Article
Automation & Control Systems
Jafar Zarei, Ebrahim Masoudi, Roozbeh Razavi-Far, Mehrdad Saif
Summary: This work focuses on passive fault-tolerant control (FTC) for discrete-time networked control systems (NCSs). Network imperfections, such as random time delay and packet dropout, are modeled using a Markov chain, resulting in a Markovian jump linear system (MJLS). Some elements of the transition probability matrix (TPM) are assumed to be unknown to address complex network issues. A comprehensive fault model that considers the stochastic nature of networks is employed, and a closed-loop NCS model is obtained using state augmentation technique. A constrained model predictive control (MPC) is proposed to develop a fault-tolerant control strategy that considers all these issues and input constraint. Linear matrix inequalities (LMIs) are used to derive sufficient conditions for designing the reliable controller. Two examples are presented to demonstrate the effectiveness of the proposed FTC, showing superior performance compared to existing studies.
Article
Automation & Control Systems
Shidong Xu, Hao Wen, Xiaoyu Wang
Summary: This article studies the observer-based robust fuzzy control of nonlinear systems subject to actuator saturation via network communication. It introduces an adaptive event-triggered mechanism for processing the system outputs in an aperiodic sampling manner. A fuzzy observer is established using the Takagi-Sugeno (T-S) fuzzy description, and a saturated fuzzy control law is derived from the observer's estimated states. The adverse effect of persistent bounded disturbance is attenuated using the L infinity performance index. A novel Lyapunov functional is investigated to analyze system stability and synthesize the desired controller, considering the characteristics of the aperiodic event-triggered scheme and transmission delays. Additionally, a novel set of sufficient conditions for controller synthesis is derived by incorporating the knowledge of asynchronous membership functions. The proposed observer-based control algorithm is verified through an illustrative example and simulation results.
Article
Mathematics, Applied
Tu Zhang, Liwei Li, Mouquan Shen
Summary: This paper focuses on the finite-time control of linear parameter-varying systems using the interval observer method. An unknown input observer framework is employed to construct the interval observer and avoid cooperativity constraints in estimation error dynamics. A control scheme with upper-lower bounds of the controller is established to handle time-varying parameters in the control input channel. Sufficient conditions formulated as LMIs are used to ensure the finite-time boundedness of error systems, and the proposed strategy's effectiveness is evaluated through numerical simulations.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Automation & Control Systems
Yanping Wang, Xiaoming Chen, Haixiao Guo
Summary: This paper proposes an event-triggered H-/L-infinity fault detection observer design method for discrete-time Lipschitz nonlinear networked control systems in finite-frequency domain, which can reduce data transmission and achieve better FD performance. The worst-case fault sensitivity performance is measured using the finite-frequency H-index, and disturbance robustness performance is measured using the L(infinity) norm. The FDO design conditions are derived and transformed using a set of linear matrix inequalities.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2022)
Article
Automation & Control Systems
Zhengtian Wu, Bo Li, Cunchen Gao, Baoping Jiang
Summary: This paper studies the Ho degrees control design for a class of singular switching semi-Markovian jump systems, proposes a Luenberger observer and state feedback controller design method, and validates the effectiveness of the obtained results through a numerical example.
Article
Computer Science, Artificial Intelligence
Wei Zheng, Zhiming Zhang, Hak-Keung Lam, Fuchun Sun, Shuhuan Wen
Summary: This article discusses the exponential mean-square stability analysis for uncertain networked control systems using a stochastic T-S fuzzy model and a dynamic output feedback strategy. By designing a fuzzy basis-dependent Lyapunov functional, stability conditions are derived and the closed-loop system is proven to be exponentially mean-square stable. Linear matrix inequalities (LMIs) technology is also employed to guarantee the prescribed H-infinity performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Automation & Control Systems
Zhenbin Du, Yonggui Kao, Ju H. Park
Summary: This paper addresses the interval type-2 fuzzy tracking control problem for nonlinear networked control systems with unreliable communication links. A tracking controller is designed for interval type-2 fuzzy sampled-data system under unreliable communication, enhancing stability through membership function characteristics and utilizing Lyapunov theory. The paper provides less conservative sufficient condition for designing networked tracking controller to ensure anticipated tracking performance, demonstrated through simulation examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Anastasia Nikolakopoulou, Moo Sun Hong, Richard D. Braatz
Summary: This article presents a synthesis method for full dynamic state feedback controllers and state and output observers that have guaranteed properties for systems approximated by dynamic artificial neural networks. The method uses linear matrix inequalities and quadratic Lyapunov function to derive sufficient conditions for controller synthesis and observer design. It is applicable to the practical situation where the steady-state values for the control input are not known.
