video · Optimal Control for Connected and Autonomous Vehicles at Signal-Free Intersections
Chen, Boli	University College London
Pan, Xiao	Imperial College London
Evangelou, Simos	Imperial College
Timotheou, Stelios	University of Cyprus
Keywords: Automatic control, optimization, real-time operations in transportation, Intelligent transportation systems, Autonomous Vehicles Abstract: The development of connected and autonomous vehicles (CAVs) is one of the central aspects in the pathway towards future intelligent mobility systems. This paper addresses the problem of coordinating CAVs crossing an uncontrolled intersection so as to maintain safe and efficient traffic flow. The proposed control strategy is based on an optimal control framework that is formulated to minimize a weighted sum of total energy consumption and travel time of all CAVs by finding the optimal velocity trajectory of each vehicle. The design procedure starts with a proper formulation of the autonomous intersection crossing problem for CAVs, with various cases of energy recovery capability by the CAVs considered, to also investigate the influence of powertrain electrification on the intersection crossing problem. This yields an optimal control problem (OCP) with nonlinear and nonconvex dynamics and constraints. In order to ensure a rapid solution search and a unique global optimum, the OCP is reformulated via convex modeling techniques. Numerical results validate the effectiveness of the proposed approaches, while the trade-off between energy consumption and travel time is illustrated by Pareto optimal solutions.
Paper VI175-02.24
PDF · Video · Truck Platoon Formation at Hubs: An Optimal Release Time Rule
Johansson, Alexander	KTH
Turri, Valerio	KTH - Royal Institute of Technology
Nekouei, Ehsan	City University of Hong Kong
Johansson, Karl H.	Royal Institute of Technology
Mårtensson, Jonas	KTH Royal Institute of Technology
Keywords: Automatic control, optimization, real-time operations in transportation, Intelligent transportation systems, Freight transportation Abstract: We consider a hub-based platoon coordination problem in which vehicles arrive at a hub according to an independent and identically distributed stochastic arrival process. The vehicles wait at the hub, and a platoon coordinator, at each time-step, decides whether to release the vehicles from the hub in the form of a platoon or wait for more vehicles to arrive. The platoon release time problem is modeled as a stopping rule problem wherein the objective is to maximize the average platooning benefit of the vehicles located at the hub and there is a cost of having vehicles waiting at the hub. We show that the stopping rule problem is monotone and the optimal platoon release time policy will therefore be in the form of a one time-step look-ahead rule. The performance of the optimal release rule is numerically compared with (i) a periodic release time rule and (ii) a non-causal release time rule where the coordinator knows all the future realizations of the arrival process. Our numerical results show that the optimal release time rule achieves a close performance to that of the non-causal rule and outperforms the periodic rule, especially when the arrival rate is low.
Paper VI175-02.25
PDF · Video · Cooperative Adaptive Cruise Control of Vehicle Platoons with Fading Signals and Heterogeneous Communication Delays
Song, Xiu-lan	Zhejiang University of Technology
Xiao, Feng	Zhejiang University of Technology
Peng, Hong	Zhejiang University of Technology
He, De-feng	Zhejiang University of Technology
Keywords: Cooperative control, Intelligent driver aids, Multi-vehicle systems Abstract: This paper proposes a new cooperative adaptive cruise control (CACC) approach of vehicle platoons with fading signals and heterogeneous communication delays. The CACC model with variable input delays is established to describe the varying time-delays from transmitting acceleration of the front vehicle. The fading signal gains may be unknown and uncertain due to heterogeneous V2V wireless channels. Then a set of decentralized time-delay feedback CACC controllers is computed in such way that each vehicle evaluates its own control strategy using only neighborhood information. In order to establish string stability of the platoon with the decentralized controllers, some sufficient conditions are obtained in form of linear matrix inequalities. The scenarios, consisting of seven different cars with heterogeneous wireless channels, are used to demonstrate the effectiveness of the presented method.

VI175-03
Human Vehicle Interaction	Regular Session
Chair: Okuda, Hiroyuki	Nagoya University
Co-Chair: Baltzer, Marcel Caspar Attila	Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE
Paper VI175-03.1
PDF · Video · Scenario-Based Stochastic MPC for Vehicle Speed Control Considering the Interaction with Pedestrians
Tran, Anh Tuan	Nagoya University
Muraleedharan, Arun	Nagoya University
Okuda, Hiroyuki	Nagoya University
Suzuki, Tatsuya	Nagoya Univ
Keywords: Autonomous Vehicles, Motion control, Human and vehicle interaction Abstract: A typical driver spends a lot of the driving time on roads shared with pedestrians and bicyclists. Unlike highway driving, when there are pedestrians and cyclists using the same space as cars, controlling the car is more complicated. This is due to the fact that the behaviors of such agents does not follow strict rules like the cars in a closed highway. Their trajectories can be expressed better with multiple probabilistic functions than deterministic ones. We suggest a scenario-based stochastic model predictive control (MPC) framework to handle this. We consider multiple pedestrian trajectories with their respective probabilities according to an Interacting Multiple-Model Kalman Filter (IMM-KF). The car dynamics and non linear constraints are considered to avoid collision. A sample-based method is used to solve this optimization problem. The control situation was simulated using MATLAB. The proposed controller is observed to give a very natural control behavior for shared road driving compared to a deterministic single scenario MPC.
Paper VI175-03.2
PDF · Video · On Nonlinear Control for Lane Keeping Assist System in Steer-By-Wire Road Wheeled Vehicles
Perozzi, Gabriele	Université Politechnique Hauts-De-France
Sentouh, Chouki	University of Valenciennes - LAMIH UMR CNRS 8201
Floris, Jerome	Université Polytechnique Haut-De-France - LAMIH-CNRS
Popieul, Jean-Christophe	University of Valenciennes/LAMIH
Keywords: Human and vehicle interaction, Adaptive and robust control of automotive systems, Vehicle dynamic systems Abstract: This paper deals with the design of a lane-keeping system in steer-by-wire road four-wheeled vehicles using a nonlinear controller. The controller is designed to take into account the driver's behavior and availability and to control the wheels' angle of the steering system. A high order sliding mode control is chosen as a feedback controller, having time-varying upperbound disturbance strictly depended by the road curvature and by the influence of the wind, which allows an easier tuning process of the parameters based on a physical meaning and a consequent attenuation of the chattering effect. The controller must be robust to minimize the lateral deviation and the heading errors, and it must be sensitive to assist the driver during the shared control mode, i.e. the assist system must give the authority to the driver when the driver is available.
Paper VI175-03.3
PDF · Video · Modeling the Decision-Making in Human Driver Overtaking
Stefansson, Elis	KTH Royal Institute of Technology
Jiang, Frank J.	KTH Royal Institute of Technology
Nekouei, Ehsan	City University of Hong Kong
Nilsson, Håkan	Uppsala University
Johansson, Karl H.	Royal Institute of Technology
Keywords: Human and vehicle interaction, Autonomous Vehicles Abstract: We propose models for the decision-making process of human drivers in an overtaking scenario. First, we mathematically formalize the overtaking problem as a decision problem with perceptual uncertainty. Then, we propose and numerically analyze risk-agnostic and risk-aware decision models, which are able to judge whether an overtaking is desirable or not. We show how a driver's decision-making time and confidence level can be primarily characterized through two model parameters, which collectively represent human risk-taking behavior. We detail an experimental testbed for evaluating the decision-making process in the overtaking scenario. Finally, we present some preliminary experimental results from two human drivers.
Paper VI175-03.4
PDF · Video · Rider Model Identification Using Dynamic Neural Networks
Loiseau, Paul	IMT Atlantique, LS2N
Boultifat, Chaouki Nacer Eddine	IRCCyN UMR CNRS 6597 (Institut De Recherche En Communication Et
Chevrel, Philippe	IMT Atlantique / LS2N
Claveau, Fabien	Ecole Des Mines De Nantes
Espié, Stéphane	INRETS
Mars, Franck	CNRS
Keywords: Human and vehicle interaction, Modeling and simulation of transportation systems, Human factors in vehicular system Abstract: Car driver modeling is a well-known research topic, with significant existing contributions. In contrast, important questions related to motorcyclist modeling remain unanswered. This study focuses on identifying a motorcyclist model that can predict the steering angle and the rider roll angle. A black box rider model in the form of a time delay neural network is presented. This model was developed using experimental data recorded with an instrumented motorcycle from the VIROLO++ research project. It is used for three main issues. First, the selection of input signals and their impact on prediction performance is discussed. Next, the model's ability to predict the behavior of a variety of motorcyclists is demonstrated. Finally, the nonlinearity of the model is analyzed. These results pave the way to the development of a cybernetic rider model.
Paper VI175-03.5
PDF · Video · A Cascade Steering Shared Controller with Dual-Level Dynamic Authority
Marcano, Mauricio	Tecnalia
Diaz, Sergio	TECNALIA
Matute, Jose Angel	Tecnalia
Irigoyen, Eloy	University of the Basque Country (UPV/EHU)
Perez Rastelli, Joshue M	Tecnalia
Keywords: Intelligent driver aids, Man-machine interface in transportation, Human and vehicle interaction Abstract: Advanced Driver Assistance Systems (ADAS) that consider the driver in the control loop (Shared Control ADAS) have the potential to influence upcoming functionalities in partially automated vehicles, improving the driving performance, reducing the workload, and increasing safety. According to the literature, two design parameters are relevant based on the cognitive level of the driving task. First, at the operational level, the steering controller must have a variable Level of Haptic Authority (LoHA), demanding more or less effort from the driver to override the system. Secondly, the tactical level needs an arbitration system to manage the transitions from manual-to-automated and automated-to-manual safely and progressively, with a variable Level of Shared Authority (LoSA). Based on these premises, this paper presents a cascade steering shared controller with a dual-level authority. The operational level consists of a hybrid MPC-PD controller, and the tactical level uses a Fuzzy Inference System (FIS). Results show the benefits of the system, assisting the driver in a collaborative overtaking maneuver.
Paper VI175-03.6
PDF · Video · Human-Vehicle Interaction with a Metaphor Based Collision Avoidance Interaction Pattern
Baltzer, Marcel Caspar Attila	Fraunhofer Institute for Communication, Information Processing A
Bloch, Marten	Fraunhofer FKIE
Wasser, Joscha	Fraunhofer FKIE
Flemisch, Frank	RWTH Aachen University
Keywords: Man-machine interfaces, Human factors in vehicular system, Safety Abstract: Following the successful digitalisation of tasks within the aviation domain, this development has now also reached road-based vehicles and is quickly progressing in the form of computer-based, assisted and automated driving. As these systems are becoming increasingly more complex and intelligent, design and interaction patterns can be an effective tool to translate complex systems into schemes that are intuitive to use and thus play a crucial part in the systematic resolution of conflicts between computers and humans. One example of such a conflict are collision avoidance systems due to it overruling the input of the driver in an emergency. As a potential solution, an interaction pattern approach is presented for a non-line-of sight collision avoidance and subsequently evaluated in a driving simulator setting. Here a state of the art emergency brake was compared with an escalating interaction pattern, implemented with different degrees of multi-modality. The authors propose the use of Image schemas, applying their underlying metaphorical extensions to support an intuitive interaction. An evaluation with Bayesian regression models suggests that a visual and multimodal implementation improves user experience and safety.
Paper VI175-03.7
PDF · Video · Corridor-Based Shared Autonomy for Teleoperated Driving
Schitz, Dmitrij	University of Rostock
Graf, Gaetano	LMU
Rieth, Dominik	BMW Group
Aschemann, Harald	University of Rostock
Keywords: Teleoperation, Autonomous Vehicles, Trajectory and Path Planning Abstract: Given the on-going development of powerful hardware, software and algorithms for automated driving, the number of tasks that vehicles can solve autonomously steadily increases. However, fully autonomous driving in all situations is highly demanding and currently not feasible yet. It may happen that the vehicle faces situations in which the decision system is overstrained and, hence, falls back into a predefined safe state. In the future, moreover, neither control interfaces like a steering wheel and foot pedals nor a qualified driver may be available to assist the car in a blocking situation. This contribution, hence, presents a concept for teleoperated driving, i.e., a remote operation with distinct human machine interactions that explicitly addresses such highly complex driving tasks. It quickly copes with such undesired blocking situations in order to minimize the need for a both time- and cost-intensive road assistance. The concept focusses on teleoperated driving of road vehicles in urban environments. Based on the methodology of a shared autonomy, a corridor-based planning scheme is derived. The remote operation task takes advantage of a fusion of automated driving functions and human-predefined corridors. Within this specified corridor, a path planning algorithm using dual projected Newton method determines a collision-free path that the vehicle is capable to follow. Simulation results show the effectiveness of the proposed method and highlight the achieved driving safety.
Paper VI175-03.8
PDF · Video · A Real-Time Driver Fatigue Detection Method Based on Two-Stage Convolutional Neural Network
He, Hu	Central South University
Zhang, Xiaoyong	Central South University
Jiang, Fu	Central South University
Wang, Chenglong	Central South University
Yang, Yingze	Central South University
Liu, Weirong	Central South University
Peng, Jun	Central South University
Keywords: Safety, Information processing and decision support Abstract: Fatigue-related traffic accidents have a higher mortality rate and cause more significant damage to the environment. To ensure driving safety, a real-time driver fatigue detection method based on convolutional neural network (CNN) is proposed in this paper. The proposed fatigue driving detection method is cascaded by two CNN-based stages, including a detecting phase and classifying phase. The Location Detection Network is designed to extract facial features and localize the driver’s eyes and mouth regions. Then the State Recognition Network is training to recognize the driver’s eyes and mouth status. Simulations show that the proposed method has good effect of real time process and high accuracy of detection. Experiments conducted on Raspberry Pi 4 embedded system indicate that the proposed method has a good performance in the real driving environment.

VI175-04
Mission Planning and Decision Making for Autonomous Vehicles	Regular Session
Chair: Stursberg, Olaf	University of Kassel
Co-Chair: van de Mortel-Fronczak, Joanna	Eindhoven University of Technology
Paper VI175-04.1
PDF · Video · Decision Making for Autonomous Vehicles: Combining Safety and Optimality
Verbakel, Jeroen Johannes	Eindhoven University of Technology
Fusco, Mauro	TNO
Willemsen, Dehlia	TNO
van de Mortel-Fronczak, Joanna	Eindhoven University of Technology
Heemels, Maurice	Eindhoven University of Technology
Keywords: Autonomous Vehicles, Mission planning and decision making, Multi-vehicle systems Abstract: In this paper, we propose a novel decision maker design for an autonomous vehicle driving on a highway, considering safety and optimality, and which is scalable, i.e., remains computationally tractable for more complex situations. This is realized in two stages. First, all safe actions are found, and second, from these actions the optimal action is selected, according to (weighted) criteria that capture safety, comfort and efficiency. The design combines rule-based safety checks with the solution of a Markov decision process, found through a tree search algorithm, to fulfill the safe, smart and scalable requirements of the decision maker. The design is validated in simulation using eight different scenarios. The performance of the new design is compared to the performance of a rule-based controller. This comparison is done using three performance criteria that aim to capture safety, efficiency and comfort.
Paper VI175-04.2
PDF · Video · Minimizing the Information Leakage Regarding High-Level Task Specifications
Hibbard, Michael	University of Texas at Austin
Savas, Yagiz	The University of Texas at Austin
Xu, Zhe	The University of Texas at Austin
Topcu, Ufuk	University of Pennsylvania
Keywords: Mission planning and decision making, Trajectory and Path Planning, Autonomous Mobile Robots Abstract: We consider a scenario in which an autonomous agent carries out a mission in a stochastic environment while passively observed by an adversary. For the agent, minimizing the information leaked to the adversary regarding its high-level specification is critical in creating an informational advantage. We express the specification of the agent as a parametric linear temporal logic formula, measure the information leakage by the adversary's confidence in the agent's mission specification, and propose algorithms to synthesize a policy for the agent which minimizes the information leakage to the adversary. In the scenario considered, the adversary aims to infer the specification of the agent from a set of candidate specifications, each of which has an associated likelihood probability. The agent's objective is to synthesize a policy that maximizes the entropy of the adversary's likelihood distribution while satisfying its specification. We propose two approaches to solve the resulting synthesis problem. The first approach computes the exact satisfaction probabilities for each candidate specification, whereas the second approach utilizes the Frechet inequalities to approximate them. For each approach, we formulate a mixed-integer program with a quasiconcave objective function. We solve the problem using a bisection algorithm. Finally, we compare the performance of both approaches on numerical simulations.
Paper VI175-04.3
PDF · Video · Set-Based Scheduling for Highway Entry of Autonomous Vehicles
Eilbrecht, Jan	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Mission planning and decision making, Trajectory and Path Planning, Intelligent transportation systems Abstract: This paper proposes a framework for generation of collision-free reference trajectories in a cooperative multi-agent setting. The approach is hierarchical: a high-level controller schedules groups of cooperating agents, for which trajectories are then determined by a lower-level trajectory planner. Admissible behaviors of a cooperative group are encoded by so-called maneuvers, which are modeled by hybrid automata. This allows to plan trajectories by solving hybrid optimal control problems. Controllable sets characterize the solution sets of these problems and are used for quick assessment of feasibility prior to planning. This enables the high-level controller to quickly assess the feasibility of different maneuver options and cooperative groups. Special emphasis is put on safety and feasibility of the framework. The efficacy of the approach is demonstrated by simulation of a highway entry scenario for autonomous vehicles.
Paper VI175-04.4
PDF · Video · Fast, Composable Rescue Mission Planning for UAVs Using Metric Temporal Logic
Fiaz, Usman A.	University of Maryland, College Park
Baras, John S.	Univ. of Maryland
Keywords: Mission planning and decision making, Trajectory and Path Planning, Navigation, Guidance and Control Abstract: We present a hybrid compositional approach for real-time mission planning for multi-rotor unmanned aerial vehicles (UAVs) in a time critical search and rescue scenario. Starting with a known environment, we specify the mission using Metric Temporal Logic (MTL) and use a hybrid dynamical model to capture the various modes of UAV operation. We then divide the mission into several sub-tasks by exploiting the invariant nature of safety and timing constraints along the way, and the different modes (i.e., dynamics) of the UAV. For each sub-task, we translate the MTL specifications into linear constraints and solve the associated optimal control problem for desired path, using a Mixed Integer Linear Program (MILP) solver. The complete path for the mission is constructed recursively by composing the individual optimal sub-paths. We show by simulations that the resulting suboptimal trajectories satisfy the mission specifications, and the proposed approach leads to significant reduction in computational complexity of the problem, making it possible to implement in real-time.
Paper VI175-04.5
PDF · Video · Optimal Control As a Tool for Solving Sonar Design, Resource Allocation, and Planning Problems in Search Applications
Kragelund, Sean	Naval Postgraduate School
Walton, Claire	Naval Postgraduate School
Kaminer, Isaac	Naval Postgraduate School
Dobrokhodov, Vladimir	Naval Postgraduate School
Keywords: Mission planning and decision making, Trajectory and Path Planning, Unmanned marine vehicles Abstract: This paper employs a computational optimal control framework which provides trajectory planning for search applications based on specific vehicle and sensor features. With its capability to handle high-dimensional, nonlinear optimal control problems with uncertainty, this framework enables detailed modeling and leveraging of vehicle/sensor features to generate better performing search plans. This paper utilizes these trajectory planning tools for the inverse problem of deciding on the vehicle and sensor characteristics themselves. Using Monte Carlo sampling, we generate multiple trajectories to examine the performance of different vehicle and sensor configurations. We use this method to study three examples: sonar mounting angle, vehicle asset allocation, and lane space planning for time-limited lawnmower search plans.
Paper VI175-04.6
PDF · Video · Design and Control of Park & Charge Lanes for Carsharing Services with Highly-Automated Electric Vehicles
Dandl, Florian	Technical University of Munich
Niels, Tanja	Bundeswehr University Munich
Bogenberger, Klaus	Technical University of Munich
Keywords: autonomic transport systems, Automatic control, optimization, real-time operations in transportation, Electric and solar vehicles Abstract: Carsharing operators could benefit from vehicle automation even before full vehicle automation is available city-wide: so-called Park- & Charge Lanes (PCL) installed in closed environments can increase customer convenience and reduce costs for parking space and charging operations. The concept introduced in this study comprises the stacking of vehicles in several lanes of optimized width, the division of lanes into charging and parking areas, and control strategies for efficient operation. Compared to conventional parking lots with two lanes and two perpendicularly arranged parking spaces, the stacking of vehicles allows for space reductions of up to 43 %. Additional cost savings can be achieved, since it is not necessary to equip every parking space with an inductive charging plate. Splitting each lane into a parking and a charging area makes the optimal control problem non-trivial: In order to provide the vehicles with a battery level that is high enough to serve customer requests, the PCL has to be controlled in a smart way. Both rule-based and model-predictive control policies are developed for assigning arriving vehicles to lanes and selecting vehicles for customer requests. An event-based simulation framework is created in order to test the performance of the introduced policies for the resulting dynamic and stochastic PCL problem. The best of the four described rule-based policies performs nearly as good as the implemented model-predictive control approach in the numerical experiment. The model-predictive control policy outperforms the random lane selection by 27 %, which clearly reflects the benefit of using advanced control strategies.
Paper VI175-04.7
PDF · Video · Multi-Level Electric Vehicle Charging Facilities with Limited Resources
Santoyo, Cesar	Georgia Tech
Nilsson, Gustav	Georgia Institute of Technology
Coogan, Samuel	Georgia Tech
Keywords: Modeling and simulation of transportation systems, Information processing and decision support, Electric and solar vehicles Abstract: In this paper, we consider electric vehicle charging facilities with limited space and power resources. We assume the facility offers a finite selection of levels, i.e., charging rates, for varying prices. Users arrive at the facility randomly, requiring a random amount of charge and possessing a random impatience factor dictating their value of time. Each user then chooses a charging rate that minimizes their total cost that includes an opportunity cost for the time required to charge associated with their impatience factor. Knowing the probability distribution of user charging demands, user impatience factors, and the number of arrivals at a charging facility, we present high-confidence bounds on the total number of active users and aggregate power use of all active users at any given time. We present a case study to illustrate the results.
Paper VI175-04.8
PDF · Video · Travel Time Estimation by Means of Google API Data
Wagner, Jan Martin Simon	Hochschule Niederrhein, University of Applied Sciences, 47805 Kr
Eschbach, Manuel	Hochschule Niederrhein
Vosseberg, Kari	Hochschule Niederrhein
Gennat, Marc	Hochschule Niederrhein University of Applied Science
Keywords: Modeling and simulation of transportation systems, Simulation, Navigation Abstract: Modern urban planning not only has to coordinate the needs of many different inhabitants and traffic participants, but also faces other challenges such as modal shift towards sustainable transportation. A comprehensive database of historical traffic, which would facilitate a decision based on data, is lacking in many cities. This became clear in consultation with our partners from the city of Krefeld. A novel method is the use of public available traffic information such as traffic colors or travel time data from navigation providers. In this contribution a method is applied to estimate the travel duration from the traffic colors on city level. Here we show for the first time how it can be applied cost-effectively and how the accuracy can be estimated in combination with a validation of the database by test drives for urban streets. It will also be investigated, whether speed variation has an influence on the estimation of driving time. We found out that this influence is negligible for the investigated example and the mean deviation of estimation accuracy from the measured values is less than six percent. Based on these promising results, it is possible to build up a database for improved urban and traffic planning at low cost. This can lead to better information for all traffic participants, thus, an improved traffic flow control could result in a reduction of car traffic emissions in the end.

VI175-05
Perception for Autonomous Vehicles	Regular Session
Chair: Zug, Sebastian	TU Bergakademie Freiberg
Co-Chair: Kowalewski, Stefan	RWTH Aachen Univ
Paper VI175-05.1
PDF · Video · Extended Target Tracking for Autonomous Street Crossing
Parravicini, Filippo	Politecnico Di Milano - Dipartimento Di Elettronica, Informazion
Corno, Matteo	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
Keywords: Autonomous Mobile Robots, Autonomous Vehicles, Sensor integration and perception Abstract: Autonomous navigation on sidewalks and pedestrian areas is a complex problem, that requires the solution of different challenging tasks. One that is particularly hard to tackle is that of autonomous street crossing, which requires the robot to be aware of the position and speed of surrounding vehicles in order to decide whether is safe to cross. This work is dedicated to the development of an obstacle speed estimation algorithm to be applied to the context of autonomous navigation at crosswalks. In particular, a novel approach to the extended-target tracking problem is presented, which leverages a nested structure and a clustering algorithm that reduces the problem to a standard target tracking one. The effectiveness of the algorithm is demonstrated through testing on a prototype parcel-delivery robot operating in a real-world urban environment.
Paper VI175-05.2
PDF · Video · Vision-Based Real-Time Indoor Positioning System for Multiple Vehicles
Kloock, Maximilian	RWTH Aachen University
Scheffe, Patrick	RWTH Aachen University
Tuelleners, Isabelle	RWTH Aachen University
Maczijewski, Janis	RWTH Aachen University
Kowalewski, Stefan	RWTH Aachen Univ
Alrifaee, Bassam	RWTH Aachen University
Keywords: Autonomous Mobile Robots, Multi-vehicle systems, Localization Abstract: We propose a novel external indoor positioning system that computes the position and orientation of multiple model-scale vehicles. For this purpose, we use a camera mounted at a height of 3.3m and LEDs attached to each vehicle. We reach an accuracy of about 1.1 cm for the position and around 0.6 ° for the orientation in the mean. Our system is real-time capable with a soft deadline of 20 ms. Moreover, it is robust against changing lighting conditions and reections.
Paper VI175-05.3
PDF · Video · Robust Feature-Based Point Registration Using Directional Mixture Model
Fahandezh-Saadi, Saman	University of California, Berkeley
Wang, Di	Xi'an Jiaotong Univeristy
Tomizuka, Masayoshi	Univ of California, Berkeley
Keywords: Autonomous Vehicles, Localization, Sensor integration and perception Abstract: This paper presents a robust probabilistic point registration method for estimating the rigid transformation (i.e. rotation matrix and translation vector) between two pointcloud dataset. The method improves the robustness of point registration and consequently the robot localization in the presence of outliers in the pointclouds which always occurs due to occlusion, dynamic objects, and sensor errors. The framework models the point registration task based on directional statistics on a unit sphere. In particular, a Kent distribution mixture model is adopted and the process of point registration has been carried out in the two phases of Expectation-Maximization algorithm. The proposed method has been evaluated on the pointcloud dataset from LiDAR sensors in an indoor environment.
Paper VI175-05.4
PDF · Video · Multi-Dimensional Failure Modeling for Shared Data in Cooperative Systems
Jäger, Georg	TU Bergakademie Freiberg
Konstantin, Kirchheim	Otto-von-Guericke-University
Schrödel, Frank	IAV GmbH
Zug, Sebastian	TU Bergakademie Freiberg
Keywords: Cooperative perception, Sensor integration and perception, Fault Detection, Diagnosis, Identification, Isolation and Tolerance for Autonomous Vehicles Abstract: Autonomous systems will share data to enrich their environmental model and provide cooperative functionality. However, as shared data might be imprecise or inaccurate, its failure characteristics have to be analyzed by the receiving system before using the data. A corresponding failure model for describing failure characteristics was proposed by Jäger et al. (2018), but is limited to one-dimensional sensory data. In this work, we extend the failure model to support multi-dimensional feature data as well. We exemplary evaluate the approach by modeling the failure characteristics of a lane detection system of a simulated car. By comparing it to state-of-the-art failure modeling techniques, we can show that the model accurately predicts failure amplitudes of previously unseen tracks even when trained on limited data.
Paper VI175-05.5
PDF · Video · LiDAR Based Obstacle Detection for Snow Groomers
Onesto, Luca	Politecnico Di Milano
Corno, Matteo	Politecnico Di Milano
Franceschetti, Luca	Politecnico Di Milano
Hokka, Ensio	TTControl
Savaresi, Sergio	Politecnico Di Milano
Keywords: Intelligent driver aids, Sensor integration and perception, Automotive sensors and actuators Abstract: The presents an obstacle detection system for snow groomers. The system is based on a 2D solid-states LiDAR sensor mounted on the top of the cabin. The measurements describe the surrounding environment through an Occupancy Grid framework, which is extended for this particular case study. The proposed approach set the occupancy probability of the surrounding environment based on the expected height of the obstacle. The method is extensively analyzed through experimental test on a snow groomer.
Paper VI175-05.6
PDF · Video · Imaging-Sonar-Based Underwater Object Recognition Utilizing Object's Yaw Angle Estimation with Deep Learning
Sung, Minsung	Pohang University of Science and Technology
Lee, Meungsuk	POSTECH
Kim, Byeongjin	POSTECH(Pohang University of Science and Technology)
Yu, Son-Cheol	Pohang University of Science and Technology
Keywords: Sensing, Learning and adaptation in autonomous vehicles, Robot Navigation, Programming and Vision Abstract: This paper proposes a method to recognize underwater target objects and estimate their yaw angle using an imaging sonar. First, a light sonar simulator generated template images of the target objects from various viewing angles. Next, a generative adversarial network predicted a semantic map by segmenting the real sonar image for reliable recognition. Then, matching the template images and semantic map identifies the target object and its yaw angle. We verified the proposed method by installing objects in the indoor water tank. The proposed method can provide relative pose information of sensing platforms which is useful for pose control and navigation.
Paper VI175-05.7
PDF · Video · Optimal Geometry for Ultra-Wideband Localization Using Bayesian Optimization
Zhao, Wenda	University of Toronto
Vukosavljev, Marijan	University of Toronto
Schoellig, Angela P.	University of Toronto
Keywords: Positioning Systems, Localization Abstract: This paper introduces a novel algorithm to find a geometric configuration of ultra-wideband sources in order to provide optimal position estimation performance with Time-Difference-of-Arrival measurements. Different from existing works, we aim to achieve the best localization performance for a user-defined region of interest instead of a single target point. We employ an analysis based on the Cramer-Rao lower bound and dilution of precision to formulate an optimization problem. A Bayesian optimization-based algorithm is proposed to find an optimal geometry that achieves the smallest estimation variance upper bound while ensuring source placement constraints. The approach is validated through simulation and experimental results in 2D scenarios, showing an improvement over a naive source placement.
Paper VI175-05.8
PDF · Video · Active Monitoring of the State of Motion in Two-Wheeled Vehicles in Absence of a Valid GPS/GNSS Signal
Gelmini, Simone	Politecnico Di Milano
Strada, Silvia	Politecnico Di Milano
Tanelli, Mara	Politecnico Di Milano
Savaresi, Sergio	Politecnico Di Milano
De Tommasi, Claudio	AlfaEvolution Technology SpA
Keywords: Intelligent driver aids, Sensing, Vehicle dynamic systems Abstract: In insurance telematics, the information about the vehicle motion is mostly derived by a combination of inertial signals derived from e-Boxes installed integral to the vehicle and GPS information, which is used for crash-detection monitoring and other vehicle-based services. However, one must cope with poor reliability and possible lack of continuity of the signals coming from Global Navigation Satellite Systems (GNSSs). In this work, a classification method that discriminates whether a two-wheeled vehicle is in motion or at standstill, through the analysis of inertial measurements, is presented. The purpose of this detection is to classify in a binary fashion, i.e., moving/non-moving the motion of the vehicle, which can be helpful for applications where this information is crucial and the speed measurement is not available or not sufficiently reliable mostly due to an invalid GPS/GNSS signal. With respect to what is proposed by many dead-reckoning algorithms, the present contribution aims to recognize when the vehicle is moving without estimating the vehicle speed, but rather by correctly interpreting the intensity of the measured inertial signals that come from a telematic eBox. The approach is extensively tested on experimental data, proving its suitability for practical applications.
Paper VI175-05.9
PDF · Video · Maneuver Classification for Road Vehicles with Constrained Filtering Techniques
Törő, Olivér	Budapest University of Technology and Economics
Bécsi, Tamás	Budapest Univ of Technology and Economics
Aradi, Szilárd	Budapest University of Technology and Economics
Kolat, Máté	Budapest University of Technology and Economics
Gaspar, Peter	SZTAKI
Keywords: Sensor integration and perception, Modeling and simulation of transportation systems, Intelligent driver aids Abstract: Environment perception and situation awareness are keystones for autonomous road vehicles. The problem of maneuver classification for road vehicles in the context of multi-model state estimation under model uncertainty is addressed in this paper. The conventional approach is to define different motion models that match the desired type of movements. In this work we used a single motion model as a starting point and applied constraints to construct such filters that are fine tuned for the predefined maneuvers. The estimation is carried out in the interacting multiple model framework, where the elemental filters are constrained Kalman filters. To capture the characteristics of the considered maneuvers linear equality and non-equality state constraints were used. The performance of the proposed method is demonstrated in a simulation environment participating an observer and a maneuvering vehicle.

VI175-06
Trajectory and Path Planning for Autonomous Vehicles	Regular Session
Chair: Axehill, Daniel	Linköping University
Co-Chair: Tumova, Jana	Royal Institute of Technology
Paper VI175-06.1
PDF · Video · Surface-Driven Next-Best-View Planning for Exploration of Large-Scale 3D Environments
Hardouin, Guillaume	ONERA
Morbidi, Fabio	Université De Picardie Jules Verne
Moras, Julien	ONERA
Marzat, Julien	ONERA - the French Aerospace Lab
Mouaddib, El Mustapha	Université De Picardie Jules Verne
Keywords: Autonomous Mobile Robots, Trajectory and Path Planning, Map building Abstract: In this paper, we propose a novel cluster-based informative path planning algorithm to simultaneously explore and inspect a large-scale unknown environment with an Unmanned Aerial Vehicle (UAV). Most of the existing methods address the surface inspection problem as a volume exploration problem, and consider that the surface has been scanned when the corresponding volume has been covered. Unfortunately, this approach may lead to inaccurate 3D models of the environment, and the UAV may not achieve global coverage. To overcome these critical limitations, we introduce a 3D reconstruction method based on TSDF (Truncated Signed Distance Function) mapping, which leverages the surfaces present in the environment to generate an informative exploration path for the UAV. A Probabilistic Roadmap planner, used to solve a TSP (Travelling Salesman Problem) over clusters of viewpoint configurations, ensures that the resulting 3D model is accurate and complete. Two challenging structures (a power plant and the Statue of Liberty) have been chosen to conduct realistic numerical experiments with a quadrotor UAV. Our results provide evidence that the proposed method is effective and robust.
Paper VI175-06.2
PDF · Video · Automatic Deep Stall Recovery Using Optimal Trajectory Planning
Babl, Martin Ludwig Dietrich	University of Stellenbosch
Engelbrecht, Jacobus Adriaan Albertus	Stellenbosch University
Keywords: Autonomous Vehicles, Safety, Trajectory and Path Planning Abstract: This paper presents the design of an automatic deep stall recovery algorithm for large transport aircraft using optimal trajectory planning. Deep stall is a condition where an aircraft is trapped in a nose-high stall condition and its elevators cannot produce enough nose-down pitching moment to recover the aircraft from the stall. The NASA Generic Transport Model (GTM) is used as the basis for the design and verification of the system. The aerodynamic model of the NASA GTM simulation model is modified to exhibit deep stall behaviour. Simulations are performed to show that the modified aircraft model can be pushed into deep stall, and cannot be recovered using elevator actions only. The deep stall recovery task is formulated as an optimal path planning problem and solved using an A* search algorithm to find the optimal sequence of control actions and the resulting optimal state trajectory to escape from the deep stall. The A* algorithm performs the planning using a simplified, three-degrees-of-freedom (3DOF) aircraft model that models only the fast rotational dynamics. The automatic deep stall recovery is then verified in simulation using the full six-degrees-of-freedom (6DOF) NASA GTM aircraft model. The simulation results show that the system successfully recovers the aircraft from deep stall. The optimal sequence of control actions first uses the rudder to yaw the horizontal tailplane out of the aircraft's own wake to regain elevator effectiveness, and then uses the elevators to pitch the nose down and recover from the stall.
Paper VI175-06.3
PDF · Video · Trajectory Planning and Vehicle Control at Low Speed for Home Zone Manoeuvres
Borrello, Giulio	Centro Ricerche FIAT S.c.p.A
Raffone, Enrico	Centro Ricerche FIAT S.c.p.A
Rei, Claudio	Centro Ricerche FIAT S.c.p.A
Fossanetti, Massimo	Centro Ricerche FIAT S.c.p.A
Keywords: Autonomous Vehicles, Trajectory and Path Planning, Motion control Abstract: Trajectory Planning and Vehicle Control at low speed is the automation of traditional manual vehicle maneuvers in home zones. We refer to living streets that are designed primarily to meet the needs of pedestrians, cyclists, children and residents and where the speeds and dominance of the cars are limited. In this study, we present the trajectory planning and vehicle control by using model predictive control (MPC) both for lateral and longitudinal dynamics. In particular, the lateral control of the vehicle solves a convex optimization with steering and lateral travel range constraints. It is based on a linear model of vehicle kinematics which is synthesized from nonlinear dynamics by using time-state control form (TSCF) transformation. The longitudinal model predictive control is based on a simple double integrator model with longitudinal travel and speed references. The performance of the proposed method is verified with a V-cycle model-based approach, starting from Model-in-the-Loop simulation through vehicle experiments on Jeep Renegade InterACT EU project prototypal vehicle.
Paper VI175-06.4
PDF · Video · Path Planning and Tracking for Autonomous Vehicle Collision Avoidance with Consideration of Tire-Road Friction Coefficient
Hu, Juqi	Concordia University
Zhang, Youmin	Concordia University
Rakheja, Subhash	Concordia Univ
Keywords: Autonomous Vehicles, Trajectory and Path Planning, Trajectory Tracking and Path Following Abstract: Autonomous vehicles (AVs) have attracted a lot of attention in recent years and fully autonomous vehicles are expected on road in the near future. Collision avoidance is one of the key driving tasks for autonomous driving which consists of path planning and tracking control. The main problem discussed in this paper is the development of a path planning and tracking framework based on model predictive control (MPC) with consideration of the estimated tire-road friction coefficient (TRFC). The planned path in terms of lateral position is generated based on the safety distance between the host and the obstacle vehicle, which is related to TRFC and vehicle speed. A new structure of MPC is further designed so that only lateral position is required to track the planned path. Moreover, the adaptive weights on the outputs to a wide range of vehicle speeds have been identified. The effectiveness of the proposed planning and tracking framework is validated through CarSim-MATLAB/Simulink co-simulations on both high- and low-friction roads.
Paper VI175-06.5
PDF · Video · Towards Integrated Perception and Motion Planning with Distributionally Robust Risk Constraints
Renganathan, Venkatraman	The University of Texas at Dallas
Shames, Iman	University of Melbourne
Summers, Tyler	University of Texas at Dallas
Keywords: Trajectory and Path Planning, Autonomous Mobile Robots, Mission planning and decision making Abstract: Safely deploying robots in uncertain and dynamic environments requires a systematic accounting of various risks, both within and across layers in an autonomy stack from perception to motion planning and control. Many widely used motion planning algorithms do not adequately incorporate inherent perception and prediction uncertainties, often ignoring them altogether or making questionable assumptions of Gaussianity. We propose a distributionally robust incremental sampling-based motion planning framework that explicitly and coherently incorporates perception and prediction uncertainties. We design output feedback policies and consider moment-based ambiguity sets of distributions to enforce probabilistic collision avoidance constraints under the worst-case distribution in the ambiguity set. Our solution approach, called Output Feedback Distributionally Robust RRT*(OFDR-RRT*), produces asymptotically optimal risk-bounded trajectories for robots operating in dynamic, cluttered, and uncertain environments, explicitly incorporating mapping and localization error, stochastic process disturbances, unpredictable obstacle motion, and uncertain obstacle locations. Numerical experiments illustrate the effectiveness of the proposed algorithm.
Paper VI175-06.6
PDF · Video · Sampling-Based Motion Planning with Temporal Logic Missions and Spatial Preferences
Karlsson, Jesper	KTH Royal Institute of Technology
Barbosa, Fernando S.	KTH Royal Institute of Technology
Tumova, Jana	Royal Institute of Technology
Keywords: Trajectory and Path Planning, Autonomous Mobile Robots, Safety Abstract: While motion planning under temporal logic specifications has been addressed in several state-of-the-art works, spatial aspects have been so far largely neglected. In this work, we enrich the semantics of robot motion specifications by including preferences on spatial relations between its trajectory and various elements in its environment. The spatial preferences are given in a fragment of Signal Temporal Logic (STL) on top of complex missions in syntactically co-safe Linear Temporal Logic (scLTL). We propose a cost function with user-specified parameters, which determines the compromise between efficiency and spatial robustness of a trajectory. The proposed modification of the incremental sampling-based RRT* driven by this cost function guarantees that the motion plan (if found) simultaneously satisfies the mission and asymptotically minimize the cost. The paper includes several case studies showcasing the effects of the user-adjustable parameters on the resulting trajectories.
Paper VI175-06.7
PDF · Video · Towards Time-Optimal CACD Motion Primitives with Smooth Transitions
Klancar, Gregor	Univ of Ljubljana
Loknar, Martina	University of Ljubljana, Faculty of Electrical Engineering
Blazic, Saso	Univ of Ljubljana
Keywords: Trajectory and Path Planning, Autonomous Mobile Robots, Vehicle dynamic systems Abstract: The present paper aims to study the time-optimal path planning problem for a wheeled mobile robot in an obstacle-free environment with given initial and final configuration and considering constraints on maximal permissible velocity, acceleration, and jerk. The path consists of analytically derived constant acceleration and constant deceleration (CACD) motion primitives, which at the junctions also ensure smooth transitions of curvature, vehicle's acceleration, and jerk. Smooth path planning is chosen to prevent instant changes of acceleration that improves the driving comfort, the tracking performance and lowers wear of actuators. Conducted experiments confirm that the proposed motion primitives form a feasible, time-optimal path under given dynamical constraints.
Paper VI175-06.8
PDF · Video · An Optimization-Based Receding Horizon Trajectory Planning Algorithm
Bergman, Kristoffer	Linkoping University
Ljungqvist, Oskar	Linköping University
Glad, Torkel	Linkoping University
Axehill, Daniel	Linköping University
Keywords: Trajectory and Path Planning, Autonomous Vehicles Abstract: This paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. The proposed approach is a two-step procedure that uses a motion planning algorithm in a first step to efficiently find a feasible, but possibly suboptimal, nominal solution to the trajectory planning problem where in particular the combinatorial aspects of the problem are solved. The resulting nominal trajectory is then improved in a second optimization-based receding horizon planning step which performs local trajectory refinement over a sliding time window. In the second step, the nominal trajectory is used in a novel way to both represent a terminal manifold and obtain an upper bound on the cost-to-go online. This enables the possibility to provide theoretical guarantees in terms of recursive feasibility, objective function value, and convergence to the desired terminal state. The established theoretical guarantees and the performance of the proposed algorithm are verified in a set of challenging trajectory planning scenarios for a truck and trailer system.
Paper VI175-06.9
PDF · Video · Autonomous-Vehicle Maneuver Planning Using Segmentation and the Alternating Augmented Lagrangian Method
Anistratov, Pavel	Linköping University
Olofsson, Bjorn	Lund University
Burdakov, Oleg	Linköping University
Nielsen, Lars	Linköping University
Keywords: Trajectory and Path Planning, Autonomous Vehicles Abstract: Segmenting a motion-planning problem into smaller subproblems could be beneficial in terms of computational complexity. This observation is used as a basis for a new sub-maneuver decomposition approach investigated in this paper in the context of optimal evasive maneuvers for autonomous ground vehicles. The recently published alternating augmented Lagrangian method is adopted and leveraged on, which turns out to fit the problem formulation with several attractive properties of the solution procedure. The decomposition is based on moving the coupling constraints between the sub-maneuvers into a separate coordination problem, which is possible to solve analytically. The remaining constraints and the objective function are decomposed into subproblems, one for each segment, which means that parallel computation is possible and beneficial. The method is implemented and evaluated in a safety-critical double lane-change scenario. By using the solution of a low-complexity initialization problem and applying warm-start techniques in the optimization, a solution is possible to obtain after just a few alternating iterations using the developed approach. The resulting computational time is lower than solving one optimization problem for the full maneuver.
Paper VI175-06.10
PDF · Video · Multi-Objective Trajectory Design for Overtaking Maneuvers of Automated Vehicles
Hegedűs, Tamás	Budapest University of Technology and Economics
Nemeth, Balazs	MTA SZTAKI
Gaspar, Peter	SZTAKI
Keywords: Trajectory and Path Planning, Autonomous Vehicles Abstract: The paper proposes a trajectory design method, in which several performances are incorporated. The method is based on a multi-objective optimization process. It is achieved by a simple mathematical representation of feasible trajectories by using a potential field approach. Furthermore, the solution of the complex computations in the optimization is approximated by neural networks. The proposed solution is based on the idea that there are a large number of collision free feasible trajectories. The goal of the method is to find the trajectory, which is suitable for the specified objectives. The result of the paper is an integrated decision for both longitudinal and lateral directions, such as longitudinal acceleration command and the values of the defined path. The effectiveness of the method is presented through CarMaker simulation environment.
Paper VI175-06.11
PDF · Video · Optimization-Based On-Road Path Planning for Articulated Vehicles
Oliveira, Rui	KTH Royal Institute of Technology
Ljungqvist, Oskar	Linköping University
Lima, Pedro Filipe	Scania CV AB
Wahlberg, Bo	KTH Royal Institute of Technology
Keywords: Trajectory and Path Planning, Autonomous Vehicles, Navigation, Guidance and Control Abstract: Maneuvering an articulated vehicle on narrow road stretches is often a challenging task for a human driver. Unless the vehicle is accurately steered, parts of the vehicle's bodies may exceed its assigned drive lane, resulting in an increased risk of collision with surrounding traffic. In this work, an optimization-based path-planning algorithm is proposed targeting on-road driving scenarios for articulated vehicles composed of a tractor and a trailer. To this end, we model the tractor-trailer vehicle in a road-aligned coordinate frame suited for on-road planning. Based on driving heuristics, a set of different optimization objectives is proposed, with the overall goal of designing a path planner that computes paths which minimize the off-track of the vehicle bodies swept area, while remaining on the road and avoiding collision with obstacles. The proposed optimization-based path-planning algorithm, together with the different optimization objectives, is evaluated and analyzed in simulations on a set of complicated and practically relevant on-road planning scenarios using the most challenging tractor-trailer dimensions.
Paper VI175-06.12
PDF · Video · Optimization-Based Motion Planning for Multi-Steered Articulated Vehicles
Ljungqvist, Oskar	Linköping University
Bergman, Kristoffer	Linkoping University
Axehill, Daniel	Linköping University
Keywords: Trajectory and Path Planning, Autonomous Vehicles, Nonlinear and optimal automotive control Abstract: The task of maneuvering a multi-steered articulated vehicle in confined environments is difficult even for experienced drivers. In this work, we present an optimization-based trajectory planner targeting low-speed maneuvers in unstructured environments for multi-steered N-trailer vehicles, which are comprised of a car-like tractor and an arbitrary number of interconnected trailers with fixed or steerable wheels. The proposed trajectory planning framework is divided into two steps, where a lattice-based trajectory planner is used in a first step to compute a resolution optimal solution to a discretized version of the trajectory planning problem. The output from the lattice planner is then used in a second step to initialize an optimal control problem solver, which enables the framework to compute locally optimal trajectories that start at the vehicle's initial state and reaches the goal state exactly. The performance of the proposed optimization-based trajectory planner is evaluated in a set of practically relevant scenarios for a multi-steered 3-trailer vehicle with a car-like tractor where the last trailer is steerable.
Paper VI175-06.13
PDF · Video · Challenges of Trajectory Planning with Integrator Models on Curved Roads
Eilbrecht, Jan	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Trajectory and Path Planning, Autonomous Vehicles, Vehicle dynamic systems Abstract: In the context of trajectory planning for autonomous vehicles, a widely used vehicle model relies on linear integrator dynamics. We consider planning with this model type, with a focus on the requirement to account for curved road topologies. As our analysis reveals, this generally gives rise to non-convex, coupled constraints on the vehicle's states and inputs, which impedes computationally efficient planning. We propose a method to resolve this issue by modification of the non-convex constraints. This modification is based on inner approximations of sub-level sets of nonlinear functions, which are obtained by quantifier elimination. The efficacy of the method is demonstrated in two example scenarios.
Paper VI175-06.14
PDF · Video · Stochastic Model Predictive Velocity Control for Automobiles Considering Uncertainty of Nearby Vehicles
Hashimoto, Kentaro	Tokyo City University
Mizushima, Yoshihide	Tokyo City University
Shibata, Koji	Tokyo City University
Okawa, Isao	DENSO CORPORATION
Nonaka, Kenichiro	Tokyo City University
Keywords: Trajectory and Path Planning, Kalman filtering techniques in automotive control Abstract: In this paper, we present vehicle velocity control based on stochastic model predictive control applied to an actual automobile near other vehicles with uncertain motion. Modern external sensors can measure the pose and velocity of transportation participants, whose motion can be predicted utilizing a model; however, observation and process noise results in uncertainty. Thus, near other vehicles, the velocity of the ego vehicle should be reduced to account for the variance of nearby vehicle motion while suppressing the reduction of speed. In this paper, we utilize stochastic model predictive control to reduce the expectation of relative velocity with respect to nearby vehicles during passing. We evaluate the proposed control using numerical simulation and an experiment with an automobile developed for self-driving and equipped with GNSS, radar, and LiDAR. The results show that the vehicle velocity is automatically reduced based on the expectation of relative velocity calculated from its probabilistic distribution.
Paper VI175-06.15
PDF · Video · Real Time Path Planning of Robot Using Deep Reinforcement Learning
Raajan, Jeevan	Indian Institute of Technology Madras
Padmanaban Venkatesan, Srihari	Indian Insititute of Technology, Madras
Pappu, Satya Jayadev	Indian Institute of Technology, Madras
Bhikkaji, Bharath	Indian Institute of Technology Madras
Pasumarthy, Ramkrishna	IIT Madras
Keywords: Trajectory and Path Planning, Learning and adaptation in autonomous vehicles, Autonomous Mobile Robots Abstract: This paper considers finding a path in real time for a robot from the given initial position to the goal position. The environment is assumed to be mapped (known completely) and the resulting path should avoid all the obstacles, both static and dynamic in the mapped environment. The robot's (agent) dynamics is assumed to be discrete LTI with process noise and is controlled with a finite set of inputs. An MDP formulation and a solution based on Deep Reinforcement Learning framework are presented for the problem. Numerical experiments are performed for the proposed method using Deep Q-Network algorithm and the results are compared with the state of the art sampling based path planning algorithms for both static and dynamic environments. It is shown that even though the proposed algorithm provides a sub-optimal path, the computational time is shown to be significantly faster compared to the traditional methods of path planning.
Paper VI175-06.16
PDF · Video · Trajectory Planning for Autonomous Vehicles Combining Nonlinear Optimal Control and Supervised Learning
Markolf, Lukas	University of Kassel
Eilbrecht, Jan	University of Kassel
Stursberg, Olaf	University of Kassel
Keywords: Trajectory and Path Planning, Learning and adaptation in autonomous vehicles, Autonomous Vehicles Abstract: This paper considers computationally efficient planning of reference trajectories for autonomous on-road vehicles in a cooperative setting. The basic element of the approach is the notion of so-called maneuvers, which allow to cast the nonlinear and non-convex planning task into a highly structured optimal control problem. This can be solved quite efficiently, but not fast enough for online operation when considering nonlinear vehicle models. Therefore, the approach proposed in this paper aims at approximating solutions using a supervised learning approach: First, training data are generated by solving optimal control problems and are then used to train a neural network. As is demonstrated for a cooperative overtaking maneuver, this approach shows good performance, while (contrasting approaches like reinforcement learning) requiring only low training effort.
Paper VI175-06.17
PDF · Video · PolySafe: A Formally Verified Algorithm for Conflict Detection on a Polynomial Airspace
Colbert, Brendon	Arizona State University
Slagel, J Tanner	NASA Langley
Crespo, Luis G	NASA Langley
Balachandran, Swee	National Institute of Aerospace
Muñoz, César	NASA Langley
Keywords: Trajectory and Path Planning, Safety, Autonomous systems Abstract: This paper presents a strategy for verifying that an aircraft following a polynomial path complies with a given set of safety criteria in continuous time. Such criteria ensure that a minimal separation between the aircraft and a set of obstacles, which can be either static or dynamic, is maintained. Dynamic obstacles are also assumed to follow a known polynomial path. Dynamic obstacles may, for example, correspond to a separation volume around another flying aircraft. In the most general case, the separation criteria vary in time depending upon the position and relative velocity between the aircraft and the obstacle. The efficiency and scalability of the proposed algorithm, to be called PolySafe, make it suitable for real-time conflict detection and path re-planning of aircraft flying in a complex and crowded airspace. PolySafe has been formally verified to guarantee the detection of conflicts within a finite time horizon.
Paper VI175-06.18
PDF · Video · Integrated Global and Local Path Planning for Quadrotor Using Particle Swarm Optimization
Hong, Youkyung	Eletronics and Telecommunications Research Institute
Kim, Suseong	Seoul National University
Cha, Jihun	Electronics and Telecommunications Research Institute (ETRI)
Keywords: Trajectory and Path Planning, Trajectory Tracking and Path Following, Autonomous Vehicles Abstract: This study proposes a new path planning method for quadrotors to determine a set of waypoints by considering both geometric constraints to avoid collisions with obstacles and dynamic constraints to reflect the dynamic characteristics of the quadrotor. The proposed path planning method can be formulated as a non-linear optimization problem that minimizes the Euclidean distance between waypoints while satisfying the geometric and dynamic constraints. Particle swarm optimization is utilized to solve the non-linear optimization problem efficiently. By utilizing the Gazebo simulator, the performance of the proposed path planning method is validated for a quadrotor.
Paper VI175-06.19
PDF · Video · Near Time Optimal Trajectory Generation for Over-Actuated Vehicles Using Nonlinear Model Predictive Controller
Wind, Hannes	University of Stuttgart
Gottmann, Frieder	University of Stuttgart
Sawodny, Oliver	Univ of Stuttgart
Keywords: Trajectory and Path Planning, Vehicle dynamic systems, Autonomous Vehicles Abstract: The generation of time dependent paths is crucial for autonomous driving. While relatively simple models are sufficient for normal driving situations, more complex models are required the closer the trajectory is planned towards the handling limits. This paper considers a near time optimal trajectory generation for combined longitudinal and lateral dynamics for an over actuated vehicle. A nonlinear model predictive controller which accounts for actuator constraints is used to generate these trajectories. The predictive model is a reduced dynamic double track model with three degrees of freedom. The resulting trajectories show the ability of following a reference path with the use of all available actuators up to the handling limits.
Paper VI175-06.20
PDF · Video · Adaptive Sampling-Based Motion Planning with a Non-Conservatively Defensive Strategy for Autonomous Driving
Li, Zhaoting	Harbin Institute of Technology
Zhan, Wei	University of California, Berkeley
Sun, Liting	University of California, Berkeley
Chan, Ching-Yao	University of California at Berkeley
Tomizuka, Masayoshi	Univ of California, Berkeley
Keywords: Autonomous Vehicles, Intelligent transportation systems, Autonomous Mobile Robots Abstract: Sampling-based motion planning methods are widely adopted in autonomous driving. Typically, sampling can be decoupled into two layers: a path sampling layer and a speed profile sampling layer. For the path sampling layer, traditional methods tend to sample with a uniform distribution over the whole feasible space, which might cause either computational inefficiency or poor performance if the sampling resolution is not set appropriately. To solve this problem, we propose an adaptive path sampling approach that samples from a time-varying distribution depending on the dynamic environment and potential costs of the ego vehicle. Such sampling strategy is then combined with a non-conservatively defensive strategy in the speed sampling layer to generate a set of safe but not overcautious trajectories. The proposed motion planning framework is tested both in simulation and a real autonomous vehicle in a roundabout scenario. The results demonstrate that it can efficiently generate non-conservative but defensive trajectories to safely drive the vehicles in dynamic environments full of uncertainties.
Paper VI175-06.21
PDF · Video · Energy-Optimal Guidance of Hybrid Ultra-Long Endurance UAV
Dobrokhodov, Vladimir	Naval Postgraduate School
Walton, Claire	Naval Postgraduate School
Kaminer, Isaac	Naval Postgraduate School
Jones, Kevin	Naval Postgraduate School
Keywords: Mission planning and decision making, Navigation, Guidance and Control, Trajectory and Path Planning Abstract: The paper addresses the problem of calculating energy optimal trajectory for a novel class of hybrid UAV equipped with hydrogen fuel cell and solar photovoltaic energy production technologies. The objective of the design is to minimize the energy used for propulsion by optimally utilizing the finite energy stored in the onboard hydrogen fuel cell and routing the aircraft through the time-varying energy fields of solar irradiance and wind. The optimal guidance task is formulated as a two-point boundary value problem with an objective offinding the minimum energy route and the associated controls. The task is solved by applying Pontryagin minimum principle to the resulting 2D kinematics of a UAV along with its aerodynamics, energy management, and propulsion models. The paper derives the necessary conditions and synthesizes the optimal control laws of the bank angle and the airspeed which depend on the time and position derivatives of the wind, and the total angle of incidence toward the sun. The developed method is used to solve the task of path planning of a long endurance flight of a hybrid UAV over multiple 1000th nmi.
Paper VI175-06.22
PDF · Video · Real-Time Optimal Motion Planning for Automated Road Vehicles
Hegedüs, Ferenc	Robert Bosch Hungary
Bécsi, Tamás	Budapest Univ of Technology and Economics
Aradi, Szilárd	Budapest University of Technology and Economics
Szalay, Zsolt	Budapest University of Technology and Economics
Gaspar, Peter	SZTAKI
Keywords: Mission planning and decision making, Trajectory and Path Planning, Trajectory Tracking and Path Following Abstract: This paper presents a real-time optimal motion planner algorithm for road vehicles. The method is based on a cubic spline trajectory planner which is able to plan a set of vehicle motions driving from a given initial state to a required final state. Maximal dynamical feasibility and passenger comfort are ensured by minimizing the lateral acceleration and tracking errors as the vehicle moves along the trajectory. Tracking of the planned motion is realized during planning and execution as well by separate longitudinal and lateral controllers. Efficient implementation and small number of optimization variables enables real-time usage. The trajectory planner is first tested in a quasi real-time simulation environment and then under real working conditions at the dynamic platform of proving ground ZalaZone with a completely drive-by-wire Smart Fortwo. Measurement results are presented and analyzed in detail, and possible future research directions are mentioned.
Paper VI175-06.23
PDF · Video · Trajectory Reconfiguration for Time Delay Reduction in the Case of Unexpected Obstacles: Application to 4-Mecanum Wheeled Mobile Robots (4-MWMR) for Industrial Purposes
Mellah, Samia	Aix Marseille Université AMU-Laboratoire d'Informatique Et Systè
Graton, Guillaume	Ecole Centrale De Marseille
El Adel, El Mostafa	Université Aix-Marseille III
Ouladsine, Mustapha	Université D'aix Marseille III
Planchais, Alain	STMicroelectronics, Rousset
Keywords: Autonomous Mobile Robots, Autonomous Vehicles, Intelligent transportation systems Abstract: Nowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper proposes a new trajectory reconfiguration approach dealing with obstacle generated time delay, applied on four wheeled omnidirectional mobile robots. A strategy is proposed to compensate or minimize the time delay caused by unexpected obstacles, allowing the robot to respect as well as possible its mission planed duration. This strategy is based on updating the velocity reference profile in real time with respect to the environment changing. The aim is to provide to the industrial a support for the robot missions planing and managing, in order to optimize the production.
Paper VI175-06.24
PDF · Video · Attacker Dispersal Surface in the Turret Defense Differential Game
Von Moll, Alexander	Air Force Research Laboratory
Fuchs, Zachariah	Wright State University
Keywords: Autonomous systems, Trajectory and Path Planning Abstract: The characteristics for the solution to the Turret Defense Differential Game are explored over the parameter space. We collapse the five natural parameters of capture radius, Attacker speed, Turret turn rate, time penalty constant, and look-angle penalty constant into two composite parameters in order to facilitate the analysis. There exist three singular surfaces in the game, two of which have an analytic form, and one of which can only be obtained numerically. We focus on the latter: the Attacker Dispersal Surface, wherein the Attacker can choose between an indirect or direct route to capture. For certain parameter settings, the Attacker Dispersal Surface is present, while for others, the surface is absent. These regions in the parameter space are identified, and the numerical procedures to do so are detailed. Backwards shooting of the optimal state and adjoint dynamics features prominently in the procedures. Two pieces of numerical evidence are utilized to indicate the presence or absence of the Attacker Dispersal Surface.
Paper VI175-06.25
PDF · Video · An Independent Trajectory Advisory System in a Mixed-Traffic Condition: A Reinforcement Learning-Based Approach
Rostami-Sharhrbabaki, Majid	Technical University of Munich
Niels, Tanja	Bundeswehr University Munich
Hamzehi, Sascha	Technical University Munich
Bogenberger, Klaus	Technical University of Munich
Keywords: Learning and adaptation in autonomous vehicles, Intelligent driver aids, Modeling and simulation of transportation systems Abstract: Achieving smooth urban traffic flow requires reduction of sharp acceleration/deceleration and accordingly unnecessary stop-and-go driving behavior on urban arterials. Traffic signals at intersections, and induced queues, introduce stops along with increasing travel times, stress and emission. In this paper, an independent reinforcement learning-based approach is developed to propose smooth traffic flow for connected vehicles enabling them to skip a full stop at queues and red lights at urban intersections. Two reward functions, i.e., a fuzzy reward engine and an emission-based reward system, are proposed for the developed Q-learning scheme. Another contribution of this work is that the necessary information for the learning algorithm is estimated based on the vehicle trajectories, and hence, the system is independent. The proposed approach is tested in a mixed-traffic condition, i.e., with connected and ordinary vehicles, via a realistic traffic simulation with promising results in terms of flow efficiency and emission reduction.
Paper VI175-06.26
PDF · Video · Shortest Bounded-Curvature Paths Via Circumferential Envelope of a Circle
Jha, Bhargav	Technion - Israel Institute of Technology
Chen, Zheng	Zhejiang University
Shima, Tal	Technion - Israel Institute of Technology
Keywords: Guidance, navigation and control of vehicles, Nonlinear and optimal automotive control, Autonomous systems Abstract: The paper characterizes the shortest bounded-curvature paths for a Dubins vehicle between two configurations with specified location and heading angle via the boundary of an intermediate circle. Only two distinct cases can arise in such engagements, first, when the shortest path is tangent to the circle at only one point, and second, when a segment of the shortest path overlaps a part of the circular boundary. Control command for both the cases are proposed, and some geometric properties for the first case are established by using necessary conditions for state inequality constraints and Pontryagin's maximum principle. Numerical examples are presented to illustrate the geometric properties of the shortest bounded-curvature paths. These geometric properties give insight about concatenation of different segments of the shortest path and allow us to state that the candidate shortest paths belong to a finite set

