Abstract
This paper investigates the static output feedback secure control problem for discrete-time hidden Markov jump systems against replay attacks. The main purpose is to realise that closed-loop systems are stochastically stable with or without replay attacks. Firstly, the tampered sensors under replay attacks can be identified via the proposed detection method. Then, an asynchronous static output feedback controller is designed, which can eliminate the negative impact caused by replay attacks in view of the detection results. Based on the linear matrix inequality technique, some sufficient conditions which ensure the closed-loop systems are stochastically stable and meet a given performance are established. Finally, a numerical example and a practical example are given to verify the effectiveness and superiority of the proposed method.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Lei Su
Lei Su received the M.S. degree in the School of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan, China, in 2016 and the Ph.D. degree in control theory and engineering from the Northeastern University in 2020. Now, he is a lecturer at the School of Electrical and Information Engineering, Anhui University of Technology, China. His research interests include fault-tolerant control, event-triggered control, Markov jump systems and cyber-physical systems.
Shinian Fang
Shinian Fang graduated from Northeast University in June 1987, majoring in material processing and control, and worked in Huatian Engineering and Technology Corporation, MCC as a senior engineer. Engaged in research on intelligent processing control.
Zijun Liu
Zijun Liu received the B.Sc. degree in Automation from Hubei University of Arts and Science, Xiangyang, China, in 2019 and the M.S. degree in the School of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan, China, in 2021. Now he works in Huatian Engineering and Technology Corporation, MCC as a primary engineer. Engaged in research on intelligent processing control.
Hao Shen
Hao Shen received the Ph.D. degree in control theory and control engineering from Nanjing University of Science and Technology, Nanjing, China, in 2011. Since 2011, he has been with Anhui University of Technology, China, where he is currently a Professor. His current research interests include stochastic hybrid systems, complex networks, fuzzy systems and control, nonlinear control. Dr Shen has served on the technical program committee for several international conferences. He is an Associate Editor/Guest Editor for several international journals, including Journal of The Franklin Institute, Applied Mathematics and Computation, Neural Processing Letters and Transactions of the Institute Measurement and Control. Prof. Shen was a recipient of the Highly Cited Researcher Award by Clarivate Analytics (formerly, Thomson Reuters) in 2019–2021.
Tian Fang
Tian Fang graduated from University of Science and Technology Beijing, majoring in control theory and control engineering, and worked in Huatian Engineering and Technology Corporation, MCC as a senior engineer. Engaged in research on control theory and intelligent control.