Article
Automation & Control Systems
Mohamed Rouamel, Faycal Bourahala, Kevin Guelton
Summary: This paper focuses on the stability analysis and controller design problem for networked control systems with network-induced delays. The objective is to provide relaxed conditions and new delay-dependent conditions to maximize the admissible range of the delays and obtain controller gains and delay bounds. The proposed methods show improvements in conservatism compared to previous results.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2022)
Article
Automation & Control Systems
Adrian Ruiz, Damiano Rotondo, Bernardo Morcego
Summary: This paper presents a shifting feedback linearization controller for nonlinear systems with input saturation. The controller is able to handle nonlinear systems with state-dependent input constraints and adjusts the closed-loop convergence speed of the system based on changes in the system's region of linearity. The proposed approach is validated through an experimental example.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
S. Mohanapriya, R. Sakthivel, Dhafer J. Almakhles
Summary: The focus of current research is to address the problem of robust output tracking, input delay compensation, and disturbance attenuation performance for a family of stochastic systems by implementing the improved equivalent input disturbance estimator and the extended Smith predictor technique. A new closed-loop configuration is presented by integrating the observer and IEID estimator with ESP. The Lyapunov based mean-square asymptotic stability criterion is obtained, and based on this criterion, an IEID and ESP-based controller is designed to guarantee exact output tracking. Simulation studies and comparisons with existing results demonstrate the effectiveness of the established control procedure.
Article
Mathematics
Hejun Yao, Fangzheng Gao
Summary: This paper studies the observer design and dynamic output feedback control for a class of nonlinear networked systems. The model of the networked systems is established using the T-S fuzzy method, and a state observer is designed for unknown system states. The paper explores the conditions for exponential stability of the system using the linear matrix inequality (LMI) method and Lyapunov stability theory. The dynamic output feedback control of the systems is designed using the observer states, ensuring exponential convergence to the origin for both the closed-loop systems and error systems. A simulation example is provided to illustrate the feasibility and effectiveness of the design method.
Article
Acoustics
Babak Ranjbar, Abolfazl Ranjbar Noiey, Behrooz Rezaie
Summary: This study proposes a decentralized controller based on a new adaptive sliding mode observer for linear interconnected systems with unknown interconnections. The stability of the system and the convergence of the estimated states are guaranteed using a combination of Luenberger observer and adaptive sliding mode technique, achieving efficient performance according to simulation results.
JOURNAL OF VIBRATION AND CONTROL
(2021)
Article
Automation & Control Systems
Ania Adil, Abdelghani Hamaz, Ibrahima N'Doye, Ali Zemouche, Taous-Meriem Laleg-Kirati, Fazia Bedouhene
Summary: In this paper, a high-gain observer design method is proposed for nonlinear systems with time-varying delayed output measurements. The HG/LMI observer allows for a larger bound of the time-delay compared to the standard high-gain methodology, and it adopts a lower tuning parameter value. The proposed methodology provides more general synthesis conditions and can be applied to systems with nonlinear outputs.
Article
Computer Science, Artificial Intelligence
Muhammad Shamrooz Aslam, Prayag Tiwari, Hari Mohan Pandey, Shahab S. Band
Summary: This study presents a new stochastic maximum power point tracking control approach for photovoltaic cells (PCs). The study focuses on isolated PC generators, which form a direct current microgrid capable of handling changing loads. The proposed networked control systems use an event-triggered approach based on a fuzzy system to handle time-varying delays. The study examines how random, variable loads impact the stability and efficiency of PC generators.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Alex S. Ira, Chris Manzie, Iman Shames, Robert Chin, Dragan Nesic, Hayato Nakada, Takeshi Sano
Summary: This study proposes a tuning framework that uses supervised machine learning to extract the human-learned cost function and an optimization algorithm for optimizing the extracted cost function, aiming to reduce tuning costs and improve performance in industrial control systems.