VI175-07
Trajectory Tracking and Path Following for Autonomous Vehicles	Regular Session
Chair: Vamvoudakis, Kyriakos G.	Georgia Tech
Co-Chair: Axehill, Daniel	Linköping University
Paper VI175-07.1
PDF · Video · Feasibility Analysis of Positioning and Navigation Strategies for Railway and Tramway Applications
Selvi, Daniela	University of Florence
Meli, Enrico	University of Florence
Allotta, Benedetto	Univ of Florence
Rindi, Andrea	University of Florence
Capuozzo, Alessandro	THALES Italia S.p.A
Rucher, Luigi	Thales
Keywords: Localization, Modeling and simulation of transportation systems, Navigation Abstract: The problem of vehicle autonomous driving currently represents a topic of great interest from both theoretical and practical points of view. Among the challenging tasks to be addressed within any autonomous driving framework, one of the most important ones is localization from data collected in real time. Within such framework, this paper is specifically focused on the localization problem for rail vehicles, such as railway and tramway vehicles. Our specific interest is on investigating solutions to the localization problem which are (as much as possible) independent on ground sensor infrastructure and are therefore suitable to be employed on any rail vehicle, irrespective of the ground equipment of the specific tracks. To this end, we refer to a multi-sensor framework and, specifically, to a sensor fusion scheme which collects data from different sensors installed on the vehicle (namely, an Inertial Measurement Unit and a Global Positioning System) and carries out a Kalman-based filtering recursion which relies on a simplified vehicle model. With the aim of identifying a solution for the localization problem providing desirable performance, we carry out a comparative simulation analysis concerning different Kalman-based data fusion strategies (in particular, the Extended Kalman Filter and the Unscented Kalman Filter are considered).
Paper VI175-07.2
PDF · Video · Off-Track Reduction Control for Roundabout Negotiation with Multi-Steering N-Trailers
Michalek, Maciej	Poznan Univ of Technology
Keywords: Motion control, Trajectory Tracking and Path Following, Control architectures in automotive control Abstract: Negotiating a roundabout with long articulated vehicles without any specialized control strategy may be dangerous or even impossible due to an excessively large off-track caused by the towed trailers. The paper provides a generic kinematic steering strategy for this type of maneuver executed with articulated vehicles towing an arbitrary number of trailers equipped with steerable wheels, and attached through an arbitrary hitching type (on- or off-axle one). The control strategy requires a feedback from the internal (easily measurable) configuration variables of a vehicle, guarantees zero off-tracking in steady motion conditions, and improves a transient response of a vehicle chain by delaying the reference steering signals with the dynamically (on-line) scheduled time-delays. A resultant control performance is illustrated by simulation results.
Paper VI175-07.3
PDF · Video · Model Predictive Trajectory Tracking for a Ground Vehicle in a Heterogeneous Rendezvous with a Fixed-Wing Aircraft
Hebisch, Christoph	Institute of Automatic Control, RWTH Aachen University
Abel, Dirk	RWTH-Aachen University
Keywords: Trajectory Tracking and Path Following, Automatic control, optimization, real-time operations in transportation, Multi-vehicle systems Abstract: The maneuver of landing a fixed-wing unmanned aerial vehicle (UAV) autonomously on a moving ground platform requires precise spatial synchronization of both agents. Depending on the desired control strategy for the maneuver, the unmanned ground vehicle (UGV) must be capable to track the UAV's trajectory robustly with respect to the ground plane even in the presence of disturbances such as wind gusts. In this paper, a linear model predictive trajectory tracking controller for a UGV based on a kinematic bicycle model is presented, assuming that the UAV aims at following a straight flight path with a given velocity. The vehicle model is discretized and linearized in each sampling step, resulting in a quadratic optimization problem which yields the optimal steering angle and motor current demand of the UGV. In the optimization problem, actuator constraints as well as hardware-related dead-times are taken into account. By constraining the yaw rate of the UGV, sideslip of the UGV is prevented, preserving the consistency of the kinematic model. Main requirements for the controller are the ability to allow sufficiently precise trajectory tracking with a longitudinal and lateral deviation of less than 0.5m, i.e., within the dimensions of the landing platform in the given hardware setup, and real-time capability. Hardware-in-the-loop simulations and experimental results with a model-scale ground vehicle are presented that indicate the validity of the proposed control scheme.
Paper VI175-07.4
PDF · Video · Vehicular Lateral Tracking Control with Winding Road Disturbance Compensation
Choi, Woo Young	Hanyang University
Lee, Seung-Hi	Hanyang Univeristy
Chung, Chung Choo	Hanyang Univ
Keywords: Trajectory Tracking and Path Following, Autonomous Vehicles, Motion control Abstract: In this paper, an innovative vehicular lateral tracking control scheme is proposed to compensate for a winding road disturbance (WRD) on a curved road. Using a dynamic lateral motion model with look-ahead distance, we propose a WRD compensator (WRDC) to sufficiently achieve satisfactory vehicular lateral tracking control performance on the curved road in the presence of WRD. The proposed tracking control scheme is designed by the WRDC gain from the dominant state for the lateral offset in the lane keeping control. By developing the WRDC, state-space reference is redesigned to compensate for tracking error. We showed that the proposed WRDC ensures that the projected tracking error converges to zero. To verify the usefulness of the tracking control, the WRDC applied to a linear quadratic regulator (LQR) controller was compared to the standard LQR, LQR with an integrator, and LQR with an anti-windup. We observed that the proposed WRDC is not only robust against road curvature variation but also outperforming the tracking performance of LQR with anti-windup.
Paper VI175-07.5
PDF · Video · Path Tracking Control for Urban Autonomous Driving
Klauer, Christian	TomTom, Location Technology, Germany
Schwabe, Manuel	TomTom
Mobalegh, Hamid	TomTom
Keywords: Trajectory Tracking and Path Following, Autonomous Vehicles, Motion control Abstract: A path tracking controller for autonomous vehicles in urban environments is presented. Based on system inversion, the steering angle causing the vehicle to follow the path in absence of disturbances is calculated. Then, the lateral distance and the orientation error w.r.t. the path are compensated by a state feedback controller. Further, a decoupling of the velocity is considered in the system-inversion and the feedback controller. Therefore, ideally, the velocity does not influence path tracking and, hence, the requirements on velocity control are relaxed. To reduce the effort for parameter identification, the controller is intentionally based on a kinematic vehicle model requiring less parameters compared to an elaborated dynamic model. It is assumed that the effects of unconsidered system components, e.g., tire slip, are then compensated by the state-feedback controller. The approach is validated on a closed proving-ground in a simulated urban scenario. Herein, for driving velocities up to 14 m/s and curve radii of down to 10 m, an RMS tracking error for the lateral distance to the path of 7.2 cm was achieved. The control system will be used in TomTom's autonomous car 'Trillian' that serves as a validation and research platform to evaluate high definition maps of road networks.
Paper VI175-07.6
PDF · Video · Longitudinal and Lateral Control for Four Wheel Steering Vehicles
Li, Laëtitia	Mines Paristech
D'Andrea-Novel, Brigitte	Ecole Des Mines De Paris
Quadrat, Arnaud	SAFRAN Electronic & Defense
Keywords: Trajectory Tracking and Path Following, Autonomous Vehicles, Vehicle dynamic systems Abstract: Vehicles evolving in harsh terrains are subject to physical phenomena with a much more important impact than in the case of road vehicle. The main problem we have to face is tire slippery which has to be taken into account when designing the control law to ensure an accurate tracking. In this paper we present a controller for cars equipped with 4 steering wheels. An accurate automatic trajectory tracking via vehicle wheel torque, front and rear steering is developed. This controller takes into account nonlinear tire effects to increase vehicle stability in presence of sliding. Promising results have been obtained with numerical simulations.
Paper VI175-07.7
PDF · Video · Linear Time-Varying Model Predictive Control for Automated Vehicles: Feasibility and Stability under Emergency Lane Change
Li, Yuchao	KTH Royal Institute of Technology
Chen, Xiao	KTH Royal Institute of Technology
Mårtensson, Jonas	KTH Royal Institute of Technology
Keywords: Trajectory Tracking and Path Following, Motion control, Autonomous Vehicles Abstract: In this work, we present a novel approach based on linear matrix inequalities to design a linear-time varying model predictive controller for a nonlinear system with guaranteed stability. The proposed method utilizes a multi-model description to model the nonlinear system where the dynamics is represented by a group of linear-time invariant plants, which makes the resulting optimization problem easy to solve in real-time. In addition, we apply the control invariant set designed as the final stage constraint to bound the additive disturbance introduced to the plant by other subsystems interfacing with the controller. We show that the persistent feasibility is ensured with the presence of such constraint on the disturbance of the specified kind. The proposed method is then put into the context of emergency lane change for steering control of automated vehicles and its performance is verified via numerical evaluation.
Paper VI175-07.8
PDF · Video · A Predictive Path-Following Controller for Multi-Steered Articulated Vehicles
Ljungqvist, Oskar	Linköping University
Axehill, Daniel	Linköping University
Keywords: Trajectory Tracking and Path Following, Navigation, Guidance and Control, Autonomous Mobile Robots Abstract: Stabilizing multi-steered articulated vehicles in backward motion is a complex task for any human driver. Unless the vehicle is accurately steered, its structurally unstable joint-angle kinematics during reverse maneuvers can cause the vehicle segments to fold and enter a jack-knife state. In this work, a model predictive path-following controller is proposed enabling automatic low-speed steering control of multi-steered articulated vehicles, comprising a car-like tractor and an arbitrary number of trailers with passive or active steering. The proposed path-following controller is tailored to follow nominal paths that contains full state and control-input information, and is designed to satisfy various physical constraints on the vehicle states as well as saturations and rate limitations on the tractor's curvature and the trailer steering angles. The performance of the proposed model predictive path-following controller is evaluated in a set of simulations for a multi-steered 2-trailer with a car-like tractor where the last trailer has steerable wheels.
Paper VI175-07.9
PDF · Video · Intersection-Traffic Control of Autonomous Vehicles Using Newton-Raphson Flows and Barrier Functions
Shivam, Shashwat	Georgia Tech
Wardi, Yorai	Georgia Institute of Technology
Egerstedt, Magnus	Georgia Institute of Technology
Kanellopoulos, Aris	Georgia Inst. of Tech
Vamvoudakis, Kyriakos G.	Georgia Tech
Keywords: Trajectory Tracking and Path Following, Trajectory and Path Planning, Autonomous Mobile Robots Abstract: This paper concerns an application of a recently-developed nonlinear tracking technique to trajectory control of autonomous vehicles at traffic intersections. The technique uses a flow version of the Newton-Raphson method for controlling a predicted system-output to a future reference target. Its implementations are based on numerical solutions of ordinary differential equations, and it does not specify any particular method for computing its future reference trajectories. Consequently it can use relatively simple algorithms on crude models for computing the target trajectories, and more-accurate models and algorithms for trajectory control in the tight loop. We demonstrate this point on an extant predictive traffic planning-and-control method with our tracking technique. Furthermore, we guarantee safety specifications by applying to the tracking technique the framework of control barrier functions.
Paper VI175-07.10
PDF · Video · Road Constrained Labeled Multi Bernoulli Filter Based on PDF Truncation for Multi-Target Tracking
Park, Woo Jung	Seoul National University
Park, Chan Gook	Seoul National Univ
Keywords: Trajectory Tracking and Path Following, Trajectory and Path Planning, Simulation Abstract: In this paper, road constrained filtering is applied to labeled multi Bernoulli (LMB) filter using PDF truncation in multi-road environment. In target tracking systems with road map information, road constraints can effectively improve the estimation performance. To apply multiple road constraints information to the tracking filter, all constraints should not be applied simultaneously and only one should be selected for each estimated trajectory. Then, probability density function (PDF) truncation is conducted which is a constrained filtering technique for inequality constraints. To verify the constrained filtering technique to LMB filter, simulations for multi-target tracking in cluttered environments are carried out. The simulation result shows that the proposed method bounded estimated trajectories on the road effectively and reduced OSPA error.
Paper VI175-07.11
PDF · Video · Robust Hierarchical Model Predictive Control for Trajectory Tracking with Obstacle Avoidance
Xu, Yanchuan	Zhejiang University
Zheng, Huarong	Zhejiang University
Wu, Weimin	Zhejiang Univ
Wu, Jun	Zhejiang Univ
Keywords: Trajectory Tracking and Path Following, Vehicle dynamic systems, Nonlinear and optimal automotive control Abstract: A robust hierarchical path planning and trajectory tracking framework is proposed to maintain a collision-free path for autonomous vehicles. For the path-planning, a constrained finite-time optimal problem is solved to generate a feasible and collision-free trajectory considering the vehicle kinematics. For the trajectory-tracking, a motion controller is proposed by solving a constrained model predictive control problem, obtaining the front wheel steering angles. Furthermore, to enhance the robustness of the motion controller against the uneven network-induced time delay and unmodelled lateral vehicle dynamics, an additional error feedback mechanism is introduced in the motion controller. Simulations are conducted when both moving obstacles and static obstacles exist. Simulation results show that the proposed hierarchical control framework can effectively guarantee safe and feasible driving maneuvers.
Paper VI175-07.12
PDF · Video · Multi-Objective Following Control for Heavy-Duty Vehicles Using Differential Dynamic Programming
Alvarez Tiburcio, Miguel	University of Maryland
Fathy, Hosam K.	Penn State University
Keywords: Automatic control, optimization, real-time operations in transportation, Trajectory and Path Planning, Trajectory Tracking and Path Following Abstract: The speed with which an ego-vehicle follows a lead vehicle through traffic cansignificantly affect the former’s fuel consumption, safety, average speed, and ride comfort.This paper merges these objectives and constraints into a unified trajectory optimizationproblem. One of the paper’s goals is to provide a unified formulation of problems traditionallytackled independently, e.g., platooning, fuel-minimizing vehicle speed trajectory optimization,etc. Another key goal is to demonstrate the degree to which Differential Dynamic Programming(DDP) provides a conceptually attractive and computationally inexpensive decomposition ofthe resulting multi-objective problem. In this decomposition, perturbations from an optimalsteady-state vehicle trajectory are controlled using a linear quadratic regulation (LQR) lawobtained analytically through DDP. We examine the performance of this controller simulatinga representative urban drive cycle with a lead vehicle. We also perform a sensitivity study onthe parameters in the objective and explore their effect in both fuel economy and deviationsfrom nominal headway distance. Finally, we explore the effect of different levels of collaborationbetween vehicles by assuming the lead vehicle shares its predicted future average acceleration.
Paper VI175-07.13
PDF · Video · Contract-Based Hierarchical Model Predictive Control and Planning for Autonomous Vehicle
Ibrahim, Mohamed	Otto-von-Guericke-Universität Magdeburg
Koegel, Markus J.	Otto-von-Guericke-Universität Magdeburg
Kallies, Christian	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Motion Control Systems, Guidance navigation and control, Identification and control methods Abstract: Planning and control of autonomous vehicles are becoming increasingly important for many applications. However, autonomous vehicles are often subject to disturbances and uncertainties, which become critical, especially in cluttered and dynamic environments. To provide guaranteed constraints satisfaction, e.g. for collision avoidance, we propose a hierarchical model predictive control and planning approach. The moving horizon planning layer and the low-level model predictive controller agree on a contract (precision conditions). The high-level moving horizon planner is based on a mixed-integer programming formulation using a simplified model on a slow time scale, and constraint tightening. The autonomous vehicle itself is controlled by a lower-level tube-based model predictive controller. The decomposition of the control problem reduces the computational cost, enables real-time implementation while it allows to provide guarantees. To ensure compatibility between the levels and guarantee safety, we do explicitly consider the problem of recursive feasibility of the hierarchical controller, ensuring constraint satisfaction and obstacle avoidance, despite the action of (unknown) disturbances. Simulation results illustrate the efficiency and applicability of the proposed hierarchical strategy.

VI181
Bio and Ecological Systems - Control in Agriculture
VI181-01 Sensing, Control, Automation and Robotics for Agriculture   Open Invited Session, 7 papers
VI181-02 Modeling and Control for Agriculture Systems   Regular Session, 8 papers

VI181-01
Sensing, Control, Automation and Robotics for Agriculture	Open Invited Session
Chair: Karkee, Manoj	Washington State University
Co-Chair: Visala, Arto	Aalto University, ELEC School
Organizer: Karkee, Manoj	Washington State University
Organizer: Visala, Arto	Aalto University, ELEC School
Organizer: Katupitiya, Jay	UNSW
Organizer: Noguchi, Noboru	Hokkaido University
Organizer: Shimizu, Hiroshi (in memory)	Kyoto University
Paper VI181-01.1
PDF · Video · Sustainability Analysis of Interconnected Food Production Systems Via Theory of Barriers (I)
Aschenbruck, Tim	Technische Universität Chemnitz
Esterhuizen, Willem	Technische Universität Chemnitz
Padmanabha, Murali	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Natural resources management, Food engineering, Modeling and control of agriculture Abstract: Controlled environment agriculture (CEA) is used for efficient food production. Efficiency can be increased further by interconnecting different CEA systems (e.g. plants and insect larvae or fish and larvae), using products and by-products of one system in the other. These interconnected systems define an overall system that can be described by models of interacting species. It is necessary to identify system parameters (e.g. initial species concentration, harvest rate, feed quality, etc.) such that the resources are not exhausted. For such systems with interacting species, modelled by the Lotka-Volterra equations, a set-based approach based on the recent results of the theory of barriers to exactly determine the so-called admissible set (also known as viability kernel) and the maximal robust positively invariant set is presented. Using an example of a larvae-fish based production system, steps to obtain special trajectories which are the boundaries of the admissible set is shown. Furthermore, conditions of the system parameters are stated, such that the existence of these trajectories can be guaranteed.
Paper VI181-01.2
PDF · Video · Model Predictive Control of a Food Production Unit: A Case Study for Lettuce Production (I)
Padmanabha, Murali	Technische Universität Chemnitz
Beckenbach, Lukas	Technische Universität Chemnitz
Streif, Stefan	Technische Universität Chemnitz
Keywords: Modeling and control of agriculture, Greenhouse control, Plant factories Abstract: Plant factories with artificial light are widely researched for food production in a controlled environment. For such control tasks, models of the energy and resource exchange in the production unit as well as those of the plant's growth process may be used. To achieve minimal operation cost, optimal control strategies can be applied to the system, taking into account the availability of resources by control reference specification. A particular advantage of model predictive control (MPC) is the incorporation of constraints that comply with actuator limitations and general plant growth conditions. In this work, a model of a production unit is derived including a description of the relation between the actuators' electrical signals and the input values to the model. Furthermore, a preliminary model based state tracking control is evaluated for production unit containing Lettuce. It could be observed that the controller is capable to track the reference while satisfying the constraint under changing weather conditions and resource availability.
Paper VI181-01.3
PDF · Video · Drone Based Mapping and Identification of Young Spruce Stand for Semiautonomous Cleaning (I)
Ouattara, Issouf	Aalto University
Hyyti, Heikki Sakari	Finnish Geospatial Research Institute (FGI), National Land Surve
Visala, Arto	Aalto University, ELEC School
Keywords: Pattern recognition and Artificial Intelligence in agriculture, Agricultural robotics, Machine learning for environmental applications Abstract: We propose a novel method to locate spruces in a young stand with a low cost unmanned aerial vehicle. The method has three stages: 1) the forest area is mapped and a digital surface model and terrain models are generated, 2) the locations of trees are found from a canopy height model using local maximum and watershed algorithms, and 3) these locations are used in a convolution neural network architecture to detect young spruces. Our result for detecting young spruce trees among other vegetation using only color images from a single RGB camera were promising. The proposed method is able to achieve a detection accuracy of more than 91%. As low cost unmanned aerial vehicles with color cameras are versatile today, the proposed work is enabling low cost forest inventory for automating forest management.
Paper VI181-01.4
PDF · Video · A Low-Cost Soil Moisture Monitoring Method by Using Walabot and Machine Learning Algorithms (I)
Niu, Haoyu	University of California, Merced
Wang, Yanan	Department of Automation, Beijing Institute of Technology
Zhao, Tiebiao	UC Merced
Chen, YangQuan	University of California, Merced
Keywords: Pattern recognition and Artificial Intelligence in agriculture, Software sensors in agriculture, Wireless sensor networks in agriculture Abstract: Soil moisture plays an important role in agricultural processes, which has great effect on crops evapotranspiration, exchange of water and energy fluxes. Recently, soil moisture can be measured by many remote sensing or proximate sensing techniques, such as thermal, optical, and microwave measurements. However, there are always limitations for the applications of theses methods, such as low spatial resolution, limited surface penetration and vegetation. Therefore, in this paper, it proposed a new low-cost soil moisture monitoring method by using a Walabot sensor and machine learning algorithms. Walabot is a pocket-sized device cutting-edge technology for Radio Frequency tridimensional sensing. Unlike the remote sensing tools such as unmanned aerial vehicles (UAVs) limited by flight time and payload capability, the Walabot can work flexibly in the field and provide data information more promptly and accurately than UAVs or satellites. By putting different moisture levels of soil on the Walabot, the Walabot can recognize small changes in different levels of soil moisture, so that waveforms generated by different signals can be used to estimate soil moisture. Then, machine learning algorithms, such as principal component analysis (PCA), linear discriminant analysis (LDA), have been applied for data processing. In our experiments, it shows a state-of-art performance in estimating soil moisture.
Paper VI181-01.5
PDF · Video · Modelling and Simulation of a Fuzzy System for Site-Specific Nitrogen Fertilization (I)
Heiß, Andreas	University of Hohenheim
Paraforos, Dimitrios S.	University of Hohenheim
Sharipov, Galibjon M.	University of Hohenheim
Griepentrog, Hans W.	University of Hohenheim
Keywords: Precision farming, Software sensors in agriculture, Identification and validation Abstract: Increasing environmental concerns are a driving force in the search for ways to improve the efficiency of mineral nitrogen (N) fertilization. Spectral sensors to determine the crop’s supply status are among the most mature precision agriculture technologies to adapt the N dose site-specifically to the crop’s need. By using artificial intelligence techniques like expert systems based on fuzzy set theory, the algorithms of such sensor systems could be adapted by the farmer to the highly varying conditions among the specific fertilization dates. This paper is dealing with the development of a fuzzy logic based model of the commercial Yara N-Sensor’s dosing algorithms. Simulations for several sets of input-output data acquired in field experiments showed high accordance with the behaviour of the N-Sensor system with good adaptability to different calibrations.
Paper VI181-01.6
PDF · Video · Leaf Area Index Soft Sensor for Tomato Crops in Greenhouses (I)
García-Mañas, Francisco	University of Almería
Rodríguez-Díaz, Francisco	Univ of Almería
Berenguel, Manuel	University of Almeria
Keywords: Software sensors in agriculture Abstract: In this work, a soft sensor for tomato crop has been developed using dynamic models to reproduce physical and biological phenomena inside a greenhouse. External weather forecasts were utilised to predict crop growth for a short-term horizon. In addition, data assimilation was performed from observable information of the process, such as measurements captured by sensors, in order to correct uncertainty errors of simulated variables by dynamic models. From the automatic control perspective, the proposed mechanism might allow to implement optimal resource management strategies. Furthermore, crop prediction systems could offer relevant information to farmers as a support tool for decision making
Paper VI181-01.7
PDF · Video · Evaluation of Centrifugal Spreader Response to Variable Rate Application by Using Task File Data (I)
Sharipov, Galibjon M.	University of Hohenheim
Heiß, Andreas	University of Hohenheim
Griepentrog, Hans W.	University of Hohenheim
Paraforos, Dimitrios S.	University of Hohenheim
Keywords: Precision farming, Modeling and control of agriculture, Software sensors in agriculture Abstract: In the site-specific fertilization based on a variable rate prescription, the application accuracy and distribution of the spreader are the key points when it comes to applying fertilizer with centrifugal disk spreaders. The application error occurs mainly due to inaccurate position, the delayed response of the spreader to rate changes and application width errors across the management zones. This study aims to evaluate the application error occurring due to rate changes at management zone boundaries across the application width of the spreader. Towards this aim, a variable rate fertilizer application was performed using a centrifugal spreader. The performed task data that included a spatial field application file in ISO XML format was recorded from a dedicated in-cab terminal to generate the "as-applied" point map. A two-dimensional (2D) matrix method based on a 2D triangular distribution was used to generate the as-applied rate to examine if it results in more accuracy to assess the applied amount of fertilizer at intersections of the management zones. The resulted "as-applied" map, as well as the raw data one, were compared with the prescription map to extract absolute errors. Statistics of absolute error resulted from the comparison was assessed to examine the application accuracy. The mean value and standard deviation of the error for the distributed rate were 13.4 and 11 kg ha-1. These figures were equal to 17.5 and 12.7 kg ha-1 for the error of the raw data "as-applied" map. Evaluation of covered area by the error in percentage also indicated a higher value for the raw data "as-applied" map than that for the distributed one.

VI181-02
Modeling and Control for Agriculture Systems	Regular Session
Chair: Gutman, Per-Olof	Technion - Israel Institute of Technology
Co-Chair: Karkee, Manoj	Washington State University
Paper VI181-02.1
PDF · Video · Automatic Blossom Detection in Apple Trees Using Deep Learning
Bhattarai, Uddhav	Washington State University
Bhusal, Santosh	Washington State University
Majeed, Yaqoob	Washington State University
Karkee, Manoj	Washington State University
Keywords: Agricultural robotics Abstract: Overcropping in fruit trees results in decreased fruit size, poor fruit quality, biennial bearing, and reduction in productive life of orchards. Although flowers and fruits are removed/thinned naturally, they require additional thinning for commercial grade fruit production. Integration of machine vision system in mechanical/chemical thinning facilitates automated selective blossom thinning. The primary requirement for automating blossom thinning is to estimate the blossom density in apple trees under varying background and lighting conditions. In this work, we implement Mask-RCNN algorithm to perform instance segmentation of apple blossoms. Different image augmentation techniques were implemented and their impact on blossom detection were assessed. Experiments were conducted to achieve optimal values of hyperparameters of the deep learning network during the training. Implementation of image augmentation was crucial to reduce validation loss and improve detection accuracy of segmentation algorithm. The proposed system achieved average precision (AP) of 0.86 in detecting blossoms in test dataset previously unseen by the network.
Paper VI181-02.2
PDF · Video · Improved Path Planning of the Blade for an Automatic Spinach Harvester
Takayama, Naoto	Shinshu University
Yamaguchi, Tasuya	Shinshu University
Fujisawa, Akihiro	Shinshu University
Kamijo, Tomokazu	Shinshu University
Nakajima, Koki	Shinshu University
Seki, Yoshifumi	Shinshu University
Hayashi, Haruki	Shinshu University
Chida, Yuichi	Shinshu Univ
Keywords: Agricultural robotics, Modeling and control of agriculture Abstract: The tendency of spinach crop to get damaged during harvesting, even when harvested by human hands, is the most significant challenge in automating the spinach harvesting process. To overcome this, an automatic spinach harvester was developed previously using a novel harvesting concept by which the crop is harvested without grasping or clamping. In this method, path planning for a root cutting blade traveling in soil is very important for successful harvesting. An effective path generation method which can handle uneven ground was proposed, but the blade motion in this method causes large variations in the depth of the path. In this study, we propose a modified path which reduces the variation in blade motion in the vertical direction by modifying the parameters of the original path generation method. Field experiments were conducted to demonstrate its effectiveness, and the results show that the modified path achieves superior harvesting performance compared to the conventional path.
Paper VI181-02.3
PDF · Video · Fish Volume Monitoring Using Stereo Vision for Fish Farms
Vale, Rodrigo Telles da Silva	University of São Paulo
Ueda, Edson Kenji	Escola Politecnica Da Universidade De Sao Paulo
Takimoto, Rogerio Yugo	Escola Politecnica Da Universidade De Sao Paulo
Martins, Thiago de Castro	University of Sao Paulo
Keywords: Animal husbandry, Monitoring Abstract: Aquaculture is an activity that is growing 10% a year in Brazil and still occupies less than 1% of the area reserved for fish farming, which shows the great productive potential of Brazil. With this growth, many challenges are emerging and many advances are being made. One technology they are starting to use in Brazilian fish farms is stereo cameras that can evaluate the average weight of Nile tilapia in a tank. This estimation of fish weight is based on its 3D length, but one of the most correlated information with the fish weight is its width. Thus, the objective of this work is to improve this estimation using stereo cameras by processing the cloud point of the surface of the fish. This paper shows some preliminary results that encourage further research since was obtained results similar to the results of the methodology currently used.
Paper VI181-02.4
PDF · Video · Computational Fluid Dynamics Simulation of Thermodynamic Behaviour of Tubular Digester
N. Vaz, Patricia	Federal University of Minas Gerais
Oliveira Filho, Delly	Federal University of Viçosa
A. Martins, Aredes	Federal University of Viçosa
C. Carlo, Joyce	Federal University of Viçosa
P. Rosa, Andre	Federal University of Viçosa
M. A. M. Mendes, Eduardo	Federal University of Minas Gerais
Keywords: CFD in agriculture, Modeling and control of agriculture, Bio-energetics Abstract: The anaerobic digesters have been widely used worldwide and followed by the environmental treatment, biogas (energy source) and biofertilizers can be produced at the same process. The plug flow digester is the most common digester system in Brazil, but it still faces great difficulties of implementation because of the low efficiency. In this context, this work proposes ways of improving the energy efficiency of such a digester. To this end, simulations were performed for this type of digester in order to analyze the thermodynamic behavior. It was possible to verify that the velocity gradient was acceptable for the studied reactor characteristics, that is, 0.054, and the average temperature reached with the heating system was 33 ºC, which is considered an optimal temperature for biogas production. The simulation proved to be an important tool in scenarios using the digester model and can be of help when designing new units and in different cases of agitation. However the model used here does not evaluate the thermal changes of the digester plastic blanket due to the simplification of the simulation.
Paper VI181-02.5
PDF · Video · A Low-Cost Prototype to Automate Agricultural Sprayers
Terra, Fabio Pedrotti	Federal Institute of Education, Science and Technology
Rosa, Gabrielle R. A. da	Federal University of Rio Grande
Prado, Jardel J. P.	Federal University of Rio Grande
Drews Jr, Paulo	Federal University of Rio Grande
Keywords: Modeling and control of agriculture, Precision farming, Agricultural robotics Abstract: The world's population growth in the last decades demanded a great increase in agricultural production, especially in food. Therefore, in order to reduce possible losses and guarantee productivity, farmers depend more and more on the application of agrochemicals in their crops. This massive use of pesticides represents not only a high cost to the farmers but also a risk to their health, to the environment and even to the safety of the food consumed by the population. In this context, new technologies have been developed to make agricultural spraying more effective, reducing the amount of pesticide applied and dosing its use according to the need of the crop. The recognition of its spatial and temporal variability is treated by Precision Agriculture. In the case of pest management it can be done using variable-rate sprayers or using on/off application with individual nozzle control. Thus, this paper proposes a low-cost prototype in a modular solution to automate existent agricultural sprayers. The solution allows individual nozzle opening, with on/off control, using solenoid valves, pressure and flow sensors, Arduino boards, and smartphone. Additionally, the prototype has a data logger function to store nozzle status and sensor values, allowing future analysis and application reports.
Paper VI181-02.6
PDF · Video · Optimal Control of Centrifugal Spreader
Rußwurm, Franz	TU Chemnitz
Osinenko, Pavel	Skoltech Institute of Science and Technology
Streif, Stefan	Technische Universität Chemnitz
Keywords: Modeling and control of agriculture, Precision farming, Man-machine systems in agriculture Abstract: Achieving an evenly distributed fertilization spread pattern is a complex technical task. A corresponding control algorithm must account for the tractor movement, the settings of the spreader, the prescribed dosage as well as machine constraints. It dictates, in particular, the fertilization process needs be estimated ahead to achieve an optimized spread pattern. The presented work is concerned with the development of a predictive control scheme for optimized fertilizer application using modeling of the tractor moving on the field and the spread pattern in form of a crescent behind the tractor. In particular, the form of the spread pattern is modeled via four normal distributions, two for each side of the pattern. The control goal is to achieve a desired fertilizer distribution on the field. The study presents three algorithms for comparison: a one-step optimization and two approaches using model-predictive control -- one with a simplified model of the spread pattern in the prediction horizon, and one with a comprehensive one model, respectively. The best results are obtained with model-predictive control using the comprehensive model.
Paper VI181-02.7
PDF · Video · Model Predictive Control of Stem Water Potential in Grapevines: A Simulation Study
Gips, El'ad	IIT - Israel Institute of Technology
Gutman, Per-Olof	Technion - Israel Institute of Technology
Linker, Raphael	Technion
Netzer, Yishay	Ariel University
Keywords: Modeling and control of agriculture, Precision farming, Speaking organism systems Abstract: Grapevines for wine production are commonly cultivated under controlled deficit irrigation, i.e. the vines are maintained in a state of mild, controlled water stress in order to enhance the quality of the berries. The vines water status can be estimated via measurements of the Stem Water Potential (SWP). The objective of the present work was to demonstrate the application of Model Predictive Control (MPC) for managing grapevine irrigation via Stem Water Potential at two levels: (1) MPC was used to determine SWP reference values for the whole season, and (2) MPC was used to estimate twice a week the irrigation required to achieve the desired SWP.
Paper VI181-02.8
PDF · Video · Soil Moisture Retrieval from Airborne Multispectral and Infrared Images Using Convolutional Neural Network
Seo, Min-Guk	Cranfield University
Shin, Hyo-Sang	Cranfield University
Tsourdos, Antonios	Cranfield University
Keywords: Pattern recognition and Artificial Intelligence in agriculture, Precision farming, Agricultural robotics Abstract: This paper deals with the modeling of soil moisture retrieval from multispectral and infrared (IR) images using convolutional neural network (CNN). Since it is difficult to measure the soil moisture level of large fields, it is essential to retrieve soil moisture level from remotely sensed data. Quadrotor unmanned aerial vehicle (UAV) is considered as sensing platform in order to acquire data with high spatial resolution at anytime by non-experts. With considerations both on the availability of sensors for the platform and the information needed to overcome the effects of the canopies covering soil, IR and multispectral images are selected to be used for soil moisture retrieval. In order to prevent information loss by the calculation of parameters from measurements and enhance the applicabiliy for online operations, CNN is applied for the construction of soil moisture retrieval model to use the sensor measurement images directly as input data. Training and testing are conducted for the proposed CNN-based soil moisture retrieval model using the data from actual quadrotor flight over an agricultural field.

VI182
Bio and Ecological Systems - Modeling and Control of Biomedical Systems
VI182-01 Advanced Modeling of Biological and Biomedical Systems   Invited Session, 5 papers
VI182-02 Precision Medicine Enabled by Automatic Control   Invited Session, 6 papers
VI182-03 Control, Mechatronics, and Imaging for Medical Devices and Systems in Medicine   Open Invited Session, 22 papers
VI182-04 Development of Control Theoretical Approaches in Biology and Medicine   Open Invited Session, 10 papers
VI182-05 Physiological Control Systems in Medicine   Open Invited Session, 43 papers
VI182-06 Biomedical and Physiological Modeling and Control   Regular Session, 18 papers
VI182-07 Estimation and Signal Analysis in Biomedicine and Social Systems   Regular Session, 7 papers

VI182-01
Advanced Modeling of Biological and Biomedical Systems	Invited Session
Chair: Wang, Jin	Auburn University
Co-Chair: Hahn, Juergen	Rensselaer Polytechnic Institute
Organizer: Wang, Jin	Auburn University
Organizer: Hahn, Juergen	Rensselaer Polytechnic Institute
Organizer: Gunawan, Rudiyanto	University at Buffalo
Paper VI182-01.1
PDF · Video · The Circadian Rhythms of Cortisol: Modelling Their Role in Regulating Homeostasis and Personalized Resilience and Adaptation (I)
Rao, Rohit	Pfizer
Androulakis, Ioannis	Rutgers University
Keywords: Cellular, metabolic, cardiovascular, pulmonary, neuro-systems, Physiological Model, Control of physiological and clinical variables Abstract: The hypothalamic-pituitary-adrenal (HPA) axis orchestrates the physiological response stress. Moreover, the HPA axis exhibits prominent circadian activity and synchronizes peripheral circadian clocks to daily environmental cycles, thereby promoting homeostasis. Persistent disruption of homeostatic glucocorticoid circadian rhythmicity due to chronic stress exposure is correlated with the incidence of various pathological conditions including depression, diabetes and cancer. Allostatic habituation of the HPA axis can therefore confer fitness advantages by preventing the sustained dysregulation of glucocorticoid-responsive signaling pathways. However, such allostatic adaptation results in a physiological cost (allostatic load) that might impair the homeostatic stress-responsive and synchronizing functions of the HPA axis. We use mathematical modeling to characterize specific chronic stress-induced allostatic adaptations in the HPA network. We predict the existence of multiple personalized regulatory strategies enabling the maintenance of homeostatic glucocorticoid rhythms, while allowing for flexible HPA response characteristics. We show that this regulatory variability produces a trade-off between the stress-responsive and time-keeping properties of the HPA axis. Finally, allostatic regulatory adaptations are predicted to cause a time-of-day dependent sensitization of the acute stress response and impair the entrainability of the HPA axis.
Paper VI182-01.2
PDF · Video · Designing Genetic Perturbation Experiments for Model Selection under Uncertainty (I)
Tasiudi, Eve	Department of Biosystems Science and Engineering, ETH Zurich
Lormeau, Claude	Department of Biosystems Science and Engineering, ETH Zurich ; S
Kaltenbach, Hans-Michael	ETH Zurich
Stelling, Joerg	ETH Zurich
Keywords: Model formulation, experiment design, Identification and validation, Kinetic modeling and control of biological systems Abstract: Deterministic dynamic models play a crucial role in elucidating the function of biological networks. However, the underlying biological mechanisms are often only partially known, and different biological hypotheses on the unknown molecular mechanisms lead to multiple potential network topologies for the model. Limitations in generating comprehensive quantitative data often prevent identification of the correct model topology and additionally leave substantial uncertainty about a model’s parameter values. Here, we introduce an experiment design method for model discrimination under parameter uncertainty. We focus on genetic perturbations, such as gene deletions, as our possible experimental interventions. We start from an initial dataset and a single model whose topology includes all different hypotheses. We obtain the set of models compatible with the initial dataset, their posterior probabilities, and the distribution of compatible parameter values using our previously published topological filtering approach. We then employ a fully Bayesian approach to identify the genetic perturbation that yields the maximal expected information gain in a subsequent experiment. This approach explicitly accounts for parameter uncertainty; it also naturally allows comparing an arbitrary number of candidate models simultaneously. In contrast to previous approaches, our intervention alters the topology of the dynamic system rather than selecting optimal inputs, observables, or time-points for measurements. We demonstrate its applicability with an in-silico study based on a published real-world biological example.
Paper VI182-01.3
PDF · Video · Efficient Sampling by Marginalization of Scaling Parameters for ODE Models with Relative Data (I)
Raimúndez, Elba	University of Bonn
Hasenauer, Jan	University of Bonn
Keywords: Parameter and state estimation, Modeling and identification Abstract: Quantitative mathematical models have become important tools for understanding and unraveling the mechanisms underlying biological signaling processing. However, the parameters of these models are in general unknown a priori and need to be inferred from experimental data. Most measurement techniques, e.g. Western blotting and fluorescence microscopy, only provide relative information about the absolute molecular state. To establish a proper statistical link between experimental data and a computational model, scaling parameters and noise parameters need to be introduced hence increasing the dimensionality of the estimation problem. In previous studies, hierarchical optimisation approaches for parameter estimation have been developed. These approaches exploit that the scaling and noise parameters can be computed analytically for a given set of model parameters. These approaches have shown a substantial benefit in the optimisation convergence for many optimisation methods and improved the conditioning of the optimisation problem. However, these concepts cannot be used for rigorous Bayesian uncertainty analysis. Here, we present results one the efficient marginalisation of the posterior.
Paper VI182-01.4
PDF · Video · Understanding Microbial Cellular Metabolism Using Systems Engineering Approaches (I)
Wang, Jin	Auburn University
Keywords: Modeling and identification, Microbial technology, Data mining tools Abstract: Biological systems and large-scale industrial processes share many similarities at the systems level, which make the integrative systems engineering approaches essential in the understanding, control and optimization of biological systems. However, biological systems also present unique challenges that cannot be readily addressed by available systems engineering tools. In this work, we present our recent progress made in developing new systems engineering tools to understand microbial cellular metabolism at genome-scale. In particular, we focus on genome-scale metabolic network modeling and dynamic transcriptomic analysis. The effectiveness of the developed tools is demonstrated using a xylose fermenting yeast, Scheffersomyces stipitis, as the model system.
Paper VI182-01.5
PDF · Video · Towards Elucidating Regulatory Structure of Metabolic Networks for Dynamic Modeling (I)
Lee, Justin	Georgia Institute of Technology
Orosco, Carlos	Georgia Institute of Technology
Nguyen, Britney	Georgia Institute of Technology
Styczynski, Mark	Georgia Institute of Technology
Keywords: Bioinformatics, Metabolic engineering, Modeling and identification Abstract: The ability to understand and manipulate metabolism is of great value in the chemical industry, as it opens the door to engineering organisms to make valuable small molecule chemicals and intermediates. However, even simple organisms like bacteria and yeast have extremely complex metabolic networks, consisting of typically well-characterized stoichiometric relationships and often poorly-characterized regulatory relationships. We have recently developed a framework for constraint-based dynamic modeling of metabolic networks, but one of the outstanding challenges in applying this framework is the need for better ways to infer the regulatory network structure in cases where only stoichiometry, not regulatory structure, is known. We will discuss the applications of machine learning relevant to developing a predictive understanding of cellular metabolism, including the use of data from systems-scale measurement of small molecules (known as metabolomics) coupled with inferred or explicitly measured metabolic flux distributions to characterize these unknown relationships. By training on a few simple models, we are able to substantially prune the large search space of candidate regulatory interactions, yielding improved identification of the true interactions from that search space. Taken together this approach is promising for future modeling and engineering of these complex biochemical systems.

VI182-02
Precision Medicine Enabled by Automatic Control	Invited Session
Chair: Brown, Lindsey S.	Harvard John A. Paulson School of Engineering and Applied Sciences
Co-Chair: Abel, John	Harvard University
Organizer: Brown, Lindsey S.	Harvard John A. Paulson School of Engineering and Applied Scienc
Organizer: Abel, John	Harvard University
Paper VI182-02.1
PDF · Video · Constructing a Control-Ready Model of EEG Signal During General Anesthesia in Humans (I)
Abel, John	Harvard University
Badgeley, Marcus	Massachusetts Institute of Technology
Baum, Taylor	MIT
Chakravarty, Sourish	Massachusetts Institute of Technology
Purdon, Patrick	Massachusetts General Hospital
Brown, Emery	MIT
Keywords: Control of physiological and clinical variables, Bio-signals analysis and interpretation, Biomedical system modeling, simulation and visualization Abstract: Significant effort toward the automation of general anesthesia has been made in the past decade. One open challenge is in the development of control-ready patient models for closed-loop anesthesia delivery. Standard depth-of-anesthesia tracking does not readily capture inter-individual differences in response to anesthetics, especially those due to age, and does not aim to predict a relationship between a control input (infused anesthetic dose) and system state (commonly, a function of electroencephalography (EEG) signal). In this work, we developed a control-ready patient model for closed-loop propofol-induced anesthesia using data recorded during a clinical study of EEG during general anesthesia in ten healthy volunteers. We used principal component analysis to identify the low-dimensional state-space in which EEG signal evolves during anesthesia delivery. We parameterized the response of the EEG signal to changes in propofol target-site concentration using logistic models. We note that inter-individual differences in anesthetic sensitivity may be captured by varying a constant cofactor of the predicted effect-site concentration. We linked the EEG dose-response with the control input using a pharmacokinetic model. Finally, we present a simple nonlinear model predictive control in silico demonstration of how such a closed-loop system would work.
Paper VI182-02.2
PDF · Video · Towards Insulin Monitoring: Infrequent Kalman Filter Estimates for Diabetes Management (I)
Wolkowicz, Kelilah	Harvard University
Deshpande, Sunil	Harvard University
Doyle, Francis	Harvard University
Dassau, Eyal	Harvard University
Keywords: Chronic care and/or diabetes, Parameter and state estimation, Biomedical system modeling, simulation and visualization Abstract: We propose a Kalman filter-based observer utilizing noisy remote compartment insulin measurements to estimate plasma insulin concentration. The design considers plant-model mismatch, sensor noise, as well as both uniform sampling intervals, mimicking infrequent continuous measurements, and non-uniform sampling intervals, mimicking infrequent on-demand measurements. The performance of the observer is demonstrated on ten in-silico subjects from the UVA/Padova simulator using real-life scenarios, including variability in sensor noise and variability in insulin pharmacokinetics. The proposed observer provides insight into the future use of insulin measurements for diabetes management.
Paper VI182-02.3
PDF · Video · Luenberger Observer Design for a Dynamic System with Embedded Linear Program, Applied to Bioprocesses (I)
De Becker, Kobe	KU Leuven
Bernaerts, Kristel	University of Leuven (KU Leuven)
Waldherr, Steffen	KU Leuven
Keywords: Parameter and state estimation, Microbial technology, Metabolic engineering Abstract: Microbial dynamics are fundamental to many processes in medicine and biotechnology. To model, estimate, and control such growth dynamics, methods of systems theory and control engineering are applied. In this paper, we use a modelling framework of dynamic constraint-based models, which appears as a system of ordinary differential equations of which the right hand side depends linearly on the optimal solution of a linear program (LP). This model describes the changes in the concentrations of extracellular metabolites and the amounts of all considered biomass components. The trajectories of the models are characterized by state-dependent switches among different optimal bases of the LP problem. The dynamics corresponding to each of these optimal bases are denoted as modes of the system. Based on such models, we study an online estimation problem in which the state variables are to be estimated from measurements according to a linear output equation. Due to the switching nature of the trajectories, we propose to use a bank of linear Luenberger observers for the different optimal bases of the LP. The system mode is estimated by a moving average of the error norm. An observer gain for each mode is determined by solving a set of Riccati equations with a common Lyapunov matrix. Simulation studies for a toy model with two bacterial species show the feasibility of this approach; from measurements of substrate and total biomass only, the observer is capable of correctly predicting the individual biomasses of the two species during exponential growth.
Paper VI182-02.4
PDF · Video · Average Measures of Phase and Synchrony in Inhomogeneous Populations of Circadian Oscillators (I)
Brown, Lindsey S.	Harvard John A. Paulson School of Engineering and Applied Scienc
Mehta, Harman	Indian Institute of Technology Delhi
Doyle, Francis	Harvard University
Keywords: Dynamics and control, Parameter and state estimation, Control of physiological and clinical variables Abstract: Circadian misalignment between the phase of molecular circadian oscillators and the external environment has been linked to adverse health effects, including cardiovascular disease, obesity, cancer, and psychiatric disorders. Desynchrony of the circadian clock within populations of oscillators has also been linked to these conditions. For this reason, we wish to develop a control strategy to shift molecular circadian phase while also controlling for population synchrony. Previous work has demonstrated that model predictive control can effectively solve this problem when synchrony is determined directly by measuring the phase of each cell in a homogeneous population. Such cell-specific phase measurements are rarely possible in vivo, and such homogeneity is not biologically plausible. For these reasons, we wish to design an observer that can accurately determine the mean phase of the population and derive a proxy for population synchrony. We show that a model parameterized with the average parameter set of the population can be used to sense phase from mean population expression levels, despite inaccuracies when sensing the phase of a single cell. Similarly, we are able to use the average amplitude of the population in comparison to the amplitude of the average population oscillator as a measure of synchrony within the population. Taken together, these two metrics, based on the average behavior of the cell, allow us to control the phase and synchrony of the population of cellular oscillators without measuring the phase of individual cells.
Paper VI182-02.5
PDF · Video · A Simulation-Based Comparative Analysis of PID and LQG Control for Closed-Loop Anesthesia Delivery (I)
Chakravarty, Sourish	Massachusetts Institute of Technology
Waite, Ayan	Massachusetts Institute of Technology
Abel, John	Harvard University
Brown, Emery	MIT
Keywords: Control of physiological and clinical variables, Pharmacokinetics and drug delivery, Biomedical system modeling, simulation and visualization Abstract: Closed loop anesthesia delivery (CLAD) systems can help anesthesiologists efficiently achieve and maintain desired anesthetic depth over an extended period of time. A typical CLAD system would use an anesthetic marker, calculated from physiological signals, as real-time feedback to adjust anesthetic dosage towards achieving a desired set-point of the marker. Since control strategies for CLAD vary across the systems reported in recent literature, a comparative analysis of common control strategies can be useful. For a nonlinear plant model based on well-established models of compartmental pharmacokinetics and sigmoid-Emax pharmacodynamics, we numerically analyze the set-point tracking performance of three output-feedback linear control strategies: proportional-integral-derivative (PID) control, linear quadratic Gaussian (LQG) control, and an LQG with integral action (ILQG). Specifically, we numerically simulate multiple CLAD sessions for the scenario where the plant model parameters are unavailable for a patient and the controller is designed based on a nominal model and controller gains are held constant throughout a session. Based on the numerical analyses performed here, conditioned on our choice of model and controllers, we infer that in terms of accuracy and bias PID control performs better than ILQG which in turn performs better than LQG. In the case of noisy observations, ILQG can be tuned to provide a smoother infusion rate while achieving comparable steady state response with respect to PID. The numerical analysis framework and findings reported here can help CLAD developers in their choice of control strategies. This paper may also serve as a tutorial paper for teaching control theory for CLAD.
Paper VI182-02.6
PDF · Video · A Bio-Inspired Geometric Model for Sound Reconstruction
Boscain, Ugo V.	DR2, CNRS, CMAP, Ecole Polytechnique
Prandi, Dario	Université Paris-Saclay, CentraleSupélec, CNRS
Sacchelli, Ludovic	Lehigh University, Bethlehem, PA
Turco, Giuseppina	CNRS, Laboratoire De Linguistique Formelle, Université De Paris
Keywords: Dynamics and control, Bio-signals analysis and interpretation, Biomedical and medical image processing and systems Abstract: The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. The algorithm transforms the degraded sound in an 'image' in the time-frequency domain via a short-time Fourier transform. Such an image is then lifted in the Heisenberg group (i.e., the celebrated Brockett integrator) and it is reconstructed via a Wilson-Cowan integro-differential equation. Numerical experiments are provided.

VI182-03
Control, Mechatronics, and Imaging for Medical Devices and Systems in Medicine	Open Invited Session
Chair: Schauer, Thomas	Technische Universitaet Berlin
Co-Chair: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Organizer: Schauer, Thomas	Technische Universitaet Berlin
Organizer: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Organizer: Benyo, Balazs	Budapest University of Technology and Economics
Organizer: Desaive, Thomas	University of Liege
Organizer: Moeller, Knut	Furtwangen University
Organizer: Pretty, Christopher	University of Canterbury
Organizer: Leonhardt, Steffen	RWTH Aachen
Organizer: Ionescu, Clara	Ghent University
Organizer: Chase, J. Geoffrey	University of Canterbury
Organizer: Medvedev, Alexander	Uppsala University
Paper VI182-03.1
PDF · Video · Acoustic Radiation Force Impulse Imaging Using Displacements of Lateral Dimension (I)
Zhang, Shengnan	Tianjin University
Xu, Yanbin	Tianjin University
Bao, Xuyang	Tianjin University
Dong, Feng	Tianjin University
Keywords: Medical imaging and processing, Biomedical and medical image processing and systems, Biomedical system modeling, simulation and visualization Abstract: Acoustic radiation force (ARF) induced elasticity imaging is usually used to obtain the elastic properties of media by detecting the induced displacement at the focal point. However, the ARF induced displacement response actually appears not only at the focal point, but also in lateral dimension at the focal depth. The relationship between the stiffness of media and the axial-directional displacements in lateral dimension at the focal depth has been analyzed through theoretical derivation, simulation and experimental verification. The results demonstrate that the maximum displacement in lateral dimension is inversely proportional to the lateral distance from the currently estimated point to the focal point. Therefore, the maximum displacement in lateral dimension at the focal depth is capable of estimating the elastic properties of the media. Based on this conclusion, an ARF impulse imaging method using displacements of lateral dimension is proposed. The induced displacements at the focal point as well as in the lateral dimension at the focal depth are detected under only the focal point excited. In this way, the proposed imaging method is expected to broaden the ARF impulse imaging region from the focal point to a larger region in the lateral dimension while reducing patient acoustic exposure and transducer heating.
Paper VI182-03.2
PDF · Video · Automatic Instrument Changer for Robotic Microsurgical Systems (I)
Zeng, Xiang-Yan	National Taiwan University
Chuang, Yi-Hang	National Taiwan University
Chen, Cheng-Wei	National Taiwan University
Keywords: Rehabilitation engineering and healthcare delivery, Biomedical and medical image processing and systems, Dynamics and control Abstract: This paper introduces a novel automatic instrument changer that allows for fast and precise tool changing in robot-assisted microsurgery. The importance of such a system is usually ignored and therefore most of the existing robotic surgical systems still require manual operation to change surgical instruments. To achieve automatic instrument changing, we apply a clamp mechanism which consists of an instrument adapter and an instrument holder. The instrument adapter creates a unified interface between the surgical instrument and the holder. The instrument holder clamps the instrument through the adapter. The instrument can be transferred to another holder when these two holders are connected. A prototype of the proposed automatic instrument changer was implemented and mounted on a surgical robot. The experimental results validate the capability of the prototypical design in automatic, precise, and fast instrument changing.
Paper VI182-03.3
PDF · Video · Mechanical Ventilation Monitoring: Development of a Network Data Acquisition System (I)
Ng, Qing Arn	Monash University
Loo, Nien Loong	Monash University
Chiew, Yeong Shiong	Monash University
Tan, Chee Pin	Monash University
Mohd Ralib, Azrina	International Islamic University Malaysia Medical Center, Pahang
Mat Nor, Basri	Department of Intensive Care, International Islamic University M
Keywords: Biomedical system modeling, simulation and visualization Abstract: Mechanical ventilator (MV) is a vital life support machine for respiratory failure patients in Intensive Care Unit (ICU). Critical and beneficial information on patient’s breathing pattern can be obtained from the ventilator for research studies in a form of ventilator waveform data (VWD). However, imperfect data collection system and lack of Electronic Health Record system integration has deterred the study of VWD to improve patient’s treatment. Furthermore, data acquisition of VWD is not easily accessible and cost-prohibitive to deploy. Therefore, current studies are limited to small samples of breathing cycle, despite continuously changing patient’s respiratory state during the day. Hence, this proposed system allows constant monitoring of patient’s ventilation data and real-time VWD visualization on mobile devices. This system consists of a data acquisition device (DAQ) to acquire VWD and a mobile web application to display patient’s breathing condition in real time. In addition, the collected VWD data are stored securely in network attached storage and onto cloud storage to prevent data loss. This framework has been successfully tested with MV attached with test lung. This proposed system can potentially expedite research studies by providing a better data collection and management specifically in the clinical environment.
Paper VI182-03.4
PDF · Video · New Modeling Results for an EEG Measurement System with Exciting and Reading Electrodes (I)
Mulinari Pinheiro Machado, Mariana	Grenoble INP
Voda, Alina	University Joseph Fourier Grenoble 1
Besancon, Gildas	Ense3, Grenoble INP
Becq, Guillaume	CNRS
David, Olivier	INSERM
Keywords: Identification and validation, Model formulation, experiment design, Biomedical system modeling, simulation and visualization Abstract: In a context where electroencephalography (EEG) is largely used for brain studies,this paper focuses on the dynamics of the measurement process itself by means of a so-called phantom EEG device developed in a former study. A model is proposed in order to better understand the physical properties of each part of the measurement chain separately, with the purpose of helping for a better recovery of neuronal activity. The model structure is based on a physical analysis, and parametric identification is used in combination with it to estimate all the underlying physical components. Numerical results are provided based on experimental data.
Paper VI182-03.5
PDF · Video · Model-Based Management of Lung Cancer Radiation Therapy (I)
Ghita, Maria	Ghent University
Drexler, Dániel András	Óbuda University
Kovacs, Levente	Obuda University
Dana, Copot	Ghent University
Muresan, Cristina Ioana	Technical University of Cluj Napoca
Ionescu, Clara	Ghent University
Keywords: Biomedical system modeling, simulation and visualization, Model formulation, experiment design, Physiological Model Abstract: A truly personalized cancer therapy demands the availability of models, of which tumor dynamics model is imperative. This paper presents a feasibility study of using a tumor growth model for lung cancer treatment planning. Recent developments in radiation therapy are outlined in this work, including target tumor based delivery of limited but highly precise treatment doses during stereotactic body radiation therapy (SBRT). Based on our prior work, we propose a methodology for quality improvement in treatment management of lung cancer, including the lung tumor motion. The paper presents the tumor behavior in various therapy scenarios by simulating different time-dose schemes for drug administration. The results indicate that the model is adequate and can be further used into the feedback scheme for treatment updates.
Paper VI182-03.6
PDF · Video · Finger Grasp Kinematics towards Exoskeleton Development (I)
McKenzie, Lachlan	University of Canterbury
Fortune, Benjamin	University of Canterbury
Chatfield, Logan Thomas	University of Canterbury
Pretty, Christopher	University of Canterbury
Keywords: Rehabilitation engineering and healthcare delivery, Kinetic modeling and control of biological systems Abstract: This paper investigates the relationships between index finger joint rotations to determine whether a one degree of freedom (DOF) exoskeleton could produce natural finger motions for a range of different users and grasping conditions. Four healthy subjects each performed ten trials involving the grasp of two cylindrical objects with diameters of 66.5mm and 47mm. Finger trajectories for each trial were recorded using a motion capture system and were used to obtain joint rotational trajectories for the Metacarpo-phalangeal (MCP) Proximal-interphalangeal (PIP) and Distal-interphalangeal (DIP) joints. Joint ranges of motion (ROM) were largest for all subjects when grasping the smaller diameter object. This effect was also seen where subjects with longer fingers tended to use a larger MCP ROM for the same object. Subject 3 was an exception to this, using the smallest MCP and PIP ROM of all subjects when grasping the large diameter object: this anomaly is thought be caused by difference in palmar engagement with the object. The profile of the MCP-PIP trajectories were similar when normalised to their range of motion, with a maximum y-axis error of 22%. This implies that the MCP-PIP relationship for a cylindrical grasp can be approximated be a general scalable polynomial. We conclude that through parabolic coupling between MCP and PIP joints, a one-DOF exoskeleton is capable of producing functional grasping movements. Through an adjustable coupling mechanism between MCP and PIP, it is also believed that an exoskeleton can be successfully adapted for differing object and finger sizes.
Paper VI182-03.7
PDF · Video · A Novel Microsurgical Robot with Double-Parallelogram RCM Mechanism and Back-Driven Instrument Translation (I)
Chen, Hsing-Chi	National Taiwan University
Su, Wei-Jiun	National Taiwan University
Chen, Cheng-Wei	National Taiwan University
Keywords: Biomedical and medical image processing and systems, Rehabilitation engineering and healthcare delivery, Dynamics and control Abstract: With the increasing demand for high-accuracy maneuvers in robot-assisted minimal invasive surgery (MIS), both the kinematic structure and the assembly errors of the microsurgical robot need to be improved. Traditionally, the insertion and retraction motion of the surgical tool is driven by a linear actuator mounted on the end-effector. However, this causes additional mass, inertia, and vibration. To mitigate this problem, a novel microsurgical robot with back-driven instrument translation is developed. Parameter optimization that considers the assembly errors of the double-parallelogram RCM mechanism is performed in the robot's mechanism design. A prototype of the design is fabricated and implemented. The experimental results validate the effectiveness of the proposed new mechanism.
Paper VI182-03.8
PDF · Video · Electrical Impedance Tomography Image Reconstruction Based on Neural Networks (I)
Bianchessi, Andre	University of Sao Paulo
Akamine, Rodrigo H.	EPUSP
Duran, Guilherme C.	EPUSP
Tanabi, Naser	EPUSP
Sato, Andre Kubagawa	Escola Politecnica Da Universidade De Sao Paulo
Martins, Thiago de Castro	University of Sao Paulo
Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Keywords: Medical imaging and processing, Biomedical and medical image processing and systems Abstract: Electrical impedance tomography (EIT) is an imaging technique with a promising future. Several methods have been used for EIT image reconstruction, such as Simulated Annealing, Gauss Newton, Kalman filter and D-Bar. Recently, some authors solved this problem using artificial neural network (ANN) through pixel by pixel reconstruction, considering a fixed resolution for the final image. This work proposes a reconstruction based on the EIT forward problem. Two different meshes were considered: a coarse and a refined mesh. The latter was used to produce simulated potentials, which are the inputs for ANN training. The nodes conductivities, which used to create the outputs for training, defined in the coarser mesh. Therefore, the proposed method consists of training the ANN with inputs from a refined mesh and outputs from a coarse mesh. Two ANN architectures are proposed and compared: one based on the LeNet architecture, and another based on the feed-forward fully connected ANN. The obtained image is not dependent on any image resolution. The preliminary results show that the LeNet architecture has better performance.
Paper VI182-03.9
PDF · Video · Estimating Elbow Torque from Electrical Stimulation Using a Particle Filter (I)
Chatfield, Logan Thomas	University of Canterbury
McKenzie, Lachlan	University of Canterbury
Fortune, Benjamin	University of Canterbury
Pretty, Christopher	University of Canterbury
Hayes, Michael	University of Canterbury
Keywords: Rehabilitation engineering and healthcare delivery, Physiological Model, Decision support and control Abstract: This study analyses the relationship between functional electrical stimulation (FES) and the induced torque for elbow flexion. The aim is to develop an FES-torque model that is simple to implement and understand, and is easily invertible so that the required FES for a desired assistive torque can be determined to enable control by FES. For accurate control, the FES-torque model must also be adaptable to time-varying behaviour of the muscle such as fatigue. The proposed FES-torque model is a sigmoid function, and a particle filter is implemented to estimate the change in parameters of the sigmoid function over time. The results show that the particle filter is successfully able to adapt to changes in the FES-induced torque and can be used to improve the estimate of FES-induced torque, with an overall average RMS error of 0.24 N.m or 7.85%. The improved FES-torque estimate allows for simple and more effective control of FES assistance and better fatigue management.
Paper VI182-03.10
PDF · Video · Electropalatography Contact Patterns in the Production of Malay Consonants among Paralysed Patients (I)
Mat Zin, Syatirah	Universiti Sains Malaysia
Suhaimi, Fatanah	Universiti Sains Malaysia
Md Shakur, Nur Fatehah	Craniofacial and Biomaterial Sciences Cluster, Advanced Medical
Mohd Noor, Siti Noor Fazliah	Craniofacial and Biomaterial Sciences Cluster, Advanced Medical
Mohamad, Ahmad Fakrurrozi	Craniofacial and Biomaterial Sciences Cluster, Advanced Medical
Zali, Nurulakma	Craniofacial and Biomaterial Sciences Cluster, Advanced Medical
Keywords: Rehabilitation engineering and healthcare delivery, Biomedical and medical image processing and systems Abstract: Various techniques are available for improving speech production among subjects with speech problems, including paralysed patients. In this study, electropalatography (EPG) that detects the tongue and hard palate contact during continuous speech is used as a therapeutic instrument for improving the production of speech among paralysed patient. Five paralysed subjects with different medical background had been chosen. All paralysed subjects were asked to wear a Reading Palate which has 62 electrodes as a sensor to detect the tongue and hard palate contacts. The electrode sensors were divided into four zones which are alveolar, postalveolar, palatal and velar zones. The signals of the electrodes were transferred to a computer and analysed using Articulate Assistant TM 1.18. The objective of this study is to determine the location of contact between the tongue and hard palate among five paralysed subjects during the production of bilabial, postalveolar, velar and glottal consonants. The contact patterns produced by the paralysed subject were compared with the contact pattern guideline of the Malay consonants. In conclusion, EPG is suitable to be used as a device to identify the difference in the contact pattern. Besides, EPG can also be used as an exercise instrument to train the muscle movement to improve the contact pattern.
Paper VI182-03.11
PDF · Video · The Effects of Insulin Infusion Protocol on the Glycemic Level of the Intensive Care Patients (I)
Zukhi, Jihan	Advanced Medical and Dental Institute, Universiti Sains Malaysia
Suhaimi, Fatanah	Universiti Sains Malaysia
Mazlan, Mohd Zulfakar	Department of Anaesthesiology and Intensive Care, School of Medi
Jamaludin, Ummu Kulthum	Universiti Malaysia Pahang
Razak, Normy	Univ of Canterbury
Mohd Sopian, Mastura	Oncological and Radiological Sciences Cluster, Advanced Medical
Keywords: Bio-signals analysis and interpretation, Biomedical system modeling, simulation and visualization Abstract: Insulin infusion protocol is the standard protocol implemented in Malaysia’s intensive care unit (ICU) for controlling the hyperglycemia. Multiple sliding scale method of the insulin infusion protocol may drive conflict in selecting an appropriate scale to be applied to the patient. The objective of this paper is to analyse the blood glucose outcome of eight sliding scales insulin infusion protocol adopted in the Universiti Sains Malaysia Hospital (HUSM). A retrospective data of 78 ICU patients of HUSM were fitted using a validated glucose-insulin system to identify insulin sensitivity profiles of the patients. Then, these SI profiles were simulated on various scale protocols. The results obtained from this study showed that among eight scales, Scale 4 had the highest percentage of BG within the HUSM’s target of 6.0 – 10.0 mmol/L. Scale 1 had the highest percentage of BG for the BG measurement more than 10.0 mmol/L while Scale 8 had the highest percentage of BG measurement of less than 6.0 mmol/L. However, none of the scale shown better performance than the current clinical practice. Furthermore, all of the eight scales had a more substantial number of BG measurement compared to the clinical. This study shows that Scale 2 and Scale 3 result in a similar outcome. Similarly, Scale 5 is almost the same as Scale 6. Thus, at least two sets of scale can be combined to reduce the number of scales. The reduction of scales consequently avoid confusion and helps the clinician in selecting the appropriate scale to be applied to the patients. From this study, it can be concluded that the HUSM protocol is a combination of scales. The scales may be shifted from one to another scale depending on patient condition and clinician judgement. A proper guideline for the scale shifting seems necessary to allow optimum glycemic management in the ICU.
Paper VI182-03.12
PDF · Video · Development of a Discrete Spectrometric NIR Reflectance Glucometer (I)
Campbell, Jake	University of Canterbury
Holder-Pearson, Lui	University of Canterbury
Pretty, Christopher	University of Canterbury
Benton, Connor	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Keywords: Bio-signals analysis and interpretation, Chronic care and/or diabetes, Identification and validation Abstract: Currently, there are no continuous, non-invasive blood glucose monitors. With over 366 million people worldwide expected to be diagnosed as diabetic by 2030, an alternative to the current invasive methods is critical. This paper investigates the use of a discrete spectometric, NIR reectance glucometer to detect a change in glucose concentration in solution. At each wavelength, an LED is used to emit light, and a reverse-biased LED detects light using wavelengths 660 nm, 850 nm, 940 nm, 1450 nm, 1550 nm, 1650 nm. The discharge time of a reverse-biased LED is proportional to the temporal integral of the detected light intensity. The sensor's response to changing glucose concentration was tested in both water and porcine blood. Glucose concentration was increased by 0.5 mmol per litre and compared with a finger stick glucometer. Each wavelength exhibited an expected change in adsorption given only an increase in glucose concentration. The inverted exponential increase in absorption is explained by Beer Lambert's law. Wavelengths 660 nm, 850nm and 1450nm showed minimal change to absorption, while 940 nm, 1550nm and 1650nm showed considerable change in absorption. The 1550nm LED gave the greatest increase in absorption with a 7% rise over 4:3 mmol per litre to 20.6 mmol per litre. Ratios of absorption responses (R1550/1650, R1550/1450 and R940/850) each gave proportional increases in absorption with increasing glucose concentrations.
Paper VI182-03.13
PDF · Video · Assessment of a Low-Cost LED Vein Detection Method - Initial Proof of Concept (I)
Stewart, Kent	University of Stuttgart
Liu, Jan	University of Stuttgart
Willmann, Pia	University of Stuttgart
Pott, Peter Paul	University of Stuttgart
Keywords: Developments in measurement, signal processing, Medical imaging and processing Abstract: Venepuncture is one of the most common invasive procedures in medical healthcare worldwide,however failure rates are still relatively high, particularly for paediatric, geriatric, darker skinned, and obese patients. Visualisation of the veins has been shown to decrease failure rates and can be achieved through trans-illumination, near infrared reflectance, or sonography. However, these techniques are either not reliable or very expensive, resulting in them not being commonly used in the clinical workplace. This paper develops a proof of concept low-cost LED vein detection device, using the photocurrent generated by LEDs in reverse bias. The prototype uses two emitting LEDs and one detecting LED to identify the location of a vein via trans-illuminance and reflectance. Various light intensities and wavelengths of the LEDs are tested in regard to resolution, noise, and signal peaks. A balance between system noise and resolution is identified for each LED in relation to the emitted intensity. No significant difference was observed in relative peak height when different wavelengths were used to identify the same superficial veins. The initial proof of concept proves the LED vein detection method and provides the foundation for further low-cost LED vein detection devices to be developed.
Paper VI182-03.14
PDF · Video · An Approach to Magnetometer-Free On-Body Inertial Sensors Network Alignment (I)
Lorenz, Michael	Technische Universität Kaiserslautern
Taetz, Bertram	Technische Universität Kaiserslautern
Bleser, Gabriele	Technische Universität Kaiserslautern
Keywords: Developments in measurement, signal processing Abstract: To capture human motion with inertial sensors, they are attached as a network on different segments. Typically the measurements received from each sensor are fused to obtain its orientation. A challenging task is to align the orientation of each sensor w.r.t. to a single common coordinate frame. To fulfill this task typically the local magnetic field is measured to provide information about the heading direction. Since especially in indoor environments magnetic field disturbances can be present, this information is not a reliable source. To overcome this problem, we present a method that aligns an on-body inertial sensor network using gyroscopes and accelerometers only. The subject wearing the network had to fulfill a predefined procedure, consisting of standing still and walking straight. To extract the heading direction, we estimated the linear acceleration and angular velocity using a maximum-a-posteriori estimator. Performing a principal component analysis on the estimated states we computed two heading directions for each estimate. Instead of using them separately, we used a fusing approach that exploits symmetrical effects. We validated the approach on a lower body configuration using an optical motion capture system. The heading direction of sensors attached on a single leg could be aligned up to median maximal deviation of 2.6 degrees and on the complete lower body of 6.6 degrees. Especially deviations of the pelvis were higher, due to a lack of motion excitation. To be able to quantify the excitation needed, we proposed an indicator based on the ratio of the eigenvalues of the principal component analysis of the angular velocities.
Paper VI182-03.15
PDF · Video · On Expressive Features for Gait Analysis Using Lower Limb Inertial Sensor Data (I)
Laufer, Felix	Technische Universität Kaiserslautern
Lorenz, Michael	Technische Universität Kaiserslautern
Taetz, Bertram	Technische Universität Kaiserslautern
Bleser, Gabriele	Technische Universität Kaiserslautern
Keywords: Bio-signals analysis and interpretation, Developments in measurement, signal processing, Parameter and state estimation Abstract: In this paper, we present a method to obtain explicit, expressive and interpretable gait feature signals from an inertial sensor, mounted on any segment of the lower limbs. The proposed method is invariant to the mounting orientation of the sensor, works without magnetometer information, requires no prior knowledge and can be used in real-time scenarios. Moreover, the constructed signals are robust for a wide variety of changing walking speeds and directions. We investigate the informational content of our three feature signals lying in the human sagittal plane with respect to the gait phase segmentation problem and compare them to other commonly used signals, such as the sagittal angular velocity and the norms of accelerations and angular velocities. To this end, we make use of the filter-based maximum relevance minimum redundancy algorithm, which is a classifier-independent feature selection method. For validating our approach, we consider gait data of twelve healthy subjects walking straight and in curves at self-chosen speeds with inertial sensors attached to either the thigh, shank or foot. Additionally, pressure measuring insoles are used to obtain ground truth toe-off and heel-strike gait events for reference. With those events as the gait phase transitions, the event detection is cast into a classification problem. To support the theoretical findings of the feature selection and ranking, we finally evaluate different choices of feature sets with a simple linear support vector machine classifier in an online fashion and obtain superior segmentation results with our feature signals.
Paper VI182-03.16
PDF · Video · Demonstrator of a Low-Cost Hand Prosthesis (I)
Mühlbauer, Pia	University of Stuttgart
Löhnert, Laura	University of Stuttgart
Siegle, Carla	University of Stuttgart
Stewart, Kent	University of Stuttgart
Pott, Peter Paul	University of Stuttgart
Keywords: Rehabilitation engineering and healthcare delivery Abstract: Upper limb absence has an impact on both physical and mental health of a human being. Nowadays, the costs of commercial, externally powered prosthetic hands range between 25.000 € and 70.000 €. A first demonstrator of a lightweight low-cost prosthetic hand is produced with 3D-printing technology (Fused Deposition Modeling). Due to integration of single-axis solid-state joints the five fingers can be printed in one piece. Thermoplastic polyurethane is used for this purpose. The flexion of all fingers is achieved by moving cords which are positioned on the palmar side of each finger. Two twisted string actuators are integrated to allow the movement of the thumb and the remaining four fingers. These actuators consist of two polyethylene strands which are twisted along their main axis by a DC motor, providing a tensile force to bend the fingers. In order to achieve simultaneous but differential actuation of the four fingers (small finger, ring finger, middle finger and index finger), a differential mechanism is used. The thumb is driven by a separate unit. In order to open the hand, the elasticity of the joints’ material is taken advantage of. With the developed mechanics it is possible to perform precision and cylindrical grasps with an opposed thumb. Weights up to 260 g can be held according to the shape and size of an object. To increase the adaption to different sizes and weights of objects, the design should be modified. It can be concluded, that the presented device is a promising basis for a lightweight, low-cost prosthetic hand in the future.
Paper VI182-03.17
PDF · Video · Inertial Sensor Based Detection of Freezing of Gait for On-Demand Cueing in Parkinson's Disease (I)
Dvorani, Ardit	SensorStim Neurotechnology GmbH
Jochner, Magdalena	Department of Neurology, Charité Universitätsmedizin Berlin
Seel, Thomas	Technische Universitaet Berlin
Salchow-Hömmen, Christina	Technische Universitaet Berlin, Control Systems Group
Meyer-Ohle, Jonas	Technische Universität Berlin, Control Systems Group, Germany
Wiesener, Constantin	SensorStim Neurotechnology GmbH
Voigt, Hanno	SensorStim Neurotechnology GmbH
Kühn, Andrea	Department of Neurology, Charité Universitätsmedizin Berlin
Wenger, Nikolaus	Department of Neurology, Charité Universitätsmedizin Berlin
Schauer, Thomas	Technische Universitaet Berlin
Keywords: Biomedical and medical image processing and systems Abstract: Freezing of Gait (FoG) is one of the cardinal symptoms of Parkinson's disease, which arises in the late stages of the disease. It affects the gait cycle and increases the risk of falling. FoG leads to heterogeneous gait cycles, which makes the detection of gait phases and events difficult. In this article, we introduce a new inertial measurement unit-based approach for detecting Parkinsonian gait phases based on the acceleration, velocity, rate of turn and orientation of the foot. Furthermore, we introduce a new gait evaluation measurement, the so-called GaitScore, for distinguishing between normal and FoG-affected motion phases and thus for detecting FoG episodes. Preliminary results show that the extreme values of the pitch angle during a motion phase provide valuable information for the detection of FoG. The proposed method can detect FoG episodes with a sensitivity of 97% and specificity of 87%. The reference data were generated by clinical experts who annotated FoG episodes in video data synchronized with the measurements of the inertial sensors. The detection of FoG in real-time enables on-demand cueing.
Paper VI182-03.18
PDF · Video · Design of a Hybrid Brain-Computer Interface and Virtual Reality System for Post-Stroke Rehabilitation (I)
Huang, Mengjie	Xi'an Jiaotong-Liverpool University
Zheng, Yuting	Xi'an Jiaotong-Liverpool University
Zhang, Jingjing	Xi'an Jiaotong-Liverpool University
Guo, Bin'ao	Xi'an Jiaotong-Liverpool University
Song, Chenyu	Xi’an Jiaotong-Liverpool University
Yang, Rui	Xi'an Jiaotong-Liverpool University
Keywords: Rehabilitation engineering and healthcare delivery Abstract: As one of common diseases among elderly, stroke often leads to motor impairment and even serious disability. Post-stroke rehabilitation is of great importance to restore the motor function and improve the life quality of stroke survivors. This study therefore sets out to propose a hybrid system based on brain-computer interface and virtual reality, which can provide various training programs including action observation, motor imagery and physical therapy for post-stroke patients with different motor control levels and training demands. The present work offers new insights into the way in which the conventional rehabilitation programs can be turned into innovative and interactive training experiences with advanced technologies to make optimal rehabilitation outcomes for stroke survivors.
Paper VI182-03.19
PDF · Video · Magnetometer-Free Inertial Motion Tracking of Arbitrary Joints with Range of Motion Constraints (I)
Lehmann, Dustin	Technische Universität Berlin
Laidig, Daniel	TU Berlin
Deimel, Raphael	TU Berlin
Seel, Thomas	Technische Universitaet Berlin
Keywords: Developments in measurement, signal processing, Rehabilitation engineering and healthcare delivery Abstract: In motion tracking of connected multi-body systems, Inertial Measurement Units (IMUs) are used in a wide variety of applications, since they provide a low-cost easy-to-use method for orientation estimation. However, in indoor environments or near ferromagnetic material, the magnetic field is inhomogeneous, which limits the accuracy of tracking algorithms using magnetometers. Methods that use only accelerometers and gyroscopes on the other hand yield no information on the absolute heading of the tracked object. For objects connected by rotational joints with range of motion constraints, a method is proposed that provides a magnetometer-free, long-term stable relative orientation estimate based on a non-linear, window-based cost function. The method can be used for real-time estimation as well as post-processing. It is validated experimentally with a mechanical joint and compared to other methods that are commonly used in motion tracking. It is shown that for the used test object, the proposed method yields the best results with a total angle error of less than 4 degrees for all experiments.
Paper VI182-03.20
PDF · Video · Sparse Magnetometer-Free Inertial Motion Tracking - a Condition for Observability in Double Hinge Joint Systems (I)
Eckhoff, Karsten	Technische Universität Berlin
Kok, Manon	Delft University of Technology
Lucia, Sergio	TU Berlin
Seel, Thomas	Technische Universitaet Berlin
Keywords: Bio-signals analysis and interpretation, Rehabilitation engineering and healthcare delivery Abstract: Inertial measurement units are commonly used in a growing number of application fields to track or capture motions of kinematic chains, such as human limbs, exoskeletons or robotic actuators. A major challenge is the presence of magnetic disturbances that results in unreliable magnetometer readings. Recent research revealed that this problem can be overcome by exploitation of kinematic constraints. While typically each segment of the kinematic chain is equipped with an IMU, a novel approach called sparse inertial motion tracking aims at inferring the complete motion states from measurements of a reduced set of sensors. In the present contribution, we combine the magnetometer-free and the sparse approach for real-time motion tracking of double-hinge joint systems with non-parallel joint axes. Analyzing the observability of the system, we find a condition which assures that the relative orientations between all segments are uniquely determined by a kinematic constraint, which contains only the gyroscope readings. Furthermore, we propose a moving-horizon estimator and validate it in a simulation study of four movements, which differ by their degrees of excitation. The results of this study confirm the theoretical conjectures and demonstrate that magnetometer-free sparse inertial real-time motion tracking is feasible under precise and simple excitation conditions.
Paper VI182-03.21
PDF · Video · Pulse Wave Velocity Measurement in the Carotid Artery Using an LED-LED Array Pulse Oximeter (I)
Campbell, Jake	University of Canterbury
Holder-Pearson, Lui	University of Canterbury
Pretty, Christopher	University of Canterbury
Bones, Phil	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Keywords: Bio-signals analysis and interpretation, Developments in measurement, signal processing Abstract: Pulse wave velocity (PWV) is frequently used as an early indicator of risk of cardiovascular disease. Conventional methods of PWV measurement are invasive and measure the regional PWV, introducing errors from unknown measurement distance to masking local changes in compliance. This paper describes the development and testing of a non-invasive PWV sensor using photoplethysmograph signals. The sensor measures the pulse in the carotid artery with three sensor arrays spaced at 20 mm, 30 mm and 50 mm spacing. Each array of 20 LED-LED sensors are placed at 5 mm to get the largest amplitude pulse across the neck, and to allow for inaccurate sensor placement. LEDs are used as light emitters and the inherent capacitance of reverse biased LEDs measure the reflected light. The foot-foot and phase difference methods were used to calculate the PWV at each measurement distance. The foot-foot method was more reliable than the phase difference at all distances with a PWV of 5.26 m/s in a single-subject trial. The sample rate of 570 Hz was deemed too slow as one sample difference resulted in a PWV change of 1.5 m/s. The developed sensor measured the local PWV within the expected physiological range around 6 m/s. All future measurements will be measured at 1 kHz and an increased LED output intensity.
Paper VI182-03.22
PDF · Video · Finite Element Simulation Based Analysis of Valve-Sparing Aortic Root Surgery (I)
Nagy, Róbert	Budapest University of Technology and Economics
Umenhoffer, Tamás	Budapest University of Technology and Economics
Somogyi, Péter	Budapest University of Technology and Economics
Szlávecz, ákos	Budapest University of Technology and Economics
Kubovje, Anikó	Budapest University of Technology and Economics
Laufer, Bernhard	Institute of Technical Medicine (ITeM), HFU Furtwangen Universit
Kovács, Katalin	Széchenyi István University
Szerafin, Tamás	University of Debrecen
Benyo, Balazs	Budapest University of Technology and Economics
Keywords: Biomedical system modeling, simulation and visualization, Biomedical and medical image processing and systems, Physiological Model Abstract: The valve-sparing aortic root surgery is frequently used in the treatment of aortic root enlargement or aortic root aneurysm. The currently used common surgical practice assumes that the valve leaflets are distributed evenly around the circle defined by the aorta wall which is frequently a false assumption according to hart anatomy studies. A finite element simulation based method is proposed in this study for the analysis of the alternative surgical outcomes of the valve-sparing aortic root surgery. The simulation methods allow the definition of the aortic valve leaflet commissure positions and the diameter of the graft used to replace the aortic root. The suggested methods are able to estimate and quantitatively compare the hemodynamic functions and the robustness of the aortic valve functions. The corresponding modeling environment makes possible the easy definition of the patient specific aortic root model that is used as an input of the simulation. The initial validation of the simulation method was done by a real patient data based simulation study. These results suggest that the currently used surgical practice can be improved.

VI182-04
Development of Control Theoretical Approaches in Biology and Medicine	Open Invited Session
Chair: Hernandez Vargas, Esteban A.	UNAM
Co-Chair: Rodriguez Gonzalez, Jesus	Unidad Monterrey
Organizer: Hernandez Vargas, Esteban A.	UNAM
Organizer: Rivadeneira, Pablo S.	Universidad Nacional De Colombia, Sede Medellín
Organizer: Califano, Claudia	La Sapienza, Università Di Roma
Organizer: Quiroz, Griselda	Universidad Autonoma De Nuevo Leon
Paper VI182-04.1
PDF · Video · Discrete-Time Switching MPC with Applications to Mitigate Resistance in Viral Infections (I)
Anderson, Alejandro	INTEC-CONICET-UNL
Gonzalez, Alejandro, Hernan	Institute of Technological Development for the ChemicalIndustry
Ferramosca, Antonio	CONICET
Hernandez Vargas, Esteban A.	UNAM
Keywords: Biomedical system modeling, simulation and visualization, Pharmacokinetics and drug delivery, Decision support and control Abstract: Many engineering applications can be described as switched linear systems, in which the manipulated control action is the time-dependent switching signal. In such a case, the control strategy must select a linear autonomous system at each time step, among a finite number of them. Even when this selection can be done by solving a Dynamic Programming (DP) problem, the implementation of such a solution is often difficult and state/control constraints cannot be explicitly accounted for. In this paper a new set-based Model Predictive Control (MPC) strategy is presented to handle switched linear systems in a tractable form. The optimization problem at the core of the MPC formulation consists in an easy-to-solve mixed-integer optimization problem, whose solution is applied in a receding horizon way. The medical application of viral mutation and its respective drug resistance is addressed to acute and chronic infections. The objective is to attenuate the effect of the mutation on the viral load, and the numerical results suggested that the proposed strategy outperform the schedule for available treatments.
Paper VI182-04.2
PDF · Video · Lyapunov-Based Switching to Mitigate Antimicrobial Resistance (I)
Tetteh, Josephine	Frankfurt Institute for Advanced Studies
Olaru, Sorin	CentraleSupelec
Parra-Rojas, César	Frankfurt Institute for Advanced Studies
Hernandez Vargas, Esteban A.	UNAM
Keywords: Decision support and control, Pharmacokinetics and drug delivery, Control of physiological and clinical variables Abstract: Drug resistant pathogens are a global public health threat and their control have become a challenging task. In this paper, a mathematical model which describes the general dynamics of microbial resistance is employed. Utilizing a two-strain bacterial population, notions from control engineering and positive switched systems are used to develop control strategies aimed at minimizing the appearance of drug resistant bacteria within the host. Based on the Lyapunov function argument, a switching strategy can be found to ensure stability of the eradication equilibrium under given conditions. Numerical simulations compare switching under different feedback controls and validate the use of the switching strategy in general for the proposed model of bacterial resistance mitigation.
Paper VI182-04.3
PDF · Video · PK/PD-Based Impulsive Control to Tailor Therapies in Infectious Diseases (I)
Hernandez Mejia, Gustavo	Frankfurt Institute for Advanced Studies (FIAS)
Hernandez Vargas, Esteban A.	UNAM
Keywords: Pharmacokinetics and drug delivery, Control of physiological and clinical variables, Healthcare management, disease control, critical care Abstract: Strategic initiatives in pharmaceutical companies and drug research have incorporated the pharmacokinetics (PK) and pharmacodynamics (PD) modeling, known as the PK/PD framework. Herein, we use an inverse optimal impulsive approach to devise PK/PD-based treatment policies for infectious diseases such as HIV and influenza. The optimal PK/PD-based HIV therapy maintains the viral load under detection levels for a thirty-year period when the treatment initiates 2 or 4 years post-infection. We also explore the implications of late HIV treatment initiation. On the other hand, the optimal PK/PD-based influenza treatment reduces ca. 30% the amount of drug compared to the treatment recommended by the Food and Drug Administration while reaching the same efficacy levels (98%). The PK/PD framework mastermind new schemes for tailoring treatments in infectious diseases.
Paper VI182-04.4
PDF · Video · Model-Based Strategies of Drug Dosing for Pharmacokinetic Systems (I)
Themans, Pauline	University of Namur
Musuamba Tshinanu, Flora	Federal Agency for Medicines and Health Products
Winkin, Joseph J.	University of Namur (UNamur)
Keywords: Pharmacokinetics and drug delivery, Kinetic modeling and control of biological systems, Decision support and control Abstract: The aim of this paper is to report analytical and individual-based methods for antibiotic dose selection, that are based on tools from system and control theory. A brief system analysis of standard population pharmacokinetic models proves that such models are nonnegative and stable. Then, an input-output analysis leads to an open-loop control law which yields a dosing for the ``average'' patient, based on the equilibrium trajectory of the system. This approach is then incorporated into a ``worst-case'' analysis based on the monotony of the state trajectories with respect to the clearance (model parameter). Finally, an heuristic method of an estimated state feedback is presented. Thanks to numerical simulations, these methods were successively illustrated on a model describing the pharmacokinetic of meropenem, an intravenous antibiotic for treatment of severe sepsis.
Paper VI182-04.5
PDF · Video · Practical Identification of a Glucose-Insulin Dynamics Model (I)
Scharbarg, Emeric	école Centrale De Nantes
Califano, Claudia	La Sapienza, Università Di Roma
Le Carpentier, Eric	Ecole Centrale De Nantes
Moog, Claude H.	CNRS
Keywords: Chronic care and/or diabetes, Identification and validation, Control of physiological and clinical variables Abstract: Glycemia regulation algorithms which are designed to be implemented in several artificial pancreas projects are often model based control algorithms. However, actual diabetes monitoring is based throughout the world on the so-called Flexible Insulin Therapy (FIT) which does not always cope with current mathematical models. In this paper, we initiate an identification methodology of those FIT parameters from some standard ambulatory clinical data. This issue has an interest per se, or for a further use in any closed-loop regulation system.
Paper VI182-04.6
PDF · Video · Dynamic Analysis and Control of the Hepatitis C Virus (I)
Castaño-Arcila, Mauricio	Centro De Investigación Y De Estudios Avanzados Del IPN, Unidad
Ramírez-Hurtado, Alberto Luis	Centro De Investigación Y De Estudios Avanzados Del IPN, Unidad
Carlos, Galvéz de León	Center for Research and Advanced Studies of the National Polytec
Rodriguez Gonzalez, Jesus	Unidad Monterrey
Keywords: Dynamics and control, Control of physiological and clinical variables, Physiological Model Abstract: The Hepatitis C Virus is the main cause of chronic liver diseases. The acute stage of infection is usually asymptomatic, and persistence in most of the infected individuals leads to chronic hepatitis, hepatic cirrhosis, and, finally, hepatocellular carcinoma. In order to avoid the chronic or advanced stages of this disease, when HCV is detected, cells activate the immune response mediated by interferon. Interferon is released by the infected hepatocytes and surrounding sentinel cells. Interferon activates the JAK-STAT signaling pathway and stimulates several ISG genes. Recently, it has been reported that only seven of them show a significant anti-HCV response. The aim of this study was to investigate, from a mathematical-modeling point of view, whether ISG over-expression leads the system to an irreversible clearance state. A mathematical model for the molecular machinery involved in cells infected with hepatitis C and the immune response was used to reproduce viral dynamics. The model considers seven ISG proteins. Our results suggest that the ISG proteins play an essential role in the hepatitis dynamics, and there is a possibility of produce the clearance state. Their robustness is evaluated.
Paper VI182-04.7
PDF · Video · Glycemia Regulation Considering Offset-Free MPC with Pulse Inputs and Parameter Variations (I)
Villa-Tamayo, María F.	Universidad Nacional De Colombia
Rivadeneira, Pablo S.	Universidad Nacional De Colombia, Sede Medellín
Keywords: Control of physiological and clinical variables, Artificial pancreas or organs, Dynamics and control Abstract: Different applications can be represented as systems controlled by pulse inputs, which are of short duration within the sampling period. Despite the vast development of control strategies for discrete systems and some others for impulsive ones, the generalization for pulse-controlled systems has not been widely studied. Here, an offset-free control approach for pulse systems is presented for the first time. This strategy aims to compensate for the offset problem caused by a plant-model mismatch or constant disturbances. It consists of an augmented model with an integrating state, an estimator to capture the mismatch, and a model predictive control (MPC) formulation that includes the estimated mismatch in the prediction model and the target calculation to achieve the objective. In addition, the strategy is tested for type 1 diabetes treatment, where physiological variations constantly change the insulin requirements of patients which, if not compensated, can lead hypoglycemia and hyperglycemia episodes. The developed method is evaluated in 10 adult virtual patients of the UVA/padova Simulator and it is compared with a zone MPC (ZMPC). Satisfactory results were obtained by achieving a time in normoglycemia range of 93% in a simulation scenario without meal announcement and 30% of parameter variations.
Paper VI182-04.8
PDF · Video · Sensitivity Analysis of the Electrocardiogram in Mouse Heart (I)
Ramírez-Hurtado, Alberto Luis	Centro De Investigación Y De Estudios Avanzados Del IPN, Unidad
Castaño-Arcila, Mauricio	Centro De Investigación Y De Estudios Avanzados Del IPN, Unidad
Humberto, Montesinos-Larrinaga	Center for Research and Advanced Studies of the National Polytec
Rodriguez Gonzalez, Jesus	Unidad Monterrey
Keywords: Control of physiological and clinical variables, Physiological Model, Bio-signals analysis and interpretation Abstract: The function of the heart is contracting and pump oxygenated blood to the body and deoxygenated blood to the lungs. To achieve this goal heart must beat regularly and continuously for entire life and respond to the changing requirements by the body. In this paper, we consider a mathematical model to produce ECG and analyze how the parametric variation can modify the electrocardiogram signal in the mouse heart. Numerical simulations were analyzed in detail, and compared with the control experiment, changes in frequency and ECG characteristics were evaluated. In agreement with physiological function, we find that the frequency of pacemaker cells can vary significantly, whereas electrical conducting cells maintain ECG characteristics in the face of parametric variations. P-wave, QRS complex, and T-wave can vary significantly in myocardial cells to parametric variations.
Paper VI182-04.9
PDF · Video · Adaptive Sliding Mode Control for Cholera Epidemic Model
Saragih, Roberd	Bandung Institute of Technology
Keywords: Healthcare management, disease control, critical care, Biomedical and medical image processing and systems, Artificial pancreas or organs Abstract: Cholera is an acute diarrhoeal infection caused by bacteria Vibrio cholerae. The SIQRB (Susceptible-Infected-Quarantined-Recovered-Bacteria) epidemic model with a control function is studied to analyze the dynamics of cholera. The control function represents the fraction of infected individuals that are submitted to treatment in quarantine until complete recovery. One of the drawbacks of mathematical modeling is the presence of parametric uncertainties. Designing a control strategy used in accommodating these uncertainty factors drives the development of robust control. In this case, the sliding mode control is applied to handle parametric uncertainties. The sliding mode control objective is reducing the number of infected individuals to zero through the desired tracking scheme of a reference function. The Lyapunov stability theorem and Barbalat’s lemma are used to examine the success of the tracking scheme. Lack of apriori knowledge related to the boundedness of the parametric uncertainties is settled using an adaptive method by updating the switching gain of sliding mode control so that the strategy is called the adaptive sliding mode control. Chattering problem that often appears in the application of sliding mode control can be reduced. Numerical simulations show that the adaptive sliding mode control satisfies the controller objectives and able to handle parametric uncertainties.
Paper VI182-04.10
PDF · Video · Maintaining Hard Infection Caps in Epidemics Via the Theory of Barriers
Esterhuizen, Willem	Technische Universität Chemnitz
Aschenbruck, Tim	Technische Universität Chemnitz
Levine, Jean	Ecole Des Mines, CAS
Streif, Stefan	Technische Universität Chemnitz
Keywords: Healthcare management, disease control, critical care, Dynamics and control Abstract: Research in epidemiology often focusses on designing interventions that result in the number of infected individuals asymptotically approaching zero, without considering that this number may peak at high values during transients. Recent research has shown that a set-based approach could be used to address the problem, and we build on this idea by applying the theory of barriers to construct admissible and invariant sets for an epidemic model. We describe how these sets may be used to choose intervention strategies that maintain infection caps during epidemics. We also derive algebraic conditions of the model parameters that classify a system as being either comfortable, comfortable-viable, viable, or desperate.

VI182-05
Physiological Control Systems in Medicine	Open Invited Session
Chair: Chase, J. Geoffrey	University of Canterbury
Co-Chair: Medvedev, Alexander	Uppsala University
Organizer: Desaive, Thomas	University of Liege
Organizer: Chiew, Yeong Shiong	Monash University
Organizer: Suhaimi, Fatanah	Universiti Sains Malaysia
Organizer: Knopp, Jennifer L.	University of Canterbury
Organizer: Kovacs, Levente	Obuda University
Organizer: Docherty, Paul D	University of Canterbury
Organizer: Cinar, Ali	Illinois Inst. of Tech
Organizer: Chase, J. Geoffrey	University of Canterbury
Organizer: Dana, Copot	Ghent University
Organizer: Breton, Marc D	University of Virginia
Organizer: Medvedev, Alexander	Uppsala University
Paper VI182-05.1
PDF · Video · Reaction Kinetic Interpretation of Mechanisms Related to Vascular Tumor Growth with Respect to Structural Identifiability (I)
Csercsik, Dávid	Pázmány Péter Catholic University
Kovacs, Levente	Obuda University
Keywords: Physiological Model, Biomedical system modeling, simulation and visualization, Identification and validation Abstract: Anti-angiogenic drugs are relatively new tools in cancer therapy with very low side effects compared to earlier approaches. These drugs inhibit the formation of new blood vessels in the tumor, thus cutting its cells from nutrient supply. As proliferating tumor cells have very intensive metabolism, the lack of nutrients provides a significant barrier for the growth rate of the tumor. In the recent years it has been shown that the dosage protocol of these drugs may be critical in terms of their efficiency. In addition, several papers are considering model-baseed methods for therapy optimization and potential feedback control of tumor growth, based on the application of anti-angiogenic drugs. In this paper we use the framework of reaction kinetic systems to formulate simple models for important mechanisms present in vascular tumor growth, and analyze their identifiability properties assuming various plausible measurable variables. The conclusions of the article may contribute to experiment design regarding identification of such and similar models.
Paper VI182-05.2
PDF · Video · Global Sensitivity Analysis on the Bergman Minimal Model (I)
Nandi, Souransu	University at Buffalo
Singh, Tarunraj	State Univ. of New York at Buffalo
Keywords: Artificial pancreas or organs, Physiological Model, Model formulation, experiment design Abstract: In this paper, a novel Global Sensitivity Analysis method is developed and is illustrated on the famous Bergman minimal model for Type 1 diabetes. Four parameters are assumed to be uncertain (random variables) in the model to mimic patient variability. An efficient algorithm is presented to evaluate sensitivity metrics by which the uncertain parameters can be ranked. Results reveal that for a single meal scenario, insulin sensitivity is one of the most important factors after the consumption of meal that influences the blood glucose concentration in people with Type 1 diabetes.
Paper VI182-05.3
PDF · Video · Virtual Mechanical Ventilation Protocol - a Model-Based Method to Determine MV Settings (I)
Arunachalam, Ganesa Ramachandran	Monash University Malaysia
Chiew, Yeong Shiong	Monash University
Tan, Chee Pin	Monash University
Mohd Ralib, Azrina	International Islamic University Malaysia Medical Center, Pahang
Mat Nor, Basri	International Islamic University Malaysia Medical Center, Pahang
Keywords: Decision support and control, Intensive and chronic care or treatment Abstract: Intensive care mechanical ventilation (MV) therapy is a lifesaving intervention for a patient with respiratory failure. MV supports patients breathing by maintaining positive airway pressure and airflow to the lung. However, there is currently little clinical consensus protocol to set the best MV setting. Hence, it is important to provide an objective and patient-specific MV settings to support patient recovery. This study presents a model-based method to find optimal MV settings using clinical bedside data. A mathematical model of the respiratory system is first used to estimate patient-specific respiratory mechanics. These mechanics are then incorporated with significant clinical findings from the literature to simulate a series of MV settings. The simulation of MV settings is performed using the single compartment lung model using the MATLAB software. From this series of simulated MV settings, optimal MV settings can be determined objectively by the clinician. This model-based method potentially provides decision support for the clinician to set optimal MV settings.
Paper VI182-05.4
PDF · Video · First Experiments of Anesthesia Control with Optimized PID Tuning (I)
Schiavo, Michele	University of Brescia
Padula, Fabrizio	Curtin University
Latronico, Nicola	University of Brescia
Merigo, Luca	University of Brescia
Paltenghi, Massimiliano	Spedali Civili Di Brescia
Visioli, Antonio	University of Brescia
Keywords: Clinical validation, Control of physiological and clinical variables Abstract: In this paper we present and discuss the first experimental results obtained with a recently devised PID control scheme for the propofol and remifentanil coadministration in general anesthesia. In particular, the depth of hypnosis is controlled by considering only the bispectral index scale as the process variable and the extra degree of freedom in the controller is handled by selecting an appropriate ratio between the infusion rates of the two drugs. The parameters of the PID controllers are selected by using a tuning rule obtained through an optimization procedure that exploits the PK/PD model of a set of patients. A gain scheduling approach is used to switch between two sets of tuning parameters, one for the induction phase and the other for the maintenance phase. The experimental results confirm the effectiveness of the overall design approach.
Paper VI182-05.5
PDF · Video · Mortality Prediction for ICU Patients with Individualized Single Classification Method (I)
Ma, Xin	Beijing University of Chemical Technology
Guo, Xiaosu	Beijing University of Chemical Technology
Wang, Youqing	Beijing University of Chemical Technology (BUCT)
Keywords: Bio-signals analysis and interpretation, Decision support and control, Healthcare management, disease control, critical care Abstract: In intensive care units (ICUs), mortality prediction is crucial to help doctors select appropriate diagnosis and treatment methods and reasonably allocate medical resources. However, the scoring system currently used by hospitals may not be suitable for every patient. Therefore, personalized diagnosis is trending because it responds to a wide range of needs. This study proposes a new combination of dynamic time warping (DTW) and one-class extreme learning machine (ELM) to improve the mortality prediction accuracy, termed as one-class DTW-ELM, where DTW is used to find similar cases for new patients, and while one-class ELM is adopted for fast and accurate model building. The testing results on the real physiological data from PhysioNet demonstrate that the area under curve (AUC) index of one-class DTW-ELM model is 0.9739, with the Lift of 8.1081 and the G-mean of 0.8137. The accuracy rate is 0.9583, with specificity and sensitivity of 1 and 0.6622, respectively. As mentioned, one-class DTW-ELM can accurately predict the future physiological state of a patient by using early physiological parameters.
Paper VI182-05.6
PDF · Video · Clinical Application of a Model-Based Cardiac Stroke Volume Estimation Method (I)
Smith, Rachel Genevieve Rose	University of Canterbury
Balmer, Joel	University of Canterbury
Pretty, Christopher	University of Canterbury
Shaw, Geoffrey M	Christchurch Hospital, Canterbury District Health Board
Chase, J. Geoffrey	University of Canterbury
Keywords: Clinical validation, Control of physiological and clinical variables, Intensive and chronic care or treatment Abstract: A system is needed for monitoring stroke volume (SV) and cardiac output (CO) in unstable patients which is non-additionally invasive, reproducible and reliable in a variety of physiological states. This study evaluates SV estimation accuracy of a non-additionally invasive pulse contour analysis method implemented using a 3-element Windkessel model. The model lumps the properties of the arterial system into 3 parameters: characteristic impedance of the proximal aorta (Z), and resistance (R) and compliance (C) of the systemic arteries. Parameter products ZC and RC are dynamically identified from measured femoral arterial pressure waveforms, and Z is a static parameter obtained by calibration. The accuracy of the model is evaluated for a cohort of 9 liver transplant patients, using thermodilution as a reference method. Data were obtained from Vital Data Bank (VitalDB). The study thus provides independent assessment of a pulse contour analysis, proven in animal studies, in an uncontrolled clinical environment. The model tracked trends in SV well over the course of the surgery. However, the 95% range for percentage error was -88% to +53%, outside acceptable limits of +/-45%. Main areas contributing to error for the model include the changing extent of reflected waves in the arterial system, dynamic response characteristics of fluid-filled pressure catheters, and the assumption of fixed Z parameter. Further investigation is needed to consider the contribution of these factors to SV estimation error by the model.
Paper VI182-05.7
PDF · Video · Analysis of Insulin Sensitivity Stochastic Models between STAR Original and Malaysian Cohorts (I)
Lee, Jay Wing Wai	Monash University Malaysia
Chiew, Yeong Shiong	Monash University
Tan, Chee Pin	Monash University
Abdul Razak, Nur Athirah	Universiti Tenaga Nasional
Razak, Normy	Univ of Canterbury
Keywords: Decision support and control, Control of physiological and clinical variables Abstract: Maintaining healthy blood glucose (BG) levels is vital in ensuring the health of intensive care unit patients. In present work, there exists model-based glycemic control protocols that capture insulin-glucose dynamics that can provide patient-specific treatments. The Stochastic Targeted Glycemic Control (STAR) protocol is a model-based glycemic control protocol that utilizes stochastic modelling together with the Intensive Control Insulin Glycemic Control (ICING) model. STAR has shown its effectiveness in Christchurch and Hungary. However, it is currently less effective in Malaysia. A study is conducted to compare the stochastic model between the STAR original and Malaysian cohort to identify if the difference in effectiveness is due to a difference in stochastic insulin sensitivity (SI) models between cohorts. Results from this study show that there could be a difference of up to 49.4% in predictive ability of the stochastic models from the two cohorts, suggesting that it could play a role in being the cause for its lack in effectiveness. With further patient data collection, this hypothesis could be proven or otherwise eliminated from the possible causes for the lack of effectiveness of the STAR protocol in Malaysia.
Paper VI182-05.8
PDF · Video · Integrating MPC with Learning-Based and Adaptive Methods to Enhance Safety, Performance and Reliability in Automated Insulin Delivery (I)
Hajizadeh, Iman	Illinois Institute of Technology
Askari, Mohammad Reza	Illinois Institute of Technology
Kumar, Ranjeet	University of Wisconsin-Madison
Zavala, Victor M.	University of Wisconsin-Madison
Cinar, Ali	Illinois Inst. of Tech
Keywords: Decision support and control, Artificial pancreas or organs, Chronic care and/or diabetes Abstract: In this work, an adaptive-learning model predictive control (AL-MPC) framework that integrates disturbance forecasting, uncertainty quantification, learning, and recursive subspace identification is developed. The proposed technique can be used for continuous systems affected by repetitive disturbances with unknown periods. The AL-MPC integrates online learning from historical data to anticipate impending disturbances and proactively counteract their effects to an adaptive MPC. This is done by using machine learning to quantify the significant disturbances from historical data and forecast their future evolution time series. Behavior patterns of the system can be identified from historical data, and the set-point, objective function weights, and constraints of the controller can be modified in advance for the anticipated time periods of the disturbance effects. AL-MPC is used to regulate glucose concentration (GC) in people with diabetes by automated insulin delivery. Simulation results indicate that the AL-MPC can regulate the BGC 75.4% of the simulation time in the target range (70-180) mg/dL without causing any hypoglycemia and hyperglycemia events.
Paper VI182-05.9
PDF · Video · Estimating (unidentifiable) Enhanced EGP in Glycaemic Control Modelling: Dancing with Minions of the Dark Lord (I)
Ormsbee, Jennifer J.	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Keywords: Physiological Model, Decision support and control, Kinetic modeling and control of biological systems Abstract: Critically ill patients frequently experience stress-induced hyperglycaemia. Glycaemic control (GC) with insulin therapy can improve patient outcomes, but effective GC is not currently well achieved in most critical care units. STAR is a model-based decision support system, utilizing the ICING model, for glycaemic control in intensive care. Understanding model-based parameters and assumptions within their clinical context is important. The ICING model uses a population constant for endogenous glucose production (EGP), but EGP can vary considerably in patients during extreme stress and trauma. This study uses data from 145 patients on the SPRINT protocol to explore the assumptions around the EGP parameter and estimate minimum EGP values when the model is constrained to a minimum insulin sensitivity (SI) value. The model is frequently constrained when there is no nutritional input, highlighting the importance of the EGP parameter for glucose flux in the model equation. Minimum EGP values were calculated when SI was less than or equal to 1e-5 L/mU/min and ranged from 1.16 mmol/min to 2.72 mmol/min, where the median value is a 12% increase from the population value of 1.16 mmol/min. This analysis provides a relative indication of EGP changes in patients and supports the use of the EGP population value as only 2.3% of hours require EGP modification.
Paper VI182-05.10
PDF · Video · Application of Neural Networks for Heart Rate Monitoring (I)
Askari, Mohammad Reza	Illinois Institute of Technology
Hajizadeh, Iman	Illinois Institute of Technology
Sevil, Mert	Illinois Institute of Technology
Rashid, Mudassir	Illinois Institute of Technology
Hobbs, Nicole	Illinois Institute of Technology
Brandt, Rachel	Illinois Institute of Technology
Sun, Xiaoyu	Illinois Institute of Technology
Cinar, Ali	Illinois Inst. of Tech
Keywords: Developments in measurement, signal processing, Bio-signals analysis and interpretation, Monitoring Abstract: This paper addresses the problem of heart rate (HR) monitoring from photoplethysmography(PPG) sensors, where artifacts caused by body movements drastically affect the quality of the measurement signal. The PPG signal is windowed into consecutive segments, and for each time-windows, a Butterworth bandpass filter is utilized to attenuate high-frequency noises. Then, the PPG signal is processed by using the singular spectrum analysis technique to obtain a smooth PPG signal. In order to remove artifacts caused by the physical activity of the subject, the 3-dimensional accelerometer signal is used as an auxiliary signal to detect the presence of motion artifact (MA). A new spectral subtraction approach is proposed for MA rejection. For the purpose of HR estimation from the PPG signal, a feature extraction method is performed, and neural network binary classifier is used to detect the most probable frequencies corresponding to the actual HR. HR estimations are passed through a Kalman filter to result in smooth and accurate HR estimations.
Paper VI182-05.11
PDF · Video · Non-Invasive Measurement of Tidal Breathing Lung Mechanics Using Expiratory Occlusion (I)
Howe, Sarah	University of Canterbury
Maerz, Melanie	Furtwangen University
Krueger-Ziolek, Sabine	Furtwangen University
Laufer, Bernhard	Institute of Technical Medicine (ITeM), HFU Furtwangen Universit
Pretty, Christopher	University of Canterbury
Shaw, Geoffrey M	Christchurch Hospital, Canterbury District Health Board
Desaive, Thomas	University of Liege
Moeller, Knut	Furtwangen University
Chase, J. Geoffrey	University of Canterbury
Keywords: Quantification of physiological parameters for diagnosis and treatment assessment, Identification and validation, Physiological Model Abstract: A great amount of research looks at whether information about lung mechanics can be obtained using spirometry, as these mechanics give clinically useful information about lung condition and disease progression. This study uses a time-varying elastance, single compartment lung model to calculate lung mechanics of 15 tidally breathing healthy subjects. A plethysmograph with a built-in shutter was used to induce an exponentially decaying airflow. Lung elastance and respiratory system resistance were separated from the decay rate of flow caused by the shutter. Occlusion resistance was calculated at shutter closure. To simulate upper airway obstruction, progressively larger resistances were added to the plethysmograph mouthpiece. Decay rates measured ranged from 5-42, with large intra-subject variation associated with muscular breathing effort. Measured lung elastance ranged from 3.9-21.2 cmH2O/L and often remained constant as resistance was increased. Resistance calculated from the decay rate was very small, ranging from 0.15-1.95 cmH2Os/L. The low resistance is due to the airflow measured originating from low resistance areas in the centre of airways. Occlusion resistance measurements were as expected for healthy subjects, and followed the expected resistance trend as resistance was increased.
Paper VI182-05.12
PDF · Video · Physiological Sex Differences in Mechanically Ventilated Premature Neonates: A Pilot Study (I)
Kim, Kyeong Tae	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Dixon, Bronwyn	Neonatal Intensive Care Unit, Christchurch Women's Hospital
Chase, J. Geoffrey	University of Canterbury
Keywords: Physiological Model, Clinical validation, Healthcare management, disease control, critical care Abstract: Mechanical ventilation (MV) is commonly used in neonatal intensive care units (NICUs) to support breathing. Anecdotally, male infants are harder to ventilate than females. In this study, the pulmonary mechanics of 10 invasively mechanically ventilated neonates from Christchurch Women’s Hospital, recorded during an observational trial with no protocolised change to care, are compared. We hypothesise males have higher specific lung elastance (elastance corrected for weight) than females, due to stiffer and less developed lungs. The specific elastance and resistance is identified for every breath using a single compartment model with a pressure loss term added to compensate for endotracheal tube resistance. Variability is determined by relative percent breath-to-breath variability (%ΔE) in specific elastance. Male infants had higher specific elastance compared to females (P≤0.01) with median [interquartile range] of 1.91[1.33‐2.48] cmH2O.kg/ml and 1.31[0.86‐2.02] cmH2O.kg/mL respectively. Males also had lower %ΔE median IQR of -0.03 [-7.56 - 8.01] and females had 0.59[-12.56 - 12.86]. The results validates our hypothesis that boys have higher elastance than girls. These results also suggests males and females should be ventilated differently.
Paper VI182-05.13
PDF · Video · Robust Hemodynamic Control under General Anesthesia Conditions (I)
Dana, Copot	Ghent University
Muresan, Cristina Ioana	Technical University of Cluj Napoca
Birs, Isabela Roxana	Technical University of Cluj-Napoca
Kovacs, Levente	Obuda University
Keywords: Biomedical system modeling, simulation and visualization, Control of physiological and clinical variables Abstract: All drug regulatory paradigms are dependent on the hemodynamic system as it serves to distribute and clear the drug in/from the body. In this work, stabilization of hemodynamic variables within the context of maintaining general anesthesia conditions is presented. Several methods for robust control are employed, all based on the emerging fractional order control algorithm with inherent robustness to gain and phase margin variations. These are important due to the inter- and intra- patient variability at hand. The results indicate the great suitability of fractional order control as a substantially robust algorithm which can be used in combination with regulatory schemes for better closed loop performance. The challenges of the hemodynamic system under analysis here is the high coupling (multivariable system) with delay-dominant dynamics. Additionally, disturbance from the anesthesiaregulatory system and realistic surgical stimulation profiles are incorporated to complete the analysis. The results support the claims.
Paper VI182-05.14
PDF · Video · Comparison between Single Compartment Model and Recruitment Basis Function Model on NICU Patients (I)
Kim, Kyeong Tae	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Dixon, Bronwyn	Neonatal Intensive Care Unit, Christchurch Women's Hospital
Chase, J. Geoffrey	University of Canterbury
Keywords: Physiological Model, Healthcare management, disease control, critical care Abstract: Respiratory distress syndrome (RDS) is commonly diagnosed in preterm infants in neonatal intensive care units (NICUs) due to prematurity at birth resulting in surfactant deficiency. Mechanical ventilation (MV) is used to support breathing of infants with RDS. In this study, respiratory mechanics of 10 invasively ventilated infants from Christchurch Women’s Hospital under standard care are compared with two lung mechanics models validated in adult MV patients. A single compartment model is compared with a parabolic basis function model with dynamic elastance (Edrs) used to capture patient-specific effort. This latter model applies parabolic and linear shapes to identify lung recruitment and distension. The model was fit to 25,657 breaths. The median [interquartile range (IQR)] of elastance from single compartment model (Elung) was 1.51[0.72 - 2.76] cmH2O/ml, and elastance from recruitment basis function (E1) was 3.42[1.88 - 5.97] cmH2O/ml. Relative breath-to-breath variability (%DeltaE) was also compared, with median IQR %DeltaElung of 0.22 [-9.73 - 12.06] and %DeltaE1 of -0.48[-9.28 - 10.34]. Elung is less sensitive than E1 to differences across infants where E1 was also less variable breath-to-breath. The parabolic model thus captured patient condition and the use of Edrs captured patient effort.
Paper VI182-05.15
PDF · Video · Dead-Zone Observer-Based Control for Anesthesia Subject to Noisy BIS Measurement (I)
Tarbouriech, Sophie	LAAS-CNRS
Queinnec, Isabelle	LAAS-CNRS
Garcia, Germain	University of Toulouse, LAAS-CNRS, Toulouse
Mazerolles, Michel	CHU Rangueil Toulouse
Keywords: Dynamics and control, Pharmacokinetics and drug delivery, Control of physiological and clinical variables Abstract: This paper deals with the maintenance phase control of general anesthesia during surgery, involving saturated input and noisy output. The objective is to maintain the patient to some given depth of hypnosis, measured by the BIS. The control law is an observer-based control, where a dead-zone observer is built in order to mitigate the presence of the output noise. The global exponential stability of the complete closed-loop system in the noise-free case is guaranteed thanks to a linear matrix inequality condition and an input-to-state property in presence of the noise is also proven. A three-steps optimization algorithm is proposed to determine the parameters of the control law and then evaluated on a patient case.
Paper VI182-05.16
PDF · Video · Modelling and Indentification for the Action of Propofol and Remifentanil on the BIS Level (I)
Silva, Jorge	Faculdade De Engenharia Da Universidade Do Porto and SYSTEC
Noé, Alberto Sancho	Universidade Zambeze
Mendonça, Teresa	Faculdade De Ciências Da Universidade Do Porto
Rocha, Paula	Univ of Porto
Keywords: Pharmacokinetics and drug delivery, Control of physiological and clinical variables, Identification and validation Abstract: In this paper a model for the action of propofol and remifentanil on the BIS level is proposed together with a novel identification method for its parameters. This identification method, which is compatible the usual clinical procedures, is validadted by means of simulations.
Paper VI182-05.17
PDF · Video · Insulin Resistance in ICU Patients: Women Have Stronger Metabolic Response (I)
Uyttendaele, Vincent	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Gottlieb, Rebecca	Medtronic Diabetes
Shaw, Geoffrey M	Christchurch Hospital, Canterbury District Health Board
Desaive, Thomas	University of Liege
Chase, J. Geoffrey	University of Canterbury
Keywords: Intensive and chronic care or treatment, Identification and validation, Quantification of physiological parameters for diagnosis and treatment assessment Abstract: Glycaemic control (GC) has been associated with improved outcomes in critically ill patients. However, inter- and intra- patient metabolic variability significantly increase the risk of hypoglycaemia when using insulin to control glycaemia. Model-based protocols often identify key physiological parameters from patient data, and demonstrated safe and effective GC. Based on recent studies showing gender difference in insulin secretion, this study uses retrospective data to identify whether there exists a difference in sexes in metabolic stress response, and thus in how personalised GC is given. Retrospective data from 145 ICU patients under GC who started GC in the first 12 hours of ICU stay are used. Insulin sensitivity (SI) is identified hourly, as well as the hour-to-hour percentage change in SI (%DeltaSI). Differences between males and females SI and %DeltaSI over 6-h blocks are compared using hypothesis and equivalence testing. A difference in SI levels would suggest a difference in metabolic stress response to insult, while a difference in %DeltaSI levels would suggest a resulting difference in the difficulty to control. Results show females are significantly more insulin resistant than males and not equivalent, suggesting stronger stress response to insult induced stress. Metabolic variability is equivalent in both groups, advocating GC safety and efficacy should be similar between males and females, despite potential higher insulin rates required for females. This study is the first to suggest potential gender differences in the metabolic stress response.
Paper VI182-05.18
PDF · Video · Pediatric Glucose Regulation without Pre-Meal Insulin Boluses: An Approach Based on Switched Control and Time-Varying IOB Constraints (I)
Fushimi, Emilia	Grupo De Control Aplicado (GCA), Instituto LEICI, Facultad De In
Serafini, Maria Cecilia	Grupo De Control Aplicado (GCA), Instituto LEICI, Facultad De In
Sánchez-Peña, Ricardo	Instituto Tecnologico De Buenos Aires (ITBA)
De Battista, Hernán	Universidad Nacional De La Plata - CONICET
Garelli, Fabricio	University of La Plata
Keywords: Artificial pancreas or organs, Decision support and control, Control of physiological and clinical variables Abstract: Artificial pancreas systems have shown to improve glucose regulation in type 1 diabetes patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, a new algorithm based on switched control and time-varying insulin-on-board constraints is presented (ARG_AE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses, and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population. Results show that the ARG_AE presents improved performance compared to the ARG algorithm even in presence of misclassified meals. Thus, future in vivo testing will involve the AE configuration.
Paper VI182-05.19
PDF · Video · Structural Identifiability of a Third-Order Continuous System under Impulsive Feedback (I)
Runvik, Håkan	Uppsala University
Medvedev, Alexander	Uppsala University
Keywords: Identification and validation, Pharmacokinetics and drug delivery Abstract: Structural identifiablity of a third-order continuous time-invariant linear plant under an intrinsic pulse-modulated feedback is analyzed. The model represents a biomedical system, where the input signal to the continuous plant is immeasurable and the feedback modulation functions have to be identified along with the continuous dynamics. It is shown that two eigenvalues of the continuous plant system matrix (i.e. time constants), along with the times and weights of impulses occurring during a finite time interval, are identifiable from the measurement of one continuous system state over the interval in question. When an infinite time horizon is considered, all parameters are identifiable, up to gain scaling and linear block permutations.
Paper VI182-05.20
PDF · Video · Virtual Patient Modeling and Prediction Validation for Pressure Controlled Mechanical Ventilation (I)
Morton, Sophie E.	University of Canterbury
Knopp, Jennifer L.	University of Canterbury
Tawhai, Merryn	University of Auckland
Docherty, Paul D	University of Canterbury
Moeller, Knut	Furtwangen University
Heines, Serge J.H	Department of Intensive Care, Maastricht University Medical Cent
Bergmans, Dennis C.J.J.	Department of Intensive Care, Maastricht University Medical Cent
Chase, J. Geoffrey	University of Canterbury
Keywords: Quantification of physiological parameters for diagnosis and treatment assessment, Clinical validation, Identification and validation Abstract: : Respiratory failure patients in the intensive care unit (ICU) require mechanical ventilation (MV) to support breathing and tissue oxygenation. Optimizing MV care is problematic. Significant patient variability confounds optimal MV settings and increase the risk of lung damage due to excessive pressure or volume delivery, which in turn can increase length of stay and cost, as well as mortality. Model-based care using in silico virtual patients can significantly affect ICU care, personalizing delivery and optimising care. This research presents a virtual patient model for pressure-controlled MV, an increasingly common mode of MV delivery, based on prior work applied to volume-controlled MV. This change necessitates predictions of flow and thus volume, instead of pressure, as the unspecified variable. A model is developed and validated using clinical data from five patients (N=5) during a series of PEEP (positive end expiratory pressure) changes in a recruitment maneuver (RM), creating a total of 242 predictions. Peak inspiratory volume, a measure of risk of lung damage, errors were 56 [26-95]mL (10.6 [5.3-19.1]%) for predictions of PEEP changes from 2-16cmH2O. Model fitting errors were all lower than 5%. Accurate predictions validate the model, and its potential to both personalise and optimise care.
Paper VI182-05.21
PDF · Video · Kalman Filter and Sliding Mode Observer in Artificial Pancreas: An In-Silico Comparison (I)
Sala-Mira, Iván	Universitat Politècnica De València
Siket, Máté	Óbuda University
György, Eigner	Obuda University
Bondia Company, Jorge	Universidad Politécnica De Valencia
Kovacs, Levente	Obuda University
Keywords: Artificial pancreas or organs, Control of physiological and clinical variables, Parameter and state estimation Abstract: Observers are essential in artificial pancreas systems, either for states or disturbance estimation. Kalman filters based on the Hovorka model are largely applied for this purpose. However, simpler approaches can be used too. We intend to analyze whether the observer structure, the applied model and the individualization of the model parameters affect the estimation accuracy. We perform an in-silico comparison between two Kalman filters and a sliding mode observer, as observer structures previously proposed in the field. All observers are implemented in population and individualized versions of the Hovorka and the simpler Identifiable Virtual Patient models. To tune the Kalman filters, a genetic algorithm based framework was developed. The results indicate that the choice of the model has a larger effect on the outcome than the choice of the observer structure. Finally, the observer based on the Hovorka model does not always perform the most accurate estimation given the higher difficulty during the identification of its parameters.
Paper VI182-05.22
PDF · Video · Virtual Patients: An Enabling Technology for Multivariable Control of Biomedical Systems (I)
Rashid, Mudassir	Illinois Institute of Technology
Samadi, Sediqeh	Illiinios Institute of Technology
Sevil, Mert	Illinois Institute of Technology
Hobbs, Nicole	Illinois Institute of Technology
Park, Minsun	University of Illinois at Chicago
Quinn, Lauretta	University of Illinois at Chicago
Cinar, Ali	Illinois Inst. of Tech
Keywords: Biomedical system modeling, simulation and visualization, Artificial pancreas or organs, Parameter and state estimation Abstract: This paper presents the development of virtual patients to enable the simulation evaluation and assessment of multivariable control algorithms for biomedical systems. The virtual patients are generated by fitting the parameters of the models to clinical experimental data, followed by the estimation of the multivariate distribution of the actual patient parameters. The estimated multivariate distribution is then incorporated with constraints to ensure the sampling of synthetic virtual patients conforms to the actual patient parameter bounds. The sampled synthetic virtual patients are analyzed through multivariate statistical techniques and data clustering algorithms to prune out virtual subjects with similar characteristics or unrealistic dynamics, yielding a virtual patient population that is diverse and with individually distinct characteristics. The generated virtual patient population is used to evaluate multivariable nonlinear and adaptive control algorithms for insulin dosing in people with Type 1 diabetes.
Paper VI182-05.23
PDF · Video · Robust Positive Control of a Nonlinear Tumor Growth Model (I)
Drexler, Dániel András	Óbuda University
Kovacs, Levente	Obuda University
Keywords: Control of physiological and clinical variables, Kinetic modeling and control of biological systems, Healthcare management, disease control, critical care Abstract: Control of physiological systems, like tumor growth dynamics, can contribute to modern medicine by designing optimized therapies or automating treatments. Typical challenges in physiological control are the positivity of the input and the interpatient variability of model parameters. We use positive dynamics extension to ensure the positivity of the input, and design a robust controller for a nominal model acquired after exact linearization and stabilizing feedback. During the controller design, we minimize the effect of the model perturbation in the worst-case sense and minimize the energy of the performance criteria. The results show enhanced performance compared to our similar robust control approach where only the performance was minimized in the worst-case sense with similar characteristics in the input signals.
Paper VI182-05.24
PDF · Video · Experimental Data-Driven Tumor Modeling for Chemotherapy (I)
Drexler, Dániel András	Óbuda University
Ferenci, Tamas	Obuda University
Füredi, András	Institute of Enzymology, Research Centre for Natural Sciences
Szakács, Gergely	Institute of Enzymology, Research Centre for Natural Sciences
Kovacs, Levente	Obuda University
Keywords: Model formulation, experiment design, Identification and validation, Pharmacokinetics and drug delivery Abstract: Mathematical models of tumor growth in response to chemotherapy are crucial for therapy optimization and outcome. We create a relatively simple tumor growth model describing the antitumor effect of pegylated liposomal doxorubicin (PLD) validated with real experimental data obtained in a genetically engineered mouse model of breast cancer. We use formal reaction kinetics to describe the pathophysiological phenomena using differential equations, and carry out parametric identification based on experiments using a mixed-effect model with stochastic approximation expectation maximization. The model gives a sufficient fit to describe tumor growth and pharmacokinetic data, and a satisfactory fit for the complex case, i.e., tumor response to chemotherapy. The results showed that identification of certain subsystems is easy using experimental data even if it is not specifically designed for identification. However, the identification of the complex pathophysiological phenomena may require experiments specially designed for identification purposes.
Paper VI182-05.25
PDF · Video · Effect of Small Airways and Viscoelasticity on Lung Mechanics from Expiratory Occlusion (I)
Howe, Sarah	University of Canterbury
Maerz, Melanie	Furtwangen University
Krueger-Ziolek, Sabine	Furtwangen University
Laufer, Bernhard	Institute of Technical Medicine (ITeM), HFU Furtwangen Universit
Pretty, Christopher	University of Canterbury
Shaw, Geoffrey M	Christchurch Hospital, Canterbury District Health Board
Desaive, Thomas	University of Liege
Moeller, Knut	Furtwangen University
Chase, J. Geoffrey	University of Canterbury
Keywords: Bio-signals analysis and interpretation, Identification and validation, Physiological Model Abstract: Monitoring the decay rate of airflow in spirometry may be clinically useful. The decay rate is expected to represent a combination of lung elastance and airway resistance. However, the decay rate calculated using the single compartment lung model is not expected to account for slower lung mechanics, such as small airways resistance and tissue viscoelasticity. This study assesses whether the decay rate is affected by these lung mechanics. An exponentially decaying flow was created using a shutter to occlude airflow during passive expiration for 15 healthy subjects. To approximate small airways resistance and viscoelasticity, the gradient of pressure increase (relaxation gradient) during shutter closure was measured. The occlusion resistance, elastance, and decay rate were also calculated for these breaths. None of these mechanics were found to be correlated with the relaxation gradient. The relaxation gradient was also found to be independent of driving pressure. Conversely, the relaxation gradient was found to depend on lung volume. The results of this study suggest using lung mechanics and decay rate to monitor changes in lung condition over time may miss information about changes in the small airways and viscoelastic lung tissue. Thus, it is useful for monitoring large airways disease, but may be ineffective for small airways disease such as ARDS.
Paper VI182-05.26
PDF · Video · Minimally Invasive Model Based Stressed Blood Volume As an Index of Fluid Responsiveness (I)
Murphy, Liam	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Davidson, Shaun M	University of Canterbury
Smith, Rachel Genevieve Rose	University of Canterbury
Desaive, Thomas	University of Liege
Keywords: Monitoring, Healthcare management, disease control, critical care, Physiological Model Abstract: Model based total stressed blood volume (SBV_T) has been shown to be a potential index of fluid responsiveness. However, current models rely on the availability of highly invasive and uncommon measurements to derive model parameters. In this work, a simple method for obtaining the necessary model parameters from currently available intensive care unit (ICU) measurements is established. The model is tested on three (3) porcine subjects administered a typical 500ml saline bolus fluid therapy and then subjected to endotoxin induced sepsis to provide a range of hemodynamic states. When compared to stressed blood volume derived from a model utilising direct measurements mean percentage error was 10.3% over a total of 716 beats. This work also examined the hypothesis a stressed blood volume below a clinically specified threshold of 145ml would yield a positive response. Increases of 37.9%, 44.7% and 22.6%, with baseline levels of 180, 120 and 75ml, were seen for pigs 1, 2 and 3, respectively. This research demonstrates the clinical validity of this model based SBV_T measure, bringing it closer to clinical feasibility.
Paper VI182-05.27
PDF · Video · Rayleigh Damping Modelling to Assess Viscous Behaviour in Actuated Breast Tissue (I)
Fitzjohn, Jessica Louise	University of Canterbury
Zhou, Cong	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Ormsby, Zane	Tiro Medical
Haggers, Marcus	Tiro Medical
Keywords: Biomedical system modeling, simulation and visualization, Bio-signals analysis and interpretation, Identification and validation Abstract: Breast cancer is a significant health problem worldwide. Emerging non-invasive methods assess tumor presence by its impact on breast tissue mechanics. This paper outlines a method to identify equivalent viscous damping in breast tissue and fit a model based on the Rayleigh damping (RD) model. Surface motion information of actuated breast tissue was captured using the Digital Image Elasto Tomography (DIET) system. The viscous damping was calculated for over 14,000 reference points using an ellipse fitted to the force-displacement hysteresis loop response data to calculate work done. A damping model based on RD is suggested and fit to median filtered data of viscous damping constant plotted against the major ellipse axis. This successfully described the trend for all 29 breasts (14 cancerous, 15 healthy) with average R^2 values ranging from 0.79-0.88. One model coefficient, 'a', proportional to local mass, showed reasonable consistency among the subjects and decreased with increasing frequency. No significant difference in this 'a' coefficient between healthy and cancerous breasts showed indication of diagnostic potential. However, consistent values across all breasts suggest it is a fundamental tissue property. Further suggestions to normalise the major axis by frequency demonstrate the potential for the model to be developed to describe viscous behaviour of breast tissue in the form of storage and loss modulus.
Paper VI182-05.28
PDF · Video · Rayleigh Damping Modelling for Tumor Detection Using Digital Image Elasto Tomography (DIET) (I)
Fitzjohn, Jessica Louise	University of Canterbury
Zhou, Cong	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Ormsby, Zane	Tiro Medical
Haggers, Marcus	Tiro Medical
Keywords: Biomedical system modeling, simulation and visualization, Bio-signals analysis and interpretation, Identification and validation Abstract: This study develops a model based on Rayleigh Damping (RD) with potential use in breast cancer diagnostics. Displacement data of over 14,000 reference points on the breast surface from 14 breasts was captured using the Digital Image Elasto Tomography (DIET) system. The reference points were split into four segments and an ellipse fit utilized to calculate the work done and consequent viscous damping constant for each reference point. Fitting a model based on RD to median filtered data gave consistent results for one model coefficient across all breasts. The other coefficient was seen to have diagnostic potential when the model was fit to unfiltered data, and is the focus of this paper. The coefficient value was compared between breast segments adjacent to and containing the tumor (locations given from X-ray mammography) to those opposite the tumor. A total of 11 out of 14 breasts had a higher coefficient found in the tumor segment and all breasts had a higher coefficient in at least one adjacent segment. This method showed potential for breast specific diagnosis and tumor localisation using the DIET system.
Paper VI182-05.29
PDF · Video · Rheological Experimentation to Investigate History Dependent Viscoelastic Properties of Ex-Vivo Ovine Brain Tissue (I)
Lilley, Rebecca L.	University of Canterbury
Reynaud, Antoine	École Nationale Supérieure De Mécanique Et Des
Docherty, Paul D	University of Canterbury
Smith, Nicole	University of Canterbury
Kabaliuk, Natalia	University of Canterbury
Keywords: Model formulation, experiment design, Kinetic modeling and control of biological systems, Medical imaging and processing Abstract: Much controversy exists around the issue of repetitive Traumatic Brain Injuries (TBIs) and long-term brain health. Little is known about the mechanical response of brain tissue to traumatic impacts and head accelerations. While history dependent characteristics of other biological tissues have been investigated experimentally, no methodology currently exists for investigating the mechanical response of brain tissue to cyclic loading and its fatigue properties. This investigation presents sample preparation, conditioning and rheological methodology for undertaking repetitive loading of ex-vivo ovine brain tissue. Rheological amplitude sweep tests undertaken at 3 Hz on ø10 mm by 5 mm ovine brain tissue samples, employing a periodic moisturisation and a normal force of 50 mN, yielded results agreeing with those reported in literature for low number of cycle loading and showed signs of history dependence at higher number of cycles. Understanding brain tissue response to repeated loading, fatigue properties and associated trauma mechanisms can be advances by undertaking high cycle rheological testing with the methodology presented in this article.
Paper VI182-05.30
PDF · Video · An In-Silico Simulation of Pressure Wave Excursions after Impact to the Frontal Lobe of a Homogenous Model of the Brain (I)
Smith, Nicole	University of Canterbury
Wright, Frederick	University of Canterbury
Docherty, Paul D	University of Canterbury
Lilley, Rebecca L.	University of Canterbury
Kabaliuk, Natalia	University of Canterbury
Keywords: Biomedical system modeling, simulation and visualization, Tracer kinetic modeling using various imaging systems, Model formulation, experiment design Abstract: Traumatic impacts to the crania are known to have chronic effects on cerebral tissue and cognitive function. However, the inaccessibility of healthy brain tissue has limited studies of the mechanical behavior of the brain during impact. Consequently, it is uncertain how specific impacts lead to injury. The well-known Head Injury Criterion (HIC) metric is stochastic in nature. Therefore, it cannot provide deterministic indications of the severity of certain impacts and is ambivalent to trauma location. This research investigated an impact to the anterior region of an isomorphic model of intracranial tissue. The impact was 18 mm lateral of the sagittal plane. The impact propagation through the brain model was observed with a focus on the depth of wave penetration. The brain model was simplified by removing material property variations across white and grey matter and in the ventricles that contain cerebrospinal fluid regions. Ultimately, homogeneity of the simplified model was assumed to show more conservative results than what may be observed in practice. The simulation showed the significance of the initial impact magnitude and location with respect to any propagated wave. It was observed that despite minimizing the effect of damping in the model, pressure waves were not significant at the anterior of the brain. Thus, it was concluded that it is unlikely that secondary impact during TBI has a significant correlation to the location and severity of injury sustained.
Paper VI182-05.31
PDF · Video · Finite Time Joint Estimation of the Arterial Blood Flow and the Arterial Windkessel Parameters Using Modulating Functions (I)
Bahloul, Mohamed A.	King Abdullah University of Science and Technology
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Identification and validation, Biomedical system modeling, simulation and visualization, Control of physiological and clinical variables Abstract: Studying the arterial hemodynamic response plays a crucial role in the understanding and the treatment of cardiovascular diseases. Due to the difficulty of measuring the arterial blood flow, its estimation through a particular arterial vessel, using non-invasive arterial pressure waveform measurements, has always been an important topic in physiology. For instance, knowing the blood flow in a specific site of the arterial network helps in the detection of arterial stenosis. It may also help in the diagnosis of heart valve’s diseases. In this paper, an algorithm based on modulating functions is proposed to estimate the arterial blood flow as well as to calibrate the conventional Windkessel model using arterial blood pressure signals measured in a particular site of the arterial system. The algorithm is presented and illustrated through several numerical tests
Paper VI182-05.32
PDF · Video · A Minimal Set of Sensors in a Smart-Shirt to Obtain Respiratory Parameters (I)
Laufer, Bernhard	Institute of Technical Medicine (ITeM), HFU Furtwangen Universit
Murray, Rua	University of Canterbury
Docherty, Paul D	University of Canterbury
Krueger-Ziolek, Sabine	Furtwangen University
Hoeflinger, Fabian	Department of Microsystems Engineering, University of Freiburg
Reindl, Leonhard	Department of Microsystems Engineering, University of Freiburg
Moeller, Knut	Furtwangen University
Keywords: Bio-signals analysis and interpretation, Biomedical system modeling, simulation and visualization, Modeling and identification Abstract: Smart-Shirts (and other wearable technologies) that provide vital medical data are becoming increasingly prevalent. However, obtaining accurate measurement of respiratory parameters via a Smart-Shirt requires ongoing research. In this study, various respiratory parameters have been captured via an optoelectronic plethysmograph and a body plethysmograph using an optimal set of spatial sensors. Sixty-four reflective markers were fixed on a compression shirt and different respiratory manoeuvres were performed by the subjects. In this analysis, Singular Value Decomposition was used to determine the minimum marker set required to yield accurate predictions of respiratory mechanics. Sufficient accuracy and precision for most clinical applications was able to be determined using positional data from nine markers. Using motions of nine sensors, the tidal volume can be predicted with a mean error of less than 139 ml and an adjusted R2 higher than 0.96. A subsequent linear regression analysis provides the location of the nine markers. These outcomes reduce the computational complexity of analysing optical based wearable technology, reducing barriers to further uptake.
Paper VI182-05.33
PDF · Video · Clinical Application Scenarios to Handle Insulin Resistance and High Endogenous Glucose Production for Intensive Care Patients (I)
Anane, Yahia	Budapest University of Technology and Economics
Benyo, Balazs	Budapest University of Technology and Economics
Chase, J. Geoffrey	University of Canterbury
Keywords: Physiological Model, Biomedical system modeling, simulation and visualization Abstract: Intensive care patients often experience hyperglycemia, insulin resistance (low insulin sensitivity), and high endogenous glucose production due to their critical situation. STAR is a model-based glycemic control protocol that uses insulin sensitivity (SI) identified on hourly bases to define patient variability. The numerical calculation of the identification phase of SI may result in negative SI value, which is an indication of high insulin resistance or another pathological patient state. Negative values of SI are physiologically not possible and are prevented in the parameter identification phase by a non-negative constraint. These cases, when SI is forced to take a non-negative value, potentially result in poor blood glucose (BG) fitting and signaling some model limitations like an estimated low EGP. Using clinical data of 717 patients from three independent ICUs (Malaysia, New Zealand, and Hungary), the time occurrence and durations of constrained SI situations are analyzed, and different practical scenarios were suggested to estimate and handle patient's EGP levels in clinical application. An EGP estimation method is used to estimate the most suitable EGP value based on model fitting. By setting different EGP higher limit values, the fitting error and remaining constrained SI values are also analyzed and assessed. Results show that 96% of these constrained SI situations happen within the first 96H, and 95% of it lasts for 3h. Results also confirm that using an EGP limit higher than 3.5 s shows no further improvement in terms of modeling accuracy. Based on results, the most practical scenario to handle these situations is to keep the increased EGP until four days of treatment passed; after that, if it happens again, we may set back EGP to the initial value after 3h each time we increase it.
Paper VI182-05.34
PDF · Video · Anticipating Meals with Behavioral Profiles in an Artificial Pancreas System - an Informed Multistage Model Predictive Control Approach (I)
Corbett, John Corbett	University of Virginia, Center for Diabetes Technology
Colmegna, Patricio Hernán	University of Virginia
García-Tirado, José Fernando	University of Virginia
Breton, Marc D	University of Virginia
Keywords: Artificial pancreas or organs, Physiological Model, Identification and validation Abstract: This contribution presents an individualized multistage model predictive control (MS-MPC) algorithm for blood glucose (BG) stabilization and improved postprandial BG control for people with type 1 diabetes (T1D) with consistent meal patterns. The multistage formulation utilizes different meal patterns as disturbance realizations entering the glucose-insulin system, then assesses the best possible control input among all of the probable scenarios. The disturbance realizations, in the form of glucose rate of appearance traces, are estimated by using meal records (time and carbohydrate amount) as the input into an individualized oral model. Meal signatures are then clustered with the k-medoids algorithm to obtain meal patterns. Two approaches, a hybrid closed-loop (HCL) and fully closed loop (FCL) MS-MPC were tested and compared with their respective control treatments (hybrid and fully automated MPC, respectively) using the complete in silico adult cohort of the FDA-accepted UVA/Padova metabolic simulator. Results confirm an improvement in both postprandial and overall percent time in 70-180 mg/dL 85.2±15.5 v. 89.6±12.2 and 94.1±6.3 v. 95.7±5.0, respectively, using the HCL approach, and 37.8±15.7 v. 63.4±16.6 and 65.8±12.7 v. 82.2±9.2, using the FCL approach.
Paper VI182-05.35
PDF · Video · Backstepping Control with Radial Basis Function Network for a Nonlinear Cardiopulmonary System (I)
Pomprapa, Anake	RWTH Aachen University
Walter, Marian	RWTH Aachen University
Leonhardt, Steffen	RWTH Aachen
Keywords: Control of physiological and clinical variables, Quantification of physiological parameters for diagnosis and treatment assessment, Biomedical system modeling, simulation and visualization Abstract: Oxygen therapy plays a vital role to recover a patient from severe hypoxia as well as to minimize the risk of hypoxia in a critical situation. Based on this therapeutic technique, this article presents an application of backstepping control for the oxygenation in a cardiopulmonary system. A nonlinear multi-compartment system with unknown hysteresis is used as a human model in this study. With no a priori knowledge of the underlying system dynamics, a radial basis function (RBF) network is integrated into a closed-loop subsystem and trained to identify the unknown nonlinear functions. Consequently, a backstepping controller is designed based on the Lyapunov stability theorem for regulating oxygenation. The theoretical framework and simulation are presented and demonstrated in terms of stability and control performance under the presence of simulated physiological changes, possibly caused by pathophysiological effects in the cardiopulmonary system i.e. critically ill patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Paper VI182-05.36
PDF · Video · Addition of New Therapeutic Agents to an Established Type 2 Diabetes Simulation Platform for Therapy Optimization: A Bayesian Model-Based Approach (I)
Gautier, Thibault	Center for Diabetes Technology - University of Virginia
Silwal, Rupesh	University of Virginia
Breton, Marc D	University of Virginia
Keywords: Physiological Model, Pharmacokinetics and drug delivery, Identification and validation Abstract: Patients with type 2 diabetes mellitus (T2DM) typically take blood glucose level lowering oral or injectable therapeutic agents to treat their condition. Titration and timing of administration of these agents can be difficult under optimal conditions. Largely because of these challenging tasks, less than half of patients with T2DM under therapy are reaching desired glycemic targets. Computer simulations have been shown in both types of diabetes to be powerful tools to design and test optimal therapies. However, the diversity of available therapeutic agents makes the construction of such a platform challenging. In this manuscript, we present a methodology to integrate pharmacokinetics (PK) and pharmacodynamics (PD) of anti-diabetic drugs into an existing T2DM population simulation platform to optimize therapy dosage and timing, and inform clinical trial designs; the mixture of insulin glargine and a glucagon-like peptide 1 receptor agonist (GLP1-RA) was used as an example. The platform was augmented with several drug-specific new/modified sub-models and the associated parameter distributions were derived from various blood measurements collected during clinical studies. The joint model parameter distribution of the augmented platform was obtained by fitting simulated glucose profiles on 2000 days of glucose sensor data in a novel Bayesian framework. The resulting platform was then validated by reproducing glucose distributions from a large clinical study, originally excluded from the training data. Finally, simulation experiments of optimal administration timing of the studied mixture were run.
Paper VI182-05.37
PDF · Video · Surface EMG-Based Estimation of Breathing Effort for Neurally Adjusted Ventilation Control (I)
Petersen, Eike	Universität Zu Lübeck
Graßhoff, Jan	Universität Zu Lübeck
Eger, Marcus	Drägerwerk GmbH & Co. KGaA
Rostalski, Philipp	Universität Zu Lübeck
Keywords: Control of voluntary movements, respiration, Bio-signals analysis and interpretation, Identification and validation Abstract: In assisted mechanical ventilation, it is of critical importance to monitor the patient's own effort to breathe. Methods currently available are either invasive (esophageal electromyography and esophageal pressure) or rely heavily on intermittent occlusion maneuvers to identify the properties of the respiratory muscles. In this article, we propose a novel, non-invasive method to identify the patient's respiratory mechanics and estimate the pressure generated by the patient, based on surface electromyographic (sEMG) measurements of the respiratory muscles. Our method is computationally efficient, real-time capable, and can be run continuously during normal ventilation. A numerical comparison with esophageal pressure measurements using three clinical data sets demonstrates the estimation procedure's good performance. Clinically, monitoring a patient's respiratory effort is of high intrinsic, diagnostic value, while also enabling a whole range of new, adaptive control algorithms for assisted mechanical ventilation.
Paper VI182-05.38
PDF · Video · Dynamic Modelling of Obstetric Patient Coagulation from Kaolin-Activated Thromboelastogram Data (I)
Fitzmaurice, Kieran P.	University of Pittsburgh
Pressly, Michelle A.	University of Pittsburgh
Clermont, Gilles	University of Pittsburgh
Waters, Jonathan H.	University of Pittsburgh Medical Center
Parker, Robert S.	University of Pittsburgh
Keywords: Decision support and control, Biomedical system modeling, simulation and visualization, Identification and validation Abstract: Defects in blood clotting (coagulopathies) are linked to severe outcomes in mothers suffering from obstetrical hemorrhage. Identifying patients with a coagulopathy poses a challenge for clinicians, who are required to make quick treatment decisions in fast-paced environments with a high degree of uncertainty. Integrating data from point-of-care coagulation tests with mathematical models of coagulation presents an exciting opportunity to improve patient outcomes by reducing this uncertainty. A model with parameters estimated from individual patient data can provide clinicians with a way to compare patients and group them into categories of probable coagulopathy based on biologically interpretable parameters. With this in mind, we developed a mechanism-inspired model of blood coagulation calibrated against thromboelastogram (TEG) data. Markov Chain Monte Carlo and sensitivity analysis were used to assess the identifiability and distribution of model parameters for 25 obstetric patients. The ability of our model to separate patients in parameter space based on differences in observed TEG response lends credence to the feasibility of using dynamic models as tools for identifying coagulopathy subtypes within the obstetric population.
Paper VI182-05.39
PDF · Video · Artificial Intelligence Based Insulin Sensitivity Prediction for Personalized Glycaemic Control in Intensive Care (I)
Benyo, Balazs	Budapest University of Technology and Economics
Paláncz, Béla	Budapest University of Technology and Economics
Szlávecz, ákos	Budapest University of Technology and Economics
Szabó, Bálint	Budapest University of Technology and Economics
Anane, Yahia	Budapest University of Technology and Economics
Kovács, Katalin	Széchenyi István University
Chase, J. Geoffrey	University of Canterbury
Keywords: Decision support and control, Physiological Model, Intensive and chronic care or treatment Abstract: Stress-induced hyperglycaemia is a frequent complication in the intensive therapy that can be safely and efficiently treated by using the recently developed model-based tight glycaemic control (TGC) protocols. The most widely applied TGC protocol is the STAR (Stochastic-TARgeted) protocol which uses the insulin sensitivity (SI) for the assessment of the patients state. The patient-specific metabolic variability is managed by the so-called stochastic model allowing the prediction of the 90% confidence interval of the future SI value of the patients. In this paper deep neural network (DNN) based methods (classification DNN and Mixture Density Network) are suggested to implement the patient state prediction. The deep neural networks are trained by using three years of STAR treatment data. The methods are validated by comparing the prediction statistics with the reference data set. The prediction accuracy was also compared with the stochastic model currently used in the clinical practice. The presented results proved the applicability of the neural network based methods for the patient state prediction in the model based clinical treatment. Results suggest that the methods' prediction accuracy was the same or better than the currently used stochastic model. These results are the initial successful step in the validation process of the proposed methods which will be followed by in-silico simulation trials.
Paper VI182-05.40
PDF · Video · Using the Adapted Levenberg-Marquardt Method to Determine the Validity of Ignoring Insulin and Glucose Data That Is Affected by Mixing (I)
Lam, Nicholas	University of Canterbury
Docherty, Paul D	University of Canterbury
Murray, Rua	University of Canterbury
Chase, J. Geoffrey	University of Canterbury
Te Morenga, Lisa	Victoria University
Keywords: Identification and validation, Kinetic modeling and control of biological systems, Pharmacokinetics and drug delivery Abstract: Most parameter ID methods use least squares criterion to fit parameter values to observed behavior. However, the least squares criterion can be heavily influenced by outlying data or un-modelled effects. In such cases, least squares estimation can yield poor results. Outlying data is often manually removed to avoid inaccurate outcomes, but this process is complex, tedious and operator dependent. This research presents an adaptation of the Levenberg-Marquardt (L-M) parameter identification method that effectively ignores least-square contributions from outlying data. The adapted method (aL-M) is capable of ignoring outlier data in accordance with the coefficient of variation of the residuals and was thus, capable of operator independent omission of outlier data using the 3 standard deviation rule. The aL-M was compared to the original Levenberg-Marquardt (L-M) method in C-peptide, insulin and glucose data. In total three cases were tested: L-M in the full dataset, L-M in the same data where the points that were suspected to be affected by incomplete mixing at the depot site were removed, and the aL-M in the full data set. There were strong correlations between the aL-M and the reduced dataset from [0.85, 0.71] for the clinically valuable glucose parameters. In contrast, the unreduced data yielded poor residuals and poor correlations with the aL-M [0.44, 0.33]. The aL-M approach provided strong justification for consistent removal of data that was deemed to be affected by mixing.
Paper VI182-05.41
PDF · Video · Detection of Signs of Parkinson's Disease Using Dynamical Features Via an Indirect Pointing Device (I)
Ushirobira, Rosane	Inria
Efimov, Denis	Inria
Casiez, Gery	CRIStAL (UMR CNRS 9189)
Fernandez, Laure	Aix-Marseille University
Olsson, Fredrik	Uppsala University
Medvedev, Alexander	Uppsala University
Keywords: Quantification of physiological parameters for diagnosis and treatment assessment, Developments in measurement, signal processing, Control of physiological and clinical variables Abstract: In this paper, we study the problem of detecting early signs of Parkinson’s disease during an indirect human-computer interaction via a computer mouse activated by a user. The experimental setup provides a signal determined by the screen pointer position. An appropriate choice of segments in the cursor position raw data provides a filtered signal from which a number of quantifiable criteria can be obtained. These dynamical features are derived based on control theory methods. Thanks to these indicators, a subsequent analysis allows the detection of users with tremor. Real-life data from patients with Parkinson’s and healthy controls are used to illustrate our detection method.
Paper VI182-05.42
PDF · Video · Toxicity-Centric Cancer Chemotherapy Treatment Design (I)
Liparulo, Joseph	University of Pittsburgh
Knab, Timothy	University of Pittsburgh
Parker, Robert S.	University of Pittsburgh
Keywords: Decision support and control, Healthcare management, disease control, critical care, Pharmacokinetics and drug delivery Abstract: Cancer chemotherapy scheduling in the mathematics and engineering literature has generally focused on optimal control formulations and tumor kill, using constraints on dose magnitude and duration to implicitly mitigate toxicity. We introduce a framework for scheduling that focuses on clinically-relevant toxicity mitigation allowing clinicians to specify toxicity limits in terms they understand. Building from the model predictive control framework, we explicitly use the pharmacokinetic model of drug distribution as well as pharmacodynamic models of both antitumor effect and drug toxicity in the optimization problem. Clinical and logistical constraints round out the treatment design problem. Rather than direct inversion, we synthesize the optimization problem in an input-discretized form and solve via graphical processing unit (GPU) calculation. The resulting suboptimal solution is shown to be clinically indistinguishable from an optimal solution (calculated via nonlinear least squares (NLS) from a relaxation of the input and logistical constraints to continuous variables). Using a docetaxel administration case study, the algorithm controlled neutropenia within user-specified toxicity constraints while maintaining tumor eradication rates equivalent to, or better than, clinically-implemented dosing schedules. Changes in patient response -- both antitumor efficacy and toxic drug sensitivity are captured via a nonlinear least squares (NLS) calculation at the end of each treatment cycle and updated in the next cycle design. By explicitly controlling treatment toxicity, this algorithm has the potential to improve patient quality-of-life.
Paper VI182-05.43
PDF · Video · Online, Data-Driven Detection of Human Position During Kegel Exercising (I)
Knorn, Steffi	Uppsala University
Varagnolo, Damiano	NTNU - Norwegian University of Science and Technology
Jackson, Roxanne	University of Passau
Budgett, David	Auckland Bioengineering Institute, the University of Auckland
Kruger, Jennifer A	Auckland Bioengineering Institute, the University of Auckland
Nielsen, Poul M F	The University of Auckland
Keywords: Bio-signals analysis and interpretation, Biomedical system modeling, simulation and visualization Abstract: This paper proposes an online, data-driven method to detect in which position (lying or standing) a women is performing Kegel exercises from measurements collected with a vaginal pressure sensor array. Pressure data has been collected with the vaginal pressure sensor from women performing Kegel exercises by playing a dedicated mobile app, which is controlled by contracting their pelvic floor muscles. Depending on their position while playing (lying or standing), the recorded pressure patterns exhibit different characteristics in terms of intensity, location and width of the pressure peak, which may be used to detect the human position. For this, the recorded data is filtered, opportune features are extracted and a suitable classifier is trained to distinguish the two positions. The results show that the human position can be accurately detected online when using individual models for each patient (in our experiments, up to 1% of false positives and 4% false negatives), whereas the detection capabilities might decrease drastically when considering the same classifier for another women (e.g., up to 95% of false positives).