INTERNATIONAL JOURNAL OF CONTROL
(2021)
Article
Automation & Control Systems
Carlos Murguia, Iman Shames, Justin Ruths, Dragan Nesic
Article
Computer Science, Information Systems
Wanchun Liu, Girish Nair, Yonghui Li, Dragan Nesic, Branka Vucetic, H. Vincent Poor
Summary: This article focuses on Wireless networked control systems (WNCSs) and derives the stability region and analyzes the average cost function through a detailed wireless communication system model. The research results can help design optimal parameters to minimize the average cost within the stability region.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Mathieu Granzotto, Romain Postoyan, Lucian Busoniu, Dragan Nesic, Jamal Daafouz
Summary: This paper analyzes the stability of deterministic nonlinear discrete-time systems, constructs a Lyapunov function for the closed-loop system, and ensures a uniform semiglobal stability property with adjustable parameters including the discount factor and horizon length. It provides less conservative stability conditions, new relationships between optimal value functions, and investigates stability with only a near-optimal sequence of inputs for discounted finite-horizon costs.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Tianci Yang, Carlos Murguia, Margreta Kuijper, Dragan Nesic
Summary: This paper introduces an observer-based estimator that provides exponential estimation of the system state even in the presence of attacks on actuators and sensors. The proposed estimator also includes tools for reconstructing and isolating attacks, as well as a control scheme to stabilize closed-loop dynamics by switching off isolated actuators. Simulation results are provided to demonstrate the effectiveness of the proposed tools.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Automation & Control Systems
Mohammad Deghat, Saeed Ahmadizadeh, Dragan Nesic, Chris Manzie
Summary: This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions. Results show that under certain conditions, solutions of the system have stability and controllable errors.
Article
Automation & Control Systems
Stefan H. J. Heijmans, Romain Postoyan, Dragan Nesic, W. P. Maurice H. Heemels
Summary: This article considers an alternative condition on the communication instants to better capture the time-varying properties of the transmission intervals, proposing a bound on the average allowable transmission interval in addition to the existence of a maximal allowable transmission interval. Through a novel Lyapunov-based analysis, stability of the NCS can still be guaranteed under this different condition on the transmission intervals.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Yankai Lin, Iman Shames, Dragan Nesic
Summary: This article explores minimizing the sum of potentially nondifferentiable convex cost functions with partially overlapping dependences in an asynchronous manner, where communication is uncoordinated. The study focuses on the behavior of an asynchronous algorithm and provides sufficient conditions for almost sure convergence, as well as a sublinear convergence rate that can be enhanced to linear under specific assumptions. Additionally, the extension of results in the literature allows for multiple and potentially overlapping blocks to be updated simultaneously with nonuniform probabilities.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Automation & Control Systems
Mathieu Granzotto, Romain Postoyan, Lucian Busoniu, Dragan Nesic, Jamal Daafouz
Summary: Optimistic planning (OP) is an important algorithm for generating near-optimal control inputs for nonlinear systems. The algorithm has been modified to overcome limitations and provide new performance guarantees, showing stability in control.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Seth Siriya, Jingge Zhu, Dragan Nesic, Ye Pu
Summary: In this paper, a certainty-equivalence scheme is proposed for adaptive control of scalar linear systems subject to additive, i.i.d. Gaussian disturbances and bounded control input constraints, without requiring prior knowledge of the bounds of the system parameters, nor the control direction. Assuming that the system is at-worst marginally stable, mean square boundedness of the closed-loop system states is proven. Lastly, numerical examples are presented to illustrate the results.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Alejandro I. Maass, Wei Wang, Dragan Nesic, Ying Tan, Romain Postoyan
Summary: This study focuses on nonlinear networked control systems (NCS) and proposes an emulation-based approach to implement the controller over multiple processors. The research starts with a stable and centralized NCS commonly found in literature, and then demonstrates how to deploy the centralized controller on multiple processors using parallel computing techniques while preserving stability under sufficiently fast computations (semi-globally and practically). An example is provided to illustrate the main findings.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Proceedings Paper
Automation & Control Systems
Mathieu Granzotto, Olivier Lindamulage de Silva, Romain Postoyan, Dragan Nesic, Zhong-Ping Jiang
Summary: This article presents a new algorithm called PI+ for optimal control of nonlinear deterministic discrete-time plants. The algorithm ensures recursive feasibility and stability, outperforming existing policy iteration approaches. The results have implications for approximate dynamic programming and reinforcement learning research, providing a clear method for verification and enhancing system safety.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Automation & Control Systems
J. Kreiss, R. Postoyan, D. Nesic, W. P. M. H. Heemels
Summary: We investigate the scenario of controlling an over-actuated plant over a network, focusing on the effect of varying transmission intervals and scheduling. We propose an emulation-based solution for controller design that takes into account the network and ensures stability of the closed-loop system. Our results provide significant improvements for over-actuated plants compared to existing literature, with new model derivation and conditions on scheduling protocols to achieve a two-measure stability property for the networked control system.