VI182-06
Biomedical and Physiological Modeling and Control	Regular Session
Chair: Shi, Dawei	Beijing Institute of Technology
Co-Chair: Seel, Thomas	Technische Universitaet Berlin
Paper VI182-06.1
PDF · Video · Smart Artificial Pancreas with Diet Recommender System for Elderly Diabetes
Padmapritha, T.	Kalasalingam Academy of Research and Education
Subathra, B.	Kalasalingam University
Ozyetkin, Munevver Mine	Adnan Menderes University
Srinivasan, Seshadhri	University of Sannio
Bekiroglu, Korkut	State University of New York - Polytechnic Institute
Keshavdev, Jothydev	Jothydev Diabetes Research Center
Krishnan, Gopika	Jothydev Diabetes Research Center
Sanal, Geethu	Jothydev Diabetes Research Center
Keywords: Artificial pancreas or organs, Control of physiological and clinical variables, Clinical trial Abstract: This investigation presents a smart artificial pancreas (AP) for treating Type 1 Diabetes Mellitus (T1DM) in elderly which simultaneously automates the insulin administration but also diet recommender system using implicit carbohydrate (CHO) measurements. Three main components of the AP are: (i) long-term model of physiological dynamics, (ii) model predictive controller and (iii) a diet recommender algorithm which uses implicit CHO measurements. We first show that long-term dynamics are important for capturing the food influences on blood glucose levels and to maintain within admissive bands. The diet recommender algorithm fuses the insulin infusion information of the MPC, long-term model, average CHO and its variations to recommend diet and its pattern. The proposed artificial pancreas with diet recommender system is illustrated using studies conducted on elderly patients with T1DM based on clinical trials conducted at Jothydev’s Diabetes Research Centre, Trivandrum, India. Our studies shows that the proposed AP not only automates the insulin infusion but also provides a recommender system for diet.
Paper VI182-06.2
PDF · Video · An Adaptive Disturbance Rejection Controller for Artificial Pancreas
Cai, Deheng	Beijing Institute of Technology
Liu, Wei	Peking University People's Hospital
Dassau, Eyal	Harvard University
Doyle, Francis	Harvard University
Cai, Xiaoling	Peking University People's Hospital
Wang, Junzheng	Beijing Institute of Technology
Ji, Linong	Peking University People's Hospital
Shi, Dawei	Beijing Institute of Technology
Keywords: Artificial pancreas or organs, Healthcare management, disease control, critical care, Control of physiological and clinical variables Abstract: Artificial pancreas (AP) systems are designed to automate glucose management for patients with type 1 diabetes. In this work, we propose an adaptive disturbance rejection control approach for AP systems to achieve safe and e ective glucose regulation. The controller is built within the framework of active disturbance rejection control, but incorporates safety operation constraints, and glucose- and velocity-dependent parameter adaptation modules for key control parameters. In silico performance comparison between the proposed controller and an adaptive zone model predictive controller (MPC) (Shi, Dassau, and Doyle III, 2019a) is conducted on the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator. For both announced and unannounced meals, the controller achieves comparable glucose regulation performance in terms of mean glucose (134.9 mg/dL vs. 135.4 mg/dL, p < 0:001; 149.7 mg/dL vs. 151.7 mg/dL, p < 0:001, respectively) and percentage time in [70, 180] mg/dL (93.8% vs. 92.4%, p < 0:001; 76.0% vs. 72.4%, p < 0:001, respectively) without increasing the risk of hypoglycemia. The results indicate the feasibility of achieving comparable glucose regulation performance through a non-optimization control law for AP systems.
Paper VI182-06.3
PDF · Video · Simple Strategies for Retrospective Detection of Meals in Diabetes Datasets
Mejía Gamarra, José Enrique	University of Piura
Reiterer, Florian	Nemak Linz GmbH
Tkachenko, Pavlo	Johannes Kepler University
Schrangl, Patrick	Johannes Kepler University Linz
Freckmann, Guido	Institut Fuer Diabetes-Technologie, Forschungs Und Entwicklungs
Ipanaqué, William	Piura University
Keywords: Bio-signals analysis and interpretation, Quantification of physiological parameters for diagnosis and treatment assessment, Physiological Model Abstract: Over the last decade many model based approaches have been proposed for a personalized insulin therapy in type 1 diabetes (T1D). These approaches rely on patient-specific models of the glucose metabolism which typically need to be identified on high quality data. However, patient data recorded in an at-home setting most often do not meet this criterion, since these are based, among others, on diary entries, which are often erroneous and incomplete. The problem is especially pronounced for recordings of meal intakes which are often accidentally omitted or recorded with wrong time stamps. This paper presents two methods for meal detection based on retrospective analysis of recorded glucose traces. The first method uses the typical signal features of postprandial glucose traces and simple heuristics to detect meals, whereas the second approach relies on similarity measures of glucose traces as compared to postprandial reference profiles. Matching the meal detection results of the algorithms with the actual patient diaries, the methods presented here can be used to find complete, high quality segments in at-home data. Being able to easily distinguish between high and low quality segments in such dataset is expected to improve the reliability of identified patient models and could thus prove to be a key factor for personalized insulin therapy via model-based treatment strategies.
Paper VI182-06.4
PDF · Video · LPV Based Control of Glucose Concentration in Type 2 Diabetes
Eringis, Deividas	Aalborg University
Munk, Peter	Aalborg University
Andersen, Benjamin	Aalborg University
Suresh, Rahul Sylvester	Aalborg University
Leth, John	Aalborg University
Keywords: Chronic care and/or diabetes, Decision support and control, Control of physiological and clinical variables Abstract: This paper investigates continuous-time LPV dynamic-output feedback for controlling a type 2 diabetes patients' fasting glucose concentration. To emulate a real life scenario, the input and measurement were specified only once per day, and biological variance was introduced. The results were evaluated by examining the settling time, variance after settling, and the violation of the nominal fasting glucose concentration range of 4−5 [mmol/l]. The LPV dynamic-output feedback controller was compared to a simple rule based titration algorithm and a PI controller tuned by LPV methods. The LPV dynamic-output feedback controller, proved to deliver better results, in particular for the transient period.
Paper VI182-06.5
PDF · Video · Multi-Step Approach for Sensitivity Analysis for a Unified Model of Glucose-Insulin Metabolism
Tolks, Christian	University of Augsburg
Ament, Christoph	Universitaet Augsburg
Eberle, Claudia	Fulda University of Applied Sciences
Keywords: Identification and validation, Chronic care and/or diabetes, Physiological Model Abstract: Mathematical models of biomedical systems often have a high number of uncertain parameters that are difficult or even impossible to estimate precisely. In order to be able to adequately describe the system, it must be known how large the influence of which factors is on the model behavior and how uncertainties in the parameters affect the model accuracy. Sensitivity analysis (SA) offers a possibility to examine to what extent the variance of the model output can be described by the variability of the input factors. In this paper, a multi-stage SA is fulfilled for a unified model of glucose-insulin metabolism that consists of an Elementary Effects Test for screening purposes, a functional principal component analysis for dimensionality reduction of the model output variance and a variance-based approach to determine the sensitivity indices. The concept is tested on several scenarios for type 1 and type 2 diabetic patients, as well as non-diabetics. Results show that parameters are of different importance, depending on the type and scenario studied, which should be considered in a further system analysis.
Paper VI182-06.6
PDF · Video · A Fast Localization and Extraction of Microaneurysm for Early Detection of Diabetic Retionopathy
Cheng, Yun	Central South University
Liu, Weirong	Central South University
Wang, Chenglong	Central South University
Gu, Xin	Central South University
Cheng, Yijun	Central South University
Wang, Shengnan	Central South University
Peng, Jun	Central South University
Keywords: Medical imaging and processing, Biomedical and medical image processing and systems, Bioinformatics Abstract: Diabetic Retinopathy (DR) is regarded as one of the leading causes of blindness globally. Microaneurysms (MAs) detection is essential to the computer aided diagnosis of DR at an early stage. However, the automatic detection of MAs is still a challenging problem as they are too tiny to be recognized and hard to be distinguished from other similar lesions. Therefore, we propose an efficient localization and extraction method for MAs, where the edge detection and Random Forest are utilized to enhance the accuracy of detection results. Finally, the proposed method is evaluated based on the public retinal image database MESSIDOR. Numerical results show that high accuracy and timely detection can be obtained with the proposed solution.
Paper VI182-06.7
PDF · Video · Energy Based Model of the Human Ear Canal and Tympanic Membrane for Sound Transmission
Madahana, Milka Cynthia Ijunga	Witwatersrand University
Ekoru, John Elisa Dimiti	University of the Witwatersrand
Nyandoro, Otis Tichatonga	University of the Witwatersrand, Johannesburg
Keywords: Biomedical system modeling, simulation and visualization, Physiological Model, Healthcare management, disease control, critical care Abstract: The objective of this paper is to present a unique energy based model of the human outer ear and the tympanic membrane. The developed model employs the Port Hamiltonian modelling approach. The tympanic membrane is modelled as an Euler-Bernoli beam. The frequency response of the model at speech frequencies which are significant for sound transmission are found to comparable to existing results in literature. This model can also be used for investigation of tympanic membrane rupture or perforations. Future work will include modelling of the ear canal as horn shaped and inclusion of the angular motion of the tympanic membrane.
Paper VI182-06.8
PDF · Video · Modelling and Simulation of the Human Cardiovascular System by Differential Hybrid Petri Net
Jorge, André	University of Sao Paulo
Pessoa, Marcosiris Amorim de Oliveira	University of Sao Paulo
Junqueira, Fabrício	Escola Politécnica, University of São Paulo
Riascos, Luis Alberto	UFABC - Federal University of ABC
Santos Filho, Diolino José	Escola Politécnica - University of São Paulo (USP)
Miyagi, Paulo Eigi	University of Sao Paulo, Escola Politécnica
Keywords: Modeling and identification, Dynamics and control, Parameter and state estimation Abstract: Clinical data surveys indicate a significant number of deaths deriving from diseases in the human cardiovascular system (HCS). This is one of the main motivations for identifying problems in this system and ways for solving them totally or partially. In this work, HCS is modeled as a hybrid system (discrete event systems combined with systems of continuous variables) for a more detailed characterization of this system functioning, by applying the formalism of the Differential Hybrid Petri Net (DHPN). The analysis of this model, using Matlab®/Simulink, presented consistent results when compared with clinical data, regarding physiological variables, such as blood pressure and blood flow rate, indicating the validity of this model.
Paper VI182-06.9
PDF · Video · Deterministic vs Stochastic Formulations and Qualitative Analysis of a Recent Tumour Growth Model
Borri, Alessandro	Istituto Di Analisi Dei Sistemi Ed Informatica "A. Ruberti" (IAS
Palumbo, Pasquale	University of Milano-Bicocca
Papa, Federico	Consiglio Nazionale Delle Ricerche
Keywords: Pharmacokinetics and drug delivery, Control of physiological and clinical variables, Kinetic modeling and control of biological systems Abstract: Mathematical modeling and control have recently played a pivotal role in the understanding of tumour growth and in treatment planning, with a special emphasis in the search for personalized therapies. In this note a recent tumour growth model is investigated. The model entails the proliferating and necrotic tumour cells dynamics, as well as the administered drug level. Inspired by a recent reaction-rate characterization of the model, the approach is further deepened with respect to cells and drug molecules copy numbers, hence resulting relevant under the double facet of the deterministic and stochastic frameworks. With regards to the deterministic model, the qualitative behavior analysis is carried out under the basic assumption of a baseline drug delivery: results are encouraging, since they show which parameter space regions allow effective control law results. Stochastic simulations are carried out by properly exploiting parameter values taken from the available experimental literature, and are consistent with the average value evolution inferred from the deterministic approach, paving the way to further stochastic investigation oriented to frameworks involving a reduced copy number.
Paper VI182-06.10
PDF · Video · A Human Inner Ear Model for Assessment of Noise Induced Hearing Loss Via Energy Methods
Madahana, Milka Cynthia Ijunga	Witwatersrand University
Nyandoro, Otis Tichatonga	University of the Witwatersrand, Johannesburg
Ekoru, John Elisa Dimiti	University of the Witwatersrand
Keywords: Physiological Model, Biomedical system modeling, simulation and visualization, Healthcare management, disease control, critical care Abstract: The main objective of this paper is to present a novel Port-Hamiltonian based model of the human inner ear. This model can be used in the assessment and diagnosis of the human inner ear diseases, for instance, Noise Induced Hearing Loss. It may also be used for understanding of sound transmission in the inner ear. The Cochlear Partition is modelled as a pair of Euler-Bernoulli beams coupled together by a linear massless distributed spring. The fluids in the Scala Vestibuli and Scala Tympani are also included in the model. The Cochlear displacement velocity is mainly enhanced by the Outer Hair Cells activities. For frequencies greater than 1 kHz the enhancements become very significant. The developed model also includes the outer hair cells. The model was validated against existing inner ear models and the results were found to be comparable. Future improvements to the model would involve inclusion of the auditory nerve to the model.
Paper VI182-06.11
PDF · Video · Model of the Oculomotor System Based on Adaptive Internal Models
Broucke, Mireille	University of Toronto
Keywords: Physiological Model, Modeling and identification, Control of voluntary movements, respiration Abstract: We propose a new model of the oculomotor system, particularly, the slow eye movement systems. We show that the system can be understood as an application of adaptive internal models. The outcome is a simple model that includes the interactions between the brainstem and the cerebellum and that accounts for behaviors in a number of oculomotor experiments. Our model suggests that a possible role of the cerebellum is to embody adaptive internal models of all persistent, exogenous disturbance signals acting on the body and observable through the sensory error signals it receives.
Paper VI182-06.12
PDF · Video · Reference Trajectory Generation for Closed-Loop Control of Electrical Stimulation for Rehabilitation of Upper Limb
Karak, Tarun	Indian Institute of Technology Kharagpur
Tiwari, Laxmi Kant	Indian Institute of Technology Kharagpur
Sengupta, Somnath	IIT Kharargpur
Nag, Sudip	Indian Institute of Technology Kharagpur
Keywords: Control of voluntary movements, respiration, Biomedical system modeling, simulation and visualization, Kinetic modeling and control of biological systems Abstract: Abstract: Functional movements in the paralyzed upper limb can be restored with the help of a brain-computer-interface (BCI). A BCI system typically adopts a functional electrical stimulation (FES) system that activates weakened muscles that are otherwise responsible for actuating finger movements. A BCI-FES system can activate muscle contraction through the delivery of electrical stimulation pulses. The control of voltage or current stimulation parameters such as pulse width, frequency, and amplitude along with feedback signals from finger joint positions are important for stable grasping. For the design of a closed-loop functional electrical stimulation controller, it is obligatory to set standard reference trajectories of finger joints’ angular positions and velocities for controlling stimulation parameters in neuroprosthetics and rehabilitation. This study proposes a new closed-loop control architecture targeted for achieving successful and stable grasping of an upper limb paralyzed subject. This can be achieved by characterizing each of the finger joints’ instantaneous angular position and velocity, through reference trajectories. These reference trajectories are generated corresponding to various types of grasping for feeding to the controller, responsible for the stimulation of muscles. Hence, to generate such trajectories, first, grasping classification has been implemented using standard machine learning algorithms on a large set of existing real-time data of different types of objects’ grasping such as various diameter, abducted thumb and other types of objects, from many healthy subjects. The results demonstrate the successful implementation of fairly accurate classifications and trajectory generations which are crucial for closed-loop control towards stable grasping.
Paper VI182-06.13
PDF · Video · Optimal Schedules of Light Exposure for Multiple Individuals for Quick Circadian Alignment
Mohamed, Anas	Monash University Malaysia
Tan, Chee Pin	Monash University
Phillips, Andrew	Monash University
Kalavally, Vineetha	Monash University Malaysia
Cain, Sean	Monash University
Keywords: Decision support and control, Control of physiological and clinical variables, Dynamics and control Abstract: The invention of quick transportation modes that allow trans-meridian travel has caused circadian misalignment to be a common problem amongst people today. This leads to lower cognitive alertness in the short term and increases the risks of other maladies in the long term. Light, when applied at correct levels and times, can shift and re-entrain the circadian clock to the local time zone, and minimize the negative impact of any circadian misalignment. In this paper, we developed a new method (algorithm) to calculate common optimal light schedules of light exposure and avoidance, to quickly re-entrain the circadian systems of a group of individuals who have different internal circadian parameters. We used an experimentally validated mathematical model to define a target circadian phase, from which, our optimization algorithm iteratively adjusts the switching times of a bang-bang light input (restricted to two light levels) to minimize the difference between the current phase of all individuals and the target phase, within a set time period. The proposed algorithm generated light schedules that successfully minimizes the re-entrainment time of all the individuals with phase shifts up to 12 hours of delay or advancement.
Paper VI182-06.14
PDF · Video · Modeling and Temperature Control of Retinal Laser Therapy
Abbas, Hossam Seddik	Institute for Electrical Engineering in Medicine, University Of
Kren, Christopher	Medical Laser Center Luebeck
Danicke, Veit	Medical Laser Center Luebeck
Theisen-Kunde, Dirk	Medical Laser Center Luebeck
Brinkmann, Ralf	University of Luebeck
Keywords: Decision support and control, Identification and validation Abstract: The development of a noninvasive technique to measure tissue temperature during retinal laser treatment allows feedback control approaches to regulate the temperature rise to desired values. The main challenge is to provide fast and consistent good control performance regardless the uncertainty of the dynamics of the temperature increase at the different irradiated spots on the retina, which is due to the large variance of the retinal light absorption. In this paper, we demonstrate a successful experimental application in ex-vivo of robust H-infinity PID control to handle such a control problem. The system input is the applied laser power and its output is the temperature increase. Based on measurements of input-output data, we employ system identification to model the range of the system dynamics at different retinal irradiation sites. Then, we use a loop shaping approach to express the performance specifications of the closed-loop system and we synthesize accordingly the controller using efficient robust H-infinity synthesis tools for fixed structure controllers. The experimental implementation of the closed-loop system for tracking different reference temperatures demonstrates the achievement of the control objectives consistently at the different irradiation sites.
Paper VI182-06.15
PDF · Video · On the Stability of a Stochastic Nonlinear Model of the Heart Beat Rate During a Treadmill Exercise
Asheghan, Mohammad Mostafa	Northeastern University
Shafai, Bahram	Northeastern Univ
Miguez, Joaquin	Universidad Carlos III
Keywords: Dynamics and control, Identification and validation, Biomedical system modeling, simulation and visualization Abstract: We investigate the stability properties of a nonlinear stochastic dynamical model of a person's heart beat rate (HBR) during a treadmill exercise. The analysis is based on the Lyapunov direct method and it is valid for systems with either known or unknown parameters. Specifically, we characterize an upper bound on the norm of the cumulative noise that holds in the presence of bounded errors in the model parameters and guarantees P-stability. Numerical simulations are presented that corroborate the theoretical results.
Paper VI182-06.16
PDF · Video · A Preliminary Analysis of Gait Performance of Patients with Multiple Sclerosis Using an Sensorized Crutch Tip
Sesar, Iñigo	University of the Basque Country (UPV/EHU)
Zubizarreta, Asier	University of the Basque Country
Cabanes, Itziar	Univ of the Basque Country
Asier, Brull	University of the Basque Country (UPV/EHU)
Jon, Torres-Unda	University of the Basque Country (UPV/EHU)
Rodriguez-Larrad, Ana	University of the Basque Country (UPV/EHU)
Keywords: Rehabilitation engineering and healthcare delivery, Bio-signals analysis and interpretation, Model formulation, experiment design Abstract: The quality of life and functional mobility of patients with Multiple Sclerosis (MS) can significantly improve with exercise and a rehabilitation therapy adjusted to the needs of each patient. The assessment of gait and functional mobility of patients with MS is usually done based on clinical scales and tests, which have various limitations. This work presents the preliminary results of a clinical study carried out with patients with MS walking with a sensorized crutch tip. This tip allows to define new indicators that can be correlated with the clinical assessment scales and provide further objective and quantitative information to assess gait performance and level of impairment of patients with MS, and characterize their gait patterns. The results suggest that parameters such as the average cycle time and the average percentage of body weight might be useful to evaluate the gait performance and level of disability. Moreover, parameters related with the pitch angle of the crutch allow to determine crutch usage patterns and spot differences between patients with similar functional performance.
Paper VI182-06.17
PDF · Video · Adaptive Iterative Learning Control of an Industrial Robot During Neuromuscular Training
Ketelhut, Maike	Institute of Automatic Control, RWTH Aachen University
Brügge, Gerrit Marc	Institute of Automatic Control, RWTH Aachen University
Göll, Fabian	German Sports University Cologne
Braunstein, Bjoern	German Sport University Cologne
Albracht, Kirsten	German Sports University Cologne
Abel, Dirk	RWTH-Aachen University
Keywords: Rehabilitation engineering and healthcare delivery, Control of physiological and clinical variables Abstract: To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.
Paper VI182-06.18
PDF · Video · An Adaptive Identification Test Monitoring Procedure for Nonlinear Behavioral Interventions
Salazar, Carlos Alberto	Escuela Superior Politecnica Del Litoral, ESPOL
Aguirre, Adriana	Escuela Superior Politécnica Del Litoral
Martin, Cesar A.	Escuela Superior Politecnica Del Litoral (ESPOL)
Rivera, Daniel E.	Arizona State University
Keywords: Environmental, health and safety implications of automation, Human-centered systems engineering Abstract: Different studies have established correlation between physical inactivity and the incidence of chronic diseases. Prior investigations have been developed around the topic of mobile physical activity interventions relying on Multiple Input Multiple Output (MIMO) dynamical models of Social Cognitive Theory (SCT) that have been obtained through control engineering and system identification approaches. Identification Test Monitoring (ITM) is a technique that yields to the estimation of an adequate model with the shortest possible duration of the experiment. In this context, Local Polynomial Method (LPM) has been applied to estimate the Frequency Response Function (FRF) and the power spectrum of the disturbing noise for linear models. However, the experimental setup of physical interventions considers a decision block that is nonlinear. This paper describes the redesign of an ITM procedure for nonlinear behavioral interventions, through new uncertainty computations and stopping criterion analysis.

VI182-07
Estimation and Signal Analysis in Biomedicine and Social Systems	Regular Session
Chair: Yue, Hong	University of Strathclyde
Co-Chair: Nikolakopoulos, George	Luleå University of Technology
Paper VI182-07.1
PDF · Video · Inter-Beat Interval Estimation from Extremely Noisy Single Lead Electrocardiograms
Burguera, Antoni	University of the Balearic Island
Keywords: Bio-signals analysis and interpretation, Developments in measurement, signal processing, Medical imaging and processing Abstract: The advent of wearable recorders poses new challenges to electrocardiogram (ECG) analysis, such as robust feature extraction in front of long-term recordings with intervals of extreme noise. This paper proposes a robust approach to improve the estimates of one particular feature, the R-R interval (RRI), extracted by an arbitrary QRS detector operating in these scenarios. The proposal performs three steps. First, a voting schema is used to detect noisy intervals. Second, a rough estimate of the RRI evolution with time is obtained. Finally, this estimate is used to guide the Kalman filter in charge of refining the RRI estimates. Two groups of experiments have been performed. The first relies on 1674 real ECG corrupted with controlled amounts of noise. The second one tests our proposal using the MIT-BIH Noise Stress Test Database. Results show that our approach is barely influenced by the initial error, leading to a large improvement in front of highly corrupted electrocardiograms at the cost of reducing the quality of the RRI estimates in absence of significant noise. Accordingly, the presented approach is suitable to process data obtained from portable ECG devices in which localized intervals of severe noise are present.
Paper VI182-07.2
PDF · Video · Risk Management to Validation VAD Design
Dias, Jeferson Cerqueira	University of São Paulo - USP
Dias, Jonatas C.	Universidade De São Paulo - USP
Stoeterau, Rodrigo	University of São Paulo - USP
Miyagi, Paulo Eigi	University of Sao Paulo, Escola Politécnica
Santos Filho, Diolino José	Escola Politécnica - University of São Paulo (USP)
Keywords: Decision support and control, Identification and validation, Model formulation, experiment design Abstract: Implantable Ventricular Assist Devices (VAD) used as heart failure advanced therapy have adverse events, including VAD malfunction. A method for improving the reliability of VAD through a risk analysis and inherent safety recommendations for bench-tested VAD is proposed. The result is presentation of an algorithm to validate VAD design. The method provides constant verification by monitoring operating variables which when compared to a standard behavior curve provides data that allow prediction of failures. Thus, in the project life cycle a continuous improvement of the reliability of VAD projects is possible.
Paper VI182-07.3
PDF · Video · Intelligent Comprehensive Occupational Health Monitoring System for Mine Workers
Madahana, Milka Cynthia Ijunga	Witwatersrand University
Nyandoro, Otis Tichatonga	University of the Witwatersrand, Johannesburg
Ekoru, John Elisa Dimiti	University of the Witwatersrand
Keywords: Healthcare management, disease control, critical care, Monitoring, Data mining tools Abstract: The objective of this work is to present a comprehensive occupational health monitoring system which provides the current state of the occupational health for mine workers. The hearing threshold shift and dust exposure of each individual mine worker is monitored using this system. The data obtained from the system is transmitted via Internet of Things to storage which may be cloud or a server. The novelty of this model lies in its dual ability to monitor both Noise Induced Hearing Loss and Pneumoconiosis which is caused by inhalation of dust particles. The output of this dual system is further processed using Machine learning and artificial intelligence techniques. Recommendations are then provided to the mine worker with regards to their state of health. This system forms part of an early intervention system in the mines. The model was validated using real data from a Platinum mine in South Africa. Future improvement to this work would entail refinement of the current preliminary implementation plan and carrying out the first phase of the implementation.
Paper VI182-07.4
PDF · Video · State Estimation in Type 2 Diabetes Using the Continuous-Discrete Unscented Kalman Filter
Clausen, Henrik Glavind	Aalborg University
Leth, John	Aalborg University
Knudsen, Torben	Aalborg University
Schiøler, Henrik	Aalborg University
Keywords: Identification and validation, Biomedical system modeling, simulation and visualization, Parameter and state estimation Abstract: Using a nonlinear model for the glucose-insulin dynamics in type 2 diabetes, formulated in continuous-time as a stochastic differential equation, we seek to estimate the system states and parameters based only on discrete-time self-monitored blood glucose measurements of fasting glucose and the known exogenous insulin dose. This is done by means of continuous-discrete unscented Kalman filtering. The results are compared to an implementation of a continuous-discrete extended Kalman filter. Simulations show that it is possible to estimate all states with good accuracy using the CD-UKF, while it is also possible to estimate one unknown parameter at the same time. Further simulations show that increasing the sample rate makes it possible to estimate more parameters, given that the meal intake of the patient is known perfectly.
Paper VI182-07.5
PDF · Video · A Bayesian Robust Observation Design Approach for Systems with (Large) Parametric Uncertainties
Yu, Hui	Fujian Institute of Research on the Structure of Matter
Yue, Hong	University of Strathclyde
Wei, Xian	Chinese Academy of Sciences
Su, Xiaoke	University of Strathclyde
Keywords: Model formulation, experiment design, Biomedical system modeling, simulation and visualization, Identification and validation Abstract: Classical optimal experimental design (OED) methods have not been fully exploited in modeling of complex systems, due to the brittle design results generated based on prior models and computational burden in the optimization scheme. In this work, a novel method for robust experimental design (RED) of combined measurement set selection and sampling time scheduling has been proposed for systems with large parameter uncertainties. A Bayesian design framework is employed, involving Gaussian quadrature formula (GQF) approximation of the expected performance of the posterior distribution over uncertain parameter domain. The robust Bayesian experimental design (BED) has been relaxed to a semi-definite programming (SDP) problem which can be solved as a convex optimization problem. The proposed method has been examined by simulation studies on a lab-scale enzymatic biodiesel production system, with results compared to OED and uniform sampling under two design scenarios.
Paper VI182-07.6
PDF · Video · On the Fear of Falling Detection by Moving Horizon Estimation
Jafari, Hedyeh	Luleå University of Technology
Sharif Mansouri, Sina	Lulea University
Nikolakopoulos, George	Luleå University of Technology
Gustafsson, Thomas	Luleå University of Technology
Keywords: Quantification of physiological parameters for diagnosis and treatment assessment, Identification and validation Abstract: Fear of falling (FoF) is a major health problem, especially in elders, which can lead to falls, injury, loss of independence, and premature needs of nursing and assistance. However, most of the studies have focused on the psychological aspect of the FoF and there is a significant lack of technological assistance and methodology to detect and eliminate the effects of this fear on maintaining balance. In this article, we propose a novel method to detect the FoF as a quantitative signal. We assumed fear as an internal disturbance inside the Central Nervous System (CNS) which can affect the generated output torque to each joint of the psychical body. Assuming the human body in a quiet stance as an inverted pendulum model, this disturbance signal is estimated by Moving Horizon Estimation (MHE). For this purpose, the body kinetics and kinematics measurements of forty-five subjects during upright stance trails as well as the psychological FoF falls efficacy test, were collected and utilized for the estimation and validation of the results. The experimental results show that the subjects with FoF present a higher variation in the estimated signal. This method can sufficiently detect the FoF by the posturographic and motion data which can be utilized on the future assistive devices for the prevention and treatment of the FoF and falls
Paper VI182-07.7
PDF · Video · Directed Evolution of Human Facial Images
Zahradnikova, Barbora	Faculty of Materials Science and Technology, Slovak University O
Budjac, Roman	Institute of Applied Informatics, Automation and Mechatronics, F
Schreiber, Peter	Institute of Applied Informatics, Automation and Mechtronics, Fa
Rydzi, Stefan	Institute of Applied Informatics, Automation and Mechatronics, F
Keywords: Criminality, Security Abstract: In a criminal investigation, situations are quite often where no evidence but a witness is available. In these cases, facial composites represent an important tool applied in order to search for a perpetrator of a crime. Facial composites are images of faces drafted by a forensic technician requiring a very precise description provided by a witness. Despites deploying the computational technique into the composition process, the naming rates remain very low (often not reaching 5%). In this paper, we present a system developed according to the latest research in psychology of facial perception which is able to automatically generate whole face images. Incorporating the interactive evolutionary algorithm, facial composites are generated based on the witness's selection, however, much faster than utilising the conventional software and without the need to decompose the memory of a seen face into individual fragments. As the system is under gradual development, it is presented in the latest tested version, providing information on the selected EA as well as several image manipulation algorithms inclusive of methods for age progression and hair manipulation. Not only applied methods and in-office testing are included. Moreover, testing in simulated field conditions is part of the paper.

VI183
Bio and Ecological Systems - Modeling and Control of Environmental Systems
VI183-01 Control and Estimation Problems in Water Systems   Open Invited Session, 8 papers
VI183-02 Integrated Assessment Modelling for Environmental Systems   Open Invited Session, 6 papers
VI183-03 Predictive Control of Large-Scale Water Systems   Open Invited Session, 5 papers
VI183-04 Modeling, Monitoring, and Control of Water Resources Systems   Regular Session, 9 papers
VI183-05 Natural and Environmental Systems   Regular Session, 5 papers

VI183-01
Control and Estimation Problems in Water Systems	Open Invited Session
Chair: Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Co-Chair: van Nooijen, Ronald Robert Paul	Delft University of Technology
Organizer: Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Organizer: Diagne, Mamadou	Rensselaer Polytechnic Institute
Organizer: van Nooijen, Ronald Robert Paul	Delft University of Technology
Paper VI183-01.1
PDF · Video · Nonlinear Model Predictive Control Design for BSM-MBR: Benchmark of Membrane Bioreactor (I)
Xingang, Guo	King Abdullah University of Science and Technology (KAUST)
Hong, Peiying	King Abdullah University of Science and Technology
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Optimal control and operation of water resources systems, Water quality and quantity management Abstract: The optimal control and operation of a Membrane Bioreactor (MBR) process by Nonlinear Model Predictive Control (NMPC) is investigated in this work. First, the Benchmark Simulation Model for MBR (BSM-MBR) provided by Maere et al. (2011) to simulate a membrane bioreactor has been extended to include a mathematical membrane fouling model where both reversible and irreversible fouling is taken into account. Then, an NMPC is designed by incorporating the nonlinear process model of BSM-MBR to control the dissolved oxygen concentration at a certain level while meeting input and other process constraints. The performance of the NMPC is evaluated under both constant influent scenarios and dynamic dry weather influent scenarios. The simulation results demonstrate that NMPC works better in the constant influent case than the dynamic influent scenario in terms of control performance.
Paper VI183-01.2
PDF · Video · Data-Driven Control of Water Reservoirs Using an Emulator of the Climate System (I)
Giuliani, Matteo	Politecnico Di Milano
Zaniolo, Marta	Politecnico Di Milano
Block, Paul	University of Wisconsin-Madison
Castelletti, Andrea	Politecnico Di Milano
Keywords: Optimal control and operation of water resources systems, Machine learning for environmental applications, Model reduction and dynamic emulation Abstract: This study presents a novel approach to combine a data-driven control strategy with an emulator model of the climate system in order to make the optimal control of water systems more flexible and adaptive to the increasing frequency and intensity of extreme events. These latter are often associated with global climate anomalies, which are difficult to model and incorporate into optimal control algorithms. In this paper, we compare a traditional control policy conditioned only on the reservoir storage with an informed controller that enlarges the state space to include the emulated dynamics of global Sea Surface Temperature anomalies. The multi-purpose operations of Lake Como in Italy, accounting for flood control and water supply, is used as a case study. Numerical results show that the proposed approach provides a 59% improvement in system performance with respect to traditional solutions. This gain further increases during extreme drought episodes, which are influenced by global climate oscillations.
Paper VI183-01.3
PDF · Video · Boundary Stabilization of a Reaction-Diffusion System Weakly Coupled at the Boundary (I)
Ghattassi, Mohamed	King Abdullah University of Science and Technology (KAUST)
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Optimal control and operation of water resources systems, Dynamics and control Abstract: This study analyses the boundary stabilization of a system of two parabolic linear PDEs weakly coupled at the boundary. This model is motivated by heat transfer in a membrane distillation based desalination modeled by two-dimensional advection-diffusion equations coupled at the boundary. Based on some physical assumptions, the 2D model can be formulated as a 1D reaction-diffusion system. Two cases were studied: full and underactuated scenarios. In the full actuated case, a backstepping approach is used to map the plant to an exponentially stable target system. The well-posedness of the kernel equations is proved. Moreover, the actuation of only one of the parabolic equations has been considered. The standard backstepping transformations are again used to transform the initial plant to the desired target system where Lyapunov analysis is adequately used. Finally, a numerical example showing the performance of the proposed control design is presented.
Paper VI183-01.4
PDF · Video · Adaptive and Robust Control for Energy Efficiency Enhancement of a Parabolic Collector Powering Desalination System (I)
Alharbi, Mohammad	King Abdullah University of Science and Technology
Aljehani, Fahad	King Abdullah University of Science and Technology
N'Doye, Ibrahima	King Abdullah University of Science and Technology (KAUST)
Laleg, Taous-Meriem	King Abdullah University of Science and Technology (KAUST)
Keywords: Optimal control and operation of water resources systems, Water quality and quantity management Abstract: In this paper, an adaptive control strategy is proposed to enhance the energy production eciency under environmental changes. The control objective is to force the outlet temperature of a solar thermal collector uid to track the desired reference temperature regardless of the solar irradiance variations. An adaptive nonlinear control that combines an inner loop feedback control and an outer loop model-free control strategy is proposed to ensure asymptotic convergence of the tracking error. The proposed adaptive control strategy is applied to an approximate bilinear model derived from the heat transfer equation. Numerical simulations are presented to illustrate the performance of the control strategy in terms of tracking accuracy and settling time. Furthermore, the improvement in energy production is highlighted through a powering thermal membrane distillation based desalination in increasing water production.
Paper VI183-01.5
PDF · Video · State Estimation in 2D Hydrological Models Using Lagrangian Sensors and Low Resolution Elevation Maps (I)
Affan, Affan	Lahore University of Management Sciences
Nasir, Hasan	The University of Melbourne
Muhammad, Abubakr	LUMS School of Science & Engineering, Pakistan
Keywords: Hydroinformatics, Modeling and identification of environmental systems, Natural resources management Abstract: In this research work, the framework to estimate 2D spatio-temporal variation in hydrodynamic variables such as water velocity (m/s) and water level (m) in complex, large scale open channels has been investigated using Lagrangian sensors. The Lagrangian sensors are passive floating platforms, which report its GPS position along with the flow of water. The 2D Saint-Venant model is simulated using HEC-RAS simulation software, the geometrical details for HEC-RAS simulations are obtained using Digital Elevation Map (DEM) of Ravi river, Pakistan. For the system model, the non-linear 2D Saint-Venant model is augmented with a Lagrangian sensor motion model. For state estimation, the GPS position of the Lagrangian sensor along with the upstream water level is assimilated in the augmented model using an Ensemble Kalman Filter (EnKF) with suitable filtering parameters in MATLAB. The hydrodynamic variables and trajectory of the Lagrangian sensor are estimated with low error.
Paper VI183-01.6
PDF · Video · A VCG Mechanism for Demand Management of Irrigation Systems (I)
Hassan, Wasim	Center for Water Informatics and Technology, Lahore University O
Jaleel, Hassan	KAUST
Manzoor, Talha	Lahore University of Management Sciences
Muhammad, Abubakr	LUMS School of Science & Engineering, Pakistan
Keywords: Optimal control and operation of water resources systems, Water quality and quantity management Abstract: Global climate change has induced changes in snow covers and precipitation patterns leading to unreliable availability of surface water for agricultural usage. Moreover, the increasing population has put additional strains on precious freshwater resources such as groundwater, leading to unsustainable practices of agriculture. Many studies suggest that demand based surface water management instead of supply based management may greatly mitigate the problem of supply-side fluctuations. Moreover, the rigidity of supply-based distribution rosters and fixed tariffs may be overcome using flexible pricing schemes. In this work, we propose a demand-driven allocation scheme for irrigation canal water enabled by the use of precision sensor technologies. The allocation is coupled with an auction based pricing mechanism. In the proposed approach, the demand can be met using surface water from an irrigation canal network, which is regulated by a principal agent such as a regulatory authority. In the face of shortage, the farmers resort to expensive pumping of non-renewable groundwater to meet their demand. A cropping season is divided into equal slots of fixed duration. At the beginning of each time slot, the principal-agent solicits the valuations of the farmers and sorts the bids received from the players in decreasing order and starts fulfilling the demands from the top. The principal agent uses Vickrey Clarke Groves (VCG) mechanism to compute the payments. The VCG mechanism for payments ensures user truthfulness. Our simulation results demonstrate that under certain realistic assumptions, this mechanism can increase profitability by reducing costs, help decrease groundwater pumping and conserve the surface water.
Paper VI183-01.7
PDF · Video · Full-Scale Seawater Reverse Osmosis Desalination Plant Simulator
Elnour, Mariam	Qatar University
Meskin, Nader	Qatar University
Khan, Khaled M.	Qatar University
Jain, Raj	Washington University in St. Louis
Zaidi, Syed Javaid	Qatar University
Siddiqui, Hammadur	Qatar University
Keywords: Model validation Abstract: Reverse Osmosis (RO) is an evolving membrane-based technology for water desalination that started to gain increased popularity in the light of the increased global water demand due its high eciency and low carbon footprint. This paper presents a full-scale Seawater Reverse Osmosis (SWRO) desalination plant simulator using MATLAB/Simulink which is a user-freidnly and commonly used simulation software. The simulator has been validated using the operational data from a local plant and it allows simulating the system behavior under different operating conditions with high exibility and minimal cost. It can be used to analyze the plant performance under dierent operating conditions, for health monitoring applications, and for research in the cybersecuity area.
Paper VI183-01.8
PDF · Video · LSTM-Based IMC Approach Applied in Wastewater Treatment Plants: Performance and Stability Analysis
Pisa, Ivan	Universitat Autònoma De Barcelona
Morell, Antoni	Universitat Autònoma De Barcelona
Vicario, Jose L.	Universidad Autònoma De Barcelona
Vilanova, Ramon	Universitat Autònoma De Barcelona
Keywords: Data-based control, Robust control Abstract: Wastewater treatment plants are industries where the reduction of residual water pollutant concentrations is performed. These kind of industries are characterised by applying highly complex and nonlinear biochemical and biological processes. Thus, some of the concentrations involved in these processes have to be controlled to assure that they are maintained at a given set-point. For that reason, different control strategies such as Proportional Integral (PI) controllers, Model Predictive Controllers (MPC), Fuzzy Logic or Internal Model Controllers (IMC) have been applied during the last years. However, the appearance of Artificial Neural Networks (ANNs) is changing this scenario. They have been adopted to predict certain WWTP parameters and then feed conventional controllers or even to implement some of them. Here, an IMC approach implemented uniquely with Long Short-Term Memory (LSTM) cells to model the direct and inverse models of the process under control is proposed. Furthermore, its stability conditions are computed adopting a data-based test since no mathematical expressions of the different models are considered. Results show that this approach is stable in the frequency region where it is operating. Besides, control performance shows that this IMC is able to significantly improve the Benchmark Simulation Model No.1 default PI control strategy.

VI183-02
Integrated Assessment Modelling for Environmental Systems	Open Invited Session
Chair: Volta, Marialuisa	University of Brescia
Co-Chair: van Nooijen, Ronald Robert Paul	Delft University of Technology
Organizer: Volta, Marialuisa	University of Brescia
Organizer: Guariso, Giorgio	Politecnico Di Milano
Organizer: van Nooijen, Ronald Robert Paul	Delft University of Technology
Organizer: Robba, Michela	University of Genova
Organizer: Minciardi, Riccardo	Univ of Genova
Organizer: Peres, Francois	ENIT-INPT Université Toulouse Midi-Pyrénées
Organizer: Carnevale, Claudio	University of Brescia
Organizer: Sun, Liangliang	Shenyang Jianzhu University
Organizer: Niamir, Leila	University of Twente
Paper VI183-02.1
PDF · Video · Valuing the Cost of Delayed Energy Actions (I)
Guariso, Giorgio	DEIB
Sangiorgio, Matteo	Politecnico Di Milano
Keywords: Climate change impact and adaptation measures, Environmental decision support systems, Air quality planning and control Abstract: Most of the building stock in Europe and, in particular, in Lombardy, North of Italy, were built without sufficient attention to energy efficiency. It must be restructured to spare energy, fuel costs, and emissions of traditional pollutants and GHGs. The paper defines an optimization problem that determines the most cost-effective interventions and where they should be actuated, considering different scenarios of evolution of economy and technology. The results are compared with real data, showing that the current pattern of adoption of energy-saving measures is definitely slower than desirable. The economic loss due to such a delayed adoption may reach billions of euros.
Paper VI183-02.2
PDF · Video · Vehicle Fleet Electrification: Impacts on Energy Demand, Air Quality and GHG Emissions. an Integrated Assessment Approach (I)
De Angelis, Elena	Università Degli Studi Di Brescia
Turrini, Enrico	Università Degli Studi Di Brescia
Carnevale, Claudio	University of Brescia
Volta, Marialuisa	University of Brescia
Keywords: Environmental decision support systems, Air quality planning and control, Risk analysis, impact evaluation Abstract: Transport sector is responsible for 25% of European GHG emissions, furthermore it has high impacts on air pollution at various scales. Electric mobility is growing fast and it could be effective in reducing road transport GHGs and pollutant emissions, but its potential depends on the energy mix used to produce electricity. In this paper an Integrated Assessment Model is proposed to analyze the energetic transition to an electric vehicle fleet at regional scale. Two scenarios are proposed to assess at the same time which are the impacts of the electric power sources and of the reduced road transport emissions. Results are presented in terms of CO2 emissions, air quality indexes, energy savings and health impacts.
Paper VI183-02.3
PDF · Video · Optimal Coordination of Buildings and Microgrids by an Aggregator: A Bi-Level Approach (I)
Ferro, Giulio	University of Genoa
Minciardi, Riccardo	University of Genova
Parodi, Luca	University of Genoa
Robba, Michela	Università Degli Studi Di Genova
Rossi, Mansueto	Università Degli Studi Di Genova
Keywords: Planning and management for participatory decision making, Environmental decision support systems, Model reduction and dynamic emulation Abstract: The introduction of renewables, distributed generation, microgrids, electric vehicles, and new market actors, such as aggregators, have led to a remarkable change in the power network. To address the issues that such a profound modification implies on a modern energy system, here a new hierarchical architecture is presented. Specifically, the proposed approach considers the case of an aggregator of consumers in the balancing market, in which incentives for local users (i.e., microgrids, buildings) are considered as well as flexibility assessment for demand response, and CO2 emissions. The main innovation is related to the overall architecture and to the formalization of the upper level decision problem that aims at coordinating local users in a democratic way, while, at the lower level, consumers want to track the aggregator's reference values performing demand response programs. The approach is applied to a real case study.
Paper VI183-02.4
PDF · Video · Multi-Objective Optimal Control of a Simple Stochastic Climate-Economy Model (I)
Carlino, Angelo	Politecnico Di Milano
Giuliani, Matteo	Politecnico Di Milano
Tavoni, Massimo	RFF-CMCC-EIEE and Politecnico Di Milano
Castelletti, Andrea	Politecnico Di Milano
Keywords: Climate change impact and adaptation measures, Environmental decision support systems Abstract: Integrated assessment modelling of climate change aims to provide quantitative solutions to inform international climate policy by employing models where socio-economic and climatic systems are integrated. Among these models, DICE (Dynamic Integrated Climate-Economy), is used to perform cost-benefit analysis that returns as output the optimal emission reduction pathway. The model makes some important assumptions: future socio-economic and climate system evolution is deterministic and economic damages of climate change are a quadratic function of the atmospheric temperature. In this study, propose a multi-objective stochastic optimal control problem formulation of the DICE model in order to account for stochastic disturbances and to align with physical targets posed by international agreements on climate change mitigation. The solutions are control policies that can handle stochastic disturbances outperforming the static inter-temporal optimization approach traditionally adopted. Moreover, such control policies are able to deal with multiple objectives making explicit the trade-offs between economic and environmental objectives.
Paper VI183-02.5
PDF · Video · A Predictive Control Approach for Air Quality Management (I)
Carnevale, Claudio	University of Brescia
De Angelis, Elena	Università Degli Studi Di Brescia
Finzi, Giovanna	University of Brescia
Mansini, Renata	University of Brescia
Tagliani, Franco Luis	University of Brescia
Turrini, Enrico	Università Degli Studi Di Brescia
Volta, Marialuisa	University of Brescia
Keywords: Air quality planning and control, Environmental decision support systems, Modeling and identification of environmental systems Abstract: The control of critical pollutant events has become one of the most relevant problems that the Local Authorities need to manage, in order to limit population exposure to high pollutant levels. The problem of the selection of suitable short terms plans allowing to maintain the pollutant concentrations under a certain threshold is particularly difficult due to the strong nonlinearity and due to the high number of parameters (sometimes not manageable, as in the case of meteorological conditions) that can affect the concentrations at a certain time. In order to help Local Authorities in taking these decision, suitable Integrated assessment Models (IAMs) have to be formalized and implemented. In this work, the formalization and implementation of an IAM for the selecting of short-term actions is presented. The system is based on a forecasting phase and on a receding horizon approach for the selection of suitable emission control actions. The system has been applied with encouraging results to the management of PM10 levels over a domain including the metropolitan area of the city of Brescia in Lombardy.
Paper VI183-02.6
PDF · Video · Remediation of Accidental River Pollution: Strategies Based on the Use of Reservoirs (I)
En-Nasyry, Alae	Laboratoire Génie De Production, LGP, Université De Toulouse, In
Chiron, Pascale	Université De Toulouse, INP-ENIT (Ecole Nationale d'Ingénieurs D
Archimede, Bernard	Universite De Toulouse, Laboratoire GeniedeProduction, Ecole Nati
Keywords: Water quality and quantity management, Environmental decision support systems, Modeling and identification of environmental systems Abstract: The origins of water pollution are numerous, they cause alterations due to their high load of dissolved substances, micropollutants and toxic substances. Many studies have focused on the implementation of remediation measures for these types of pollution. In this work, the case of rivers subject to accidental pollution and the use of reservoirs for its remediation is studied. Two strategies are implemented: the storage of pollutants in the reservoirs and the dilution of pollutants by injecting in the river clear water from reservoirs. Both methods are applied to a river with one reservoir, and their impacts are studied for different flow levels

VI183-03
Predictive Control of Large-Scale Water Systems	Open Invited Session
Chair: Feliu, Vicente	Univ of Castilla-La Mancha
Co-Chair: Maestre, Jose M.	University of Seville
Organizer: Duviella, Eric	Ecole Des Mines De Douai
Organizer: Lefevre, Laurent	Univ. Grenoble Alpes
Organizer: Ocampo-Martinez, Carlos	Universitat Politecnica De Catalunya (UPC)
Organizer: Maestre, Jose M.	University of Seville
Paper VI183-03.1
PDF · Video · Robust Fractional Order Control of a Pool of a Main Irrigation Canal in Submerged Flow Condition (I)
Gharab, Saddam	UCLM
Feliu, Vicente	Univ of Castilla-La Mancha
Keywords: Optimal control and operation of water resources systems, Modeling and identification of environmental systems Abstract: This work addresses the robust control of a pool of a main irrigation canal working in a submerged flow condition. A laboratory prototype of hydraulic canal at the University of Castilla-La Mancha is used in this study. A series connection of a non-linear static block and a linear first order plus time-delay system is proposed to model the dynamics of such process for all the considered operating regimes. The gain variations in function of the operating regimes are counted and corrected by using a gain scheduling block that inverts the before nonlinearity. However, a residual gain variation remains, whose effect is corrected by a fractional-order PI controller that is robust to process gain changes. Such controller is tuned to make the closed-loop system fulfill two temporal specifications: (a) a desired overshoot, obtained defining an equivalent phase margin frequency specification and (b) a desired settling time, obtained defining an equivalent gain crossover frequency specification. Moreover, a third specification is defined: the isophase margin condition, which accounts for the changes in the gain. The simulated results of our canal show the adequate performance of this control system.
Paper VI183-03.2
PDF · Video · Distributionally Robust Stochastic Optimal Water Flow and Risk Management (I)
Guo, Yi	The University of Texas at Dallas
Summers, Tyler	University of Texas at Dallas
Keywords: Real time control of environmental systems, Optimal control and operation of water resources systems, Risk analysis, impact evaluation Abstract: We present a computationally efficient framework to solve a multi-stage optimal water flow (OWF) problem with stochastic water demands. The proposed framework explicitly considers the feedback control policies and adjustable water flow with forecast errors over a planning horizon. The objective is to find an optimal operation schedule of controllable devices (e.g., pumps and valves) to trade off operational performance, such as economic efficiency, safety, and smoothness, and risk of constraint violations. We compute feedback policies that are robust to forecast errors in order to accommodate the fluctuating water demands. Given a probabilistic description of forecast errors, our formulations provide two broad approaches based on Conditional Value-at-Risk (CVaR) and distributionally robust optimization (DRO) that offer alternatives to the existing stochastic OWF formulations based on chance-constrained and robust optimization. Numerical case studies on a three-tank water network demonstrate that the proposed framework achieves effective and explicitly adjustable trade offs between operational efficiency and constraint violation risk.
Paper VI183-03.3
PDF · Video · Multi-Layer Model Predictive Control of Inland Waterways with Continuous and Discrete Actuators (I)
Segovia, Pau	IMT Lille Douai
Duviella, Eric	IMT Lille Douai
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Keywords: Real time control of environmental systems, Optimal control and operation of water resources systems, Hydroinformatics Abstract: This work presents the design of a three-layer control strategy to regulate the water levels in inland waterways. The upper layer allows to take into account different operating modes according to the occurrence of certain events. The intermediate layer is concerned with the design of the several controllers, one for each mode, as well as an observer that estimates both the states and the disturbances that affect the system. Finally, the lower layer solves an optimization problem that yields the scheduling of a set of discrete actuators that best approximates the solution obtained in the intermediate layer. A real case study based on part of the inland waterways in the north of France is used to test the proposed approach and demonstrate its effectiveness.
Paper VI183-03.4
PDF · Video · Control-Oriented Modeling Approach for Open Channel Irrigation Systems (I)
Conde, Gregory	Universidad De Los Andes
Quijano, Nicanor	Universidad De Los Andes
Ocampo-Martinez, Carlos	Universitat Politecnica De Catalunya (UPC)
Keywords: Hydroinformatics, Water and food security, Water quality and quantity management Abstract: In irrigation, most of the water is transported by networks of open-channel irrigation systems (OCIS). In most cases, the OCIS are manually operated showing low efficiency. Then the incorporation of control strategies is one of the most practical ways to increase the efficiency of these systems. However, in order to design an appropriate control strategy, an accurate control-oriented model that can be used for analyses, simulation, design, and test of the OCIS under realistic scenarios is necessary. In OCIS, obtaining a control-oriented model is a challenge that has aroused interest in the related literature. In spite of the multiple research in modeling of OCIS, the development of control-oriented modeling approaches that describe the dynamic and nonlinear behaviors of OCIS with gate regulation structures, remains an open problem. In this paper, a modeling approach that describes the nonlinear and dynamical behaviors of OCIS using a mass and energy balance by channel is proposed, which is compared with two modeling approaches. The comparison has been performed with a test case proposed in the literature. The results show that the proposed modeling approach is better describing the nonlinear behavior of the OCIS and presents a simpler structure that can be used in the design and test of control, prediction, and estimation strategies for these type of systems.
Paper VI183-03.5
PDF · Video · Economic Nonlinear Predictive Control of Water Distribution Networks Based on Surrogate Modeling and Automatic Clustering (I)
Fiedler, Felix	TU Berlin
Cominola, Andrea	Technische Universität Berlin
Lucia, Sergio	TU Berlin
Keywords: Optimal control and operation of water resources systems, Real time control of environmental systems, Machine learning for environmental applications Abstract: The operation of large-scale water distribution networks (WDNs) is a complex control task due to the size of the problem, the need to consider key operational, quality and safety-related constraints as well as because of the presence of uncertainties. An efficient operation of WDNs can lead to considerable reduction in the energy used to distribute the required amounts of water, leading to significant economic savings. Many model predictive control (MPC) schemes have been proposed in the literature to tackle this control problem. However, finding a control-oriented model that can be used in an optimization framework, which captures nonlinear behavior of the water network and is of a manageable size is a very important challenge faced in practice. We propose the use of a data-based automatic clustering method that clusters similar nodes of the network to reduce the model size and then learn a deep-learning based model of the clustered network. The learned model is used within an economic nonlinear MPC framework. The proposed method leads to a flexible scheme for economic robust nonlinear MPC of large WDNs that can be solved in real time, leads to significant energy savings and is robust to uncertain water demands. The potential of the proposed approach is illustrated by simulation results of a benchmark WDN model.

VI183-04
Modeling, Monitoring, and Control of Water Resources Systems	Regular Session
Chair: Blesa, Joaquim	Universitat Politècnica De Catalunya (UPC)
Co-Chair: Kolechkina, Alla G.	Delft University of Technology
Paper VI183-04.1
PDF · Video · Water Distribution Networks Optimization: A Real Case Study
Zanoli, Silvia Maria	Università Politecnica Delle Marche
Astolfi, Giacomo	Università Politecnica Delle Marche
Orlietti, Lorenzo	I.process
Frisinghelli, Matteo	Novareti SpA, Rovereto Trento
Pepe, Crescenzo	Alperia Bartucci SpA
Keywords: Optimal control and operation of water resources systems Abstract: This paper presents a project aimed at the optimization of a water distribution network located in Trento (Italy). Several in-depth hydraulic studies have been conducted in order to perform hardware modifications through sectorization procedures. Advanced Process Control methods have been designed in order to optimally and automatically manage the net pressure and the scheduling of the involved pumping stations. Net pressure has been minimized through two-layer Model Predictive Control techniques, while advanced logics have been designed for the pumps scheduling. The developed Advanced Process Control system has been successfully installed on the considered network and the achieved results are here illustrated.
Paper VI183-04.2
PDF · Video · Leak-Diagnosis Approach for Water Distribution Networks Based on a K-NN Classification Algorithm
Bermúdez Hernández, José Roberto	Tecnológico Nacional De México/ IT Tuxtla Gutiérrez
Lopez-Estrada, Francisco-Ronay	Tecnológico Nacional De Mexico. Instituto Tecnológico De Tuxtla
Besancon, Gildas	Ense3, Grenoble INP
Torres, Lizeth	UNAM
Santos-Ruiz, Ildeberto	TecnolÓgico Nacional De México / Instituto TecnolÓgico De Tuxtla
Keywords: Optimal control and operation of water resources systems, Modeling and identification of environmental systems, Modeling and identification of environmental systems, Environmental decision support systems Abstract: This paper proposes an approach based on a k-Nearest Neighbour classification algorithm (k-NN) to identify regions in a water distribution network (WDN) that are affected under presence of leaks. The classification algorithm is trained with numerical data coming from a MATLAB simulator based on a dynamic model of the WDN that involve leaks in its formulation. Concretely, the training is done by using the numerical solutions of a dynamic model of the WDN under several leak cases. The dynamic model is formulated by taking into account typical assumptions of the rigid water column (RWC) theory and using the graph theory. The proposed approach was evaluated in a hydraulic pilot plant.
Paper VI183-04.3
PDF · Video · Stability of a Class of Controllers for a Sequence of Canals and Structures
van Nooijen, Ronald Robert Paul	Delft University of Technology
Kolechkina, Alla G.	Delft University of Technology
Keywords: Real time control of environmental systems, Natural and environmental systems, Optimal control and operation of water resources systems Abstract: Networks of open channels form an important category of environmental systems. They are used not only to transport irrigation and drainage water, but also as highways for barges transporting raw materials and goods. Automatic control of these systems poses specific problems. A local stability analysis for an open canal that is split into several parts by sluice gates under discrete time control is proposed. Theoretical justification is provided, and the method is tested for a simple controller. The analysis allows the establishment of local stability of a series of canals when equipped with a controller from a large class, linear and non-linear. The analysis is based on the analysis of the eigenvalues of a matrix derived from the controlled system that is small enough to allow for parameter optimization.
Paper VI183-04.4
PDF · Video · Planning, Testing and Commissioning of Automation Solutions for Waste Water Treatment Plants Using Simulation
Alex, Jens	Ifak Institut für Automation und Kommunikation e.V.
Hübner, Christian	Ifak Institut für Automation und Kommunikation e.V.
Förster, Leonie	Ifak Institut für Automation und Kommunikation e.V.
Keywords: Real time control of environmental systems, Optimal control and operation of water resources systems Abstract: In Germany, the EU and worldwide, the demands placed on wastewater treatment plants in terms of energy efficiency, cleaning performance, operational reliability and minimization of operating costs continue to grow. This results in an increasing demand for automation solutions with high quality requirements that are well integrated with process engineering and equipment specification. Integrated planning of automation technology in combination with mechanical equipment and process engineering requires the use of simulation tools in planning. A once existing simulation model of a plant can then not only be used for planning and optimization, but also for further questions about the life cycle of the plant. The automation concept simulated during the planning can be used, for example, as a precise requirement specification for the programming of the automation. A powerful application scenario is the virtual commissioning of the automation system.
Paper VI183-04.5
PDF · Video · Lessons Learnt from the Application of a Participatory Modelling Approach in the Framework of a River Restoration Project: Case of the Gave De Pau River, Hautes-Pyrénées, France
Yassine, Rabab	Toulouse INP ENIT
Peres, François	ENIT-INPT Université Toulouse Midi-Pyrénées
Frysou, Olivier	PLVG
Roux, Hélène	Institut De Mécanique Des Fluides De Toulouse (IMFT) - Universit
Cassan, Ludovic	INP Toulouse
Keywords: Risk analysis, impact evaluation, Natural and environmental systems, Environmental decision support systems Abstract: Considering the diversity of criteria and stakes, the uncertain and stochastic nature of the physical phenomena and the multi-scale aspects to be taken into account, a river restoration project can be viewed as a complex problem. Many river managers and scientific researchers have been investigating the subject as river restoration projects deal with significant safety, environmental and economic issues. A project manager can hardly be an expert in all the disciplines to consider to come up with the optimal solution that satisfies all the involved dimensions. The integration of both local stakeholders with field experience and technicians and academics with scientific knowledge can hence benefit river restoration projects. The aim of this paper is to present an approach that considers the integration of various stakeholders engaged in river restoration issues to gather their knowledge and define the solutions that offer decent compromise considering all the dimensions involved. To this end, a group of stakeholders identified according to specific selection criteria were engaged in a modeling approach based on Bayesian Networks (BNs). BNs are increasingly being used as tools for decision-making in river management due to their natural ability to adjust to complex multi-criteria systems with multiple interactions. A participatory approach based on BNs that led to the elaboration of causal graphs is introduced in this paper. This study considers the combination of both physical knowledge associated to river systems and the relation constraints to river users and managers. The work is conducted in the framework of the restoration project of the "Lac des Gaves", an artificial lake that undergone years of sediment extractions over the past century and important flood events that highlighted several numbers of impairments.
Paper VI183-04.6
PDF · Video · Dynamic Model for a Water Distribution Network: Application to Leak Diagnosis and Quality Monitoring
Delgado Aguiñaga, Jorge Alejandro	Universidad Del Valle De México
Becerra López, Fernando Ignacio	Universidad De Guadalajara
Torres, Lizeth	UNAM
Besancon, Gildas	Ense3, Grenoble INP
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Jiménez Magaña, Martín	FES, UNAM
Keywords: Water quality and quantity management, Optimal control and operation of water resources systems, Hydroinformatics Abstract: This paper presents a model based on the rigid water column (RWC) theory to describe the flow and the decay of chlorine in water distribution networks (WDNs), which can be used for developing tools to diagnose leaks and estimate chlorine concentrations. The model includes the continuity equation for each node of the network such that i) the relation of the flow rates entering and leaving the nodes is explicit, and ii) the computation of pressures and flow rates can be simultaneously done. The chlorine decay in each node and in each pipeline section of the WDN is predicted from the computed flow rates by using the third order accurate Warming-Kutler-Lomax (WKL) method. At the end of this paper, it is shown that the chlorine decay rate is well predicted by using the WKL method according to a comparison with simulations results obtained by using the EPANET-MSX software. Furthermore, it is shown that several single leak-diagnosis scenarios can be successfully solved by using an improved sensitivity matrix method together with the proposed model.
Paper VI183-04.7
PDF · Video · A Hybrid Model Based on Stacking and Multi-Correction Mechanisms for Urban Water Demand Prediction
Lan, Yang	Shanghai Jiao Tong University
Wang, Jingcheng	Shanghai JiaoTong Univ
Bai, Miaoshun	Shanghai Municipal Engineering Design Institute (Group)CO., LTD
Brahmia, Ibrahim	Shanghai Jiao Tong University
Xu, Haotian	Shanghai Jiao Tong University
Hu, Piao	Shanghai Jiaotong University
Long, Yuhao	Shanghai Jiaotong University
Zhang, Yeming	Shanghai Municipal Engineering Design Institute (Group)CO., LTD
Keywords: Water supply and distribution systems, Konwledge discover (data mining), Intelligent system techniques and applications Abstract: Water demand prediction is the key link for the effective operation of urban intelligent water supply system. Since the non-linearity and complex variability of water consumption, it is difficult for traditional water demand prediction models to guarantee high accuracy for a long period. Different holiday types and even tiny changes in temperatures can affect urban water demand seriously. This paper proposes a Stacking-based hybrid model which integrates multi-correction mechanisms to address these problems. A better stacking model is proposed to minimize the generalization error. The stability and reliability of predictions are improved through the design of multi-correction mechanisms such as high temperature weather compensation feature, holiday-type correction model and water quantity fluctuation correction model. Comparing different models before and after stacking also before and after correcting, the prediction accuracy of the proposed hybrid model is much higher and the predictions are more stable and reliable.
Paper VI183-04.8
PDF · Video · First Results in Leak Localization in Water Distribution Networks Using Graph-Based Clustering and Deep Learning
Romero, Luis	UPC
Blesa, Joaquim	Universitat Politècnica De Catalunya (UPC)
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Cembrano, Gabriela	CSIC-UPC
Trapiello, Carlos	UPC
Keywords: Fault diagnosis, Hydroinformatics, Monitoring Abstract: This paper presents a methodology for the localization of leaks in water distribution networks (WDN) by means of the combination of a deep learning approach and a graph-based clustering technique. A data set for all possible leak locations is generated from pressure measurements and utilized to feed an image encoding process based on the Gramian Angular Field (GAF) technique, hence producing an equivalent data set of images. The pressure measurements are generated through the WDN simulation engine EPANET. To accomplish the training stage, the network is iteratively segmented into clusters using the Graph Agglomerative Clustering (GAC) method, and a deep learning neural network is trained to correctly indicate the leak location at one of the created clusters by means of the image data set. Therefore, the achieved neural networks tree can be traversed through its different branches depending on each classification result, until the final cluster is reached.
Paper VI183-04.9
PDF · Video · Leak Localization in Water Distribution Networks Using Classifiers with Cosenoidal Features
Santos-Ruiz, Ildeberto	TecnolÓgico Nacional De México / Instituto TecnolÓgico De Tuxtla
Blesa, Joaquim	Universitat Politècnica De Catalunya (UPC)
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Lopez-Estrada, Francisco-Ronay	Tecnológico Nacional De Mexico. Instituto Tecnológico De Tuxtla
Keywords: Fault diagnosis, Hydroinformatics, Optimal control and operation of water resources systems Abstract: This paper presents a leak localization approach for water distribution networks using classifiers with pressure residuals as input features. This approach is based on applying a non-linear transformation to the residuals of the node pressures to increase the separability of the leak classes. The transformed features can be interpreted as the direction cosines in the subspace spanned by the residuals of the measured pressures. In order to illustrate the method, different tests were performed with MATLAB applying four different classification algorithms on a synthetic dataset obtained from an EPANET model of the Hanoi network. Then, by considering the cosenoidal features, a significant improvement in the leak location error was achieved. In this way, the leak location error decreases by more than 97% compared to the use of residual features when accurate measurements are used, and about 50% when noisy measurements with 60dB SNR are used.

VI183-05
Natural and Environmental Systems	Regular Session
Chair: Botelho, Silvia	Universidade Federal Do Rio Grande
Co-Chair: Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Paper VI183-05.1
PDF · Video · A Minimal Soil Moisture Model Fit to Environmental Data from Multiple Pasture Locations in Taranaki, New Zealand
Knopp, Jennifer L.	University of Canterbury
Keywords: Modeling and identification of environmental systems, Modeling and control of agriculture, Environmental decision support systems Abstract: The application of models and precision technology to optimize productivity and sustainability is increasingly common in agriculture. Soil moisture (SM) modelling is an important component of pasture growth modelling, or for runoff/catchment modelling. This paper examines a minimal modelling approach for SM modelling using soil moisture data from 10 locations in the Taranaki region, New Zealand. Several simple compartment-based models are tested with/without daylight and temperature effects on terms relating to SM loss, and gain from rainfall. It was found that SM dynamics differed from site to site, with a simple loss dynamic proportional to current SM level dominating in soils with moisture levels above field capacity. A SM loss term modified by temperature and day length described sites where SM was below field capacity. Thus, a simple model was able to fit locational data, and distinguished between differing dynamics based on SM level relative to field capacity. This is model is a first step towards a model-predictive approach to soil moisture modelling requiring a minimum of measured inputs.
Paper VI183-05.2
PDF · Video · Observer Design for State and Parameter Estimation in a Landslide Model
Mishra, Mohit	Univ. Grenoble Alpes, CNRS, Grenoble INP - Institute of Engineer
Besancon, Gildas	Ense3, Grenoble INP
Chambon, Guillaume	Univ. Grenoble Alpes, IRSTEA, UR ETGR, Grenoble, France
Baillet, Laurent	Univ. Grenoble Alpes, CNRS, ISTerre, Grenoble, France
Keywords: Natural and environmental systems, Modeling and identification of environmental systems, Environmental decision support systems Abstract: This paper presents an observer-based state and parameter estimation for the extended sliding-consolidation model of a landslide. This system is described by a pair of coupled Ordinary Differential Equation (ODE) and Partial Differential Equation (PDE), with a mixed boundary condition for the PDE. The coupling appears both in the ODE and in the Neuman boundary condition of the PDE. The observer consists of a copy of the PDE part of the system and Kalman-like observer for the ODE. It is shown to ensure exponential convergence of the state and parameter estimates by means of Lyapunov tool. Finally, a simulation result of the extended sliding-consolidation model is presented to illustrate the effectiveness of the proposed observer.
Paper VI183-05.3
PDF · Video · Model-Based Adaptive Filtering of Harmonic Perturbations Applied to High-Frequency Noninvasive Valvometry
de Figueiredo Barroso, Nelson	Inria
Ushirobira, Rosane	Inria
Efimov, Denis	Inria
Sow, Mohamedou	Université De Bordeaux
Massabuau, Jean-Charles	UMR CNRS 5805 EPOC - OASU, Bordeuax I
Keywords: Parameter and state estimation, Fault diagnosis, Monitoring Abstract: In this paper, a model-based adaptive filter is used to suppress electrical noise in a high-frequency noninvasive valvometry device, which is part of an autonomous biosensor system using bivalve mollusks valve activity measurements for ecological monitoring purposes. The proposed model-based adaptive filter uses the dynamic regressor extension and mixing method to allow a decoupled estimation of the parameters. Once the desired regression form of the output model is obtained, a fixed-time estimation approach is used to identify its parameters. By applying these two techniques, a flexible filter structure is obtained with the property of retaining the major relevant components of interest of the original valve activity signals, even in the case when the unwanted signal frequency components are in the same frequency range as the useful variables.
Paper VI183-05.4
PDF · Video · Comparison of Optical and Ultrasonic Methods for Quantification of Underwater Gas Leaks
Takimoto, Rogerio Yugo	Escola Politecnica Da Universidade De Sao Paulo
Matuda, Marcelo	Universidade De Sao Paulo
Lavras, Timoteo	Universidade De Sao Paulo
Adamowski, Julio Cezar	University of Sao Paulo
Sato, Andre Kubagawa	Escola Politecnica Da Universidade De Sao Paulo
Martins, Thiago de Castro	University of Sao Paulo
Tsuzuki, Marcos de Sales Guerra	University of Sao Paulo
Keywords: Water quality and quantity management, Hydroinformatics Abstract: The quantification of underwater gas leakage using optical and ultrasound technologies is presented. In the optical method, a high-speed camera is utilized, and the captured images are processed with segmentation techniques. The bubble is considered as an ellipsoid and its projected largest diameter is determined. The case of bubbles partial overlapping is also processed. In the ultrasound method, a ultrasonic linear array is used to capture images. For both methods, vertical speed, size of the bubbles, the bubble emission rate and the leak rate are measured. The results of the optical and acoustic methods are compared and analyzed.
Paper VI183-05.5
PDF · Video · Perna Perna Mussels Network As Pollution Biosensors of Oil Spills and Derivatives
Guterres, Bruna de Vargas	Federal University of Rio Grande
Guerreiro, Amanda da S.	Federal University of Rio Grande
Botelho, Silvia	Universidade Federal Do Rio Grande
Sandrini, Juliana Z.	Federal University of Rio Grande
Keywords: Bioresponses, Bio-signals analysis and interpretation, Natural and environmental systems Abstract: Since the availability of petroleum and derivatives has great impact over the world economy, the oil industry lies in both the formation and the maintenance of modern industrial economy. Petroleum exploration, transport, distribution and storage activities can compromise water resources and provide serious consequences to exposed organisms due to the risk of accidental spillage of oil and refinery effluents. Perna perna mussels are acknowledged for their sentinel characteristics being affected by slight environmental changes and one of the promising species in the aquaculture world. Thus, this study aimed to demonstrate that the behavior of Perna perna mussels is a suitable biomarker of exposure to petroleum and derivatives. The present research proposes the construction of an online aquatic pollution biosensor based on the behavioral analysis of Perna perna mussels network. Thirty-nine mussels instrumented with Hall Effect sensors and magnets were exposed to 0 (control), 5%, and 20% of Water-Accommodated Fraction (WAF) of Diesel S-500 for up to 42 hours. The sensors network outputs were used to evaluate the behavioral parameters average amplitude, filtration activity, transition frequency, amount of motion reversals and weighted average of the ten largest Fourier magnitudes after the first 12 hours of experiment using 6-hours intervals. The employment of the behavioral parameters weighted average of the ten largest Fourier magnitudes and transition frequency provided greater efficacy in distinguishing groups of animals exposed to contaminants in relation to the control group with significant differences in at least 80% of the analyzed intervals.

VI184
Bio and Ecological Systems - Biosystems and Bioprocesses
VI184-01 Trends in Control Theory at the Interface of Systems & Synthetic Biology   Open Invited Session, 16 papers
VI184-02 Modeling and Control of Bioprocesses   Regular Session, 16 papers

VI184-01
Trends in Control Theory at the Interface of Systems & Synthetic Biology	Open Invited Session
Chair: Khammash, Mustafa H.	Swiss Federal Institute of Technology (ETH)
Co-Chair: Waldherr, Steffen	KU Leuven
Organizer: Oyarzún, Diego A.	University of Edinburgh
Organizer: Waldherr, Steffen	KU Leuven
Organizer: Khammash, Mustafa H.	Swiss Federal Institute of Technology (ETH)
Paper VI184-01.1
PDF · Video · Robust Sensitivity Analysis for Uncertain Biochemical Networks: Some Vertex Results (I)
Blanchini, Franco	Univ. Degli Studi Di Udine
Colaneri, Patrizio	Politecnico Di Milano
Giordano, Giulia	University of Trento
Zorzan, Irene	University of Padova
Keywords: Modeling and identification, Microbial technology Abstract: We consider the problem of computing the sensitivity of uncertain biochemical networks in the presence of input perturbations around a stable steady state. The uncertain system parameters are assumed to take values in a hyperrectangle. Recent literature has shown that, for systems admitting the BDC-decomposition, this analysis can be efficiently carried out by means of vertex algorithms, namely by considering exclusively the vertices of the hyperrectangle in the parameter space. Here we consider a broader class of systems: totally multilinear systems, where any minor of the Jacobian matrix is a multilinear function of the uncertain parameters. For this broader class, we prove that analogous vertex results hold for assessing robust nonsingularity and for providing robust sensitivity bounds. We also discuss vertex-type approaches to robustly assess the assumed stability of the steady state.
Paper VI184-01.2
PDF · Video · Spatial Heterogeneity in Bacterial Cells (I)
Barajas, Carlos	Massachusetts Institute of Technology
Del Vecchio, Domitilla	MIT
Keywords: Modeling and identification Abstract: Commonly used models of genetic circuits assume a well-mixed ensemble of species. However, experimental data suggests that appreciable spatial heterogeneity exists in bacteria cells. There exists no unified modeling framework to capture this spatial phenomena. To this end, we model spatial heterogeneity inside bacterial cells and propose a simple framework that accounts for spatial information. In this document, we start with a generic spatial-temporal partial differential equitation (PDE) model. Then, we exploit time scale separation between diffusion and the reaction dynamics to derive a reduced model consisting solely of ordinary differential equations (ODEs). This result is then applied to study an enzymatic-like reaction. It is shown that spatial heterogeneity modifies the binding strength between two species that reversibly bind to each other. We show that the modified binding rate for certain cases can be larger or smaller than that of a well-mixed model. Therefore, this work takes a step forward towards creating a general and simple framework to model spatial heterogeneity in bacterial cells and thus improving the predictive power of current models that are used to design genetic circuits
Paper VI184-01.3
PDF · Video · Control Strategies for Sustained Oscillations in a Disrupted Biological Clock (I)
Chambon, Lucie	INRIA
Gouze, Jean-Luc	INRIA
Keywords: Dynamics and control Abstract: As many disorders have been correlated with dysfunctional biophysical rhythms, new therapies based on the control of clock functions are emerging for the slowdown of disease progression. In this context, a general disrupted biological clock is modeled by the canonical form of a genetic negative feedback loop. When the unique fixed point of this N-dimensional non-linear differential system is stable, the model reproduces accurately the damped oscillations observed in a damaged oscillator. First, a synthetic modification of the network is proved to generate sustained oscillations and allow to recover a functional clock. The desired periodic trajectories are obtained by destabilizing the fixed point of the model and monotone properties are applied for global results. In a limit case, this modification of the loop is shown to be equivalent to an external piecewise constant control law, supporting the conjecture that simple qualitative control strategies may be able to guarantee sustained oscillations. From the perspective of a biological implementation, this result is promising as these types of control are well adapted to experimental constraints. To support this theoretical work, the methods are applied to the disrupted circadian clock observed in human cancer cells.
Paper VI184-01.4
PDF · Video · Robustness Analysis of Combined Transcriptional and Translational Resource Allocation Controllers (I)
Darlington, Alexander	University of Warwick
Bates, Declan G.	Univ. of Warwick
Keywords: Dynamics and control, Kinetic modeling and control of biological systems, Microbial technology Abstract: Recent work on engineering synthetic cellular circuitry has shown that non-regulatory interactions brought about through competition for shared gene expression resources, such as RNA polymerase and ribosomes, can result in degraded performance or even circuit failure. Transcriptional and translational resource allocation controllers based on orthogonal `circuit-specific' gene expression machineries have been separately designed to enforce modularity and improve circuit performance. However, combining these controllers can result in instability. Here we apply tools from robust control theory to study the impact of uncertainty due to experimental implementations on the operation of dual transcriptional-translational resource allocation controllers.
Paper VI184-01.5
PDF · Video · Study of Piecewise Multi-Affine Models for Genetic Regulatory Networks Via a Lyapunov Approach: An LMI Framework (I)
Pasquini, Mirko	Imperial College
Angeli, David	Imperial College
Keywords: Dynamics and control, Kinetic modeling and control of biological systems Abstract: In this work we study convergence properties of Piecewise Multi-Affine models of genetic regulatory networks, by means of a Lyapunov approach. These models, quantitatively more accurate than their Piecewise Affine counterpart, are obtained by a Piecewise Linear approximation of sigmoids regulation functions. In this work, using a linear matrix inequalities framework, we are able to find, if one exists subject to a box partitioning of the state space, a Piecewise Quadratic Lyapunov function, which is non-increasing along any system trajectory. In the first part of the paper we describe the considered model, defining and motivating the hyper-rectangular partition of the state space, while in the second part, using a result on the expression of multi-affine functions on an hyper-rectangle, we can define a set of linear matrix inequalities, whose solution gives the description of a piecewise quadratic Lyapunov function for the system. Convergence properties based on such functions are discussed and a numerical example will show the applicability of the results.
Paper VI184-01.6
PDF · Video · Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations (I)
Paulino, Nuno M. G.	University of Warwick
Foo, Mathias	Coventry University
de Greef, Tom F. A.	Eindhoven University of Technology
Kim, Jongmin	Pohang University of Science and Technology
Bates, Declan G.	Univ. of Warwick
Keywords: Dynamics and control, Modeling and identification Abstract: Chemical reaction networks based on catalysis, degradation, and annihilation may be used as building blocks to construct a variety of dynamical and feedback control systems in Synthetic Biology. DNA strand-displacement, which is based on DNA hybridisation programmed using Watson-Crick base pairing, is an effective primitive to implement such reactions experimentally. However, experimental construction, validation and scale-up of nucleic acid control systems is still significantly lagging theoretical developments, due to several technical challenges, such as leakage, crosstalk, and toehold sequence design. To help the progress towards experimental implementation, we provide here designs representing two fundamental classes of reference tracking control circuits (integral and state-feedback control), for which the complexity of the chemical reactions required for implementation has been minimised. The supplied 'minimally complex' control circuits should be ideal candidates for first experimental validations of nucleic acid controllers.
Paper VI184-01.7
PDF · Video · Optimizing Bacterial Resource Allocation: Metabolite Production in Continuous Bioreactors (I)
Yabo, Agustín Gabriel	INRIA
Gouze, Jean-Luc	INRIA
Keywords: Dynamics and control, Modeling and identification, Industrial biotechnology Abstract: We show preliminary results addressing the problem of resource allocation in bacteria in the continuous bioreactor framework. We propose a coarse-grained self-replicator dynamical model that accounts for the microbial population growth inside a continuous bioreactor, and we study its asymptotic behavior through a dynamical systems analysis approach, in order to provide conditions for the persistence of the bacterial population. We then study the two most relevant cases of steady-state production in this scheme: 1) biomass production, classical in high-tech industrial processes as well as in research environments; and 2) metabolite production through the introduction of a heterologous metabolic pathway. Both problems are explored in terms of the internal allocation control-which can be externally disrupted-and the constant volumetric flow of the bioreactor; and analyzed through a numerical approach. The resulting two-dimensional optimization problem is defined in terms of Michaelis-Menten kinetics using the parameter values of previous works, and taking into account the constraints for the existence of the equilibrium of interest.
Paper VI184-01.8
PDF · Video · A Genetic Optimizer Module for Synthetic Biology (I)
Gyorgy, Andras	New York University Abu Dhabi
Menezes, Amor	Univ. of Florida
Arcak, Murat	UC Berkeley
Keywords: Dynamics and control, Cellular, metabolic, cardiovascular, pulmonary, neuro-systems, Scheduling, coordination, optimization Abstract: Living organisms must fine-tune a vast array of complex processes for optimal performance, including metabolism, respiration, and growth. Performance decisions are intertwined due to a limited availability of resources, and involve a large collection of unknown trade-offs. Although synthetic biology enables us to control gene expression, we currently lack an ability to automatically tune expression to an optimal level online, to maximize/minimize a user-defined performance metric (e.g., biomass production or growth rate) in a way that is responsive to changing environmental conditions. To attain such tuning, we present an optimizer module that can be constructed from standard genetic parts. Our feedback control module is inspired by classical gradient-based numerical methods, but conforms to unique biological constraints such as non-negative concentration signals. Importantly, we show that the performance of our optimizer module is robust to parameter variations in an unknown and time-varying plant and objective function, as well as to disturbances that affect the optimizer itself.
Paper VI184-01.9
PDF · Video · Automatic Analysis of Large-Scale Nanopore Data Using Hidden Markov Models
Zhang, Jianhua	OsloMet - Oslo Metropolitan University
Liu, Xiuling	East China University of Science and Technology
Keywords: Bioinformatics, Parameter and state estimation, Microbial technology Abstract: In this paper we developed a modified Hidden Markov Model (HMM) to analyze the raw nanopore experimental data. Traditionally, prior to further analysis the measured nanopore data must be pre-filtered, but the filtering usually distorts the waveform of the blockage current, especially for rapid translocations and bumping blockages. The HMM is known to be robust with respect to strong noise and thus suitable for processing the raw nanopore data, but its performance is susceptible to the setting of initial parameters. To overcome this problem, we use the Fuzzy c-Means (FCM) algorithm to initialize the HMM parameters in this work. Then we use the Viterbi training algorithm to optimize the HMM. Finally, both the simulated and experimental data analysis results are presented to show the effectiveness of the proposed method for detection of the nanopore current blockage events in analytical chemistry.
Paper VI184-01.10
PDF · Video · Inference of the Statistics of a Modulated Promoter Process from Population Snapshot Gene Expression Data (I)
Cinquemani, Eugenio	INRIA Grenoble - Rhône-Alpes
Keywords: Bio-signals analysis and interpretation, Kinetic modeling and control of biological systems, Parameter and state estimation Abstract: In previous work, we have developed mathematical tools for the analysis of single-cell gene expression data from population snapshots, and an inference algorithm for the estimation of stationary statistics of promoter activation. In this work, we address the inference problem in the nonstationary case of modulated processes. This is of special relevance to control scenarios, where an exogenous input modulates the time evolution of promoter activation. We provide an effective method for the computation of the output statistics of a reaction network with a nonstationary, causal input process of modulated form. Based on this we devise and demonstrate an algorithm for the reconstruction of the promoter (input) process statistics from snapshot data.
Paper VI184-01.11
PDF · Video · Extremum Seeking Control of a Three-Stage Anaerobic Digestion Model
Sbarciog, Mihaela	KU Leuven
Vande Wouwer, Alain	Université De Mons
Van Impe, Jan F. M.	KU Leuven
Dewasme, Laurent	Université De Mons
Keywords: Dynamics and control, Bioenergy production, Wastewater treatment processes Abstract: Anaerobic digestion systems are of increasing interest as they are able to produce biogas while treating waste/wastewater. However, their dynamics is complex and not fully understood, which makes their operation and optimization difficult. In this paper, an extremum seeking control algorithm is applied to a three-stage anaerobic digestion system to maximize the outflow rate of methane. In a first stage, the stability analysis of the three-stage model is performed, which provides valuable information on the type of steady states the system possesses, the occurrence of the optimal steady state and good practices to successfully operate the system. In a second stage, an extremum seeking controller, which employs a recursive least-squares algorithm for block-oriented models, is implemented and tested on the anaerobic digestion model. Simulation results show that the proposed controller globally stabilizes the process dynamics at the optimal operating point. Compared to the classical extremum seeking algorithms, the proposed technique allows for a faster convergence, in an imposed time period assigned by the designer.
Paper VI184-01.12
PDF · Video · Synchronisation of Yeast Cell Cycle through Quorum Sensing Coupling (I)
Perrino, Giansimone	Telethon Institute of Genetics and Medicine
di Bernardo, Diego	TIGEM
Keywords: Dynamics and control Abstract: The cell cycle is present in all cells of all species and it is of fundamental importance in coordinating all the steps required for cell replication, including growth, DNA replication and cell division. Budding yeast is an unicellular organism characterised by a mother cell that buds to generate a daughter cell at each cell cycle. Each cell in a population buds at a different time. Despite its importance in biological applications, such as unravelling cell-cycle machinery mechanisms and production of valuable bioproducts, at present no yeast strain is capable of budding synchronously. To overcome this problem, we used control theory to propose a strategy to modify the yeast cell to endow it with the ability to synchronise its cell cycle across the population. Our strategy relies on a quorum sensing molecule diffusing freely in and out of the cell. The quorum sensing molecule is produced only during a specific phase of the cell cycle and couples the cell-cycle across the cell population. Here we model the proposed strategy with ordinary differential equations and numerically simulate it to demonstrate the feasibility of such an approach.
Paper VI184-01.13
PDF · Video · The Turnpike Property in Maximization of Microbial Metabolite Production (I)
Caillau, Jean Baptiste	University of Nice Sophia-Antipolis
Djema, Walid	INRIA
Giraldi, Laetitia	Université Cote d'Azur, LJAD, INRIA Sophia-Antipolis
Gouze, Jean-Luc	INRIA
Maslovskaya, Sofya	INRIA
Pomet, Jean-Baptiste	INRIA
Keywords: Dynamics and control, Cellular, metabolic, cardiovascular, pulmonary, neuro-systems, Industrial biotechnology Abstract: We consider the problem of maximization of metabolite production in bacterial cells. Numerical methods showed that the major phase of the solutions for different initial states and final times is the singular regime which exhibits a special structure reminiscent of the turnpike phenomenon. We prove that singular trajectories indeed have the turnpike property by providing an estimate both on singular trajectories and on the associated controls. This result can be further used for construction of simple realistic suboptimal control strategies.
Paper VI184-01.14
PDF · Video · Comparative Analysis for Noise Propagation in a Coarse-Grained Model Linking Metabolism to Cellular Growth (I)
Borri, Alessandro	Istituto Di Analisi Dei Sistemi Ed Informatica "A. Ruberti" (IAS
Palumbo, Pasquale	University of Milano-Bicocca
Singh, Abhyudai	University of Delaware
Keywords: Modeling and identification, Metabolic engineering Abstract: Fluctuations in growth rate have been shown to be important drivers of phenotypic heterogeneity. So far they have been usually related to gene expression or enzymatic reactions, since the metabolism was supposed to average the mixture of many and different noisy reactions involved in it. On the other hand, single-cell experiments have recently highlighted how noise may well propagate also from metabolic reactions, and influence cellular growth rate. In this work, a coarse-grain model of the relationships linking cellular resources to growth rate and metabolism is investigated with respect to noise propagation. An incoherent feedforward control is exerted by growth rate on metabolic enzymes, since growth is supposed to positively control both metabolic enzymes production and degradation. Different noise sources have been addressed, affecting metabolic production, cellular resource clearance and production. Noise sources have been addressed one at a time, and noise propagation has been investigated by means of a Stochastic Hybrid System model, whose shape is modulated according to the different noise sources. Results provide interesting biological insights about the causal relationship concerning noise propagation from growth to metabolism and vice versa.
Paper VI184-01.15
PDF · Video · Modeling a Population of Switches Via Chaotic Dynamics (I)
Buscarino, Arturo	University of Catania
Belhamel, Loubna	University of Catania
Bucolo, Maide	University of Catania
Palumbo, Pasquale	University of Milano-Bicocca
Manes, Costanzo	Università Dell'Aquila
Keywords: Dynamics and control, Modeling and identification, Parameter and state estimation Abstract: This note investigates the behavior of a population of interconnected irreversible switches, whose switching mechanism is triggered by a chaotic map. Motivation comes from the fact that many emergent properties of biological systems are ruled by the activation of a population of biochemical switches, whose timing and fluctuations may lead to different cell fates. They have been usually investigated according to a stochastic approach, and in this work we show how some properties could be similarly explained in terms of the emergent properties of a chaotic system. With respect to noise, chaos comes out from a deterministic framework, thereby allowing the implementation of experimental procedures directed to investigate the behavior of the system according to different scenarios by means of a rigorous deterministic passage from mathematics to simulation, that cannot be honestly rendered for the stochastic framework, since pseudo-random sequences are usually invoked.
Paper VI184-01.16
PDF · Video · Division Stochasticity Can Be Transmitted to Protein Expression through Chromosome Replication (I)
Nieto, Cesar	Universidad De Los Andes
Vargas-Garcia, Cesar Augusto	Agrosavia
Singh, Abhyudai	University of Delaware
Pedraza, Juan	Universidad De Los Andes
Keywords: Model formulation, experiment design, Modeling and identification, Kinetic modeling and control of biological systems Abstract: Stochastic fluctuations (noise) are a fundamental characteristic of protein production. In this work, we explore how these fluctuations can originate from the stochasticity on division events. Here we consider the classical gene expression model with chromosome replication following the known Helmstetter & Cooper model. This model predicts intervals of the cell cycle where bacteria can have more than one copy of a particular gene. Considering the transcription rate as proportional to the number of chromosomes and division based on a continuous rate model, we explore how stochasticity in division or equivalently in cell size, could be transmitted to gene expression. Our simulations suggest that division can be an important source of such fluctuations only if chromosomes are replicating, otherwise, this noise is not well transmitted. This effect happens even if replication is deterministic. This work can be helpful in understanding cell cycle dynamics and their interplay with phenotypic variability.