Article
Automation & Control Systems
Tianci Yang, Carlos Murguia, Chen Lv, Dragan Nesic, Chao Huang
Summary: This study addresses the problem of robust state reconstruction for discrete-time nonlinear systems when the actuators and sensors are injected with potentially unbounded attack signals. By exploiting redundancy in sensors and actuators and using a bank of unknown input observers (UIOs), the proposed observer-based estimator is capable of providing asymptotic estimates of the system state and attack signals under the condition that the numbers of sensors and actuators under attack are sufficiently small. Methods for isolating the compromised actuators and sensors are provided using the proposed estimator.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Computer Science, Theory & Methods
Carlos Murguia, Iman Shames, Farhad Farokhi, Dragan Nesic, H. Vincent Poor
Summary: The paper focuses on maximizing privacy of stochastic dynamical systems by randomizing quantized sensor data before transmission to prevent accurate estimation of the system state. The joint probability distribution of additive vectors is designed to minimize mutual information between system state and randomized sensor data. Simulation experiments are presented to illustrate the privacy scheme.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Automation & Control Systems
Xiaoyu Luo, Chengcheng Zhao, Chongrong Fang, Jianping He
Summary: This paper investigates the problem of false data injection attacks in multi-agent dynamical systems and proposes FDI attack set selection algorithms to maximize the convergence error by finding the optimal subset of compromised agents.
Article
Automation & Control Systems
Nitin K. Singh, Abhisek K. Behera
Summary: In this paper, a twisting observer is proposed for robustly estimating the states of a second-order uncertain system. The observer approximates the unknown sign term for the non-measurable state with a delayed output-based switching function, and achieves the desired steady-state accuracy by controlling the delay parameter. The application of the observer to output feedback stabilization is also discussed.
Article
Automation & Control Systems
Alexander Aleksandrov
Summary: This paper investigates the absolute stability problem for positive Persidskii systems with delay, proposes a special construction method for diagonal Lyapunov-Krasovskii functionals, and derives a criterion for the existence of such functionals guaranteeing the absolute stability, as well as obtaining sufficient conditions for a family of time-delay Persidskii systems to construct a common diagonal Lyapunov-Krasovskii functional. The efficiency of the developed approaches is demonstrated through four examples.
Article
Automation & Control Systems
Noureddine Toumi, Roland Malhame, Jerome Le Ny
Summary: This paper addresses large multi-agent dynamic discrete choice problems using a linear quadratic mean field games framework. The model incorporates the features where agents have to reach a predefined set of possible destinations within a fixed time frame and running costs can become negative to simulate crowd avoidance. An upper bound on the time horizon is derived to prevent agents from escaping to infinity in finite time. The existence of a Nash equilibrium for infinite population and its epsilon-Nash property for a large but finite population are established. Simulations are conducted to explore the model behavior in various scenarios.
Article
Automation & Control Systems
Philippe Schuchert, Vaibhav Gupta, Alireza Karimi
Summary: This paper presents the design of fixed-structure controllers for the As2 and Asw synthesis problem using frequency response data. The minimization of the norm of the transfer function between the exogenous inputs and performance outputs is approximated through a convex optimization problem involving Linear Matrix Inequalities (LMIs). A general controller parametrization is used for continuous and discrete-time controllers with matrix transfer function or state-space representation. Numerical results show that the proposed data-driven method achieves performance equivalent to model-based approaches when a parametric model is available.