VI184-02
Modeling and Control of Bioprocesses	Regular Session
Chair: Valentin, Claire	UCB Lyon 1 Et CPE Lyon
Co-Chair: Van Impe, Jan F.M.	KU Leuven
Paper VI184-02.1
PDF · Video · On the Observability of Activated Sludge Plants
Bezerra Leite Neto, Otacílio	Federal University of Ceará
Mulas, Michela	Federal University of Ceara
Corona, Francesco	Aalto University
Keywords: Wastewater treatment processes, Dynamics and control, Modeling and identification Abstract: In this work, the full-state observability properties of a class of biological wastewater treatment plants are analysed. Specifically, the five biological reactors and the secondary settler in the Benchmark Simulation Model no. 1 are studied. For the task, we represented the activated sludge plant as a dynamical system consisting of 145 states, 8 controls, 14 disturbances and 12 outputs and as a complex network to study its observability properties from a structural and a classical point of view. By analysing the topology of the network, we show how the system is not observable in the structural sense and thus how it is also not observable in the classical sense for all possible realisations of its parameters. As this is also true for a linearisation commonly used in the literature, we analysed a reduced-order system that, based on such linearisation, does not consider the state variables corresponding to dissolved oxygen and alkalinity in the upper-layers of the settler. We show how this system configuration is only observable in a structural sense.
Paper VI184-02.2
PDF · Video · Brewery Wastewater Treatment Plant Key-Component Estimation Using Moving-Window Recurrent Neural Networks
Dewasme, Laurent	Université De Mons
Keywords: Data mining tools, Monitoring, Wastewater treatment processes Abstract: This work proposes an experimental validation of software sensors for advanced on-line anaerobic digester process monitoring. The considered strategy is based on cheap available measurements (conductivity, temperature, pH, redox potential, etc) to reconstruct key component trajectories such as volatile fatty acid, carbonate and alkalinity concentrations, as well as biogas composition (methane, carbon dioxide, etc). The proposed solution considers a radial basis function artificial neural network (RBF-ANN) structure, using data processing (principal component analysis) and an efficient and fast sequential learning algorithm. In order to better reproduce unknown and complex process dynamics, the combination of a moving-window technique with a simple Jordan recurrent ANN structure (MW-RBF-RNN) is proposed. Comparative results based on real industrial data illustrate the estimation improvements provided by the MW-RBF-RNN with respect to the classical RBF-ANN structure.
Paper VI184-02.3
PDF · Video · Parameter Estimation for Dynamic Resource Allocation in Microorganisms: A Bi-Level Optimization Problem (I)
Mairet, Francis	Ifremer
Bayen, Terence	University of Montpellier 2
Keywords: Modeling and identification, Parameter and state estimation, Dynamics and control Abstract: Given their key roles in almost all ecosystems and in several industries, understanding and predicting microorganism growth is of utmost importance. In compliance with evolutionary principles, coarse-grained or genome-scale models of microbial growth can be used to determine optimal resource allocation scheme under dynamic environmental conditions. Resource allocation approaches have given important qualitative results, but it still remains a gap towards quantitiative predictions. The first step in this direction is parameter calibration with experimental data. But fitting these models results in a bi-level optimization problem, whose numerical resolution involves complex optimization issues. As a case study, we present here a coarse-grained model describing how microalgae acclimate to a change in light intensity. We first determine using the Pontryagin maximum principle and numerical simulations the optimal strategy, corresponding to a turnpike with a chattering arc. Then, a bi-level optimization problem is proposed to calibrate the model with experimental data. To solve it, a classical parameter identification routine is used, calling at each iteration the bocop solver to solve the optimal control problem (by a direct method). The calibrated model is able to represent the photoacclimation dynamics of the microalga Dunaliella tertiolecta facing a down-shift of light intensity.
Paper VI184-02.4
PDF · Video · Optimal Control of a Fed-Batch Reactor with Overflow Metabolism (I)
Martinez, Carlos	INRIA Sophia Antipolis
Gouze, Jean-Luc	INRIA
Keywords: Dynamics and control, Industrial biotechnology, Microbial technology Abstract: Fast growing E.coli cells in glucose-aerobic conditions excrete fermentation by-products such as acetate. This phenomenon is known as overflow metabolism and can pose a major problem in industrial bio-processes. In this paper, we study optimal control strategies for feeding a fed-batch reactor subject to overflow metabolism. We consider that acetate has an inhibitor effect on the glucose uptake, and we also consider the cost associated to process duration. In our approach, using the Pontryagin Maximum Principle and numerical solutions we describe the optimal feeding policy that maximizes biomass productivity and minimizes the cost duration of the process. We show that a singular regime is possible, in which cells grow at a slow rate to prevent acetate formation. If the cost associated to the process is too high, only bang-bang solutions are allowed.
Paper VI184-02.5
PDF · Video · Antithetic Integral Feedback for the Robust Control of Monostable and Oscillatory Biomolecular Circuits
Olsman, Noah	Harvard University
Forni, Fulvio	University of Cambridge
Keywords: Dynamics and control, Microbial technology, Modeling and identification Abstract: Biomolecular feedback systems are now a central application area of interest within control theory. While classical control techniques provide valuable insight into the function and design of both natural and synthetic biomolecular systems, there are certain aspects of biological control that have proven difficult to analyze with traditional methods. To this end, we describe here how the recently developed tools of dominance analysis can be used to gain insight into the nonlinear behavior of the antithetic integral feedback circuit, a recently discovered control architecture which implements integral control of arbitrary biomolecular processes using a simple feedback mechanism. We show that dominance theory can predict both monostability and periodic oscillations in the circuit, depending on the corresponding parameters and architecture. We then use the theory to characterize the robustness of the asymptotic behavior of this circuit in a nonlinear setting.
Paper VI184-02.6
PDF · Video · Representation of a Continuous Settling Tank by Hybrid Partial Differential Non Linear Equations for Control Design
Valentin, Claire	UCB Lyon 1 Et CPE Lyon
Dochain, Denis	Univ. Catholique De Louvain
Jallut, Christian	Université Claude Bernard Lyon 1
Dos Santos Martins, Valérie Sylvie	Université Claude Bernard Lyon 1
Keywords: Wastewater treatment processes, Modeling and identification Abstract: The representation of the main physical phenomena of continuous sedimentation within a settling tank (hydrodynamics of two-phase suspensions) is essential for the further control design of the quality of the solid-liquid separation. The model is still made of non-linear partial differential equations after simplifying assumptions and considering a one dimensional settler. It comes from both mass and momentum balance equations and includes effective solid stress appearing when the solid particles concentration is above a given threshold which depends on the quality of the sludge. Then a mobile interface appears between two different behaviours. The settler is divided into two zones to represent this discrete phenomenon. Our goal is to develop a model that can be used for a further control design of the water quality at the top outlet of the settling tank. A hybrid state space representation is provided with the different dynamics in each of the two zones, the constitutive equations and the boundary conditions. The steady state profile is calculated. A simplified version of a settling tank model is simulated.
Paper VI184-02.7
PDF · Video · Linearization in the Large of the Anaerobic Digestion Process Using a Reduced-Order Koopman Operator
Garcia-Tenorio, Camilo	Universidad Naciona, Universite De Mons
Sbarciog, Mihaela	KU Leuven
Mojica-Nava, Eduardo	Universidad Nacional De Colombia
Vande Wouwer, Alain	Université De Mons
Keywords: Wastewater treatment processes, Modeling and identification, Data mining tools Abstract: The identification of accurate models for the anaerobic digestion process is essential for the characterization of the region that guarantees the conservation of the bacteria population. Traditional techniques involve the identification of nonlinear models based on data from the system. In this paper, we introduce data-driven techniques that allow the characterization of the system's behavior via the approximation of the Koopman operator with the extended dynamic mode decomposition algorithm. We propose methods to reduce the order and dimension of the representation based on orthogonal polynomials.
Paper VI184-02.8
PDF · Video · Application of Model-Based Online Monitoring and Robust Optimizing Control to Fed-Batch Bioprocesses
Hille, Rubin	Bayer AG
Brandt, Heiko	TU Dortmund
Colditz, Vera	Bayer AG
Classen, Jens	Bayer AG
Hebing, Lukas	TU Dortmund, Process Dynamics and Operations Group
Langer, Matthaeus	Bayer AG
Kreye, Steffen	Bayer AG
Neymann, Tobias Claus	Bayer Technology Services GmbH
Kraemer, Stefan	INEOS Koeln
Traenkle, Jens	Bayer AG
Brod, Helmut	Bayer AG
Jockwer, Alexander	Bayer HeathCare AG
Keywords: Dynamics and control, Parameter and state estimation, Modeling and identification Abstract: The aim of the quality by design initiative is to assure a continuous and high-quality production of pharmaceuticals despite the presence of process variations and disturbances. This need for optimal process operation necessitates the use of accurate prediction and fault detection methods in combination with advanced control strategies. However, the critical component for the success of such an approach is a mathematical model providing an adequate representation of the bioprocess under study. This work presents a framework for bioprocess online optimization that utilizes rigorous modelling and control methods tailored for fed-batch and perfusion cultures. The basis of the methodology is a hybrid process modelling approach which enables both monitoring and optimization of cell culture processes. To account for inherent process variability of biological organisms, an adaptive state estimation approach is utilized which employs multiple models in parallel thus providing improved robustness to a possible occurrence of model-plant mismatch. Furthermore, optimal process trajectories for online optimization are calculated using a robust multistage nonlinear model predictive control approach which considers different scenarios based on the employed process models. Recent promising results from experimental fed-batch CHO fermentations are presented which show significant productivity increases.
Paper VI184-02.9
PDF · Video · Heterogeneous Multi-Population Evolutionary Dynamics with Migration Constraints
Barreiro-Gomez, Julian	New York University
Obando, Germán	Universidad De Los Andes
Pantoja, Andres	Universidad De Narino
Tembine, Hamidou	New York University
Keywords: Dynamics and control, Scheduling, coordination, optimization Abstract: We present a novel distributed heterogeneous multi-population evolutionary dynamics approach, which can be used in diverse engineering applications as a distributed optimization-based algorithm. We also provide stability certificates of Nash equilibria under the proposed approach. Finally, over the end of this paper, an example illustrates the performance of the aforementioned multi-population evolutionary dynamics.
Paper VI184-02.10
PDF · Video · Noise Propagation in Bacterial Cells Optimized for Growth
Krah, Laurens	Utrecht University
Hermsen, Rutger	Utrecht University, Department of Biology, Theoretical Biology G
Keywords: Dynamics and control, Scheduling, coordination, optimization, Metabolic engineering Abstract: Single-cell microscopy experiments have shown that the instantaneous cellular growth rate fluctuates strongly between bacterial cells, even in clonal populations under constant conditions. At the same time, reporter studies have demonstrated that, within each cell, the copy numbers of individual protein species fluctuate significantly, affecting the metabolic flux catalyzed by these proteins, and eventually the growth rate. Using an extension of Metabolic Control Analysis, we here argue that, contrary to common intuitions, highly expressed proteins are expected to be most relevant for the observed fluctuations in the cellular growth rate. Our results are obtained when evolution has shaped protein expression to be optimal for growth. During such an evolutionary process growth control -and therewith noise propagation properties- shifts towards proteins with higher mean expression. This increased control compensates the lower noise levels of highly abundant proteins, causing fluctuations in those proteins to propagate most strongly to the cellular growth rate.
Paper VI184-02.11
PDF · Video · The Modelling and Simulation of a Drying Process in a Poultry By-Product Processing Plant
Mäkinen, Vili	Honkajoki Oy
Vilkko, Matti Kalervo	Tampere University
Keywords: Food engineering, Dynamics and control, Modeling and identification Abstract: This paper studies the modelling and simulation of a drying process in a poultry by-product processing plant. In a poultry by-product processing plant, the material is separated into liquids, fats and solids. The liquids are removed, either by pressing or drying, the fats are collected in a centrifuge and the solid mass is dried and manufactured into a protein-rich solid powder. The process contains two rendering operations, where heat is applied to the material to both remove extra moisture and to raise the temperature of the material. These processes are vital for the sterilization of the material as well as for the quality of the product. To improve the understanding behind the drying process, a mathematical model is created using first principles and the obtained model is complemented with experimental data from the real-world process to produce a dynamic model of the drying process. The model is built on a digital computer, using a simulation software. The model is validated with data from the real process plant and used to reveal the underlying dynamics that complicate the control of the process. The model enables the design of automatic control for the process in a safe environment.
Paper VI184-02.12
PDF · Video · Data-Driven Metabolic Network Reduction for Multiple Modes Considering Uncertain Measurements
Pohlodek, Johannes	Otto-von-Guericke-Universität Magdeburg
Rose, Alexander	Otto-von-Guericke-Universität Magdeburg
Morabito, Bruno	Otto-von-Guericke-Universität Magdeburg
Carius, Lisa	Otto-von-Guericke-Universität Magdeburg
Findeisen, Rolf	Otto-von-Guericke-Universität Magdeburg
Keywords: Modeling and identification Abstract: Dynamic models of biotechnological processes form the basis of process optimization, control, and estimation. Metabolic network models are often at the core of such models. Since metabolic network models can be very large, and consequently computationally expensive, model reduction techniques can be applied. The derivation of a suitable reduced metabolic network that captures the essential metabolism is still a challenging problem. State-of-the-art network reduction algorithms utilize a priori defined phenotypes that reflect the expected behavior of the biological system. However, most bioprocesses undergo changes in the metabolism, hence, a switch in the cellular phenotype. If these phenotypes are unknown a priori, the reduced network fails to represent all observed metabolic behaviors. Contrary to these approaches, we propose a method that reduces genome-scale metabolic networks models using data from real experiments instead of relying on predefined phenotypes. Doing so, we circumvent the use of a priori information and guarantee that the network is capable to describe all observed phenotypes and can be reliably used for estimation, prediction, and optimization.
Paper VI184-02.13
PDF · Video · Analytical Computation of the Power Spectral Density for Unimolecular Stochastic Reaction Networks
Gupta, Ankit	ETH Zurich
Khammash, Mustafa H.	Swiss Federal Institute of Technology (ETH)
Keywords: Modeling and identification, Dynamics and control, Parameter and state estimation Abstract: Stochastic reaction networks model noisy intracellular processes, like gene-expression, where randomness typically arises due to low copy-numbers of the constituent biomolecular species. The frequency spectrum of each single-cell stochastic trajectory generated by such models contains valuable information about the network architecture and the reaction parameters. In this talk we demonstrate how this frequency spectrum can be analytically computed for any unimolecular reaction network under mass-action kinetics. We provide analytical expressions for the power spectral density (PSD) for simple three-node feedforward and feedback topologies in terms of the model parameters. Moreover we establish structural results that highlight the key differences between the PSD generated by these topologies irrespective of the model parameters.
Paper VI184-02.14
PDF · Video · Hybrid Cybernetic Modeling of Polyhydroxyalkanoate Production in Cupriavidus Necator Using Fructose and Acetate As Substrates
Duvigneau, Stefanie	Otto Von Guericke University Magdeburg
Dürr, Robert	Max Planck Institute for Dynamics of Complex Technical Systems
Carius, Lisa	Otto Von Guericke University Magdeburg
Kienle, Achim	Otto Von Guericke University Magdeburg
Keywords: Modeling and identification, Metabolic engineering, Microbial technology Abstract: Due to their advantageous properties, polyhydroxyalkanoates are a promising alternative to conventional petroleum-based plastics. Currently, high production costs in upstream and downstream have to be reduced to make the plastic material competitive. As most of the PHA producing organisms metabolize a wide range of substrates upstream cost can be reduced using carbon rich waste material. For large scale application sophisticated control approaches based on mathematical models can help to further increase the productivity. In the present work, a hybrid cybernetic model approach is presented, which is adapted to experiments with fructose and acetate feeding, respectively. Furthermore, the validated model was used to qualitatively predict the effect of co-substrate feeding.
Paper VI184-02.15
PDF · Video · An Integrated Approach for Experimental Design, Control, and Optimization of Perfusion Bioreactors
Rodrigues, Diogo	University of California, Berkeley
Keywords: Scheduling, coordination, optimization, Dynamics and control, Modeling and identification Abstract: This paper presents methods for experimental design, control, and optimization of perfusion bioreactors as well as the vision for their integration. After describing a generic model of perfusion bioreactors, the paper proposes a control scheme via rate estimation and feedback linearization with useful properties with respect to steady-state error, stability, and performance. The paper also introduces data-driven and hybrid procedures for experimental design that are tailored to the intended use of the model for steady-state optimization. Lastly, the methods are illustrated via a simulation example of a perfusion bioreactor.
Paper VI184-02.16
PDF · Video · Trade-Off-Based Multi-Objective Optimisation of a Simultaneous Saccharification and Fermentation Process
De Buck, Viviane	KU Leuven
Sbarciog, Mihaela	KU Leuven
Van Impe, Jan F. M.	KU Leuven
Keywords: Scheduling, coordination, optimization, Modeling and identification, Industrial biotechnology Abstract: The demand for sustainable replacements for fossil-based products is steadily increasing, especially now that the effects of climate change are becoming more prominent. Lignocellulose, which is a sustainable and abundant carbon source, is dubbed to be the perfect replacement. Lignocellulose consists of lignin, hemicellulose, and cellulose. During the Simultaneous Saccharification and Fermentation (SSF) of cellulose, the hydrolysis and fermentation of the produced C6-sugars occurs simultaneously in the same vessel. The SSF process has mainly been developed to circumvent inhibitory effect and increase the overall product yield. Although the concept of the SSF process is promising, the applications are still limited. This contribution presents the trade-off-based multi-objective optimisation of an SSF process. Multi-objective optimisation allows for optimising (bio-)process with respect to multiple, and often conflicting, objectives. These optimisation problems do not render a unique optimal solution but instead an infinite set of so-called Pareto-optimal solutions, the Pareto front. From the Pareto front, the decision maker should select one working point. To aid decision makers in this selection process, the application of a novel genetic optimisation algorithm is presented in this contribution, i.e., tDOM, that is capable of filtering solutions using t-domination. This results in a less dense Pareto front that only contains solutions that are of interest for the decision maker. Additionally, by extending the t-domination concept to two subsequent solution populations, a novel problem-relevant stopping criterion is developed, resulting in a significant gain in the required computational time. A comparison to the well known NSGA-II is provided.

VI191
Social Systems - Economic, Business, and Financial Systems
VI191-01 Ageineering-Challenges of Engineering, Management and Control in Ageing Societies   Invited Session, 5 papers
VI191-02 Game Theories   Regular Session, 8 papers
VI191-03 Modeling and Control of Economic Systems   Regular Session, 5 papers

VI191-01
Ageineering-Challenges of Engineering, Management and Control in Ageing Societies	Invited Session
Chair: Bogataj, David	Zavod INRISK
Co-Chair: Dimovski, Vlado	Faculty of Economics, University of Ljubljana
Organizer: Bogataj, David	Zavod INRISK
Organizer: Dimovski, Vlado	Faculty of Economics, University of Ljubljana
Organizer: Temeljotov Salaj, Alenka	Norwegian University of Science and Technology
Paper VI191-01.1
PDF · Video · Digital Transformation of Integrated Care: Literature Review and Research Agenda (I)
Colnar, Simon	Faculty of Economics, University of Ljubljana
Penger, Sandra	School of Economics and Business, University of Ljubljana
Grah, Barbara	Faculty of Economics, University of Ljubljana
Dimovski, Vlado	Faculty of Economics, University of Ljubljana
Keywords: Social Resource Planning and Management, Urban Healthcare, eHealth Abstract: Ambient assisted technologies have the potential to prolong the life of older adults with declining functional capacities in the community, which is of key importance in ageing societies. It also facilitates work and improves work outcomes in care systems. Currently, in European Union member states, many older adults seek acceptance to nursing homes too early. Current capacities of available nursing homes are in several member states insufficient to cater to increasing demand from the ageing population. How to prolong living in the community and postpone the reallocation to the nursing home is a major challenge in the European ageing society. According to the Web of Science, in the last 20 years, there has been growing research interest in ambient assisted living. Until now, the field of nursing and the field of social care in many member states are not integrated sufficiently, resulting in increased expenditures for nursing and social care on one hand and lack of services provided for a growing number of older adults with declining functional capabilities on the other hand. This paper aims to review the literature on the ambient assisted living and introduce the multiple decrement model for the measurement of efficiency of developed ambient assisted living technologies that are incorporated into the systems for management and control of long-term care services. Based on the proposed model, the future research agenda is outlined.
Paper VI191-01.2
PDF · Video · Ambient Assisted Living in Lifetime Neighbourhoods (I)
Bogataj, David	Zavod INRISK
Rogelj, Valerija	Zavod INRISK
Drobez, Eneja	Institute INRISK
Temeljotov Salaj, Alenka	Norwegian University of Science and Technology
Keywords: Econometric models and methods, Data-Driven Decision Making, Urban Healthcare Abstract: Municipalities are responsible for organizing and financing long-term–care services. These expenditures will triple in the next 40 years (to 9.5% of the GDP of Norway). This study seeks to investigate the exposure to different risks presented by the built environments of current neighbourhoods and the valuation of the benefits attained through the development of lifetime neighbourhoods. Ambient assisted living technologies embedded in lifetime neighbourhoods can significantly decrease the risk of falls and other accidents. Digital social networks and other support to the community can facilitate inclusion and mitigate loneliness. The spatial planning, development, and management of lifetime neighbourhoods with embedded ambient intelligence as a risk mitigation strategy in fast ageing cities are of specific interest. We wish to evaluate how the development of lifetime neighbourhoods mitigates the risk of accidents and social exclusion, thereby creating value for the community. The creation of value by the mitigation of the risk of falls, diseases, and social exclusion will be measured with the actuarial present value generated using the multiple decrement model approach, which is a novelty. The actuarial present value will provide scientific evidence of the benefits of the development and management of various lifetime neighbourhoods and housing arrangements.
Paper VI191-01.3
PDF · Video · Smart Lifetime Neighbourhoods: Literature Review and Research Agenda (I)
Rogelj, Valerija	Zavod INRISK
Bogataj, David	Zavod INRISK
Keywords: Urban Healthcare, Sustainability, Forecasting Abstract: Municipalities in European Union are ageing fast. Consequently, the development and financing of smart social infrastructure to support the growing number of older adults with declining functional capacities to postpone their moving to nursing homes so that they live longer in the community is a major challenge for European municipalities. In this context, social innovations based on the digital transformation of health care and social care delivery systems can support older adults to live autonomously and independently in their own communities and postpone or even prevent entering nursing homes. The innovations will enable a more efficient combination of existing societal resources in the communities for the provision of health care and social needs of the ageing members of society who are dependent on the help of others due to illness or functional decline. On the supply side, new scientific (optimisation of supply networks), organisational (self-managed communities) and technological innovations such as robotics, domotics and CPS – based on the Internet of Things and cloud computing – offer new utilities and create new businesses for the supply of goods and services to older people while also providing new job opportunities for younger residents. The aim of this paper is to consider the development and financing of community smart social infrastructure with a focus on Slovenia.
Paper VI191-01.4
PDF · Video · Real Estate Taxation and Other Fiscal Policies As Regulators of Growth in Ageing Regions (I)
Bogataj, Marija	CERRISK INRISK
Bogataj, David	Zavod INRISK
Drobne, Samo	University of Ljubljana, Faculty of Civil and Geodetic Engineeri
Keywords: Migration, Intrastructure (including energy, telecoms, political, physical etc.), Data-Driven Decision Making Abstract: Because of ageing, the availability of human resources is decreasing and only an increase in taxes can assure new public facilities for residents with declining functional capacities. Urban shrinkage is a remarkable phenomenon which cannot be convincingly explained by existing theories of urban growth, but it is strongly linked with the market in human resources in production economics. Within the human resource market, commuting or migration costs are compensated, thus influencing wage rates and/or land rent, capitalized on the value of residential properties. Therefore, those institutions that are planning the location and intensity of activities in the nodes of a supply chain should consider the influence of the required level of all kind of taxation, also the real estate, as well as the net wages, which depends on the spatial dispersion of the workers’ dwellings. Therefore, owners and managers of a supply chain also have to consider the fiscal policy in the region and the central location where they intend to invest in production or distribution unit. So, the intensity of the flow of items (in-process inventories) and intensity of the inflow of human resources interact in the area in which the activity cell is located and, together with tax policy and subventions, if such exist, influence the net expected profit of the business. Therefore, the paper presents an approach to the integration of the gravity model of spatially dispersed human resources with the supply systems described by extended MRP Theory, explicitly focused on the fiscal policy of the local authorities of a city and its functional region. The numerical examples show how the demographic projections which we calculated for 2019-2070, giving the ratio between active population and population 65+ in Slovenian regions influence the availability of human resources in the region, influencing the managerial decision of where to look for a workforce, and how these policies influence growth or decline of urban areas and their functional regions in the case of Slovenia.
Paper VI191-01.5
PDF · Video · Smart Silver Villages As Part of Social Infrastructure for Older Adults in Rural Areas (I)
Bogataj, David	Zavod INRISK
Campuzano-Bolarín, Francisco	Universidad Politécnica De Cartagena
Kavsek, Marta	ZAVOD INRISK
Rogelj, Valerija	Zavod INRISK
Keywords: Social Resource Planning and Management, Environmental, health and safety implications of automation, eHealth Abstract: Rural areas in European Union are ageing faster than urban areas, in many cases due to outmigration of young cohorts. Social innovations based on the digital transformation of health care and social care delivery systems can support older adults to live autonomous and independent in their own communities and postpone or even prevent entering a nursing home. Extensions of these innovations in service provision to rural are the subject of this paper. Development of Smart Eko Social Villages present opportunities for the development of new digitally supported health and social infrastructure in rural areas. The innovations will enable more an efficient combination of the existing societal resources in the communities for the provision of the health care and social needs of the ageing members of the society who are dependent on the help of others due to illness or functional decline. On the supply side, new scientific (optimization of the supply networks), organisational (self-managed communities) and technological innovations, like robotics, domotics, CPS based on the Internet of Things and cloud computing, offer new utilities and create new businesses for the supply of goods and services to the older people, and also provide new job opportunities for the younger residents. The aim of this paper is to consider the development of Smart Silver Villages as part of social infrastructure in rural areas supporting autonomy and independence of the rural population in their old age.

VI191-02
Game Theories	Regular Session
Chair: Gruene, Lars	Univ of Bayreuth
Co-Chair: Yu, Changbin (Brad)	Australian National University
Paper VI191-02.1
PDF · Video · Stackelberg Mean-Field-Type Games with Polynomial Cost
Frihi, Zahrate El Oula	Badji-Mokhtar University
Barreiro-Gomez, Julian	New York University
Choutri, Salah Eddine	KTH
Djehiche, Boualem	Royal Technical University of Stockholm
Tembine, Hamidou	New York University
Keywords: Game theories Abstract: This article presents a class of Stackelberg mean-field-type games with multiple leaders and multiple followers. The decision-makers act in sequential order with informational differences. The state dynamics is driven by jump-diffusion processes and the cost function is non-quadratic and has a polynomial structure. The structures of Stackelberg strategies and costs of the leaders and followers are given in a semi-explicit way in state-and- mean-field- type feedback form. A sufficiency condition is provided using an infinite dimensional partial integro-differential system. The methodology is extended to multi-level hierarchical systems. It is shown that not only the set of decision-makers per level matters but also the number of hierarchical levels plays a key role in the global performance of the system. We also identify specific range of parameters for which the Nash equilibrium coincides with the hierarchical solution independently of the number of layers and the order of play.
Paper VI191-02.2
PDF · Video · Robustness against Indirect Invasions in Asymmetric Games
Narang, Aradhana	Indian Institute of Technology Madras, Chennai
Shaiju, A.J.	IIT MADRAS
Keywords: Game theories Abstract: The concept of robustness against indirect invasions is well-known for symmetric games. We are concerned with the technical aspects and relevance of this concept for asymmetric games with continuous strategy space. For such games, we show that the set of all indirect neutral mutants of a robust profile is equivalent to a minimal evolutionarily stable set. It is also proved that a globally strong uninvadable profile is robust and the set of its indirect neutral mutants is a singleton. The results are illustrated using examples.
Paper VI191-02.3
PDF · Video · Verification and Design of Zero-Sum Potential Games
Li, Changxi	Harbin Institute of Technology
He, Fenghua	Harbin Institute of Technology
Hao, Ning	Harbin Institute of Technology
Keywords: Game theories Abstract: Zero-sum game is a class of game where one player's gain is equivalent to another's loss, which can be used in competitive situation. But pure Nash equilibrium maybe not exist in general zero-sum games. Potential games have nice properties, such as existence of pure Nash equilibrium. To combine advantages of zero-sum games and potential games, zero-sum potential game is proposed in this paper. Verification for a finite non-cooperative game being a zero-sum potential game is considered. Conversely, how to design a zero-sum potential game is also studied when the potential function is given. We show that verification and design of zero-sum potential game can be realized by solving linear equations. Furthermore, we find that if any two players play the zero-sum potential game in a network, then the networked game is also a zero-sum potential game.
Paper VI191-02.4
PDF · Video · The Evolution of Cooperation and Reward in a Corrupt Environment
Liu, Linjie	University of Electronic Science and Technology of China
Chen, Xiaojie	University of Electronic Science and Technology of China
Keywords: Game theories Abstract: The maintenance of cooperative behaviors in many complex social systems has always been a great challenge. It has been suggested that costly punishment and reward can both facilitate the evolution of cooperation. Recent theoretical work, however, reveals that the positive role of centralized punishment in promoting cooperation has been challenged when violators can bribe centralized authorities to escape from sanctions. Naturally, the question arises as to how cooperation evolves when defectors can bribe rewarders for getting the reward. Here, we propose an evolutionary game theoretical model in which defectors can choose to bribe the rewarders probabilistically, and meanwhile rewarders will stochastically receive bribes from defectors in the public goods game. We theoretically study deterministic dynamics in infinite populations, and find that cooperators, defectors, and rewarders can coexist and the fraction of each strategist in the population remains unchanged in the coexistence state. Furthermore, we numerically investigate stochastic dynamics in finite populations, and reveal that cooperative behaviors can be maintained since the population can spend most of the time in the region where cooperators, defectors, and rewarders coexist.
Paper VI191-02.5
PDF · Video · Exerting Control in Repeated Social Dilemmas with Thresholds
Frieswijk, Kathinka	University of Groningen
Govaert, Alain	Groningen
Cao, Ming	University of Groningen
Keywords: Game theories Abstract: Situations in which immediate self-interest and long-term collective interest conflict often require some form of influence to prevent them from leading to undesirable or unsustainable outcomes. Next to sanctioning, social influence and social structure, it is possible that strategic solutions can exist for these social dilemmas. However, the existence of strategies that enable a player to exert control in the long-run outcomes can be difficult to show and different situations allow for different levels of strategic influence. Here, we investigate the effect of threshold nonlinearities on the possibilities of exerting unilateral control in finitely repeated n-player public goods games and snowdrift games. These models can describe situations in which a collective effort is necessary in order for a benefit to be created. We identify conditions in terms of a cooperator threshold for the existence of generous, extortionate and equalizing zero-determinant (ZD) strategies. Our results show that, for both games, the thresholds prevent equalizing ZD strategies from existing. In the snowdrift game, introducing a cooperator threshold has no effect on the region of feasible extortionate ZD strategies. For extortionate strategies in the public goods game, the threshold only restricts the region of enforceable strategies for small values of the public goods multiplier. Generous ZD strategies exist for both games, but introducing a cooperator threshold forces the slope more towards the value of a fair strategy, where the player has approximately the same payoff as the average payoff of his opponents.
Paper VI191-02.6
PDF · Video · A Scalar-Parameterized Mechanism for Two-Sided Markets
Ndrio, Mariola	University of Illinois at Urbana-Champaign
Alshehri, Khaled	University of Illinois at Urbana-Champaign
Bose, Subhonmesh	University of Illinois at Urbana Champaign
Keywords: Game theories, Agent technology for business and economy, Financial systems Abstract: We consider a market in which both suppliers and consumers compete for a product via scalar-parameterized supply offers and demand bids. Scalar-parameterized offers/bids are appealing due to their modeling simplicity and desirable mathematical properties with the most prominent being bounded efficiency loss and price markup under strategic interactions. Our model incorporates production capacity constraints and minimum inelastic demand requirements. Under perfect competition, the market mechanism yields allocations that maximize social welfare. When market participants are price-anticipating, we show that there exists a unique Nash equilibrium, and provide an efficient way to compute the resulting market allocation. Moreover, we explicitly characterize the bounds on the welfare loss and prices observed at the Nash equilibrium.
Paper VI191-02.7
PDF · Video · Game of the Byzantine Generals on Time-Varying Graphs
Li, Yuke	Yale University
Yu, Changbin (Brad)	Australian National University
Keywords: Game theories, Security, Social networking, agile society, and societal intelligence Abstract: In this paper, we propose a game of the Byzantine Generals, which is a coordination game of agents seeking consensus after strategically transmitting information on a sequence of time-varying communication graphs. The first scenario of the game is where the generals cannot communicate with others at the same ``level'' in the communication graph. The second scenario is where those generals can. In either scenario, we examine the influences of the number of traitors and the decision rule held by the generals on equilibrium predictions of the game.
Paper VI191-02.8
PDF · Video · Simple Utility Design for Welfare Games under Global Information
Wada, Takayuki	Osaka University
Makabe, Ayumi	Osaka University
Fujisaki, Yasumasa	Osaka Univ
Keywords: Robustness analysis, Decentralized control, Large scale optimization problems Abstract: Welfare game is a game-theoretic model for resource allocation problem which is to find an allocation to maximize the welfare function. In order to determine it in a distributed way, each agent is assigned to an admissible utility function such that the resulting game possesses desirable properties, for example, scalability, existence and efficiency of pure Nash equilibria, and budget balance. In this paper, supposing that each agent can access the global information, marginal contribution based utility design is proposed. It is shown that utility functions based on the above design have scalability and existence of pure Nash equilibria. Furthermore, efficiency is the same as that of the conventional utility design via Shapley value.

VI191-03
Modeling and Control of Economic Systems	Regular Session
Chair: Fracastoro, Giulia	Politecnico Di Torino
Co-Chair: Alexeeva, Tatyana	National Research University Higher School of Economics
Paper VI191-03.1
PDF · Video · Time-Delay Control for Stabilization of the Shapolalov Mid-Size Firm Model
Alexeeva, Tatyana	National Research University Higher School of Economics
Barnett, William	University of Kansas
Kuznetsov, Nikolay	Saint-Petersburg State Univ
Mokaev, Timur	St. Petersburg State University
Keywords: Control in economics, Financial systems, Computational Economics Abstract: Control and stabilization of irregular and unstable behavior of dynamic systems (including chaotic processes) are interdisciplinary problems of interest to a variety of scientific fields and applications. Using the control methods allows improvements in forecasting the dynamics of unstable economic processes and offers opportunities for governments, central banks, and other policy makers to modify the behaviour of the economic system to achieve its best performance. One effective method for control of chaos and computation of unstable periodic orbits (UPOs) is the unstable delay feedback control (UDFC) approach, suggested by K. Pyragas. This paper proposes the application of the Pyragas' method within framework of economic models. We consider this method through the example of the Shapovalov model, by describing the dynamics of a mid-size firm. The results demonstrate that suppressing chaos is capable in the Shapovalov model, using the UDFC method.
Paper VI191-03.2
PDF · Video · An Optimal Control Method to Coordination of Pricing and Advertising for a Supply Chain: The Consignment Mode
Wu, Zhihui	Harbin University of Science and Technology
Liu, Guoping	University of South Wales
Hu, Jun	Harbin Institute of Technology
Keywords: Control in economics, Game theories Abstract: This paper addresses the channel coordination problem under the consignment mode based on the optimal control method. Considering the impacts from the advertising and platform goodwill onto the market demand, the equilibrium strategies regarding the pricing and the advertising are computed within the centralized and decentralized settings by applying the optimal control theory. Moreover, this paper compares the optimal control strategies in the two decision structures, where the comparison shows that the channel players invest more in advertising under the centralized case only when the share of the revenue exceeds a certain threshold. In addition, a contract scheme including the platform use fees and the cooperative advertising is proposed, which leads to profit Pareto improvements for the channel members. Finally, some simulations are provided to illustrate the impacts of the systems parameters onto the platform goodwill and coordination.
Paper VI191-03.3
PDF · Video · Survival and Neural Models for Private Equity Exit Prediction
Calafiore, Giuseppe	Politecnico Di Torino
Morales, Marisa Hillary	Politecnico Di Torino
Tiozzo, Vittorio	Politecnico Di Torino
Fracastoro, Giulia	Politecnico Di Torino
Marquie, Serge	Eurostep Digital AS
Keywords: Financial systems, Computational Economics, Econometric models and methods Abstract: Within the Private Equity (PE) market, the event of a private company undertaking an Initial Public Offering (IPO) is usually a very high-return one for the investors in the company. For this reason, an effective predictive model for the IPO event is considered as a valuable tool in the PE market, an endeavor in which publicly available quantitative information is generally scarce. In this paper, we describe a data-analytic procedure for predicting the probability with which a company will go public in a given forward period of time. The proposed method is based on the interplay of a neural network (NN) model for estimating the overall event probability, and Survival Analysis (SA) for further modeling the probability of the IPO event in any given interval of time. The proposed neuro-survival model is tuned and tested across nine industrial sectors using real data from the Thomson Reuters Eikon PE database.
Paper VI191-03.4
PDF · Video · On Simultaneous Long-Short Stock Trading Controllers with Cross-Coupling
Deshpande, Atul	University of Wisconsin-Madison
Gubner, John	Univ of Wisconsin-Madison
Barmish, B. Ross	Univ of Wisconsin
Keywords: Financial systems, Control in economics, Business and Financial Analytics Abstract: The Simultaneous Long-Short (SLS) controller for trading a single stock is known to guarantee positive expected value of the resulting gain-loss function with respect to a large class of stock price dynamics. In the literature, this is known as the Robust Positive Expectation (RPE) property. An obvious way to extend this theory to the trading of two stocks is to trade each one of them using its own independent SLS controller. Motivated by the fact that such a scheme does not exploit any correlation between the two stocks, we study the case when the relative sign between the drifts of the two stocks is known. The main contributions of this paper are three-fold: First, we put forward a novel architecture in which we cross-couple two SLS controllers for the two-stock case. Second, we derive a closed-form expression for the expected value of the gain-loss function. Third, we use this closed-form expression to prove that the RPE property is guaranteed with respect to a large class of stock-price dynamics. When more information over and above the relative sign is assumed, additional benefits of the new architecture are seen. For example, when bounds or precise values for the means and covariances of the stock returns are included in the model, numerical simulations suggest that our new controller can achieve lower trading risk than a pair of decoupled SLS controllers for the same level of expected trading gain.
Paper VI191-03.5
PDF · Video · Modeling and Prediction for Optimal Human Resources Management
Abbracciavento, Francesco	Politecnico Di Milano
Formentin, Simone	Politecnico Di Milano
Gualandi, Emanuela	Rekeep S.p.A
Nanni, Rita	Rekeep S.p.A
Paoli, Andrea	Rekeep S.p.A
Savaresi, Sergio	Politecnico Di Milano
Keywords: Social Resource Planning and Management, Business and Financial Analytics, Data-Driven Decision Making Abstract: Human resources management is key for the retention and development of quality staff in modern companies. With the advent of big data and the recent boost in computing power, modeling and predictive analytics have shown their potential to increase HR-related performance, thus making the companies more competitive on the market via data-driven solutions. In this work, we develop a predictive model of the annual hourly cost per employee in big maintenance companies, which is usable for sales, marketing and HR purposes. With experimental real data, we show that such a model outperforms the typically employed solutions, by also allowing for an adaptive implementation using monthly updates.

VI192
Social Systems - Social Impact of Automation
VI192-01 Ethical Challenges for Systems & Control   Invited Session, 5 papers

VI192-01
Ethical Challenges for Systems & Control	Invited Session
Chair: Moreno, Ubirajara F.	Federal Univ of Santa Catarina
Co-Chair: Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Organizer: Moreno, Ubirajara F.	Federal Univ of Santa Catarina
Organizer: Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Paper VI192-01.1
PDF · Video · Ethical Stakes of Industry 4.0 (I)
Trentesaux, Damien	Université Polytechnique Hauts De France
Caillaud, Emmanuel	Université De Strasbourg
Keywords: Ethics, Ethical issues in the cyber-space operations, Cultural impacts of automation technology Abstract: Industry 4.0 provokes a shift in the way production systems are designed and used that raises ethical questions. This shift stems from several features relevant to Industry 4.0, specifically the increase of the importance of the digital world and the fostering of the development of more autonomous and intelligent systems that will interact and interoperate with humans in more open production environments. The first aim of this paper is to study to what extent Industry 4.0 impacts ethics. The second one is to raise the awareness of researchers regarding potential ethical risks when designing and evaluating future Industry 4.0 compliant production systems. For that purpose, the ethical stakes of industry 4.0 are first presented. Then, an overview of related work is done to evaluate the different scientific fields potentially contributing to the study of the ethical dimension in Industry 4.0. A discussion is finally proposed from this overview. The main conclusion of this discussion concerns the urgent need to address the ethical dimension of scientific contributions relevant to Industry 4.0, given the lack of work in that field.
Paper VI192-01.2
PDF · Video · A Framework for Ethics in Cyber-Physical-Human Systems (I)
Khargonekar, Pramod	University of California, Irvine
Sampath, Meera	State University of New York
Keywords: Ethics, Ethical issues in the cyber-space operations, Cultural impacts of automation technology Abstract: This paper proposes a conceptual framework for consideration of ethical issues in the emerging category of smart cyber-physical systems. Cyber-physical systems (CPS) that bring together controls, communications, computing, and physical systems are being developed in a wide variety of application domains ranging from transportation, energy, and manufacturing, to biomedical and agriculture. Smart CPS are already being and will increasingly be deployed to work with humans, in workplaces, homes, or public spaces, resulting in the creation of cyber-physical human systems (CPHS). Ethical issues in smart CPS and CPHS can be examined within the larger frameworks of ethics of technology and ethics of artificial intelligence. We begin with a description of trends and visions for the future development of smart CPS. We next outline fundamental theories of ethics that offer foundations for thinking about ethical issues in smart CPHS. We argue that it is necessary to fight the tendency toward technological determinism. We argue that in analyzing ethics of smart CPHS, we need to anticipate increasing capabilities and the future deployment of such systems. Ultimately, if these systems are widely deployed in society, they will have a very significant impact, including possible negative consequences, on individuals, communities, nations, and the world. Our framework has two main dimensions: (i) stage of development of CPHS domain from early stage research to mature technologies; and (ii) locus of decision making: individual, corporate, and government settings. We illustrate the framework with some specific examples.
Paper VI192-01.3
PDF · Video · A Control Approach to Address Ethical Issues on Social (robotic) Networks (I)
Salem, Feres A.	Univ. Federal De Santa Catarina
Moreno, Ubirajara F.	Federal Univ of Santa Catarina
Lamnabhi-Lagarrigue, Françoise	CNRS-EECI
Keywords: Cultural impacts of automation technology, Social networking, agile society, and societal intelligence, Ethical issues in the cyber-space operations Abstract: From the first Internet-based social networking applications designed to get people in contact and make friends to social networks made up of over 2 billion users, the combination of communication networks, portable devices, and AI has changed the way people interact and make decisions. The extent of this influence could be observed not only in marketing and social behavior but also in referendums and elections, leading to distortion of democratic manifestations and representations. Considering this, the consequences of the misuse of Internet-based social networks could have a substantial impact on society, and it is important to define ethical guidelines and policies for developers, rulers, operators, and social actors. Considering this aim, the objective of this paper is to show that an approach based on Systems & Control could be effective in evaluating the impact of such policies in order to meet ethical issues. The starting point from this analysis are the models of information spreading in dynamic social networks, and these models are adapted and updated to encompass the complex behavior from users, as well as some regulatory policies. The analyses were based on simulations of these models on small and large scale networks.
Paper VI192-01.4
PDF · Video · The Concept of "safety Bubble" to Build Ethical Reconfigurable Assembly Systems (I)
Berger, Thierry	Université Polytechnique Hauts-De-France
Bonte, Therese	University of Valenciennes
Santin, Jean-Jacques	LAMIH F-59313 Valenciennes Univ Lille Nord De France
Sallez, Yves	Polytechnic University of Hauts-De-France
Keywords: Environmental, health and safety implications of automation, Ethics, Human-centered systems engineering Abstract: The concept of Reconfigurable Assembly System has been proposed in the last decade to deal with mass-customization problems and volatile market environment. If physical design or control issues of these systems have been studied intensively, very few works concern the inherent ethical risks and associated safety problems. However these issues are of first interest for reconfigurable robotized systems with frequent interventions of human operators. Indeed, the re-configurability features of these manufacturing systems induce new issues in safety. The manufacturing enterprises must pay attention to the possible consequence of the Reconfigurable Assembly System design on the safety of the humans and on their possible responsibility in case of an accident. The present paper proposes the concept of safety bubble aiming to insure human’s safety by cooperation among safe robotized units. After a presentation of the ethical considerations, a design methodology of such safety bubble is detailed. The on-going works in simulation and on a real demonstrator, including collaborative robots and mobile robots, are then described.
Paper VI192-01.5
PDF · Video · Non-Cooperative Optimization of Charging Scheduling for Electric Vehicle Via Stackelberg Game and Matching Theory (I)
Yoshihara, Miyu	Keio University
Namerikawa, Toru	Keio University
Keywords: Social Resource Planning and Management, Data-Driven Decision Making, Econometric models and methods Abstract: In this paper, we deal with the charging scheduling optimization problem of electric vehicle in highway via Stackelberg game and matching theory. At first, we propose an algorithm for electric vehicle allocation to charging station which aims to uniformize waiting time of each charging station. In addition, we present energy demand and price decision problem and solve it using Stackelberg game. We compare Stackelberg equilibrium point and Nash equilibrium point and confirm Stackelberg game provide bigger benefit to charging station. Finally, we show validation of proposed algorithm via numerical simulations.

VI193
Social Systems - Smart Cities
VI193-01 Control and Modeling for Smart Cities   Open Invited Session, 9 papers
VI193-02 Building Automation and Control   Regular Session, 7 papers

VI193-01
Control and Modeling for Smart Cities	Open Invited Session
Chair: Jia, Qing-Shan	Tsinghua University
Co-Chair: Dotoli, Mariagrazia	Politecnico Di Bari
Organizer: Jia, Qing-Shan	Tsinghua University
Organizer: Dotoli, Mariagrazia	Politecnico Di Bari
Organizer: Parisio, Alessandra	The University of Manchester
Organizer: Cassandras, Christos G.	Boston Univ
Organizer: Malikopoulos, Andreas	University of Delaware
Paper VI193-01.1
PDF · Video · Dual-Stage Attention Based Spatio-Temporal Sequence Learning for Multi-Step Traffic Prediction
Cui, Ziqiang	Zhejiang University
Zhao, Chunhui	Zhejiang University
Keywords: Intelligent Transportation, Urban Mobility Abstract: Traffic prediction has great significance including but not limited to mitigating traffic congestion, reducing traffic accidents, and reducing waiting time. At the same time, traffic prediction, especially multi-step prediction, faces many difficulties including temporal correlations and spatial correlations. We propose a dual-stage attention based spatio-temporal sequence learning for multi-step traffic prediction which can not only express temporal correlation and spatial correlation, but also can adaptively learn the contribution weights of different related roads and historical moments. More specifically, for spatial dependencies, we first generate the input vector for each historical moment considering the information of relevant road segments by the method of spatial region of support and further add the first-stage attention termed spatial attention to automatically determine the weight of each relevant road segment for each historical moment. For temporal dependencies, we use LSTM based encoder-decoder networks to fully learn the temporal characteristic and make multi-step prediction considering temporal correlation between multi steps. We further add the second-stage attention termed temporal attention in the decoder part to automatically learn the contribution of different historical moments to each prediction moment. In addition, we consider external factors including weather and holidays and characterize their impacts using fully connected networks. Finally, the effectiveness of the proposed method is evaluated using traffic data in Hangzhou, China.
Paper VI193-01.2
PDF · Video · Control of Vehicular Platoons: Stochastic Robustness against Jamming Attacks (I)
Rezaee, Hamed	Imperial College London
Parisini, Thomas	Imperial College & Univ. of Trieste
Polycarpou, Marios M.	University of Cyprus
Keywords: Connected Vehicles, Intelligent Transportation, Security Abstract: Control of a platoon of vehicles subject to jamming attacks is addressed in this paper. Because of jamming attacks, some communicated information and radio data are assumed to be lost or delayed in a stochastic manner. By considering the constant time-gap spacing policy, we propose a control strategy which under certain conditions guarantees the almost sure regulation of the vehicles in desired relative distances. Accordingly, depending on the control gains, the robustness of the platoon against a wide range of jamming attacks is guaranteed. The main contribution of the paper is that the proposed control scheme is robust against jamming attacks on both the communication network and vehicles radars. Simulation results illustrate the performance of the proposed control strategy.
Paper VI193-01.3
PDF · Video · Motion Planning with Event-Driven Recurrent Q-Learning (I)
Jin, Xinze	Tsinghua University
Jia, Qing-Shan	Tsinghua University
Ren, Dongchun	Meituan-Dianping
Bai, Yu	Meituan-Dianping
Keywords: Intelligent Transportation, Data-Driven Decision Making, Cognitive aspects of automation systems and humans Abstract: Autonomous driving at intersection has great potential on control for smart cities to relieve the energy consumption and transportation congestion. However, it remains challenging to find promising behavior sequence in multi-agent environment with uncertain participation of obstacles. This work develops Event-driven Recurrent Q-Learning (ERQL) to focus on the motion planning task towards intersection scenarios to conclude a sample path with safety and efficiency. We elaborate the definition of events to capture the environment structure and introduce recurrency to process sequence model. Besides, we incorporate collision-avoidance into the event-driven framework and design a mechanism to extract recurrent feature from replay buffer in Q-learning framework. Simulation results show that the developed off-line learning procedure can adapt to on-line decision making towards uncertain agent behaviors.
Paper VI193-01.4
PDF · Video · Drugs Cross Distribution Management in Urban Areas through an Incentives Scheme
Fanti, Maria Pia	Polytechnic of Bari
Mangini, Agostino Marcello	Politecnico Di Bari
Roccotelli, Michele	Polytechnic of Bari
Silvestri, Bartolomeo	Polytechnic of Bari
Keywords: Urban Mobility, Sustainability, Intelligent Transportation Abstract: The modern societies have witnessed several developments and changes in cities in the recent years. In order to make cities smart, new technological infrastructures are required to connect networks of actors, sensors and actuators embedded throughout the urban ground, and to interact with wireless mobile devices. In this context, this paper proposes an innovative approach for optimizing drug delivery and cost saving, inspired by the collaborative urban logistics concept. More in detail, the proposed approach is based on the use of a shared city warehouse managed by a network of pharmacies where it is possible to pick up the missing drugs. The paper develops a pharmacy supplying method based on an incentive system to engage pharmacists in the drug distribution process. An interactive drug distribution algorithm, based on an Integer Linear Programming (ILP) problem, is proposed to minimize the external and transport costs. Finally, a case study is introduced, and the method efficiency is shown through the related simulations.
Paper VI193-01.5
PDF · Video · Average Density Detectability in Traffic Networks Using Virtual Road Divisions (I)
Rodriguez-Vega, Martin	CNRS, Grenoble INP, GIPSA-Lab
Canudas de Wit, Carlos	CNRS-GIPSA-Lab
Fourati, Hassen	GIPSA-LAB, University Grenoble Alpes
Keywords: Intelligent Transportation, Urban Mobility Abstract: In this paper, we demonstrate the existence of a reduced-order open-loop observer to estimate the average density in a region of a large scale traffic network. We show that traffic networks are not generally average detectable, but that it is possible to find a virtual representation of the network using inhomogeneous road divisions such that the observer converges to the true values. We express the conditions for the required number of cells per road and their lengths such that the system is average detectable in terms of the network's topology and physical parameters. Moreover, we propose a method to calculate these divisions and give asymptotic bounds on the quality of the approximations.
Paper VI193-01.6
PDF · Video · Fast Trajectory Planning in Cartesian Rather Than Frenet Frame: A Precise Solution for Autonomous Driving in Complex Urban Scenarios (I)
Li, Bai	Hunan University
Zhang, Youmin	Concordia University
Keywords: Intelligent Transportation, Urban Mobility, Social Resource Planning and Management Abstract: On-road trajectory planning is a direct reflection of an autonomous vehicle’s intelligence level when traveling on an urban road. The prevalent on-road trajectory planners include the spline-based, sample-and-search-based, and optimal-control-based methods. Path-velocity decomposition and Frenet frame have been widely adopted in the aforementioned methods, which, nonetheless, largely degrade the trajectory planning quality when the road curvature is large and/or the scenario is complex. This paper aims to plan precise and high-quality on-road trajectories, thus we choose to describe the concerned scheme as an optimal control problem, wherein the urban road scenario is described completely in the Cartesian frame rather than in the Frenet frame. The formulated optimal control problem should be numerically solved in real-time. To that end, a light-weighted iterative computation architecture is built. In each iteration, a tunnel construction strategy tractablely models the collision-avoidance constraints, and a constraint softening strategy helps to find an intermediate trajectory for constructing the tunnels in the next iteration. Efficacy of the proposed on-road trajectory planner is validated by simulations on a high-curvature urban road wherein the ego vehicle is surrounded by multiple social vehicles at various speeds.
Paper VI193-01.7
PDF · Video · Autonomous Intersection Management Over Continuous Space: A Microscopic and Precise Solution Via Computational Optimal Control (I)
Li, Bai	Zhejiang University
Zhang, Youmin	Concordia University
Jia, Ning	Institute of Systems Engineering, Tianjin University
Peng, Xiaoyan	College of Mechanical and Automobile Engineering
Keywords: Intelligent Transportation, Computational Social Sciences, Social Resource Planning and Management Abstract: Autonomous intersection management (AIM) refers to planning cooperative trajectories for multiple connected and automated vehicles (CAVs) when they pass through an unsignalized intersection. In modeling a generic AIM scheme, the predominant network-level or lane-level methods limit the cooperation potentiality of a multi-CAV team because 1) lane changes are forbidden or only allowed at discrete spots in the intersection, 2) each CAV’s travel path is fixed or selected among a few topological choices, and 3) each CAV’s travel velocity is fixed or set to a specified pattern. To overcome these limitations, this work models the intersection as a continuous free space and describes the AIM scheme as a multi-CAV trajectory optimization problem. Concretely, a centralized optimal control problem (OCP) is formulated and then numerically solved. To derive a satisfactory initial guess for the numerical optimization, a priority-based decentralized framework is proposed, wherein an x-y-time A* algorithm is adopted to generate a coarse trajectory for each CAV. To facilitate the OCP solution process, 1) the collision-avoidance constraints in the OCP are convexified; and 2) a stepwise computation framework is adopted. Simulation results show the efficacy of the proposed offline AIM method. Benefits in the travel efficiency to formulate such a continuous-space and continuous-time problem are also investigated.
Paper VI193-01.8
PDF · Video · Equilibrium Manifolds in 2D Fluid Traffic Models (I)
Tumash, Liudmila	TU Berlin
Canudas de Wit, Carlos	CNRS-GIPSA-Lab
Delle Monache, M. L.	Inria Grenoble - Rhône Alpes
Keywords: Intelligent Transportation, Urban Mobility Abstract: The main goal of this paper is to analytically find a steady-state in a large-scale urban traffic network with known and constant demand and supply on its boundaries. Traffic dynamics are given by a continuous two-dimensional macroscopic model, where state corresponds to the vehicle density evolving in a 2D plane. Thereby, the flux magnitude is given by the space-dependent fundamental diagram and the flux direction depends on the underlying network topology. In order to find a steady-state, we use the coordinate transformation such that the 2D equation can be rewritten as a parametrized set of 1D equations. This technique allows us to obtain the curves along which the traffic flow evolves, which are essentially the integral curves of the flux field constructed from the network geometry. The results are validated by comparing the obtained steady-state with the one estimated by using a microsimulator.
Paper VI193-01.9
PDF · Video · Weak Control Approach to Consumer-Preferred Energy Management
Shibasaki, Suzuna	Keio University
Inoue, Masaki	Keio University
Arahata, Mitsuru	Keio University
Gupta, Vijay	University of Notre Dame
Keywords: Energy and Distribution Management Systems, Human-centered systems engineering, Dynamic Resource Allocation Abstract: This paper is devoted to a consumer-preferred community-level energy management system (CEMS), in which a system manager allows consumers their selfish decisions of power-saving while regulating the overall demand-supply imbalance. The key structure of the system is to weakly control consumers: the controller sends the allowable range of the power-saving amount to each consumer, which is modeled by a set-valued control signal. Then, the consumers decide the amount in the range based on their private preference. In this paper, we address the design problem of the controller that generates the set-valued control signals. The controller structure is based on internal model control, which plays the essential role of guaranteeing the consumer-independent stability and the worst-case control performance of the overall CEMS. Finally, a numerical experiment of the consumer-preferred CEMS is performed to demonstrate the design procedure of the controller and to show its effectiveness.

VI193-02
Building Automation and Control	Regular Session
Chair: Gros, Sebastien	NTNU
Co-Chair: Jones, Colin, N	EPFL
Paper VI193-02.1
PDF · Video · Economic NMPC for Multiple Buildings Connected to a Heat Pump and Thermal and Electrical Storages
Rastegarpour, Soroush	Politecnico Di Milano
Ferrarini, Luca	Politecnico Di Milano
Gros, Sebastien	Assistant Pr. Chalmers University, Göteborg
Keywords: Building Automation Abstract: This paper studies the impact of different types of energy storage integrated with a heat pump to improve energy effciency in multiple radiant-floor buildings. In particular, the buildings and the heating generation system are decoupled through a 3-element mixing valve, which enforces a fixed flow rate but a variable temperature in the inlet water entering the building pipelines. The paper presents an optimal control formulation based on an Economic Nonlinear MPC scheme, in order to find the best compromise among different goals: make the heat pump work when it is more effcient, store electrical energy when it is cheap, store thermal energy in the tank when the heat pump is more effective, modulate the inlet water temperature to satisfy the user's comfort constraints, exploit the buildings thermal inertia. The nonlinearity of the system stems from the variable flow rate into the hot water tank due to the variable action of the mixing valve. The model is also time-varying due to the fact that the heat pump effciency depends on external conditions. The simulation results show that the proposed optimal control algorithm is able to economically distribute energy among all storages in order to insure cost benefits (almost 20% electricity cost saving) and comfort satisfaction with the feasible computational effort.
Paper VI193-02.2
PDF · Video · Tube-Based Internal Model Control and Its Application to Temperature Control in Buildings
Loehning, Martin	Robert Bosch GmbH
Reimann, Sven	Robert Bosch GmbH
Kotman, Philipp	Robert Bosch GmbH
Keywords: Building Automation, Energy and Distribution Management Systems Abstract: Indoor climate control is a central topic in modern buildings. Especially office spaces have to provide a high comfort for the occupants while at the same time the building operation should require as little energy as possible. Moreover, an upcoming topic in building automation is a fast reaction to user feedback. The traditional design of a room temperature controller focuses solely on a good rejection of input disturbances such as variations of occupancy and solar radiation. Since the transfer functions of the user feedback and the input disturbances to the room temperature differ, a fast reaction to user feedback requires rethinking the design of a room temperature controller. Altogether, there is a desire to use modern controllers for room temperature control. To ensure indoor comfort, the room temperature has to be kept within a certain interval. In this paper, the internal model control method is extended such that the controlled variable is kept in the tube defined by this temperature interval. The main idea is to compute an admissible tube for the planned trajectory. This results in an interval for the control input, which provides a degree of freedom. This is used to minimize the energy consumption. For the implementation in reality, the proposed controller is discretized in time. To ensure a good disturbance attenuation, the controller is combined with a Kalman Filter. The closed-loop behavior of the developed controller is validated in a real building and compared with a state-of-the-art controller.
Paper VI193-02.3
PDF · Video · Multiple Kernel Based Transfer Learning for the Few-Shot Recognition Task in Smart Home Scene
Chang, Shuchao	Zhejiang University
Zhao, Chunhui	Zhejiang University
Keywords: Building Automation, Security Abstract: With the development of artificial intelligence, smart home plays an increasingly important role in daily life. Since new objects may constantly appear at home and the collecting of enough training samples sometimes can be hard, the few-shot recognition task is essential and practical in smart home scene. MULticlass Transfer Incremental LEarning (MULTIpLE) is an effective algorithm that can perform transfer learning for class increment with few new samples based on Support Vector Machine (SVM). But the features of images are generally high-dimensional and the selection for kernel function affects the performance of MULTIpLE. In this paper, a new transfer learning algorithm based on multiple kernel learning, termed MULticlass Transfer Incremental LEarning based on Multiple Kernel Learning (MULTIpLE-MKL), is proposed for the few-shot recognition task in smart home scene. There are two main steps for the MULTIpLE-MKL, including the first multiple kernel learning stage and the second transfer learning stage. Specifically, multiple kernel learning is first applied in the construction of SVM models to optimize the selection of kernel function. When different kernels are calculated based on different features, the sparse kernel coefficients achieve the key feature selection. Second, the SVM models learn a new class from few samples by the virtue of the transfer learning algorithm, MULTIpLE. Compared with conventional methods, experiments based on the benchmark Caltech-256 dataset demonstrate that the proposed MULTIpLE-MKL not only maintains the good performance in original classes but also shows improving recognition ability for new classes only with few training samples.
Paper VI193-02.4
PDF · Video · Hardware-In-The-Loop Test of Learning-Based Controllers for Grid-Supportive Building Heating Operation
Frison, Lilli	Fraunhofer Institute for Solar Energy Systems
Paul, Sweetin	Fraunhofer Institute for Solar Energy Systems ISE
Koller, Torsten	University of Freiburg
Fischer, David	Fraunhofer Institute for Solar Energy Systems ISE
Frison, Gianluca	University of Freiburg
Boedecker, Joschka	University of Freiburg
Engelmann, Peter	Fraunhofer Institute for Solar Energy Systems ISE
Keywords: Energy Storage Operation and Planning, Building Automation Abstract: While MPC is the state-of-the-art approach for building heating control with proven cost savings and improvement in energy flexibility, in practice, buildings are operated by simple rules-based controllers which are not able to accomplish an energy efficient and flexible operation. This paper explores the suitability of deep neural networks for approximating optimal economic MPC strategies for this task. In particular, we develop a convolutional neural network controller and test it in a closed-loop simulation against MPC and an improved predictive rule-based controller. The learned controller is easy to implement and fast to process on standard building control hardware. The feasibility, performance and robustness of the learned controller is validated in a realistic hardware-in-the-loop test setup for the demand-responsive operation of a heat pump combined with a storage tank.
Paper VI193-02.5
PDF · Video · Distributed Multi-Building Coordination for Demand Response
Su, Junyan	ShanghaiTech University
Jiang, Yuning	ShanghaiTech University
Bitlislioglu, Altug	Ecole Polytechnique Fédérale De Lausanne
Jones, Colin N.	EPFL
Houska, Boris	ShanghaiTech University
Keywords: Smart grids, Control system design, Control of renewable energy resources Abstract: This paper presents a distributed optimization algorithm tailored for solving optimal control problems arising in multi-building coordination. The buildings coordinated by a grid operator, join a demand response program to balance the voltage surge by using an energy cost defined criterion. In order to model the hierarchical structure of the building network, we formulate a distributed convex optimization problem with separable objectives and coupled affine equality constraints. A variant of the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN) method for solving the considered class of problems is then presented along with a convergence guarantee. To illustrate the effectiveness of the proposed method, we compare it to the Alternating Direction Method of Multipliers (ADMM) by running both an ALADIN and an ADMM based model predictive controller on a benchmark case study.
Paper VI193-02.6
PDF · Video · An Incremental Scenario Approach for Building Energy Management with Uncertain Occupancy
Karshenas, Arman	University of Oxford
Margellos, Kostas	University of Oxford
Garatti, Simone	Politecnico Di Milano
Keywords: Smart grids, Control system design Abstract: We deal with the problem of energy management in buildings subject to uncertain occupancy. To this end, we formulate this as a finite horizon optimization program and optimize with respect to the windows’ blinds position, radiator and cooling flux. Aiming at a schedule which is robust with respect to uncertain occupancy levels while avoiding imposing arbitrary assumptions on the underlying probability distribution of the uncertainty, we follow a data driven paradigm. In particular, we apply an incremental scenario approach methodology that has been recently proposed in the literature to our energy management formulation. To demonstrate the efficacy of the proposed implementation we provide a detailed numerical analysis on a stylized building and compare it with respect to a deterministic design and the standard scenario approach typically encountered in the literature. We show that our schedule is not agnostic with respect to uncertainty as deterministic approaches, while it requires fewer scenarios with respect to the standard scenario approach, thus resulting in a less conservative performance.
Paper VI193-02.7
PDF · Video · Multi-Building Systems Thermal and Energy Management Via Geothermal Heat Pump (I)
Liang, Lei	Tsinghua University
Wang, Xiaotian	Tsinghua University
Zhang, Xuan	Tsinghua-Berkeley Shenzhen Institute
Sun, Hongbin	Tsinghua University
Keywords: Building Automation, Energy and Distribution Management Systems Abstract: With the growing concern on energy consumption, optimization and control of Geothermal Heat Pump (GHP) systems have become a research hotspot, which can help solve the problem of building energy conservation and shortage. The superiority of current control schemes of GHP systems is often reflected on an individual building with a separate GHP system. However, with the development of urban construction and the increase of population density, study on the district/area case in built-up areas deserves more attention. This paper focuses on typical cases of one GHP system serving multiple buildings and the community-level coordination of GHP systems. In particular, we present a high-order thermal dynamic model of radiator pipes combined with a commonly used second-order resistance-capacitance model for radiator heating/cooling. We design controllers to improve the efficiency of heat pumps and the ability to track a given nominal point of electrical power consumption in a distributed way, without sacrificing too much user comfort. Simulation results show that the proposed real-time distributed temperature control schemes are effective.

VI194
Social Systems - Control Education
VI194-01 Automatic Control in Aerospace Engineering Education   Invited Session, 6 papers
VI194-02 Software in Control Education   Invited Session, 6 papers
VI194-03 Virtual and Remote Labs in Control Engineering Education   Invited Session, 8 papers
VI194-04 Benchmarks and Case Studies for Control Education   Open Invited Session, 13 papers
VI194-05 Advances in Control Education   Regular Session, 11 papers

VI194-01
Automatic Control in Aerospace Engineering Education	Invited Session
Chair: Mimmo, Nicola	University of Bologna
Co-Chair: Invernizzi, Davide	Politecnico Di Milano
Organizer: Castaldi, Paolo	University of Bologna
Organizer: Invernizzi, Davide	Politecnico Di Milano
Organizer: Lovera, Marco	Politecnico Di Milano
Organizer: Mimmo, Nicola	University of Bologna
Paper VI194-01.1
PDF · Video · Application of the H_infinity Control Theory to Space Missions in Engineering Education (I)
Henry, David	Université De Bordeaux
Keywords: University-industry cooperation for training control engineers, Continuing control education in industry Abstract: This paper is a training paper for aerospace engineering education. Its aim is to give the necessary backgrounds for the application of the mixed-sensitivity approach of the robust Hinfini control theory, to space missions. As a support example, the auto-landing phase of a re-entry mission is considered. The considered re-entry vehicle is the HL-20. The paper covers all the aspects of the engineer exercise, i.e. from establishing the non-linear model of the vehicle, considering especially the aerodynamic coefficients, until the implementation of the robust Hinfini controller in the simulator, with a graphical interfacing with the FlightGear flight simulator. Download the complete package simulator + controller design at http://www.ims-bordeaux.fr/images/IFAC_WC2020_HL20.zip and read the file "ToDo.txt"
Paper VI194-01.2
PDF · Video · A Mathematical Model in Automatic Control Aerospace Engineering Education (I)
Castaldi, Paolo	University of Bologna - Aerospace Engineering Faculty
Mimmo, Nicola	University of Bologna
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training Abstract: The aerospace engineering educational system aims to create future professionals able to solve problems of high complexity, with time constraints and which solutions matches prescribed level of performance. In our past work, we introduced the innovative concept of the Professional Readiness Level (PRL) as a unique parameter to quantify how close the students are to the aerospace industry. In this paper we propose a dynamic model, of the PRL, capable to capture, in simple but effective way, the student behaviour we, as professors, observed in our educative experience.
Paper VI194-01.3
PDF · Video · Automatic Control Theory As a Part of Aerospace Training in Russia (I)
Nebylov, Alexander	State University of Aerospace Instrumentation
Nebylov, Vladimir	State University of Aerospace Instrumentation
Keywords: Control and Automation Systems for International Aid, Complexity modelling, Systems Theory Abstract: The article describes the history and achievements of Russian scientists in the field of automatic control theory and systems. The great role of automatic control methods in the essential space projects was shown. The example of automatic landing of aerospace plane Buran was considered. The long scientific activity of acad. Boris E. Chertok as the deputy General Designer for automatic control was analyzed. The particular methods of robust systems synthesis in frequency domain popular in Russia are analyzed and their effectiveness in aerospace projects was shown. The main Russian Universities training students in aerospace technologies are listed.
Paper VI194-01.4
PDF · Video · A Project-Oriented Course on Guidance and Control of Autonomous Aerial Vehicles (I)
Nejjari, Fatiha	Universitat Politecnica De Catalunya
Morcego, Bernardo	Universitat Politecnica De Catalunya
Puig, Vicenç	Universitat Politècnica De Catalunya (UPC)
Trapiello, Carlos	UPC
Keywords: Teaching curricula developments for control and other engineers Abstract: In this paper, a project oriented course on Guidance and control of autonomous aerial vehicles is described. The paper describes the different modules of the course and how they are addressed using the project oriented approach. The project uses a quadrotor UAVs that is used as the case study during the course. In this course, the students learn how to mathematically model quadrotor UAV flight characteristics and develop and tune feedback control algorithms to enable stable flight control, and fuse sensor measurements using Kalman filter techniques to estimate the UAV position and orientation. Students realize these concepts through both simulation and interaction with UAV real measurements. Throughout the course, students build a full 6-degree-of-freedom simulation of controlled quadrotor UAV flight using MATLAB and Simulink.
Paper VI194-01.5
PDF · Video · Various Student’s Projects Related to Aerospace Control Education (I)
Siguerdidjane, Houria	CentraleSupelec
Sordi, Gabriele	Politecnico Di Milano
Keywords: Teaching curricula developments for control and other engineers Abstract: This paper presents the various types of projects that students have to deal within the area of automatic control and signal processing applications at CentraleSupelec, School of Engineering, Université Paris-Saclay. The courses offered during the academic teaching terms or through the elective courses and the laboratory practice sessions are devoted to enable the students to gain knowledge on the one hand and, on the other hand, to foster their skills in different topics. Besides, a focus is made through engineering projects in a framework of industry fulfillment, including professional projects. The aforementioned students’ projects have to be related to the subjects that may or may not be taught as well as to an industrial problematic, encouraging students to propose innovative solutions. Besides, they constitute the first step to get the opportunity to be hired right after graduation. The different subjects are thus adequately designed to train the students on the way forward work in a framework of industry collaboration and requirements. Similar projects are also offered to students enrolled in exchange programs with top European institutions (especially within the Erasmus program). In this paper, some examples of these projects are described, including indoor tests as well as the organization planning.
Paper VI194-01.6
PDF · Video · The Role of Laboratory Activities in Aerospace Control Education: Two Case Studies (I)
Giurato, Mattia	Politecnico Di Milano
Invernizzi, Davide	Politecnico Di Milano
Panza, Simone	Politecnico Di Milano
Lovera, Marco	Politecnico Di Milano
Keywords: Balance issues of theoretical-versus-practical training, Control education using laboratory equipment Abstract: Aerospace control education can significantly benefit from actual hands-on experience. In most cases, however, such experience can only be provided to students in small-scale project activities. In this paper the experience gathered in integrating laboratory activities in aerospace control education in the UAV Lab and in the Advanced Aerospace Control courses is presented and discussed. UAV Lab is an extra-curricular course aimed at an interdisciplinary group of students covering the whole design cycle for a multirotor UAV, from conceptual design to in-flight validation, with specific emphasis on hands-on experience in hardware/software integration, data collection and analysis and flight testing. Advanced Aerospace Control, on the other hand, is a curricular Master course in robust and nonlinear control, in the framework of which students are requested to solve a control design problem formulated over the dynamics of a multirotor UAV. The paper presents the course syllabi, discusses the role of laboratory activities and provides an overview of the obtained results.

VI194-02
Software in Control Education	Invited Session
Chair: Dormido, Sebastián	UNED
Co-Chair: Žáková, Katarína	Slovak University of Technology in Bratislava
Organizer: Dormido, Sebastián	UNED
Organizer: Žáková, Katarína	Slovak University of Technology in Bratislava
Paper VI194-02.1
PDF · Video · EduBal: An Open Balancing Robot Platform for Teaching Control and System Theory (I)
Framing, Christian-Eike	RWTH Aachen University
Hedinger, Raffael	Institute for Dynamic Systems and Control, ETH Zürich
Santiago Iglesias, Emmanuel	RWTH Aachen University
Hesseler, Frank-Josef	RWTH Aachen University, Institute of Automatic Control
Abel, Dirk	RWTH-Aachen University
Keywords: Control education using laboratory equipment, Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training Abstract: In this work we present EduBal, an educational open-source hardware and software platform for a balancing robot. The robot is designed to be low-cost, safe and easy to use by students for control education. Along with the robot we present example tasks from system identification as well as SISO and MIMO control. Using Simulink, students can quickly implement their control algorithms on the robot. Individual control parameters can be tuned online while analyzing the resulting behavior in live signal plots. At RWTH Aachen University and ETH Zurich 28 units have so far been built and used in control classes. In first laboratory experiences students show high intrinsic motivation and creativity to apply the studied concepts of control theory to the real system.
Paper VI194-02.2
PDF · Video · An Interactive Teaching/learning Approach to the Design of Robust Linear Control Systems Using the Closed-Loop Shaping Methodology (I)
Díaz, Jose Manuel	UNED
Dormido, Sebastián	UNED
Costa-Castelló, Ramon	Universitat Politècnica De Catalunya (UPC)
Keywords: Balance issues of theoretical-versus-practical training, Virtual and remote labs, E-learning in control engineering Abstract: Usually the controller is designed working on the open-loop transfer function. However, it is also possible to design the controller working on the closed-loop transfer functions. The closed-loop shaping methodology offers a straightforward framework with allows designers and students to focus on the required specification fulfillment and dealing with inherent linear systems limitations without complex computations or using difficult algorithms. This article summarizes the basic ideas of the manual closed-loop shaping methodology, and its application to the design of robust controllers for uncertainty linear systems. An interactive software tool for learning/teaching this methodology is also presented.
Paper VI194-02.3
PDF · Video · A Control Education Software Suite to Bridge Methodological and Engineering Aspects (I)
Leva, Alberto	Politecnico Di Milano
Cimino, Chiara	Politecnico Di Milano
Seva, Silvano	Politecnico Di Milano
Keywords: Balance issues of theoretical-versus-practical training, Control education using laboratory equipment Abstract: Software obviously plays a relevant role in both control education and engineering. Methodology-centred tools help learning in the class and are also useful for high-level tasks in the profession. Engineering-centred ones are necessary for any realistically sized problem, and their comprehension helps designing efficient and well maintainable control applications. However, brutalising for brevity, the two sets of tools hardly intersect one another, and are most often addressed with very different educational viewpoints---and frequently with some under-emphasis on the engineering side if not for laboratory practice. This paper provides a reasoned overview of the scenario just sketched, and based on a long experience, proposes a coordinated set of tools, selected among well assessed and solidly maintained ones, to help the students bridge methodological and engineering aspects into a unitary forma mentis.
Paper VI194-02.4
PDF · Video · H-Infinity Interactive Controller Design for Teaching Purposes (I)
Díaz, Jose Manuel	UNED
Dormido, Sebastián	UNED
Nicolau Jorda, Bernat	Universitat Politècnica De Catalunya
Costa-Castelló, Ramon	Universitat Politècnica De Catalunya (UPC)
Keywords: E-learning in control engineering, Virtual and remote labs, Teaching curricula developments for control and other engineers Abstract: H-infinity-based controller design is one of the most powerful methodologies for controller design in the frequency domain. Unfortunately, its use requires advanced knowledge of control theory. The use of interactive tools allows to a non-specialized public to use these techniques and to learn the fundamental concepts behind the Hinf theory. In this work a graphical and completely interactive tool used to introduce students in H-infinity control is presented.
Paper VI194-02.5
PDF · Video · Teaching Nonlinear Model Predictive Control with MATLAB/Simulink and an Internal Combustion Engine Test Bench (I)
Keller, Martin	RWTH Aachen University
Ritter, Dennis	RWTH Aachen University
Schmitt, Lukas	RWTH Aachen University
Hänggi, Severin	ETH Zürich
Onder, Christopher Harald	Swiss Federal Institute of Technology Zurich (ETH Zürich)
Abel, Dirk	RWTH-Aachen University
Albin, Thivaharan	RWTH Aachen University
Keywords: Teaching curricula developments for control and other engineers, Control education using laboratory equipment Abstract: Model Predictive Control (MPC) is used for more and more applications in an industrial context. The applications are characterized by increasing complexity while the available computation time is getting smaller and smaller. MPC is the most important advanced control technique with even increasing importance. Hence, this topic should be covered in control lectures during the academic studies in order to prepare students for their future work. For the successful implementation of MPC algorithms, knowledge from multiple disciplines is crucial and needs to be taught. Besides teaching knowledge in classical control theory, especially fundamentals in the fields of modeling, simulation and numerical optimization are required for understanding MPC. Programming skills are inevitable to apply the concept in real-world applications. This paper presents a concept for teaching MPC from the theory to the application to real-world systems. Details about the lectures covering the relevant topics are given. In the hands-on exercises, students implement their own linear as well as nonlinear MPC in MATLAB/Simulink. As example application in the exercises, the air path of a turbocharged diesel engine with high pressure exhaust gas recirculation is investigated. At the end of the semester, students can test their developed controllers on a real diesel engine test bench and compete against each other for the best control performance.
Paper VI194-02.6
PDF · Video · Interactive Software Tool for Design of Higher Derivative Degree PID Controllers (I)
Bistak, Pavol	Slovak University of Technology in Bratislava
Huba, Mikulas	Slovak Univ. of Tech
Keywords: Virtual and remote labs, Internet based teaching of control engineering, E-learning in control engineering Abstract: A new class recently developed controllers extends the family of PID regulators by several new features. The aim of this contribution is to present an interactive software tool for computer support of these controllers among researchers, students and broader research community by providing them with a graphical interface enabling to interact with the controllers and choose their tuning that best fulfils specified requirements. The main advantage of the new controllers, which cover the gap between traditional and fractional-order PID controllers, is that the more consistent solution to the noise filtering problem makes possible work with higher order derivatives and achieving broader spectrum of performance specifications. The paper briefly summarizes in a general way the design of PID controllers with higher derivative degree, noise attenuation and compensation of time delays. Based on this summary and further references the developed software tool is being described that takes the form of a virtual laboratory. The back-end of the tool relies on Matlab simulations, when it provides data of setpoint and disturbance step responses in the chosen loop, where the controlled system is represented by the first order time-delayed system distorted by a noise. The output data of Matlab simulations are processed with the front-end part of the software tool that uses possibilities of JavaScript programming language to interact with the control system and graphically visualize the results in different views within the Web browser environment.

VI194-03
Virtual and Remote Labs in Control Engineering Education	Invited Session
Chair: Dormido, Sebastián	UNED
Co-Chair: de la Torre, Luis	Spanish Open University (UNED)
Organizer: Dormido, Sebastián	UNED
Organizer: de la Torre, Luis	Spanish Open University (UNED)
Paper VI194-03.1
PDF · Video · Cost-Effective Server-Side Re-Deployment for Web-Based Online Laboratories Using NGINX Reverse Proxy (I)
Lei, Zhongcheng	Wuhan University
Zhou, Hong	Wuhan Univ
Ye, Shengwang	Wuhan University
Hu, Wenshan	Wuhan University
Liu, Guoping	University of South Wales
Keywords: Virtual and remote labs, E-learning in control engineering, Control education using laboratory equipment Abstract: Web-based online laboratories are easy-access and non-intrusive for online experimentation, which play a key role in online learning and distance education. For web-based online laboratories, the server-side deployment is vital to provide continuous and stable experimental services which are important features of online laboratories. This paper explores the re-deployment of two versions of a web-based online laboratory, the NCSLab system, with the leverage of the NGINX reverse proxy. With proper configuration, the deployed NGINX server enables a modular backend that can integrate different backend technologies such as Tomcat, PHP and file servers together. To support secure access, only one HTTPS certificate is required to be installed on the NGINX proxy server to support the two systems. The proposed methodology provides solutions for server re-deployment without the change of previous network topology. Moreover, the re-deployment is cost-effective for enabling the re-use of the previous domain name, standard HTTP and HTTPS ports as well as the HTTPS certificate.
Paper VI194-03.2
PDF · Video · Development of a Remote Industrial Laboratory for Automatic Control Based on Node-RED (I)
Domínguez, Manuel	Universidad De León
González-Herbón, Raúl	Universidad De León
Rodríguez-Ossorio, José R.	Universidad De León
Fuertes, Juan J.	Universidad De Leon
Prada, Miguel Angel	Universidad De Leon
Morán álvarez, Antonio	Universidad De Leon
Keywords: Virtual and remote labs, Control education using laboratory equipment, Internet based teaching of control engineering Abstract: In this paper, we propose a remote laboratory for automatic control that enables an easier interconnection and integration of its elements. It is based on Node-RED and the MQTT protocol, which enable the easy development of laboratories and an intuitive but flexible user interface for the students. Node-RED is an open-source programming platform oriented to easily connect hardware devices, APIs and online services. The remote laboratory uses three different elements: an instructor’s client, one student’s client for each student and a central broker. The instructor’s client is the only one with direct access to the plant, through a Modbus TCP connection to the PLC, so it decides which student can manage the system and monitor their actions, hiding the complexity of automation to the students and providing an additional layer for safety and security. The students’ clients are installed in the laboratory or students’ own PCs. To perform the tasks, the students use a predefined dashboard or the Node-RED editor for easy graphical programming. In any case, the process is as follows: instructor’s client reads/writes variables of the plant, publishes their values using a multi-level hierarchical structure, subscribes to the control actions published by the students’ clients and manages how and when those actions are sent to the corresponding pilot plant. This approach has been assessed through the implementation of a hands-on task where students need to set the parameters of a PID to appropriately control the level of a tank in a real pilot plant.
Paper VI194-03.3
PDF · Video · A Virtual Lab for Modeling and Control of a Solar Collector Field (I)
Guzman, Jose Luis	University of Almeria
Berenguel, Manuel	University of Almeria
Merchan, Alejandra	University of Almeria
Gil, Juan Diego	Universidad De Almería
álvarez, José Domingo	University of Almería
Keywords: Virtual and remote labs, Internet based teaching of control engineering Abstract: Research and teaching on renewable energies are very important topics worldwide. Most of the renewable energy processes are quite complex to analyze and to study. For that reason, educational resources as support for the teaching and learning of these processes dynamics are very useful. Thus, this paper presents a virtual lab as support to the modeling and control concepts of a solar collector field, as these kind of solar plants are widely used at industrial level requiring control skills. This interactive tool is used as part of several subjects in a Master on Solar Energy at the University of Almería, Spain. Examples about open and closed-loop exercises are presented.
Paper VI194-03.4
PDF · Video · Learning Planar Robotics with an Open Source Online Laboratory (I)
Saenz, Jacobo	UNED
de la Torre, Luis	Spanish Open University (UNED)
Chacón, Jesús	Universidad Nacional De Educación a Distancia
Dormido, Sebastián	UNED
Keywords: Virtual and remote labs, Control education using laboratory equipment, Internet based teaching of control engineering Abstract: This work describes two open source and low-cost online laboratories to explore the field of planar robotics and the tools used to create them. Each lab contains two versions:a simulation lab and a remote lab, both ready-to-use within an online course or available to be built by the students. Additionally, the reduced cost of the remote lab allows students to make it at home as a classical hands-on system. This last do-it-yourself approach provides them the means to gain experiential knowledge and perform tasks related with control, electronics, robotics and programming
Paper VI194-03.5
PDF · Video · ELab: A Lightweight SCADA System for Control Engineering Research and Education (I)
Kaluz, Martin	Slovak University of Technology in Bratislava, Slovakia
Cirka, Lubos	Slovak University of Technology in Bratislava
Fikar, Miroslav	Slovak University of Technology in Bratislava
Keywords: Virtual and remote labs, Control education using laboratory equipment Abstract: This paper presents a lightweight SCADA system eLab that is based on open-source and affordable hardware/software technologies. The primary purpose of eLab is to provide an easy means for researchers and students to perform laboratory experiments, without requirements for extensive configuration on the side of the user. The architecture of the system consists of several functional parts. I/O nodes are hardware devices that directly connect and electrically control sensors and actuators of laboratory equipment. For this purpose, an implementer can either use a dedicated MCU, such as Arduino board, a single-board computer like Raspberry Pi, or any device with UART communication capabilities. The central part of eLab is a SCADA master, i.e., the computer that serves all the functionalities required by a SCADA system. The SCADA software is implemented in server-side JavaScript (Node.js). The communication between I/O nodes and SCADA master is served via XBee radio modules. The master computer acts as a communication gateway between I/O nodes and other parts of the system. The gateway provides a dedicated RESTful API that is used for the front-end connection to control software or HMI. Additionally, the system uses an internal database for configuration of experiments, tags, and data sessions. The eLab also provides a novel integration with DCore blockchain technology so that the users can store the data either in private or public blockchain network. The use of blockchain ensures the preservation, immutability, and verifiability of measured data.
Paper VI194-03.6
PDF · Video · 3D Visualization Methods in Online Control Experimentation (I)
MatiŠák, Jakub	Faculty of Electrical Engineering and Information Technology, Sl
Žáková, Katarína	Slovak University of Technology in Bratislava
Keywords: Virtual and remote labs, Internet based teaching of control engineering, Virtual classes, departments, laboratories and schools Abstract: Classical teaching of control theory that is based on mathematical models can sometimes be quite difficult for students. Not everybody is able to understand physical meaning of differential equations immediately. The use of various visualizations can facilitate the process of learning. The paper describes the system that presents animations of mechatronic systems to students. They can be run in two modes – in open loop to follow the dynamical behavior of the system without the use of any controller and in closed loop that considers the basic PID controller. The aim is to show students the effect of the individual components of the controller, i.e. the effect of P, I and D part. The visualization is realized in two forms: first, we use 3D animation that is available as the web application and then we decided to use increasingly popular augmented reality. This kind of simulation is available via smartphones and it is based on Google Services for AR platform, built for augmented reality experience. Both types of visualizations will be illustrated on the model of towercopter that we have in our laboratory also as a real plant. Using the presented educational environment allows students to achieve first experience with the system, before they want to use a real device in laboratory.
Paper VI194-03.7
PDF · Video · Remote Control Laboratory for Three-Tank Hydraulic Using Matlab, Websockets and JavaScript (I)
Bistak, Pavol	Slovak University of Technology in Bratislava
Keywords: Virtual and remote labs, Internet based teaching of control engineering, Virtual classes, departments, laboratories and schools Abstract: This work aims to introduce a new architecture for building virtual and remote laboratories where the building blocks are represented by the Matlab/Simulink computing and simulation software, WebSocket communication technology and a front-end application created in JavaScript programming language. Matlab does not have direct support for WebSockets, but the implementation of the MatlabWebSocket library on the Matlab server has allowed connection through WebSockets that has been accepted with the client side realized in JavaScript. Additionally to the interactivity that is heavily supported by JavaScript, the remote laboratory has been visualized on the client side in 3D by implementation of the Three.js JavaScript library. From the control point of view the new remote laboratory enables to compare nonlinear feedback control with dynamical feedforward control respecting input saturation where in both cases a nonlinear disturbance observer can be used. WebSocket communication technology and the corresponding client interface in the form of a web application create possibilities for the presented remote laboratory to run from the Internet browser and no dedicated application is needed as it was in previous Matlab based laboratories what can be considered as a main contribution.
Paper VI194-03.8
PDF · Video · Scalable Remote Experiment Manager (I)
Rábek, Matej	Slovak University of Technology in Bratislava
Žáková, Katarína	Slovak University of Technology in Bratislava
Keywords: Virtual and remote labs, Internet based teaching of control engineering, Control education using laboratory equipment Abstract: This paper describes an online laboratory system prioritizing modular and generalized solutions. The system provides a unified user interface to access, manage and control remote experiments. At the same time it does not put up restrictions limiting usable control algorithms or even simulation environments. Several connected devices are integrated with the use of Matlab and Scilab software so users can create their control block diagrams in either Simulink or Xcos. It is even possible to declare variables within these diagrams and then initialize them through the system's user interface. A set of commands was selected to represent the possible operations a device can implement. This serves to optimize the communication, since each of these commands is interpreted by a specialized python or shell script transferring all the user inputs and other necessary data either directly to the device or to a running instance of a simulation environment. System's functionality is demonstrated on a remote experiment based on levitating ball in a vertical tube. This method of control makes the system highly scalable as the new experiments can be added while the system is deployed.

VI194-04
Benchmarks and Case Studies for Control Education	Open Invited Session
Chair: Rossiter, J. Anthony	Univ of Sheffield
Co-Chair: Visioli, Antonio	University of Brescia
Organizer: Rossiter, J. Anthony	Univ of Sheffield
Organizer: Visioli, Antonio	University of Brescia
Organizer: Serbezov, Atanas	Rose-Hulman Institute of Technology
Organizer: Žáková, Katarína	Slovak University of Technology in Bratislava
Paper VI194-04.1
PDF · Video · Blended Learning in Control Engineering Teaching; an Example of Good Practice (I)
Rossiter, J. Anthony	Univ of Sheffield
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training, Perspectives of e-learning versus traditional learning Abstract: This paper focuses on good practice in terms of pedagogies rather than technical content, but with reference to a control engineering curriculum. A new lecturer will need to ask questions not only about the content of a course but also, how should that content be delivered? The paper presents arguments for a holistic or blended approach to student development and illustrates how that can be wrapped around technical learning outcomes. A core part of this approach is effective use of modern technologies. This paper provides a summary of good practice and an illustrative benchmark module.
Paper VI194-04.2
PDF · Video · A Software Tool to Make Primary School Students Aware of Control Systems (I)
Giacomelli, Marco	University of Brescia
Beschi, Manuel	University of Brescia
Simoni, Luca	University of Brescia
Visioli, Antonio	University of Brescia
Keywords: Virtual and remote labs Abstract: In this paper we present a simple software tool, designed as a game, that can be used to make (especially primary) school students aware of the importance of control systems. An overhead crane model is used as an effective dynamic system to show the difficulty of applying manual control in some contexts and how a control system can help to achieve the required performance. In addition to the technical details of the tool, which has been developed in Matlab, the overall experience with the students is explained in the paper and some preliminary results of its use with people without expertise in control are discussed.
Paper VI194-04.3
PDF · Video · A First Course in Feedback, Dynamics and Control: Findings from 2019 Online Survey of the International Control Community (I)
Rossiter, J. Anthony	Univ of Sheffield
Žáková, Katarína	Slovak University of Technology in Bratislava
Huba, Mikulas	Slovak Univ. of Tech
Serbezov, Atanas	Rose-Hulman Institute of Technology
Visioli, Antonio	University of Brescia
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training Abstract: This paper summarizes the results from a large-scale survey on the content and teaching philosophy of the first, and in many cases the only, control course taken by undergraduate students in engineering and applied sciences around the world. The IFAC Technical Committee on Education developed and administered the survey in 2019. At the time of writing, 201 control professionals have responded to the survey. The majority view is that the first course in control should focus on concepts and avoid excessive mathematical proofs. The responders ranked the depth of coverage of 63 topics commonly found in introductory control texts. Based on the ranking results, a sample curriculum for a first control course is outlined.
Paper VI194-04.4
PDF · Video · Active Learning in Control Education: A Pocket-Size PI(D) Setup (I)
Juchem, Jasper	Ghent University
Chevalier, Amélie	Ghent University
Dekemele, Kevin	Ghent University
Loccufier, Mia	Ghent University
Keywords: Control education using laboratory equipment, Teaching curricula developments for control and other engineers Abstract: Active learning techniques have the possibility to enhance student performance. In control engineering these techniques unravel concepts such as feedback control, proportional-integral-derivative control, system dynamics, etc. This paper presents the development of pocket-size PID setups and how they are implemented in an undergraduate course of control engineering. The setup makes use of an electrical circuit which has the capability of mimicking a wide range of processes, thus appealing to the multidisciplinary character of the student group. Custom-made analog PID printed circuit boards are developed, making each part of the controller transparent. Open-source software is used to build a graphical user interface to communicate with data-acquisition cards used in industry. It is shown in this paper that investing in mobile setups which are numerous, allows for active learning in control education. This leads to better understanding of abstract concepts and increased student performance.
Paper VI194-04.5
PDF · Video · LQG Controller for the LEGO MINDSTORMS EV3 Gyroboy Segway Robot (I)
Hughes, Timothy H.	University of Exeter
Willetts, Gareth Haydn	University of Exeter
Kryczka, Jakub	University of Exeter
Keywords: Control education using laboratory equipment, Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training Abstract: This paper details the development of a Segway robot demonstrator for undergraduate and Masters level systems and control courses based on the LEGO MINDSTORMS EV3 robotics platform. The purpose of the demonstrator is to provide a physical and interactive device for explaining concepts that feature on many systems and control courses, notably: model-based control, linearisation, the Linear-Quadratic Regulator (LQR), pole placement, noise amplification due to dierentiation, reference following, Kalmanltering, and the principle of separation of estimation and control. The demonstrator is designed using a standard LEGO MINDSTORMS model from the Education EV3 core set|the Gyroboy. This is interfaced with using the Simulink Support Package for LEGO MINDSTORMS EV3 Hardware. Reference inputs can be provided from either a keyboard or an Xbox One gamepad. To the best of our knowledge, this is the first example of the successful implementation of an observer-based reference-following feedback controller for a Segway robot built entirely using LEGO MINDSTORMS EV3 components, with previous designs being either not observer-based or based on the now outdated LEGO MINDSTORMS NXT platform.
Paper VI194-04.6
PDF · Video · FloatShield: An Open Source Air Levitation Device for Control Engineering Education (I)
Takács, Gergely	Slovak University of Technology
Chmurčiak, Peter	Slovak University of Technology in Bratislava
Gulan, Martin	Slovak University of Technology
MikuláŠ, Erik	Slovak University of Technology in Bratislava
Kulhánek, Jakub	Slovak Technical University in Bratislava
Penzinger, Gábor	STU
Podbielancik, Milos	STU BA
Lučan, Martin	Slovak University of Technology in Bratislava
Salka, Peter	Slovak Technical University in Bratislava, Faculty of Mechanical
Šroba, Dávid	UAMAI STU
Keywords: Control education using laboratory equipment, Teaching curricula developments for control and other engineers Abstract: A novel reference design for an air levitation system to teach control engineering and mechatronics is introduced. The device is built as a swappable and compact extension shield for Arduino embedded microcontroller prototyping boards. The fully documented hardware design uses off-the-shelf electronic components and 3D printed mechanical parts to encourage easy and low-cost replication with editable design files provided online. The open source software includes an application programming interface for the Arduino IDE, MATLAB and Simulink. The examples included with the software demonstrate possibilities for typical classroom use.
Paper VI194-04.7
PDF · Video · Highly Automated Electric Vehicle Platform for Control Education (I)
Fehér, árpád	Budapest University of Technology and Economics
Aradi, Szilárd	Budapest University of Technology and Economics
Bécsi, Tamás	Budapest Univ of Technology and Economics
Gaspar, Peter	SZTAKI
Keywords: Control education using laboratory equipment, Intelligent Transportation, Balance issues of theoretical-versus-practical training Abstract: The paper presents a small-scale electric vehicle framework for vehicle control education and research. The main goal of the project is to serve as a good experimental platform for the students on any level of vehicle mechatronics education. It offers wide range of possibilities for embedded system, control design and machine learning applications. The proposed system is a redesigned version of our former experimental vehicle framework. The project was scheduled for two main goals. One was to design and implement a Robot Operating System based vehicle with Ackermann steering. The other was to develop a platform, which can be highly integrated into vehicle control education. In the paper the system architecture, the sensors and the control units are detailed, furthermore the educational benefits and some use cases are presented.
Paper VI194-04.8
PDF · Video · Model-Based System Engineering in Control Education Using HIL Simulators (I)
Cech, Martin	University of West Bohemia in Pilsen
Goubej, Martin	University of West Bohemia
Sobota, Jaroslav	University of West Bohemia in Pilsen
Visioli, Antonio	University of Brescia
Keywords: Balance issues of theoretical-versus-practical training, Control education using laboratory equipment, University-industry co-operation in control engineering education Abstract: Nowadays, model-based and knowledge-based system engineering bring completely new demands also to the master degree teaching process and programs. Specifically, it is necessary to establish gluing technologies between individual master degree courses while full STEM education scope is covered. Since huge changes in educational system are often subject to complex, time demanding evaluation and approval process, there is usually significant delay between actual industrial needs and time when universities are able to deliver to the market engineers with required knowledge and curricula. Consequently, solutions which can be implemented in actual courses without huge investments of money and time is what educators should strive for. This paper shows how simple hardware-in-the-loop (HIL) simulators may help during the whole training period while respecting needs of already established courses dealing e.g. with modelling and simulation, control design, industrial IT and communication, control HW and electronics, sensors and actuators. The concept is demonstrated on several examples of already proven procedures in primary and second control courses.
Paper VI194-04.9
PDF · Video · Experience with Use of HIL Simulators in Control Engineering Course (I)
Goubej, Martin	University of West Bohemia
Langmajer, Martin	University of West Bohemia
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training, Control education using laboratory equipment Abstract: The goal of the paper is to share experience with the use of hardware-in-the-loop (HIL) simulators in a control-engineering course being taught at the University of West Bohemia. The hardware simulators were introduced recently in the course curriculum aiming to get more realistic application scenarios for the students. They allow simple explanation of the concepts of model-based systems engineering in a form close to the workflow used in industrial practice. The achieved results show some significant benefits when compared to former course content, which relied on numerical simulations only. The paper presents one of the application use-cases dealing with the problem of active car suspension control. Individual phases of the control system development as done by students are explained step by step, revealing the main benefits of the hands-on experience with the physical setup.
Paper VI194-04.10
PDF · Video · A Hardware-In-The-Loop Prototype to Design Benchmarks for Automation and Control Education (I)
Castilla, Maria del Mar	University of Almeria
Rodríguez-Díaz, Francisco	Univ of Almería
álvarez, José Domingo	University of Almería
Donaire, Julian G.	University of Almería
Ramos-Teodoro, Jerónimo	University of Almería
Keywords: Teaching curricula developments for control and other engineers, Control education using laboratory equipment, Virtual classes, departments, laboratories and schools Abstract: At present, most of the systems which can be found in an industrial environment present both sequential (discrete) or mixed (continuous and discrete) dynamics that must be controlled, monitored and supervised. For this reason, studying these systems and how they can be controlled is a crucial issue which should be covered in engineering education. This article presents a Hardware-in-the-Loop prototype which can be used for automation and control training. This prototype allows teachers to design, in an intuitive manner, different benchmarks to be solved by students in laboratory practice sessions. These benchmarks can be easily adapted to the level and the area of knowledge of students. An example of benchmark has been proposed and commented. Moreover, students' opinion regarding a preliminary version of the prototype has been included and discussed.
Paper VI194-04.11
PDF · Video · Introducing Control Theory in Industry: The Case of V-Model Embedded Software Developers (I)
Tiberi, Ubaldo	Volvo Group Trucks Technology
Keywords: Continuing control education in industry Abstract: This paper presents an education course on Control Theory suitable for embedded software developers that are familiar with the V-model. The need of such course is due to the specific audience and business needs, but it can be easily be adapted and employed in other domains. The course is structured in terms of a Control Theoretical workflow that resembles the development workflow provided by the Vmodel. Each phase represents an education module. The effectiveness of the course is evaluated through questionnaires and an ad-hoc analysis of the quality of the software deliveries of some employees before and after having attended the course
Paper VI194-04.12
PDF · Video · Automatic Control: The Natural Approach for a Quantitative-Based Personalized Education (I)
Knorn, Steffi	Uppsala University
Varagnolo, Damiano	NTNU - Norwegian University of Science and Technology
Keywords: Perspectives of e-learning versus traditional learning, Knowledge networks Abstract: This paper proposes an engineering-oriented framework that casts the problem of learning as an automatic control problem, and that can ultimately be used to design education activities that autonomously adapt to individual students’ abilities, prerequisites, learning goals and other restrictions. The framework leverages on quantitative descriptions of knowledge flows within university programs in terms of Knowledge Components Matrices (KCMs) and Knowledge Flow Graphs (KFGs), that serve as the basis for developing the aforementioned automated approach to personalized education. Essentially, the manuscript proposes to: 1) combine these descriptions with results from exams and assessments to statistically estimate the learning status of a student; 2) combine these descriptions with data-driven approaches to derive models of how knowledge ladders logically and in time; 3) use these two ingredients to automatically design suitable and personalized study activities for a student, given his/her current knowledge status and desired learning outcome. We describe all steps (modelling of the knowledge flows, estimating the current learning status, and derivation of suitable learning activities to close the loop) with formal and control-oriented notation. The paper serves thus the purpose of showing how methods from the field of system theory and control engineering are naturally useful for the implementation of quantitative-based personalized education.
Paper VI194-04.13
PDF · Video · Networked and Autonomous Model-Scale Vehicles for Experiments in Research and Education (I)
Scheffe, Patrick	RWTH Aachen University
Maczijewski, Janis	RWTH Aachen University
Kloock, Maximilian	RWTH Aachen University
Kampmann, Alexandru	RWTH Aachen University
Derks, Andreas	RWTH Aachen University
Kowalewski, Stefan	RWTH Aachen Univ
Alrifaee, Bassam	RWTH Aachen University
Keywords: Control education using laboratory equipment, Connected Vehicles Abstract: This paper presents the MicroCar, a 1:18 model-scale vehicle with Ackermann steering geometry developed for experiments in networked and autonomous driving in research and education. The vehicle is open source, moderately costed and highly flexible, which allows for many applications. It is equipped with an inertial measurement unit and an odometer and obtains its pose via WLAN from an indoor positioning system. The two supported operating modes for controlling the vehicle are (1) computing control inputs on external hardware, transmitting them via WLAN and applying received inputs to the actuators and (2) transmitting a reference trajectory via WLAN, which is then followed by a controller running on the onboard Raspberry Pi Zero W. The design allows identical vehicles to be used at the same time in order to conduct experiments with a large amount of networked agents.

VI194-05
Advances in Control Education	Regular Session
Chair: van Nooijen, Ronald Robert Paul	Delft University of Technology
Co-Chair: Sotomayor-Moriano, Javier	Pontificia Universidad Católica Del Perú
Paper VI194-05.1
PDF · Video · An Embedded Systems Laboratory for Aerospace Students
de la Puente, Juan Antonio	Universidad Politecnica De Madrid
Alonso, Alejandro	Univ. Politécnica De Madrid
Garrido, Jorge	Universidad Politecnica De Madrid
Zamorano, Juan	Universidad Politécnica De Madrid
Keywords: Control education using laboratory equipment, Teaching curricula developments for control and other engineers Abstract: The UPM Master in Space Systems (MUSE) is a two-year graduate program focused on space systems technology. The program is largely project-based, with the UPMSat-2 satellite mission as a general framework to which the various course subjects are applied. The course on Data Housekeeping deals with the hardware and software aspects of the on-board computer systems in charge of data acquisition, monitoring and control within a spacecraft, with special reference to UPMSat-2, as well as the command and supervision functions of the associated ground segment. Since the real hardware used on the satellite is expensive and thus not amenable to use in laboratory work, except in very limited situations, a simplified engineering model of it has been developed by the authors. The model is based on a cheap, reduced size microcomputer board kit that can be easily acquired and taken home by the students in order to carry out the laboratory assignments and supplementary work as needed. The hardware and software components of the laboratory kit, its use in the course, and its impact on the students performance, are described in the paper.
Paper VI194-05.2
PDF · Video · Real-Time Control and Hardware-In-The-Loop Simulation for Educational Purposes of Wind Energy Systems
Gambier, Adrian	Fraunhofer IWES, Fraunhofer Institute for Wind Energy Systems
Keywords: Control education using laboratory equipment, University-industry cooperation for training control engineers, University-industry co-operation in control engineering education Abstract: The education of students in the area of wind energy engineering for industrial as well as research activities is every day more and more challenging. Wind energy converters become continuously larger and more complex and therefore advanced expertise is necessary. On the other hand, large machines are not available neither for research nor for teaching. In particular, the field of control of wind turbines is principally affected because control systems have to be proved in real-time and new control engineers are not able to be familiar with such systems and then it is not possible to gain practical experience. To this end, Hardware-in-the-Loop (HiL) simulation and control can play an important role in this sense. In the present contribution, an architecture of a HiL system for real-time control and simulation of wind turbines is presented. The use of the system helping students in the development of their Master thesis is illustrated by some examples.
Paper VI194-05.3
PDF · Video · Teaching Model-Based Fault Detection and Isolation Using a Virtual Laboratory Environment
Sotomayor-Moriano, Javier	Pontificia Universidad Católica Del Perú
Pérez Zuñiga, Gustavo	Pontifical Catholic University of Peru
Soto Angles, Mario	Pontificia Universidad Católica Del Perú
Enciso Salas, Luis Miguel	Pontificia Universidad Católica Del Perú
Keywords: Control education using laboratory equipment, Virtual and remote labs, Continuing control education in industry Abstract: Fault detection and isolation (FDI) systems play a key role to provide efficiency, reliability and safety in today’s industrial processes. The teaching of FDI systems is facilitated if it is carried out not only with theoretical lectures but also with practical experiences. This paper proposes a virtual laboratory environment (VLE) to carry out online practical experiences with FDI systems for a benchmark process. Thanks to this VLE, students can set up faults in sensors, actuators or in the process itself, program model-based FDI algorithms and test FDI system performance. The use of this environment is illustrated by testing the performance of FDI systems for the quadruple-tank process (4TP) under different fault scenarios. Finally, the procedure of using this proposal for practical experience with two model-based FDI design methods is shown.
Paper VI194-05.4
PDF · Video · Facilitating Learning Progress in a First Control Course Via Matlab Apps
Koch, Anne	University of Stuttgart
Lorenzen, Matthias	University of Stuttgart
Pauli, Patricia	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: E-learning in control engineering Abstract: It is well-known that students learn substantially more if a lecture is complemented by active inquiry-based activities and problem solving than from only passively listening to a lecture. Naturally, this requires the teacher to include elements into the course such as laboratories, group projects, tutorials and interactive e-learning modules. For the most effective teaching concept, all such components of the course work are tightly intertwined and work together towards the same goal and learning objectives. Therefore, we show in this paper how Matlab apps can be included into the wider effort of learning facilitation in an introductory automatic control course. Among other advantages, Matlab apps can offer an unlimited number of exercises and examples that can be generated automatically, they offer interactive interfaces that can include gamification aspects such as levels and highscore lists to increase the motivation, and they can be done at the students' own pace. The course evaluation and the feedback from students at the University of Stuttgart suggest that the inclusion of the Matlab apps presented in this paper is indeed a success.
Paper VI194-05.5
PDF · Video · CSPS: An Interactive Tool for Control Design and Analysis of Processes with Industrial Characteristics
Silva, Lucian Ribeiro da	Universidade Federal De Santa Catarina
Flesch, Rodolfo C. C.	Federal University of Santa Catarina
Normey-Rico, Julio Elias	Federal Univ of Santa Catarina
da Costa Mendes, Paulo Renato	Federal University of Santa Catarina
Keywords: E-learning in control engineering, Continuing control education in industry, Balance issues of theoretical-versus-practical training Abstract: This work presents an user friendly interactive tool for control design, simulation and analysis of systems with characteristics commonly found in industry, such as dead time, constraints and measurement noise. The tool is able to validate and compare, in a simple and intuitive way, the performance and robustness of the three control structures most widely used in industrial applications: proportional-integral-derivative (PID), dead-time compensators (DTC), and model predictive control (MPC). Furthermore, the tool provides several options of techniques for handling input and output process constraints. A case study is used to illustrate some of the features of the tool.
Paper VI194-05.6
PDF · Video · Smartphone Apps for Learning Progress and Course Revision
Pauli, Patricia	University of Stuttgart
Koch, Anne	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: E-learning in control engineering, Perspectives of e-learning versus traditional learning Abstract: Smartphones as our permanent companion seem to be an expedient choice for the implementation of e-learning tools in the form of smartphone apps due to their convenience and accessibility. We hence present two recently published smartphone apps that were developed for an introductory control course. The apps serve the purposes of (i) improving learning progress and (ii) revision of course content between lectures. In this paper, we explain how the apps align with our lecture Introduction to Automatic Control, put them into context of our e-learning strategy and describe our pursued goals. Moreover, a survey among third year control students is discussed, which supports the presented approach. Finally, we discuss and compare the mean (smartphone app) to other measures, considering both content and goals.
Paper VI194-05.7
PDF · Video · A Pedagogical Path from the Internal Model Principle to Youla-Kučera Parametrization
Hedberg, Erik	Linköping University
Löfberg, Johan	Linköping University
Helmersson, Anders	Linköpings Universitet
Keywords: Teaching curricula developments for control and other engineers Abstract: We propose a sequence of pedagogical steps for introducing the Youla-Kučera parametrization and a number of related concepts, starting from the internal model principle, and introducing the control structures of disturbance observer and internal model control along the way. We provide some background on the concepts and a brief survey of their treatment in control textbooks.
Paper VI194-05.8
PDF · Video · Water System Examples for Control Education
van Nooijen, Ronald Robert Paul	Delft University of Technology
Kolechkina, Alla G.	Delft University of Technology
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training Abstract: Management of water systems is becoming more and more complex; this creates opportunities for the application of control theory. These opportunities are the subject of a course on operational water management given to students of the water management department, Delft University of Technology, over the past 15 years. Traditional examples in control theory courses are taken from industry and do not easily map to water systems, so examples were developed that use water systems to illustrate control theory concepts. This provided the students with a link between control theory and water management practice.
Paper VI194-05.9
PDF · Video · Modelling for Control: Combination of Education Approaches
Atanasijevic-Kunc, Maja	University of Ljubljana
Karer, Gorazd	University of Ljubljana
Zdesar, Andrej	University of Ljubljana
Keywords: Teaching curricula developments for control and other engineers, Balance issues of theoretical-versus-practical training, Control education using laboratory equipment Abstract: At the University of Ljubljana, Faculty of Electrical Engineering we have introduced several years ago the Bologna study. At the postgraduate or master level, students can choose among eight different possible study fields, where one is Control systems and computer engineering. In the first semester of this study field, all students have to attend the course entitled Modelling methods. As students come from different faculties, their first-level education differs. As a consequence, some additional effort is needed each year to adjust the knowledge, which is very important for all the participants, while new lessons have to be presented in a suitable manner as well. This has to be realized taking into account the available hours for this course and the personal knowledge of all students. The problem was addressed through the combination of different approaches: through the modular organization of the lectures and laboratory exercises, through e-learning extensions, through the development of Matlab toolbox, and through the project-oriented work and exams, which enable additional research activity with the possibility of students’ competition participation and/or presentation and publication of research results. Such an organization seems to have significant motivation potential.
Paper VI194-05.10
PDF · Video · Position Control of a Mobile Robot Using Reinforcement Learning
Farias, Gonzalo	Pontificia Universidad Catolica De Valparaiso (PUCV)
Garcia, Gonzalo	Florida Atlantic University
Montenegro, Guelis	Pontificia Universidad Católica De Valparaíso
Fabregas, Ernesto	Universidad Nacional De Educación a Distancia (UNED)
Dormido Canto, Sebastián	UNED
Dormido, Sebastián	UNED
Keywords: Teaching curricula developments for control and other engineers, Control education using laboratory equipment Abstract: Robotics has been introduced in education at all levels during the last years. In particular, the application of mobile robots for teaching automatic control is becoming more popular in engineering because of the attractive experiments that can be performed. This paper presents the design, development, and implementation of an algorithm to control the position of a wheeled mobile robot using Reinforcement Learning in an advanced 3D simulation environment. In this approach, the learning process occurs when the agent makes some actions in the environment to get some rewards. Trying to make a balance between the new information of the environment and the current knowledge about it. In this way, the algorithm is divided into two phases: 1) the learning stage, and 2) the operational stage. In the first stage, the robot learns how to reach a known destination point from its current position. To do it, it uses the information of the environment and the rewards, to builds a learning matrix that is used later during the operational stage. The main advantage of this algorithm concerning traditional control algorithms is that the learning process is carried out automatically with a recursive procedure and the result is a controller that can make the specific task, without the need for a dynamic model. Its main drawback is that the learning stage can take a long time to finish and it depends on the hardware resources of the computer used during the learning process.
Paper VI194-05.11
PDF · Video · Optimization of Students' Graduation by the University Taking into Account the Needs of the Labor Market
Agarkov, Gavriil	Ural Federal University Named after the First President of Russi
Tarasyev, Alexandr A.	Ural Federal University Named after the First President of Russi
Sushchenko, Anastasia	Ural Federal University
Keywords: Optimal control theory, Differential or dynamic games, Control problems under conflict and/or uncertainties Abstract: The development of the socio-economic system and the labor market is directly related to the training of young specialists in higher education institutions in accordance with the needs of developing regions. To optimize the functioning of the labor market, it is necessary to compensate for the shortage of highly qualified personnel depending on the areas of training and determine the structural proportions of the optimal number of graduates, based on the share of employed and unemployed in various sectors of the economy. The University meets the needs of regional labor markets with a significant proportion of young highly qualified specialists. To optimize the educational process, it is necessary to analyze and model the impact of educational paths of graduates on the labor market by determining the equilibrium unemployment in the labor market. The proposed approach combines a model for maximizing the expected salary of students with a modification of the search and matching model. At the first level of model construction, we apply an econometric model that allows us to adapt educational paths to the interests of students. At the second level, we describe the behavior of students, choosing an educational path. At the third level, the structure of graduates adapts to the requirements of the labor market. The research perspective is the introduction of feedback mechanisms from graduates of regional Universities using surveys for a comprehensive assessment of the quality of graduate programs of the University with administrative data on the educational paths of graduates.

VI195
Social Systems - Technology, Culture and International Stability
VI195-01 Past, Present and Future: Technology Developments in View of Their Impact on Society, the Environment and International Stability   Open Invited Session, 6 papers
VI195-02 Social Aspects of Automation   Regular Session, 13 papers

VI195-01
Past, Present and Future: Technology Developments in View of Their Impact on Society, the Environment and International Stability	Open Invited Session
Chair: Stapleton, Larry	Waterford Institute of Technology
Co-Chair: O'Neill, Brenda	Insyte, Waterford Institute of Technology
Organizer: Stapleton, Larry	Waterford Institute of Technology
Organizer: Brandt, Dietrich	RWTH Aachen University
Organizer: Gill, Karamjit S	University of Brighton
Organizer: Groumpos, Peter	University of Patras
Organizer: O'Neill, Brenda	Insyte, Waterford Institute of Technology
Organizer: Hersh, Marion A.	University of Glasgow
Organizer: Hancke, Tania	DLR
Paper VI195-01.1
PDF · Video · Identification, Definition and Improvement of Factors Which Significantly Influence International Stability and Improve Its Effectiveness (I)
Pearson, Sue	Sue Pearson
Keywords: Cognitive aspects of automation systems and humans, International Development, Knowledge Society Abstract: This paper looks at the converging relationship between artificial intelligence and the human brain, the consequences and risks of the human/machine interface, its effects on individual, national and international stability, and an alternative pathway for human development.
Paper VI195-01.2
PDF · Video · Climate Change, Artificial Intelligence and the Un-Foreseeability of the Future (I)
Lamotte, Malenka de	Le Poet-Celard
Keywords: Knowledge Society, Value systems, Ethics Abstract: If we continue to act like we did since about 100 years, we will most probably end up in an overheated Earth where living conditions for human beings are everything but comfortable. We know that survival would be hard or impossible for many species living today. Most scholars in the independent scientific community agree on that. Thus the question is what to do about it. I would like to put this question before our group of IFAC participants during our joint Open Track session on Past, present and future.
Paper VI195-01.3
PDF · Video · A Discourse on AI and Society: Your Calculus May Be Greater Than His Calculus but Will It Pass the Sullenberger Hudson River Test? (I)
O'Neill, Brenda	Insyte, Waterford Institute of Technology
Stapleton, Larry	Waterford Institute of Technology
Gill, Karamjit S	University of Brighton
Brandt, Dietrich	RWTH Aachen University
Keywords: Maintenance models and services, Intelligent maintenance systems Abstract: This paper is on our technology development with the emphasis on manufacturing in view of their impact on humans, society, the environment and international stability. It deals with automation per se, the "Factory of the Past" and the "Factory of the Future" and "Industry 4.0", also referring explicitly to AI systems. In the center of our paper stands the engineer, philosopher and author Michael Cooley from Ireland, and his recent poem Insulting Machines. It means that we are using the narrative patterns of poetry leading up to Cooley’s fight for the - still controversial - concept of Human Centered Technology Design.
Paper VI195-01.4
PDF · Video · Intelligent Control and Automation Systems: Mike Cooley's Vision of Socially-Responsible, Human-Centred Technology (I)
McInerney, Patrick	Insyte, Waterford Institute of Technology
O'Neill, Brenda	Insyte, Waterford Institute of Technology
Stapleton, Larry	Waterford Institute of Technology
Keywords: Ethics, Knowledge networks, Knowledge Society Abstract: Michael Cooley was a founding member of the Human Centred Systems movement, which argued for a symbiosis in which the complementary strengths of machine and human were balanced in the development of automation and control systems. Cooley’s pioneering work and the research that followed, placed social effects and human factors at the heart of intelligent human-machine systems development and profoundly influenced the CC9 group of IFAC technical committees. In this paper we concentrate on his vision of human-machine symbiotics, applying it to web-based intelligent systems engineering. Following a survey of the literature the paper concludes that human-machine systems engineering praxis, as embodied in contemporary ontology engineering methodologies, overlooks critical aspects of human knowledge and craftmanship. Some basic principles are established by which to enhance and reframe systems development methodologies, and human-machine control and automation systems engineering research trajectories are offered to address the gaps.
Paper VI195-01.5
PDF · Video · TECIS Inclusion and Diversity Working Group Vision (I)
Doyle-Kent, Mary	Waterford Institute of Technology
Chowdhury, Fahmida	National Science Foundation
Costello, Orlagh	INSYTE Centre
O'Neill, Brenda	Insyte, Waterford Institute of Technology
Organ, John	INSYTE, Waterford Institute of Technology
Kopacek, Peter	Vienna University of Technology
Stapleton, Larry	Waterford Institute of Technology
Keywords: Multi-cultural interaction, Ethics, Digital Divide Abstract: Abstract: There has been considerable focus on building inclusion and diversity into engineering careers and education, especially in developed countries, but despite this, the percentages for minorities remain unchanged over decades. The multi-cultural interaction of TECIS was a springboard for the launch of a working group to investigate the reasons for this lack of improvement. The genesis of this working group occurred in Sozopol, Bulgaria at the TECIS 2019 conference where twenty-three researchers from over ten countries came together to discuss the lack of women and other marginalized groups in engineering. The objective of this paper is threefold, to outline the future direction of the inclusion and diversity working group in TECIS, to support and foster greater knowledge of gender diversity in engineering education and to outline future research activities that could make a substantial contribution to our understanding of diversity issues in engineering in addition to making best practice recommendations that can be used in the engineering industry. The scope of this paper is limited to women in engineering. Future work will look at other inclusion and diversity issues in STEM.
Paper VI195-01.6
PDF · Video · The IFAC TC SWIIS Past, Present, Future (I)
Kopacek, Peter	Vienna University of Technology
Stapleton, Larry	Waterford Institute of Technology
Keywords: Ethics, Sustainability, Knowledge Society Abstract: The IFAC TC on "Supplemental Ways for Improving International Stability – SWIIS" is one of the longest situated in IFAC. According to first ideas during the IFAC World Congress in Kyoto 1981 this IFAC – at that time - Working Group organised in 1983 the first Workshop in this highly interdisziplinary field in Austria. Meanwhile a Technical Committee in IFAC, SWIIS was always a bridge between (control) engineers and various other disziplines to open IFAC to other related fields. It`s a tradition to present on nearly each IFAC World Congress an update of this dynamic TC. Therefore in this contribution the role of process and manufacturing automation especially control engineering will be presented and discussed based on previous papers. In addition Ethics and Diversity are shortly discussed. As an indicator selected Keywords of the main sponsored events of this TC were used. This contribution is based on Kopacek,P, L.Stapleton, M.Dimirovski (2017).

VI195-02
Social Aspects of Automation	Regular Session
Chair: O'Neill, Brenda	Insyte, Waterford Institute of Technology
Co-Chair: Kozak, Stefan	Faculty of Electrical Engineering and Information Technology
Paper VI195-02.1
PDF · Video · Enlightenment, Artificial Intelligence and Society
Lamotte, Malenka de	Le Poet-Celard
Keywords: Climate change, Knowledge Society, Value systems Abstract: Scholars in the independent scientific community agree on that living conditions may deteriorate fast because of climate changes. Thus the question is what to do about it. I would like to look at the developments of the recent Past: Enlightenment and Human Rights, and Artificial Intelligence as it has grown out of those two movements, and their possible contributions to improving our developments into our global future.
Paper VI195-02.2
PDF · Video · A Human-Centred Systems Theory of E-Agriculture Automation and Control Systems Adoption: An Empirical Study of the Social Effects of Digital Control and Automation Systems in Agricultural Communities
O'Neill, Sinead	Waterford Institute of Technology
Stapleton, Larry	Waterford Institute of Technology
Keywords: eAgriculture, Multi-cultural interaction, Knowledge networks Abstract: Climate change, biodiversity crises and other challenges impinge upon agricultural communities who must adapt to these pressures. However, in many countries agriculture lags behind other sectors in its uptake of digital automation and control systems on the farm. In spite of decades of research into technological innovation adoption factors we still do not have a good understanding as to why this sector is slower than others to adopt these new systems. This paper is based on a qualitative study of farmers in the south-east of Ireland which explored social effects in technology adoption. It draws out key themes associated with Irish farming as communities of knowledge networks, learning and innovation dynamics and cultural features, as well as tensions in relationships between farmers and institutions. From this analysis new theoretical "RooT" model is offered to reorient control and automation technology adoption theories and better support agricultural technology innovation.
Paper VI195-02.3
PDF · Video · An Intelligent M-Healthcare System for Improving the Service Quality in Domestic Care Industry
Lam, Hoi Yan	The Hang Seng University of Hong Kong
Tang, Yuk Ming	The Hong Kong Polytechnic University
Tang, Valerie	The Hang Seng University of Hong Kong
Wu, Chun Ho	The Hang Seng University of Hong Kong
Keywords: eHealth, AI for business and economy, Urban Healthcare Abstract: Due to declining fertility rate and increasing life expectancy, population aging has become a growing problem in Hong Kong. Domestic elderly service providers and public health institutions have been suffering from a shortage of experienced staff for elderly healthcare, which has led to a drop in both the quality and efficiency of the local elderly service. With the rising popularity of mobile applications and the betterment of machine vision technology, this paper describes the design of an Intelligent m-Healthcare System (ImHS) for relieving the manpower pressure on local elderly service providers by lowering the technical threshold and simplifying staff training process. Face recognition technology is applied to identify the elderly by searching and tracing the elderly medical record through the FaceAPI service. In addition, the proposed ImHS provides the immediate insight into healthcare knowledge for users, which lowers the occurrence of Adverse Drug Event (ADE) and shortens the duration of pill distribution process. By conducting a case study in a local elderly home, the proposed system allowed the nursing staff to better allocate healthcare resources and to improve the operation effectiveness and efficiency.
Paper VI195-02.4
PDF · Video · The ENRICHER Method for Human Machine Symbiotics & Smart Data a Socially Responsible Approach to the Intelligent Augmentation of Knowledge Work
Stapleton, Larry	Waterford Institute of Technology
O'Neill, Brenda	Insyte, Waterford Institute of Technology
McInerney, Patrick	Insyte, Waterford Institute of Technology
Keywords: Ethics, Knowledge Society, Multi-cultural interaction Abstract: The systems development community is in need of a new culture, embodied in methodologies which assert human knowledge and dignity in technology development effort, especially where automation shapes working-life. Recent research, though limited, provides initial evidence to suggest industry 4.0 factory environments can satisfy the goals of human dignity and improved productivity amongst knowledge workers by developing human-centred systems. This paper looks at the unique differences between human and machine intelligences and introduces human-machine symbiotic, evolutionary development approaches. It extends the work of human centred systems in industry 4.0 settings into a very different knowledge work context: archiving cultural heritage, which has received little attention to date in IFAC. The Insyte-Cooley Research Lab (I-CRL) using action research have sown the seeds of a new culture embodied in a systems development process called "ENRICHER" which valorises human knowledge with positive results. Extensible machine-readable knowledge models are co-evolved by both technologists and users which support digitisation.
Paper VI195-02.5
PDF · Video · Social Responsibility, Human Centred Systems and Engineering Ethics: A New Manifesto for Systems Engineering Design Praxis
O'Neill, Brenda	Insyte, Waterford Institute of Technology
Stapleton, Larry	Waterford Institute of Technology
Keywords: Ethics, Multi-cultural interaction, Systems Theory Abstract: Praxis is defined in the Cambridge English Dictionary as "the process of using a theory or knowledge in a practical way. Michael Cooley was one of the founding members of the Human Centered Systems(HCS) movement where human tacit knowledge is valorized and the human is empowered with technology and automation at the service of, and controlled by, the human. This paper proposes a set of ethical guidelines, in the form of a Manifesto, for a systems engineering design praxis. The rationale is to detach from "the one best way" that the Agile Software Development process has become, to value tacit knowledge by giving the client the right to reject, to rebalance power from the designer to the client and to slow down or depressurize the development process. This Manifesto emerges from the ongoing work on the digitization of the Cooley Collection by the interdisciplinary team members of the Insyte-Cooley Research Lab in the Luke Wadding Library of Waterford Institute of Technology. Work on this manifesto has raised serious questions – is the systems design process that involves interdisciplinary teams, responsible design and development of non commercial but socially beneficial systems, a very different and emergent model? Is it compatible with, a very different design approach? An ideology is presented, from which, as the lab progresses a supporting methodology specific to cultural heritage systems development is evolving.
Paper VI195-02.6
PDF · Video · Automating Morals – on the Morality of Automation Technology, Ironies of Automation and Responsible Research and Innovation
Herzog né Hoffmann, Christian	Universität Zu Lübeck
Keywords: Ethics, Value systems, Sustainability Abstract: The prevalence and impact of morals in technology design is increasingly better understood. Likewise, advances in machine learning, systems theory and control continue to push the boundary with respect to the applications in which automation may be considered. The present paper is intended to act as a precursor to a lively debate about professional ethics within the control community regarding automation in morally charged situations and beyond. First, the paper provides a primer on the actualities of applications in which morals already play a significant role. It further claims that–in contrast to typical expositions–within the scope of systems in which automation is employed, there is a continuum between addressing morally charged contexts to actually performing a kind of automated moral deliberation, though technically and philosophically there may be a vast difference. Second, from this perspective, the paper presents a first indication about potential new and persistent "ironies" within the context of automating morals. Third, the paper draws conclusions, essentially calling for the community to open up and engaging in participatory research and development settings as a matter of professional ethics.
Paper VI195-02.7
PDF · Video · Ironies of Automation 4.0
Hancke, Tania	DLR
Keywords: Knowledge Society, Human-centered systems engineering, Complexity modelling Abstract: This paper revisits a truly classic publication: Bainbridge’s Ironies of Automation (1983) - but it also aims to make the point that the insights gained many years ago are today becoming more important than ever. As we all know, it is due to technological advances that automation is leading to increasingly complex systems which considerably raises the impact of the potential effects. Bainbridge’s insights originated from manufacturing processes, but they equally apply to process control in general and to vehicle control, e.g., airplanes, road vehicles or trains. This paper shows that comparable observations can be reported and suggests a human-centered approach to overcome the problems.
Paper VI195-02.8
PDF · Video · Responsible Innovation in Support of Society 5.0 - Aspects of Audit and Control
Nagy, Karoly	BME-UBT Joint Transformative Research Center
Hajrizi, Edmond	University for Business and Technology
Palkovics, László	Szent István University
Keywords: Knowledge Society, International Development, Globalisation Abstract: We have developed an innovation model through which the benefits of the transformation of social needs into each other can be exploited. The model manages the planning and implementation processes of innovation in a unified system, approximately in parallel. Responsible innovation, as we have named our approach, minimizes the "development slack", increasing the effectiveness of financial support for innovation. Reviewing the concept of the Japanese Society 5.0 initiative, we came to the conclusion that our model would always have been tailored to the innovation needs of Society 5.0. At the same time, the Society 5.0 culture would be the most favorable medium for the completion and spread of our model. Responsible innovation is based on transformative research, and the "soul" of its implementation is modularization. This requires appropriate standards, audit and control support. Thanks to technological development and based on the opportunities inherent in responsible innovation, virtual economic zones, which provide a regulatory and organizational framework for mdular enterpris, have now become feasible and create. These can play an important role in making financial support for the recovery from the COVID-19 crisis effective.
Paper VI195-02.9
PDF · Video · Meaning - Thinking - AI
Soeffner, Jan	Zeppelin University
Keywords: Knowledge Society, Value systems, Ethics Abstract: This paper investigates on the relation between consciousness and meaning. Questioning AI’s ability to produce both, it irst makes the case for a sharper terminology regarding AI’s 'cognitive' abilities. In arguing that meaning requires more than content production, it offers a definition of meaning that offers a clear distinction between human and non-human intelligences.
Paper VI195-02.10
PDF · Video · Fuzzy Cognitive Maps Analysis of Green Supply Chain Management: A Case Study Approach
Bevilacqua, Maurizio	Università Politecnica Delle Marche
Ciarapica, Filippo Emanuele	Politecnical University of Marche
Marcucci, Giulio	Università Politecnica Delle Marche
Mazzuto, Giovanni	Università Politecnica Delle Marche
Keywords: Sustainability, Modelling Social and Environmental Change, Human-centered systems engineering Abstract: The Green Supply Chain has proposed to innovate industrial production by implementing a radical change in the productive perspective: trying to reconcile economy and ecology. This study aims to contribute to the realisation of a new idea of eco-sustainable industrialisation. Anyone making decisions within any dynamic system faces serious difficulties. For this reason, the proposed study analyses this system using Fuzzy Cognitive Maps arriving at the formation of a real map of the causal relationships between the concepts identified, then divided by areas of membership. In doing so, the most relevant factors affecting the Green Supply Chain decision-making process have been identified and analysed.
Paper VI195-02.11
PDF · Video · Ubiquitous Model for Persuasive Behavior Change Systems: A Case Study on Energy Efficiency
Mota, Fernanda P.	Federal University of Rio Grande
Primo, Tiago T.	Federal University of Pelotas
Botelho, Silvia	Universidade Federal Do Rio Grande
Keywords: Cognitive aspects of automation systems and humans, Human-centered systems engineering, Cyber-space and societal developments Abstract: In this paper, we develop a model for analyzing the motivation of individuals through persuasive ubiquitous technologies called the Ubiquitous Model for Persuasive Behavior Change Systems (UMPSBC). In the proposal of UMPSBC, we changed the Fogg Behavior Model (FBM) by inserting the Hierarchical Model of Intrinsic and Extrinsic Motivation (HMIEM) situational motivation level into FBM's motivation layer. UMPSBC was applied in a case study focused on energy efficiency in which we evaluated whether intervention in the motivation of individuals causes a change in behavior regarding sustainability and consequently if this change causes u-learning processes, making the individual behavior more sustainable. The results suggest that there are indications of u-learning processes, as individuals responded positively to most triggers (tips) and also by the fact that there was a reduction in electricity consumption.
Paper VI195-02.12
PDF · Video · Is Fear of Robots Stealing Jobs Haunting European Workers? a Multilevel Study of Automation Insecurity in the EU
Kozak, Michal	University of Bergen
Kozak, Stefan	Faculty of Electrical Engineering and Information Technology
Kozáková, Alena	Slovak University of Technology in Bratislava
Martinák, Dávid	Slovak Academy of Sciences
Keywords: Cultural impacts of automation technology, Cognitive aspects of automation systems and humans, Cyber-space and societal developments Abstract: The paper examines how workers in the EU perceive impact of technological changes on employment and whether they experience automation insecurity, or fear of robots stealing their jobs. In particular, the paper seeks to determine whether subjectively perceived automation insecurity reflects workers’ vulnerability and exposure to objective automation risk. The paper analyzes representative survey data from Eurobarometer for all 28 EU member countries and uses mixed-effects logistic regression models with random intercepts and slopes to model workers’ probability of automation insecurity as a function of their individual characteristics, contextual characteristics of countries they live in and as of possible interactions between the two. The results show that European workers are greatly concerned with labor-substituting effects of new technologies, and that this subjective insecurity to a great extent reflects their exposure to objective automation risk.
Paper VI195-02.13
PDF · Video · The Distributed Situational Centers System As an Instrument of State and Corporate Strategic Goal-Setting in the Digital Economy
Raikov, Alexander	Institute of Control Sciences RAS
Avdeeva, Zinaida	V.A. Trapeznikov Institute of Control Sciences of RAS; National
Lepskiy, Vladimir	Institute of Philosophy RAS
Kovriga, Svetlana	V.A. Trapeznikov Institute of Control Sciences of the Russian Ac
Slavin, Boris	Financial University under the Government of RF
Zatsarinny, Alexander	RAS Federal Reseach Center Computer and Control
Keywords: AI for business and economy, Cognitive aspects of automation systems and humans, Social Networks Abstract: The increasing complexity of corporate digital design, goal setting and management, for which the power of classical scientific approaches to management is insufficient in the digital economy, is noted. In the digital economy, the known principle of the impossibility to automate chaos is replaced by a need for situational control based on providing multi-level fully functional project management using artificial intelligence (AI) and artificial general intelligence (AGI). At the same time, the system of distributed situational centers can become an effective tool for supporting strategic goal-setting. Much that has been done in this field and in the field of AI is of profound significance, but the classical approach to AI cannot embrace the different levels of the subjects’ emotions, consciousness, and the collective unconscious. The aspects of breakthrough and disruptive management urgently need to be developed. Attention must be focused on the issue of collective decision making under conditions of uncertainty causes and in unforeseen situations. Priority should be given to the socio-humanitarian and collective cognitive aspects of AI applications. Under these conditions, distributed situational centers system and some methods of AGI become the main cross-cutting digital technologies for ensuring corporate strategic goal-setting in the digital economy.