Correction
Automation & Control Systems
Zhijun Guo, Gang Chen
Article
Automation & Control Systems
Matteo Della Rossa, Thiago Alves Lima, Marc Jungers, Raphael M. Jungers
Summary: This paper presents new stabilizability conditions for switched linear systems with arbitrary and uncontrollable underlying switching signals. The study focuses on two specific settings: the robust case with completely unknown and unobservable active mode, and the mode-dependent case with controller depending on the current active switching mode. The technical developments are based on graph-theory tools and path-complete Lyapunov functions framework, enabling the design of robust and mode-dependent piecewise linear state-feedback controllers using directed and labeled graphs.
Article
Automation & Control Systems
Elena Petri, Romain Postoyan, Daniele Astolfi, Dragan Nesic, W. P. M. H. (Maurice) Heemels
Summary: This study investigates a scenario where a perturbed nonlinear system transmits its output measurements to a remote observer via a packet-based communication network. By designing both the observer and the local transmission policies, accurate state estimates can be obtained while only sporadically using the communication network.
Article
Automation & Control Systems
Jonas Krook, Robi Malik, Sahar Mohajerani, Martin Fabian
Summary: This paper proposes a method to synthesise controllers for cyber-physical systems subjected to disturbances, such that the controlled system satisfies specifications given as linear temporal logic formulas. The approach constructs a finite-state abstraction of the original system and synthesises a controller for the abstraction. It introduces the robust stutter bisimulation relation to account for disturbances and uncertainty, ensuring that related states have similar effects under the same controller. The paper demonstrates that the existence of a controller for the abstracted system implies the existence of a controller for the original system enforcing the linear temporal logic formula.
Article
Automation & Control Systems
Clement Chahbazian, Karim Dahia, Nicolas Merlinge, Benedicte Winter-Bonnet, Aurelien Blanc, Christian Musso
Summary: The paper derives a recursive formula of the Fisher information matrix on Lie groups and applies it to nonlinear Gaussian systems on Lie groups for testing. The proposed recursive CRLB is consistent with state-of-the-art filters and exhibits representative behavior in estimation errors. This paper provides a simple method to recursively compute the minimal variance of an estimator on matrix Lie groups, which is fundamental for implementing robust algorithms.
Article
Automation & Control Systems
Yiheng Fu, Pouria Ramazi
Summary: This study investigates the characteristics of decision fluctuations in heterogeneous populations and explores the uncertainties in imitation behavior. The findings are important for understanding the bounded rationality nature of imitation behaviors.
Article
Automation & Control Systems
Lars A. L. Janssen, Bart Besselink, Rob H. B. Fey, Nathan van de Wouw
Summary: This paper introduces a mathematical relationship between the accuracy of reduced-order linear-time invariant subsystem models and the stability and accuracy of the resulting reduced-order interconnected linear time-invariant model. This result can be used to directly translate the accuracy characteristics of the reduced-order subsystem models to the accuracy properties of the interconnected reduced-order model, or to translate accuracy requirements on the interconnected system model to accuracy requirements on subsystem models.
Article
Automation & Control Systems
Piyush Gupta, Vaibhav Srivastava
Summary: We study the optimal fidelity selection for a human operator servicing tasks in a queue, considering the trade-off between high-quality service and penalty due to increased queue length. By modeling the operator's cognitive dynamics and task fidelity, we determine the optimal policy and value function numerically, and analyze the structural properties of the optimal fidelity policy.
Article
Automation & Control Systems
Lukas Schwenkel, Alexander Hadorn, Matthias A. Mueller, Frank Allgoewer
Summary: In this work, the authors study economic model predictive control (MPC) in periodic operating conditions. They propose a method to achieve optimality by multiplying the stage cost by a linear discount factor, which is easy to implement and robust against online changes. Under certain assumptions, they prove that the resulting linearly discounted economic MPC achieves optimal asymptotic average performance and guarantees practical asymptotic stability of the optimal periodic orbit.
Article
Automation & Control Systems
Taher Ebrahim, Sankaranarayanan Subramanian, Sebastian Engell
Summary: We propose a robust nonlinear model predictive control algorithm for dynamic systems with mixed degrees of freedom. This algorithm optimizes both continuous and discrete manipulated variables, enhancing closed-loop performance. Our approach relies on a computationally efficient relaxation and integrality restoration strategy and provides sufficient conditions to establish recursive feasibility and guarantee robust closed-loop stability. The effectiveness of the approach is demonstrated through two nonlinear simulation examples.