VI199
Late Breaking Results
VI199-01 Late Breaking Results I   Regular Session, 35 papers
VI199-02 Late Breaking Results II Applications   Regular Session, 30 papers

VI199-01
Late Breaking Results I	Regular Session
Chair: Muller, Matthias A.	Leibniz University Hannover
Co-Chair: Shim, Hyungbo	Seoul National University
Paper VI199-01.1
PDF · Video · Kernel Based Parametric Modeling with Accurate Step Responses
Sugie, Toshiharu	Kyoto University
Hori, Yuki	Kyoto University
Keywords: Bayesian methods, Input and excitation design, Identification for control Abstract: This paper is concerned with kernel-based system identification. An approach to estimate a parametric model with given structure is shown, which approximates the step response of the target system. It is composed of two parts. First, taking account of the step responses, an IIR model is estimated via kernel regularization with an appropriate input. Second, a parametric model with given structure is obtained from the obtained impulse response via a prediction error method. A numerical example is given to demonstrate the effectiveness of the proposed approach.
Paper VI199-01.2
PDF · Video · High-Order State-Derivative Controller Design for Nonlinear Systems
Alvarez, Jorge Luis	Instituto Tecnológico De Sonora
Vázquez, David	Sonora Institute of Technology
Tapia, Alan	National Autonomous University of Mexico (UNAM)
Bernal, Miguel	Sonora Institute of Technology
Keywords: Controller constraints and structure, Descriptor systems, Lyapunov methods Abstract: A novel controller design for nonlinear systems based on inducing a set of differential algebraic equations is presented. The method generalises the state-derivative feedback control by employing an arbitrary number of derivatives of the state vector pre-multiplied by nonlinear gains. To determine these gains, an intermediary control law is indirectly synthesised via convex modelling and linear matrix inequalities through an induced singular system subject to the Pantelides algorithm. An example illustrates the effectiveness of the proposal.
Paper VI199-01.3
PDF · Video · Nonlinear Switching Control with Increment Estimate of Unmodeled Dynamics
Zhang, Yajun	Northeastern University
Chen, Xinkai	Shibaura Institute of Technology
Zuo, Jiwen	Xurui Educational Institution, Shenyang Liaoning 110819, China
Keywords: Data-based control, Switching stability and control, Disturbance rejection (linear case) Abstract: We present a new switching control method for controlling a class of nonlinear systems. The key design idea behind the control method lies in using the data of unmodelled dynamics, that is, the unmodelled dynamics of the last sampling instant and the estimate of unknown increment. The proposed algorithm is based on a new estimation algorithm, which contributes of two nonlinear controllers. The system performance is evaluated by a numerical simulation.
Paper VI199-01.4
PDF · Video · Decentralized Control for Multi-Agent System Formation Based on Regular Polygons
Marçal Ferreira, Ernesto Franklin	Instituto Federal Do Maranhão
Selmic, Rastko R.	Louisiana Tech Univ
Fonseca Neto, Joao Viana da	Federal Univ. of Maranhao
Keywords: Design methodologies, Motion Control Systems, Autonomous robotic systems Abstract: In multi-agent systems, the control is decentralized when decision-making is done by agents individually and not by a centralized unit that processes the states of all agents together. The main mathematical difference when working with centralized versus decentralized control, more precisely when presenting the x-dot dynamic system, is the absence of a switching or grouping matrix such as the Laplacian matrix, which presents the characteristics of interconnection between the agents of the system, with the absence of the same the system does not have a complete information on the number of agents and the way of connection between them.
Paper VI199-01.5
PDF · Video · Continuous-Time Accelerated Algorithm for Distributed Optimization Over Undirected Graph
Fitri, Ismi Rosyiana	Seoul National University of Science and Technology
Kim, Jung-Su	Seoul National University of Technology
Keywords: Distributed optimisation for large-scale systems, Consensus Abstract: This paper investigates a distributed optimization problem for a group of agents where the objective function is the sum of convex local functions associated with the individual agents on connected and undirected graph topologies. Inspired by the discrete-time accelerated gradient algorithm for solving a centralized optimization problem, this paper designs a continuous-time algorithm for solving the distributed optimization problem. By using a standard Lyapunov analysis, it is proved that the proposed method converges exponentially to the optimal solution when the local costs are strongly convex with a local Lipschitz gradient. Furthermore, it is also shown that faster convergence could be easily achieved by increasing one design parameter. Numerical simulations illustrate the result.
Paper VI199-01.6
PDF · Video · Modeling in the Loewner Framework: From Linear Dynamics to Quadratic Nonlinearities
Gosea, Ion Victor	Max Planck Institute for Dynamics of Complex Technical Systems
Karachalios, Dimitrios	Max Planck Institute for Dynamics of Complex Technical Systems
Antoulas, Athanasios C.	Rice Univ
Keywords: Frequency domain identification, Nonlinear system identification, Continuous time system estimation Abstract: In this contribution, we address an extension of the Loewner framework for modeling quadratic systems from data.
Paper VI199-01.7
PDF · Video · Numerical Evaluation on Frequency Domain Nonparametric Modelling for Stable/Unstable Systems with I/O Noise
Sugie, Toshiharu	Kyoto University
Khurewattanakul, Natchanon	Kyoto University
Keywords: Frequency domain identification, Nonparametric methods, Closed loop identification Abstract: Though most of the existing work focus on parametric modeling, non-parametric modeling methods have attracted a lot of attention these days, partly because it does not require the structural information such as system orders. From the viewpoint of control system analysis and synthesis, frequency responses are crucial in practice. Hence, the frequency domain models are important. Nevertheless, there are not so many reports which evaluate the effectiveness of nonparametric frequency modeling methods so far. Hence, this paper focuses on numerical evaluation of such modeling methods. First, the effectiveness of the periodic input (for identification) is demonstrated for a stable system in the presence of input noise as well as the output one. Second, it is shown that the frequency domain methods are effective for a closed loop system with unknown nonlinear stabilizing controller.
Paper VI199-01.8
PDF · Video · State-Switching Control of the Second-Order Chained Form System
Ito, Masahide	Aichi Prefectural University
Keywords: Guidance navigation and control, Identification and control methods, Robots manipulators Abstract: This paper addresses a motion planning problem of the second-order chained form system. The author presents a novel control approach based on switching a state. The second-order chained form system is composed of three subsystems including two double integrators and a nonlinear system. Switching a single state of the double integrators can modify the nature of the nonlinear system. Such state-switching and sinusoidal control construct the basis of the proposed control approach. The effectiveness is validated by a simulation result.
Paper VI199-01.9
PDF · Video · Towards Model Order Selection for Robust-Control-Relevant System Identification
Tacx, Paul	Eindhoven University of Technology
de Rozario, Robin	Eindhoven University of Technology
Oomen, Tom	Eindhoven University of Technology
Keywords: Identification and control methods, Modeling, Motion Control Systems Abstract: Robust control allows for guaranteed performance for a range of candidate models. The aim of this paper is to investigate the role of model complexity in the identification of model sets for robust control. A key observation is that model accuracy and model complexity should depend on the control goal. Regularization using a worst-case control criterion in conjunction with a specific model uncertainty structure allows robust control of multivariable systems. Simulations confirm that the model order depends on the control objectives. Overall, the framework enables systematic identification of model sets for robust control.
Paper VI199-01.10
PDF · Video · Closed-Loop Identification of Ill-Conditioned Systems Using Rotation
Friman, Mats	Neles
Keywords: Identification for control, Closed loop identification Abstract: A simple and practical method for closed-loop identification of ill-conditioned systems is presented. The method uses rotation matrices to identify the process in directions important for control. This approach simplifies the identification and improves reliability, because simple first order models are usually adequate in the identification step. An open-loop / closed-loop duality is introduced, which gives a new holistic viewpoint on control-relevant identification of 2x2 ill-conditioned systems. Pitfalls, and some guidelines how to avoid them, in control-relevant identification of ill-conditioned systems are discussed.
Paper VI199-01.11
PDF · Video · Port-Hamiltonian System Model Identification of a Micro-Channel
Cisneros, Nelson	Universidad De Concepcion
Rojas, Alejandro	Universidad De Concepcion
Ramirez, Hector	Universidad Federico Santa Maria
Keywords: Identification for control, Experiment design, Continuous time system estimation Abstract: In this paper we identify the parameters for a finite Port-Hamiltonian system (PHS) model of a micro-channel using ordinary least squares method. The PHS model is based on the interconnection of basic finite elements equivalent to capacitors, inductance and resistors. The interconnection of several basic element models can represent the micro-channel model behavior. The parameter capacitance depends on the geometry of the channel, but the inertance, the uncontrolled and the controlled resistance are difficult to measure. The PHS based Fluid-structure interconnected system can estimate the behavior of the process as well as Partial Differential Equations (PDE) based models. The resultant model can then be used to design a controller to have a desired level at any given position in the micro-channel.
Paper VI199-01.12
PDF · Video · Performance Guarantees in Dual Control Using Gain Scheduling
Venkatasubramanian, Janani	University of Stuttgart
Köhler, Johannes	University of Stuttgart
Berberich, Julian	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Learning for control, Identification for control, Closed loop identification Abstract: We present a novel strategy for robust dual control of linear time-invariant systems based on gain scheduling with performance guarantees. This work relies on prior results of determining uncertainty bounds of system parameters estimated through exploration. Existing approaches are unable to account for changes in the mean of system parameters in the exploration phase. We address this limitation by selecting the future (uncertain) mean as a scheduling variable in the control design. This results in a single semi-definite program that computes a suitable exploration strategy and a robust gain-scheduled controller.
Paper VI199-01.13
PDF · Video · Robust Neural Networks Via Lipschitz Regularization and Enforced Lipschitz Bounds
Pauli, Patricia	University of Stuttgart
Koch, Anne	University of Stuttgart
Berberich, Julian	University of Stuttgart
Allgower, Frank	University of Stuttgart
Keywords: Machine learning Abstract: Neural networks are successful in many fields, yet they can be easily fooled by imperceptible adversarial perturbations. One measure of robustness of an NN to such perturbations in the input is the Lipschitz constant of the input-output map defined by the NN. In this work, we therefore propose a framework for training of single-hidden layer NNs that not only minimizes the underlying loss but also encourages the NN’s robustness by keeping its Lipschitz constant small. The resulting optimization problem is solved using the alternating direction method of multipliers that splits the problem into two subproblems, the minimization of the training loss and a semidefinite programming-based regularizer that penalizes the Lipschitz constant. A variation of the framework allows not only for minimization of the Lipschitz constant but for enforcing a desired Lipschitz bound during training.
Paper VI199-01.14
PDF · Video · A Polynomial Time Algorithm for Minimizing Strongly Convex Functions with Strongly Convex Constraints
Costandin, Marius-Simion	Technical University of Cluj-Napoca
Costandin, Beniamin Ioan	NTT Data
Dobra, Petru	Technical Univ of Cluj
Keywords: Machine learning, Consensus and Reinforcement learning control, Extremum seeking and model free adaptive control Abstract: We present a novel feasibility criteria for the intersection of finitely many convex sets where each set is given by an inequality. This criteria allows us to easily assert the feasibility by analyzing the unconstrained minimum of a certain convex function, that we form with the given sets. Such a criteria is then used together with bisection techniques to solve general convex optimization problems within a desired precision in polynomial time. A simple complexity analysis is given for the case where the functions involved are strongly convex, but the method can be used for general convex functions.
Paper VI199-01.15
PDF · Video · Game-Theoretic Approach to Decision Making for Multiple Vehicles at Roundabout
Pruekprasert, Sasinee	National Institute of Informatics
Dubut, Jeremy	National Institute of Informatics
Zhang, Xiao-Yi	National Institute of Informatics
Huang, Chao	Northeastern University
Kishida, Masako	National Institute of Informatics
Keywords: Mission planning and decision making, Autonomous Vehicles Abstract: In this paper, we study the decision making of multiple autonomous vehicles in a roundabout. The behaviours of the vehicles depend on their aggressiveness, which indicates how much they value speed over safety. We propose a distributed decision-making process that balances safety and speed of the vehicles. In the proposed process, each vehicle estimates other vehicles' aggressiveness and formulates the interactions among the vehicles as a finite sequential game. Based on the Nash equilibrium of this game, the vehicle predicts other vehicles' behaviours and makes decisions. We perform numerical simulations to illustrate the effectiveness of the proposed process, both for safety (absence of collisions), and speed (time spent in the roundabout).
Paper VI199-01.16
PDF · Video · Control System Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control
Oyama, Henrique	Wayne State University
Durand, Helen	Wayne State University
Keywords: Model predictive and optimization-based control, Process control applications, Nonlinear process control Abstract: Cybersecurity of control systems is a topic of increasing concern for chemical processes. In this work, we develop two techniques for detecting cyberattacks involving false state measurements being provided to a specific control formulation known as Lyapunov-based economic model predictive control (LEMPC) that take advantage of the closed-loop stability properties of the control formulation to seek to detect attacks after they occur. The first approach utilizes an integrated detection, control, and state estimation framework to flag deviations of the state estimates from ``normal" process behavior as problematic cyberattacks, and the second control framework uses randomized modifications to an LEMPC formulation online, with reference to a baseline LEMPC design, to potentially detect cyberattacks.
Paper VI199-01.17
PDF · Video · Informativity for Data-Driven Model Reduction through Interpolation
Burohman, Azka Muji	University of Groningen
Besselink, Bart	University of Groningen
Scherpen, Jacquelien M.A.	University of Groningen
Camlibel, Kanat	University of Groningen
Keywords: Model reduction, Data-based control Abstract: A method for data-driven interpolatory model reduction is presented in this extended abstract. This framework enables the computation of the transfer function values at given interpolation points based on time-domain input-output data only, without explicitly identifying the high-order system. Instead, by characterizing the set of all systems explaining the data, necessary and sufficient conditions are given under which all systems in this set share the same transfer function value at a given interpolation point. After following this so-called data informativity perspective, reduced-order models can be obtained by classical interpolation techniques. An example of an electrical circuit illustrates this framework.
Paper VI199-01.18
PDF · Video · On Minimum Time Control for Dynamical Transportation Using ADMM
Adachi, Ryosuke	Yamaguchi University
Wakasa, Yuji	Yamaguchi Univ
Kobayashi, Koichi	Hokkaido University
Keywords: Multi-agent systems, Distributed optimisation for large-scale systems, Control over networks Abstract: In this paper, a dynamical transportation problem over the graph is discussed. Over the graph, multiple agents transport their assets to goals. In transportation, all agents share capacities of nodes and edges. The dynamical transportation problems are formulated as an optimization problem such that the total transportation time is minimized by using finite optimal control problems. The optimization problem is dispersively solved by using the alternating direction method of multipliers.
Paper VI199-01.19
PDF · Video · Periodic Economic MPC for Nonlinear Constrained Systems
Köhler, Johannes	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Allgower, Frank	University of Stuttgart
Keywords: Nonlinear predictive control, Predictive control, Constrained control Abstract: In this paper, we consider the problem of periodic optimal control of nonlinear systems subject to online changing and periodically time-varying economic performance measures using model predictive control (MPC). The proposed economic MPC scheme uses an online optimized artificial periodic orbit to ensure recursive feasibility and constraint satisfaction despite unpredictable changes in the economic performance index. We demonstrate that the direct extension of existing methods to periodic orbits does not necessarily yield the desirable closed-loop economic performance. Instead, we carefully revise the constraints on the artificial trajectory and provide closed-loop average performance guarantees.
Paper VI199-01.20
PDF · Video · Guaranteed Learning in Model Predictive Control
Soloperto, Raffaele	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Allgower, Frank	University of Stuttgart
Keywords: Nonlinear predictive control, Predictive control, Constrained control Abstract: In this paper, we propose a novel learning-based model predictive control framework for nonlinear systems able to guarantee closed-loop learning. The employed cost function is formed by a combination of a primary and a learning cost. The proposed approach is easy to implement and differs from standard MPC schemes only by an additional constraint.
Paper VI199-01.21
PDF · Video · Cyclo-Dissipativity and Thermodynamics
van der Schaft, Arjan J.	Univ. of Groningen
Keywords: Nonlinear process control, Process modeling and identification, Real time optimization and control Abstract: The dissipativity formulation of both the First and Second Law of thermodynamics involve the notion of cyclo-dissipativity. This motivates to revisit the, rather scarce, literature on cyclo-dissipativity. It turns out that by 'symmetrizing' the basic definitions of dissipativity theory as introduced in the seminal 1972 paper of Jan Willems some novel results can be obtained which have direct consequences for cyclo-dissipativity. A related contribution, also motivated by thermodynamics, is the notion of one-port cyclo-passivity, which provides a new angle to the Second Law of thermodynamics.
Paper VI199-01.22
PDF · Video · Development of a Structure Identification Method for Nonlinear SISO Systems
Santhakumaran, Sarmilan	Covestro Deutschland AG - Technical University of Ilmenau
Maul, Christine	Covestro Deutschland AG
Shardt, Yuri A.W.	Technical University of Ilmenau
Keywords: Nonlinear system identification, Nonparametric methods Abstract: The basis of nonlinear system identification underlies a proper functional structure provided through either a detailed physical process description or a-priori knowledge from experts. However, these conditions are not provided in many engineering disciplines due to continuously changing functional structures depending on acting operational points and complex plant operations, which makes classical White-Box- or Grey-Box-Modelling difficult or even impossible. In order to achieve a reliable performance in nonlinear system identification, this paper seeks to examine a data-driven approach to identify the functional structure for the special case of nonlinear single-input-single-output (SISO) systems. The identified functional structures from the proposed method will be embedded as nonlinear candidates into the sparse regression method as system identification procedure and the performance of the estimation will be observed.
Paper VI199-01.23
PDF · Video · Static Optimal Output Feedback Design for Linear Quadratic Regulator Using Nonlinear Optimal Controller Design
Mizuguchi, Kodai	Tokyo Metropolitan University
Masuda, Shiro	Tokyo Metropolitan University
Keywords: Optimal control theory, Regulation (linear case), Output feedback control (linear case) Abstract: The paper proposes static optimal output feedback design that achieves linear quadratic regulator for a single-input, single-output, continuous-time, time-invariant system. The proposed approach constructs the closed-loop system via static feedback control, then optimizes the initial state value representing a constant static output feedback gain. The Euler-Lagrange equation is derived for characterizing the optimal initial state value for the finite time quadratic cost criterion. The paper also gives some analysis regarding the optimal condition for the static output feedback gain using the solution of the Ricatti differential equation. Finally, the paper shows a numerical example that supports the proposed derivation of the optimal static output feedback gain.
Paper VI199-01.24
PDF · Video · Passivity Based Velocity Tracking and Formation Control without Velocity Measurements
Li, Ningbo	University of Groningen
Scherpen, Jacquelien M.A.	University of Groningen
van der Schaft, Arjan J.	Univ. of Groningen
Borja, Luis Pablo	University of Groningen
Mahony, Robert	Australian National University
Keywords: Passivity-based control, Tracking, Distributed nonlinear control Abstract: This abstract proposes a passivity-based control method for velocity tracking and formation control of nonholonomic wheeled robots without velocity measurements. Coordinate transformations are used to incorporate the nonholonomic constraints, which are then avoided by controlling the front end of the robot rather than the center of the wheel axle into the differential equations. Starting from the passivity-based coordination design, the control goals are achieved via an internal controller for velocity tracking and heading and an external controller for formation in the port-Hamiltonian framework, leading to a clear physical interpretation. To avoid the unavailable velocity measurements or unreliable velocity estimates, we derive the distributed control law with only position measurements by introducing the idea of dynamic extension. Simulations are provided to illustrate the effectiveness of the approach.
Paper VI199-01.25
PDF · Video · Distributed Model Predictive Control for Consensus of Constrained Homogeneous Linear Systems
Hirche, Matthias	University of Stuttgart
Köhler, Philipp N.	University of Stuttgart
Muller, Matthias A.	Leibniz University Hannover
Allgower, Frank	University of Stuttgart
Keywords: Predictive control Abstract: We consider the problem of designing a distributed control strategy such that a homogeneous multi-agent system is asymptotically driven to consensus. The agents' dynamics are assumed to be linear, discrete-time and subject to convex input and state constraints. We propose a sequential distributed model predictive control algorithm that asymptotically steers the agents to consensus in the outputs. In their individual model predictive control optimisation problems, the agents track an auxiliary target output while simultaneously minimising its distance to those of their neighbours.
Paper VI199-01.26
PDF · Video · Novel Convex Decomposition of Piecewise Affine Functions
Schlüter, Nils	Universität Paderborn
Schulze Darup, Moritz	Universität Paderborn
Keywords: Predictive control, Numerical methods for optimal control Abstract: In this paper, we present a novel approach to decompose a given piecewise affine (PWA) function into two convex PWA functions. Convex decompositions are useful to speed up or distribute evaluations of PWA functions. Different approaches to construct a convex decomposition have already been published. However, either the two resulting convex functions have very high or very different complexities, which is often undesirable, or the decomposition procedure is inapplicable even for simple cases. Our novel methodology significantly reduces these drawbacks in order to extend the applicability of convex decompositions.
Paper VI199-01.27
PDF · Video · Indirect and Direct Feedback in Stochastic Model Predictive Control
Hewing, Lukas	ETH Zurich
Zeilinger, Melanie N.	ETH Zurich
Keywords: Predictive control, Stochastic optimal control problems Abstract: In contrast to the unconstrained case, there is no closed-form solution to constrained optimal control problems of linear systems under additive stochastic noise. Stochastic model predictive control (SMPC) is an approximate solution strategy for such problems, in which a simplified problem is repeatedly solved over a reduced prediction horizon. In this contribution, we compare two forms of feedback in SMPC formulations in terms of their closed-loop performance, as well as their conservatism regarding constraint satisfaction. First, we consider a direct feedback formulation, which corresponds to the typical implementation of SMPC schemes. This formulation aims to satisfy constraints with respect to the predicted state distribution conditioned on the current measured state at each time step during the receding horizon control. The second, denoted indirect feedback, introduces feedback through the cost only, and instead considers constraints by introducing a suitable virtual or nominal state. This results in a linear evolution of a closed-loop error state which can be used for constraint tightening, providing closed-loop constraint satisfaction. In numerical examples, we demonstrate that this can significantly improve performance, as well as reduce conservatism in closed-loop and that it recovers the unconstrained optimal solution given by LQR control when it is feasible also for the constrained optimal control problem.
Paper VI199-01.28
PDF · Video · Input-To-State Stability of Time-Distributed Optimization in Real-Time Model Predictive Control
Liao-McPherson, Dominic	The University of Michigan
Nicotra, Marco M.	University of Colorado Boulder
Kolmanovsky, Ilya V.	University of Michigan
Keywords: Real-time optimal control, Nonlinear predictive control, Input-to-State Stability Abstract: This paper presents a general system theoretic framework for the analysis of Time-distributed Optimization (TDO) in the context of real-time Model Predictive Control (MPC). When implemented using TDO, an MPC controller maintains a running estimate of the solution of the underlying optimal control problem and improves it at each sampling instant, instead of computing high precision solutions. TDO can be conceptualized as the combination of truncation and warmstarting in online optimization and includes the real-time iteration scheme as a special case. This paper considers a broad class of optimization algorithm/MPC formulations combinations and derives sufficient conditions under which it is possible for TDO based MPC controllers to recover the stability and robustness properties of optimal MPC using a finite amount of computational power.
Paper VI199-01.29
PDF · Video · Cascade Affine Constant Recursive Algorithm for Model Based Control
Cerne, Gregor	University of Ljubljana
Skrjanc, Igor	Univ of Ljubljana
Keywords: Recursive identification, Identification for control Abstract: The paper tackles trade-off between slow parameter adaptation and parameter variance of recursive least square estimation (rLSE) after a system change. In this paper, the cascade affine constant (CAC) estimation for linear systems is presented, which uses rLSE parameters as an apriori knowledge for affine constant estimation, as it can be estimated faster with lower variance as the result of its simple structure. In this configuration, rLSE uses a slower forgetting rate for more accurate dynamics estimation, while affine constant is used to react faster to changes in the system. The developed method is compared to recursive least squares in predictive functional control, in which all metrics are better or at least equal.
Paper VI199-01.30
PDF · Video · Toward Nonlinear Dynamic Control Over Encrypted Data for Infinite Time Horizon
Kim, Junsoo	Seoul National University
Farokhi, Farhad	The University of Melbourne
Shames, Iman	University of Melbourne
Shim, Hyungbo	Seoul National University
Keywords: Secure networked control systems, Control over networks, Quantized systems Abstract: Based on the use of homomorphic encryption schemes, recent studies on encrypted control has been presented, aiming for security enhancement by control operation directly performed over encrypted data without decryption. In the meantime, implementing dynamic controllers over encrypted data has been a challenge, due to the fact that the number of operations for an encrypted message may be limited so that it may not be capable of performing the recursive operation for infinite time horizon. Toward unlimited dynamic control, in this note, we address that it is possible to run a dynamic controller over encrypted data for infinite time horizon utilizing both encryptions of the input and output of the plant, when the output of the system can be represented as a function of the previous outputs and inputs. Then, we suggest a class of nonlinear systems to which the proposed approach can be applied, while it guarantees that the performance error of the proposed encrypted controller due to quantization can be made arbitrarily small with the choice of parameters. As an example, it is suggested that the proposed method is applicable for all linear systems, with the guarantee of performance.
Paper VI199-01.31
PDF · Video · On Sensor Attack Detection in Control Systems Using Moving Horizon Estimation and Control Performance
Isono, Kei	Hokkaido University
Kobayashi, Koichi	Hokkaido University
Adachi, Ryosuke	Yamaguchi University
Yamashita, Yuh	Hokkaido University
Keywords: Secure networked control systems, Estimation and filtering Abstract: The sensor attack detection problem in control systems is important in the field of cybersecurity. In this paper, we propose a sensor attack detection method based on both moving horizon estimation and control performance. In the existing methods, the signal from an attacker is regarded as the unknown input or the error in state estimation. In the proposed method, we suppose that the closed-loop system is composed of the plant, the state estimator, and the controller by the linear quadratic regulator. We utilize moving horizon estimation for linear singular systems. Then, a sensor attack is detected based on the control performance. By a numerical example, the effectiveness of the proposed method is presented.
Paper VI199-01.32
PDF · Video · A Nonlinear Small Phase Theorem
Chen, Chao	The Hong Kong University of Science and Technology
Zhao, Di	Hong Kong University of Science and Technology
Chen, Wei	Peking University
Qiu, Li	Hong Kong Univ. of Sci. & Tech
Keywords: Stability of nonlinear systems, Robust control, Passivity-based control Abstract: In this paper, we propose a definition of phase for a class of stable nonlinear systems called semi-sectorial systems from a pure input-output perspective. The definition involves Hilbert transform as a key tool for the purpose of complexifying real-valued signals. The proposed nonlinear system phase, serving as a counterpart of L2-gain, quantifies the passivity and is highly related to the dissipativity. A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems. It generalizes a version of the passivity theorem and the linear time-invariant small phase theorem.
Paper VI199-01.33
PDF · Video · Consistency Analysis of the Extended Observability Matrix of Output-Error Closed-Loop Subspace Model Identification
Oku, Hiroshi	Osaka Institute of Technology
Ikeda, Kenji	Tokushima University
Keywords: Subspace methods, Closed loop identification Abstract: This paper studies statistical properties of a closed-loop subspace model identification method for a system described with the output-error state-space representation. For details, the limit value of the matrix to be singular-value-decomposed to estimate the extended observability matrix is investigated. The contribution is to ensure that the estimate of the extended observability matrix is consistent up to a similarity transform.
Paper VI199-01.34
PDF · Video · Decoupling Problems for Switching Linear Systems without Knowledge of the Switching Signal
Conte, Giuseppe	Universita' Politecnica Delle Marche
Perdon, Anna Maria	Universita' Politecnica Delle Marche
Zattoni, Elena	Alma Mater Studiorum - University of Bologna
Keywords: Switching stability and control, Disturbance rejection (linear case), Complex systems Abstract: The disturbance decoupling problem with asymptotic stability is considered in the framework of switching linear systems assuming that no information on the actual value of the switching signal or of the current mode of the system is available. By introducing the novel notion of strong conditioned invariant subspace and relating it to feedback stabilizability, the solvability of the problem is completely characterized in the case of switching signals with sufficiently large dwell time. Constructive procedures to check necessary and sufficient solvability conditions and to construct solutions, if any exists, are given.
Paper VI199-01.35
PDF · Video · Adaptive Switching Control Based on the Balance Equation
Zhang, Jin	CNPC Beijing Richfit Information Technology
Keywords: Tracking, Analytic design Abstract: This paper presents an adaptive switching control strategy based on the Balance Equation. Previous work has described the development of the Balance Equation inspired by the PI/PID design rule in the framework of Internal Model Control. The linear algebraic relationship between the proportional and integral contributions of a PI controller revealed by the Balance Equation is utilized as the driving force for the adaptive switching among a set of candidate controllers. A performance index is calculated through the difference between the integral contribution given by the ideal controller and that given by a candidate controller. By minimizing this performance index, the adaptive switching strategy aims at finding the candidate controller that is closest to the ideal controller. For step changes in the set-point, as long as the candidate controller set covers the ideal controller, the adaptive control strategy can always switch to this controller in a timely fashion. Extensive simulation results have shown that the adaptive switching control strategy can always identify the best controller from the candidate controller set and achieve good set-point tracking performance even in the presence of significant variation in the process time constant. This adaptive control switching strategy serves as a good demonstration for the value of the Balance Equation, which can enable more new insight, better control performance, and stronger adaptation ability in wider applications.

VI199-02
Late Breaking Results II Applications	Regular Session
Chair: Nagahara, Masaaki	The University of Kitakyushu
Co-Chair: Scherpen, Jacquelien M.A.	University of Groningen
Paper VI199-02.1
PDF · Video · Adaptive Backstepping Control in the Presence of Quantization: Application to a 2-DOF Helicopter System
Schlanbusch, Siri	University of Agder
Zhou, Jing	University of Agder
Keywords: Adaptive control, Stability of nonlinear systems, Networked systems Abstract: Recent years have witnessed a growing interest in investigating quantized control systems. In quantized control system, the control signal to the system is a piece-wise constant function of time and the system is interacted with information quantization. The main motivation is its theoretical and practical importance in the area of digital control systems, hybrid systems, and networked control systems. An important aspect is to use quantization schemes that have sufficient precision and require low communication rate. This paper proposes a quantized adaptive control algorithm for a helicopter system in the presence of quantization. A nonlinear mathematical model is derived for the 2-DOF helicopter system based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. The input and states are quantized by a class of bounded error quantizers. It is a nonlinear multiple-input multiple-output system, with challenges in controller design due to its nonlinear behavior, its coupling, and with uncertainties both in the model and the parameters, and with disturbance from the quantized inputs. A new adaptive control algorithm is developed by using backstepping technique to track the pitch and yaw position references independently. Only quantized signals are used in the developed control which reduces communication rate and costs. It is shown that not only the ultimate stability is guaranteed by the proposed controller, but also the designers can tune the design parameters in an explicit way to obtain the required closed loop behavior. Experiments are carried out on the Quanser Aero system to validate the effectiveness, robustness and control capability of the proposed scheme.
Paper VI199-02.2
PDF · Video · A Track-Before-Detect Approach to Multi-Target Tracking on Automotive Radar Sensor Data
Meister, David	University of Stuttgart
Holder, Martin F.	Technical University of Darmstadt
Winner, Hermann	Technical University of Darmstadt
Keywords: Bayesian methods, Estimation and filtering, Particle filtering/Monte Carlo methods Abstract: In recent years, Bayes filter methods in the labeled random finite set formulation have become increasingly powerful in the multi-target tracking domain. One of the latest outcomes is the Generalized Labeled Multi-Bernoulli (GLMB) filter which allows for stable cardinality and target state estimation as well as target identification in a unified framework. In contrast to the initial context of the GLMB filter, this paper makes use of it in the Track-Before-Detect (TBD) scheme and thus, avoids information loss due to thresholding and other data preprocessing steps. This paper provides a TBD GLMB filter design under the separable likelihood assumption that can be applied to real world scenarios and data in the automotive radar context. Its applicability to real sensor data is demonstrated in an exemplary scenario. To the best of the authors' knowledge, the GLMB filter is applied to real radar data in a TBD framework for the first time.
Paper VI199-02.3
PDF · Video · Up-Down Counter Based Detection of Current Wind Direction Change for a Wind Turbine
Odgaard, Peter Fogh	Goldwind Energy
Keywords: Control of renewable energy resources, Applications of FDI and FTC, Computational methods for FDI Abstract: For optimizing wind turbine designs it is of importance to reduce extreme structural loads. Control schemes plays an important role in this. In this work detection of Coherent gust and direction changes (ECD) is developed, which enables mitigating actions to prevent potential turbine shutdowns due to over speed during ECD events. The proposed scheme can detect the ECD cases within to 2.5 s, which is early enough to avoid over speed caused shutdowns of the wind turbine.
Paper VI199-02.4
PDF · Video · Construction and Application of User-Driven Robot Development Methodology
Sakaue, Tomoki	Tokyo Electric Power Company Holdings, Inc
Keywords: Design methodologies, field robotics, Telerobotics Abstract: Infrastructure inspection robots and disaster respond robots are required. These robots are designed and manufactured for specific purposes and are not standardized. In order to develop robots that meet the on-site need and can be securely installed in a short period of time, a user-driven robot development methodology has been constructed. This methodology starts from the on-site need and defines system requirements based on the site environment and risk assessment. The design, prototype, and verification are repeated to satisfy the requirements. A survey robot using this methodology was deployed to Fukushima Daiichi Nuclear Power Station, and an inspection robot for transmission lines was also developed. This methodology is similar to a waterfall approach. However, we would like to introduce an agile methodology to minimize development uncertainty and improve it through actual cases in the future.
Paper VI199-02.5
PDF · Video · Fast Extremum-Seeking Control with Self-Tuning Dilution Rate Amplitude for Biogas Production in Anaerobic Bioreactors
Motta, Miguel	Pontifícia Universidade Católica Do Rio Grande Do Sul
Araujo Pimentel, Guilherme	Pontifícia Universidade Católica Do Rio Grande Do Sul
Castro, Rafael da Silveira	PUCRS
Vargas, Alejandro	Instituto De Ingenieria UNAM
Keywords: Dynamics and control, Optimal control and operation of water resources systems, Wastewater treatment processes Abstract: The paper presents a new fast extremum-seeking control (FESC) strategy, based on the FESC proposed by Ramírez-Carmona et al. (2018). The objective of this new controller is to decrease the oscillation of the output/flowrate of biogas by updating the values of upper and lower bounds. In order to numerically validate the strategy, we consider the methanisation of organic matter with the objective to maximize the production of biogas in anaerobic bioreactors. Simulations show that the new approach reaches the optimal productivity regions with smaller variance if compared with the FESC proposed by Ramírez-Carmona et al. (2018). In consequence of that, the process reaches larger productivity, it produces 13% more biogas than the conventional fast extremum-seeking control.
Paper VI199-02.6
PDF · Video · ADMM-Based Optimization of Distributed Energy Management Systems with Demand Response
Ogawa, Daiki	Hokkaido University
Kobayashi, Koichi	Hokkaido University
Yamashita, Yuh	Hokkaido University
Keywords: Energy systems, Power systems, Large scale optimization problems Abstract: Design of distributed energy management systems composed of several agents is important for realizing smart cities. Demand response for saving the power consumption is also important. In this paper, we propose a design method of distributed energy management systems with real-time demand response. Here, we use ADMM (Alternating Direction Method of Multipliers). In the proposed method, demand response is performed in real-time, based on the difference between the planned demand and the actual value. Furthermore, utilizing the blockchain is also discussed.
Paper VI199-02.7
PDF · Video · Control of a Manipulator Mounted on an Independent Controlled Moving Platform
Pedroso de Oliveira, Carlos Eduardo	Federal University of Rio Grande Do Sul (UFRGS)
Fetter Lages, Walter	Federal University of Rio Grande Do Sul (UFRGS)
Henriques, Renato Ventura Bayan	University of Rio Grande Do Sul
Keywords: field robotics, Robots manipulators, Guidance navigation and control Abstract: This paper deals with the control of a manipulator robot mounted on a moving platform. It is supposed that the moving platform is independently controlled, therefore sensor and control signals for the platform are not available. As the motion of the platform produces perturbations on the robot motion, it is the purpose of the proposed controllers to compensate for those effects on the end-effector. A 9-axis inertial measurement unit (IMU) mounted on the top of the moving platform is used to recover the orientation, velocity and acceleration of the platform joints, which are required for the implementation of the proposed control laws. The modeling of the IMU to recover the platform motion signals is based on the platform Jacobian and the proposed controllers are based on the computed torque controller. The IMU signal processing and the controllers are implemented using the Robot Operating System and the ros_control framework, making it possible to run the controller in real-time. Simulated results using the Gazebo simulator shows the effectiveness of the proposed controller. The performance improvements with respect to a computed torque controller without compensation for the platform motion were evaluated by using the RMS error of the joints as a metric.
Paper VI199-02.8
PDF · Video · Development of ROV for Underground Power Transmission Equipment Inspection in Submerged Manhole
Nagakita, Toru	Tokyo Electric Power Company Holdings, Inc
Sakaue, Tomoki	Tokyo Electric Power Company Holdings, Inc
Keywords: field robotics, Telerobotics, Robotics technology Abstract: When inspecting underground power transmission equipment inside a submerged manhole, it is necessary to pump up groundwater inside the manhole before the inspection. Since pumping up groundwater requires large costs, it is expected to reduce costs by applying a Remotely Operated Vehicle (ROV) which does not require pumping up groundwater. This ROV requires high mobility, wide visibility, and sufficient operating time, to inspect underwater objectives and above-water objectives inside the manhole. However, commercially available ROVs could not meet these requirements. Therefore, we developed an ROV that can satisfy the requirements. As a result of the verification test using a prototype, good results were obtained for the mobility, but issues such as insufficient resolution of the camera and the voltage drop were also confirmed. In the future, we aim to solve the issues by changing the camera specifications and compensating the voltage, in order to complete the ROV.
Paper VI199-02.9
PDF · Video · Customization of Agent-Based Manufacturing Applications Based on Domain Modelling
Casquero, Oskar	University of the Basque Country (UPV/EHU)
Armentia, Aintzane	Universidad Del Pais Vasco
Estévez, Elisabet	Universidad De Jaén
López García, Alejandro	University of the Basque Country (UPV/EHU)
Marcos, Marga	ETSI Bilbao, Universidad Del País Vasco
Keywords: Flexible and reconfigurable manufacturing systems, Model-driven systems engineering, Multi-agent systems applied to industrial systems Abstract: Agent-based architectures have become a mainstream technological concept that may allow factories to adopt distributed intelligence patterns that enable the advanced manufacturing model of Industry 4.0. However, there is a lack of methodologies and tools that support the specification, deployment and execution of agent-based manufacturing applications. This article describes the first steps to build an agent-based platform that provides a reusable software core that can be customized to offer the services required for factory-specific manufacturing systems. In this sense, the contribution of this article is two-fold: on the one hand, the proposal of a model-based definition of manufacturing applications based on factory-specific concepts that are represented in three XML schemas; on the other hand, a proposal for distributing the complexity of product intelligence in a set of agents that allow achieving separation of concerns regarding customer interaction and traceability of the production.
Paper VI199-02.10
PDF · Video · Nonlinear Attitude Tracking Maneuver of Spacecraft with Reaction Control System and Reaction Wheel
Takaku, Yuichi	Shonan Institute of Technology
Ikeda, Yuichi	Shonan Institute of Technology
Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles Abstract: Missions involving rapid and large-angle attitude maneuvers have been conceived in astronomical and earth observation satellites in recent years. Since the rotational motion of a spacecraft in such missions is nonlinear, it will be required to design an attitude control system that takes into account nonlinear motion. As an actuator capable of generating a large torque is also going to be required, it will also be necessary to consider characteristics of an actuator in designing a control system. Actuators capable of generating a large torque include reaction control system (RCS). RCS gives an on/off input as it uses the reaction force from fuel injection by thrusters, it can generate a large moment. In addition, the control system of current application satellites normally uses both RCS and reaction wheel (RW) conventionally used for attitude control. This paper considers large angle attitude maneuver of spacecraft by a combination of RCS and RW. To this end, characteristics of RCS and RW are defined, and a model for control system design is derived. Then, we design a nonlinear controller so that the closed-loop system becomes input-to-state stable (ISS) using the concept of backstepping approach. Finally, the effectiveness of proposed control method is verified by numerical simulations.
Paper VI199-02.11
PDF · Video · Application of Maximum Hands-Off Control to Cellular Metabolic Oscillation
Kunida, Katsuyuki	Graduate School of Biological Sciences, Nara Institute of Science
Nagahara, Masaaki	The University of Kitakyushu
Keywords: Kinetic modeling and control of biological systems, Metabolic engineering, Dynamics and control Abstract: Biological oscillation is one of the most important biological functions for maintaining homeostasis. In particular, it is known that yeast and Escherichia coli maintain homeostasis by oscillating the intracellular metabolite to increase the intracellular energy production in a starvation state where there is no nutrient such as glucose in the external environment. In this paper, we focus on the dynamical model of metabolic oscillations in yeast and report on tracking control from non-oscillation to oscillation using maximum hands-off control, also known as sparse control.
Paper VI199-02.12
PDF · Video · Update on 2D MEMS Raster and Vector Scanning Mirrors for Medical Imaging and High Laser Power Applications
Sandner, Thilo	Fraunhofer Institute for Photonic Microsystems, Dresden
Grasshoff, Thomas	Fraunhofer IPMS
Merten, André	Fraunhofer IPMS
Schwarzenberg, Markus	Fraunhofer IPMS
Birnbaum, Klemens	Fraunhofer IPMS
Grahmann, Jan	Fraunhofer Institute for Photonic Microsystems
Schroedter, Richard	Vienna University of Technology
Huenig, Paul	Technische Universität Dresden
Janschek, Klaus	Technische Universität Dresden
Keywords: Micro and Nano Mechatronic Systems, Mechatronic systems Abstract: Compact 2D MEMS scan modules for vectorial (2D quasi-static) scanning of a high power laser or fast raster scanning for medical imaging are presented, enabling more compact medical laser scanning based instruments (e.g. in ophthalmology). Flatness based control algorithms with jerk-limited trajectory design was implemented for precise position control of the low damped qs MEMS scanners.
Paper VI199-02.13
PDF · Video · Grade Transition Control of Tennessee Eastman Process Using Adaptive Dual MPC
Kumar, Kunal	IIT Bombay
Patwardhan, Sachin C.	Indian Institute of Technology Bombay
Noronha, Santosh	Indian Institute of Technology Bombay
Keywords: Model predictive and optimization-based control, Control of large-scale systems, Process control applications Abstract: There is a renewed interest in the development of adaptive dual MPC (ADMPC) formulations that simultaneously inject probing perturbations while controlling a plant. The majority of available dual MPC schemes are based on output error (OE) models. Recently, ARMAX model based ADMPC formulations have been proposed that explicitly capture the effect of unmeasured disturbances. In this work, we compare performances of ADMPC formulations based on OE and ARMAX models using the Tennessee Eastman (TE) challenge control problem proposed by Downs and Vogel [1993]. In particular, two grade transition problems defined in Ricker and Lee [1995] are considered. Simulation studies reveal that ADMPC formulation based on the OE model solves only one grade transition problem while the ARMAX model based formulation is able to solve both the grade transition problem satisfactorily. Thus, the inclusion of structured noise models in ADMPC formulation enables the operation of the TE problem over a very wide operating range.
Paper VI199-02.14
PDF · Video · A Machine Learning Approach to Traffic Flow Prediction Using CP Data Tensor Decompositions
Steffen, Thomas	Loughborough University
Lichtenberg, Gerwald	Hamburg University of Applied Sciences
Keywords: Modeling and simulation of transportation systems, Information processing and decision support, Intelligent transportation systems Abstract: This paper deals with the prediction of highway traffic flow based on historic data. The methodology is based on canonical polyadic (CP) tensor decompositions of traffic flow data. This step captures the regular elements of the traffic signal based on daily and weekly rhythms and typical geographical distributions of the traffic, while significantly reducing the amount of data required to describe these. The key factors are then extrapolated into the future, and the traffic data is reconstructed from the decomposition. Applied to traffic flow data from the M62 in the North of England in October 2019, this approach provides a surprisingly accurate prediction based on a very compact model, which is a distinct advantage compared to conventional machine learning approaches. Using 4 factors, the prediction captures 90% of the signal energy, which beats existing rolling average prediction techniques.
Paper VI199-02.15
PDF · Video · Space-Filling Subset Selection for an Electric Battery Model
Gesner, Philipp	Mercedes-Benz AG
Gletter, Christian	Mercedes-Benz AG
Landenberger, Florian	Mercedes-Benz AG
Kirschbaum, Frank	Daimler AG
Morawietz, Lutz	Institute of Automotive Technology Dresden
Bäker, Bernard	Technical University Dresden
Keywords: Modeling, supervision, control and diagnosis of automotive systems, Modeling and simulation of transportation systems, Engine modelling and control Abstract: Dynamic models of the battery performance are an essential tool throughout the development process of automotive drive trains. The present study introduces a method making a large data set suitable for modeling the electrical impedance. When obtaining data-driven models, a usual assumption is that more observations produce better models. However, real driving data on the battery's behavior represent a strongly non-uniform excitation of the system, which negatively affects the modeling. For that reason, a subset selection of the available data was developed. It aims at building accurate nonlinear autoregressive exogenous (NARX) models more effciently. The algorithm selects those dynamic data points that fill the input space of the nonlinear model more homogeneously. It is shown, that this reduction of the training data leads to a higher model quality in comparison to a random subset and a faster training compared to modeling using all data points.
Paper VI199-02.16
PDF · Video · Model-Free Control for Machine Tools
Villagra, Jorge	Centre for Automation and Robotics (CSIC-UPM)
Join, Cédric	UHP-Nancy & ALIEN INRIA-Futurs
Haber, Rodolfo	Center for Automation and Robotics (UPM-CSIC)
Fliess, Michel	Ecole Polytechnique
Keywords: Motion Control Systems, Micro and Nano Mechatronic Systems, Mechatronics Abstract: Cascade P-PI control systems are the most widespread commercial solutions for machine tool positioning systems. However, friction, backlash and wearing effects significantly degrade their closed-loop behaviour. This works proposes a novel easy-to-tune control approach that achieves high accuracy trajectory tracking in a wide operation domain, thus being able to mitigate wear and aging effects.
Paper VI199-02.17
PDF · Video · Compressive Feedback for Robot Motion Control
Li, Congjian	The University of Hong Kong
Wang, Siyu	The University of Hong Kong
Bi, Sheng	The University of Hong Kong
Xi, Ning	The University of Hong Kong
Keywords: Motion Control Systems, Perception and sensing, Robots manipulators Abstract: Robot motion control aims at generating control inputs for a robotic system to track a planned trajectory. Feedbacks provided by sensors play an essential role in motion control by improving the system performance when external disturbances and/or initial errors exist. However, feedback signals, such as images are often of large size, which imposes a heavy computational burden on the system. In this paper, a new robot motion control scheme is proposed based on a low dimensional compressive feedback to increase the feedback rate. The controller is designed in the non-vector space with compressive feedback. As an application, visual servoing is formulated under the proposed framework by considering a feedback image as a set, instead of a traditional feature vector. Experiments are conducted to validate the proposed control scheme.
Paper VI199-02.18
PDF · Video · Locating Nonlinearities in Mechanical Systems: A Dynamic Network Approach
Noël, Jean-Philippe	Eindhoven University of Technology
Dietrich, Jennifer	University of Liège
Oomen, Tom	Eindhoven University of Technology
Keywords: Nonlinear system identification, Vibration and modal analysis, Dynamic Networks Abstract: Accurately modelling nonlinearities is becoming increasingly important in the many high-tech sectors of mechanics, in particular in the context of model-based control design. During the nonlinear modelling process, a key step is the determination of the physical locations of the nonlinearities. The present work aims at developing a data-driven approach to nonlinearity location based on analysing nonparametric frequency response functions (FRFs). To achieve this objective, measurement locations in mechanical systems are interpreted as an arrangement of nodes in a dynamic network, and linearisation techniques are applied to the FRFs constructed from node to node. Illustrative results obtained on a numerical three-degree-of-freedom mechanical system demonstrate the effectiveness of the proposed approach.
Paper VI199-02.19
PDF · Video · Hybrid MODE-SVR Algorithm for Nonparametric Dynamic System Identification of Autonomous Helicopter
Tijani, Ismaila	Higher Colleges of Technology
Akmeliawati, Rini	University of Adelaide
Keywords: Nonparametric methods, Mechanical and aerospace estimation, Time series modelling Abstract: Practical application of SVR in nonparametric modeling requires not only achievement of acceptable model accuracy but also optimal reduction of the model complexity in terms of the associated support vectors. Attaining these performance metrics is not only challenging due to inherently conflicting nature of the duo performances, but also as a result of several structural parameters needed to be tuned in SVR deployment. In order to address this problem, a hybrid algorithm of SVR based on Multi Objective Differential Evolution (MODE-SVR) is proposed to search for the SVR structural parameters that provides Pareto-based optimal solutions for both model complexity and accuracy. The proposed algorithm is evaluated on nonparametric model of a UAV helicopter yaw dynamics. Performance analysis and comparative study with an existing method in MATLAB shows the effectiveness of the proposed hybrid algorithm. This is expected to simplify and enhance the practical application of SVR in machine learning applications.
Paper VI199-02.20
PDF · Video · Diagnostic Models and Estimators for LDI in Transmission Pipelines
Kowalczuk, Zdzislaw	Gdansk University of Technology
Tatara, Marek	Gdańsk University of Technology, Faculty of Electronics, Te
Keywords: Parameter estimation based methods for FDI, Filtering and estimation for FDI, FDI for nonlinear Systems Abstract: This article considers and compares four analytical models of the pipeline flow process for leak detection and location tasks. The synthesis of these models is briefly outlined. Next, the methodology for generating data and diagnosing pipes is described, as well as experimental settings, assumptions and implemented scenarios. Finally, the quality of model-based diagnostic estimators has been evaluated for their bias, standard deviations and computational complexity. The global level of optimality served as a general indicator of the quality and performance of multidimensional estimators.
Paper VI199-02.21
PDF · Video · Stereo Vision for Unmanned Aerial Vehicle Detection, Tracking, and Motion Control
Brunet, Maria	Purdue University
Aramizo Ribeiro, Guilherme	Purdue University
Mahmoudian, Nina	Michigan Technological University
Rastgaar, Mo	Purdue University
Keywords: Perception and sensing, Flying robots, Autonomous robotic systems Abstract: An innovative method of detecting Unmanned Aerial Vehicles (UAVs) is presented. The goal of this study is to develop a robust setup for an autonomous multi-rotor hunter UAV, capable of visually detecting and tracking the intruder UAVs for real-time motion planning. The system consists of two parts: object detection using a stereo camera to generate 3D point cloud data and video tracking applying a Kalman filter for UAV motion modeling. After detection, the hunter can aim and shoot a tethered net at the intruder to neutralize it. The computer vision, motion tracking, and planning algorithms can be implemented on a portable computer installed on the hunter UAV.
Paper VI199-02.22
PDF · Video · Visual Navigation with a 2-Pixel Camera - Possibilities and Limitations
Baillieul, John	Boston Univ
Kang, Feiyang	Boston University
Keywords: Perception and sensing, Motion Control Systems, Mechatronics for Mobility Systems Abstract: Borrowing terminology from fluid mechanics, the concepts of Eulerian and Lagrangian optical flow sensing are introduced. Eulerian optical flow sensing assumes that each photoreceptor in the camera or eye can instantaneously detect feature image points and their velocities on the retina. If this assumption is satisfied, even a two pixel imaging system can provide a moving agent with information about its movement along a corridor that is precise enough to be used as a robust and accurate steering signal. Implementing Eulerian optical flow sensing poses significant challenges, however. Lagrangian optical flow, on the other hand, tracks feature image points as they move on the retina. This form of visual sensing is the basis for many standard computer vision implementations, including Lukas-Kanade and Horn-Schunck. Lagrangian optical flow has its own challenges, not least of which is that it is badly confounded by rotational components of motion. Combined steering and sensing strategies for mitigating the effects of rotational motions are considered.
Paper VI199-02.23
PDF · Video · Intelligent Working Point Control for Solar Thermal Energy Collectors
Juuso, Esko Kalevi	University of Oulu
Keywords: Process control applications, Nonlinear process control, Process modeling and identification Abstract: Solar power plants are aimed to collect available thermal energy in a usable form at the desired temperature range. The thermal energy in form of hot oil can be used for electricity generation or a desalination plant. The Control is achieved by means of varying the flow pumped through the pipes in the field during the operation. In the utilization of the solar thermal energy, storages are highly important in integrating the collector systems with overall energy sources and usage: nights and the heavy cloud periods as well as load disturbances and changes need to come up with them. At a parabolic trough collector field, the linguistic equation (LE) controllers have shown reliable operation in varying operating conditions and extend the operation to varying cloudy and even heavy cloudy conditions and handle efficiently disturbances in energy demand. In a recent idea, the working point controller sets a goal for the operation by selecting the operating area which is then checked by the intelligent analysers to define the achievable setpoint. This improves the operation in connection with the other energy sources and the efficiency of the energy collection in varying operating conditions. Weather forecasts are needed in further scheduling the strengths of the collecting periods.
Paper VI199-02.24
PDF · Video · A Simple Approach for Real Time and Autonomous Measurement of Regulating Power
Hiroe, Takaharu	Mitsubishi Heavy Industries, Ltd
Ide, Kazunari	Mitsubishi Heavy Industries, Ltd
Keywords: Smart grids, Impact of deregulation on power system Control, Instrumentation and control systems Abstract: For stable electric power supply operation, creation of incentive to regulating power is necessary. However, unlike electric energy (kWh) has electricity meters for billing purposes; regulating power does not have even measuring devices as that simple. In this paper, we consider a policy of "net-mileage" for real time and autonomous measurement of it. The main difference from well-known "mileage" policy is that it counts only the stability contribution of "mileage", it measures fast contribution like governor free mode operation, and it also measures the contribution of the demand side. Simulation case studies are presented to show the effectiveness.
Paper VI199-02.25
PDF · Video · On the Passivity of Clustered District Heating Subsystems
Machado Martinez, Juan Eduardo	University of Groningen
Cucuzzella, Michele	University of Groningen
Scherpen, Jacquelien M.A.	University of Groningen
Keywords: Stability of nonlinear systems, Energy systems, Passivity-based control Abstract: We present in this brief note a nonlinear model of a cluster of district heating subsystems, each of which is conformed by a local producer, a storage tank, and a local consumer. We explicitly provide storage functions and adequately chosen outputs from which we establish, under certain assumptions, that such a system is shifted passive, opening the possibility for decentralized and distributed passivity-based control design.
Paper VI199-02.26
PDF · Video · Modeling Evolutionary Effects of Anticancer Therapies by Spatial Games with Resources
Swierniak, Andrzej	Silesian Technical Univ
Borys, Damian	Silesian University of Technology
Keywords: Control of physiological and clinical variables, Kinetic modeling and control of biological systems, Bioinformatics Abstract: We propose an extension of spatial evolutionary games which enables simulation of evolutionary changes in cancer cells population resulting from anticancer therapies treated as external interventions. There are two non-standard issues used in this type of games. The first one is based on the assumption that heterogeneity of tumor populations takes place on the cell level which is realized by the use of multilayer spatial structures. The other one is related to variability of entries of pay-off tables representing changes in external resources which describe anticancer treatment.
Paper VI199-02.27
PDF · Video · Combination of Reinforcement Learning and Bio-Inspired Odor Source Searches under a Time-Variant Gas Mapping
Hernandez Reyes, Cesar	Tokyo Institute of Technology
Okajima, Kei	Yokohama National University
Shigaki, Shunsuke	Osaka University
Kurabayashi, Daisuke	Tokyo Institute of Technology
Sanada, Kazushi	Yokohama National Univ
Keywords: Guidance navigation and control, Intelligent robotics, robot ethology Abstract: Searching for odor sources such as hazardous objects or gas leaks is desirable in a robot. In the literature, many approaches to odor source search are bio-inspired or probabilistic. However, the performance of either method can decrease if exploring and exploiting olfactory information is unbalanced. In this paper we investigated whether a balance can be achieved by a hybrid strategy composed of a bio-inspired search and infotaxis, which is an RL-based method of the literature. We tested infotaxis and the hybrid algorithm under a time-variant virtual odor plume. We obtained this plume from readings of a gas sensor array and a wind tunnel. From this we found that the hybrid algorithm showed better search performance and less deviation from the plume centerline. Therefore we believe that combining probabilistic and bio-inspired policies might be useful to balance exploration and exploitation and efficiently perform olfactory searches.
Paper VI199-02.28
PDF · Video · Normalized Passivity Control for Hardware-In-The-Loop with Contact
Insam, Christina	Technical University of Munich
Peiris, Lokukankanamge Dushyantha Hashan	University of Bath
Rixen, Daniel	TU München
Keywords: Hardware-in-the-loop simulation, Identification and control methods, Mechatronic systems Abstract: Mechanical contact occurs in many engineering applications. Contact dynamics can lead to unwanted dynamic phenomena in mechanical systems. Hence, it would be desirable to investigate the influence of contact dynamics on a dynamical system already in the development stage. An appropriate method is Hardware-in-the-loop (HiL) on mechanical level. However, the coupling procedure in HiL is prone to stability problems and previous studies revealed that HiL tests of systems with contact are even more challenging, as the dynamics of the investigated system change rapidly when contact occurs. Passivity-based control schemes, well-known from teleoperation, have recently been used to stabilize HiL simulations of systems with continuous dynamics. Here, we investigate the applicability of Normalized Passivity Control to HiL tests of a one-dimensional mass-spring-damper system experiencing contact. Experimental results reveal that using this kind of passivity control manages to keep the test stable and also improves the fidelity of the HiL simulation. This research is an important first step in using passivity control for stable and safe hybrid simulation of complex systems with contact using HiL approaches.
Paper VI199-02.29
PDF · Video · Design of In-Silico Optimal Controller for Adaptive Molecular Network Based on Particle Filter
Takeru, Murayama	Graduate School of Biological Sciences, Nara Institute of Science
Sakumura, Yuichi	Graduate School of Biological Sciences, Nara Institute of Science
Kunida, Katsuyuki	Graduate School of Biological Sciences, Nara Institute of Science
Keywords: Kinetic modeling and control of biological systems, Parameter and state estimation, Dynamics and control Abstract: Cell transmit dynamical signals from extracellular stimulation such as growth factor and hormones to downstream gene expression, controlling various cellular function. In this study, we report the application of optimal control based on particle filter to adaptive molecular network. We have implemented the tracking control of output generated from the adaptive molecular network to sine signal as a reference signal by using the particle filter based optimal controller.
Paper VI199-02.30
PDF · Video · Tuning Rules for a Class of Port-Hamiltonian Mechanical Systems
Chan, Carmen	University of Groningen
Borja, Luis Pablo	University of Groningen
Scherpen, Jacquelien M.A.	University of Groningen
Keywords: Stability of nonlinear systems, Passivity-based control, Application of nonlinear analysis and design Abstract: In this extended abstract, we propose a tuning approach for nonlinear mechanical systems to modify the behavior of the closed-loop system, where we are particularly interested in attenuating oscillations from the transient response. Towards this end, we inject damping into the system, and we provide two tuning methods to select the gains that are appropriate for our purposes. Furthermore, we apply these tuning rules to a 2DoF planar manipulator and present its simulation results.