Abstract
This paper investigates the filtering problem for a class of discrete-time singular Markov jump nonlinear systems against hybrid attacks via a fuzzy-model-based method, in which the hybrid attacks contain deception attacks and denial of service attacks. Two random variables subject to the Bernoulli distribution are used to describe whether the hybrid attacks are encountered during the measurement output of the original system being transmitted to the filter. By using linear matrix inequality technology and Lyapunov stability theory, some sufficient conditions are given to guarantee the considered systems are stochastically admissible and meet performance index γ. The design approach of the secure filter and a specific form to acquire the expected secure filter gains are obtained, respectively. Finally, to demonstrate the effectiveness of the proposed approach, both a numerical example and a practical example are provided.
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Notes on contributors
Guanqi Wang
Guanqi Wang is now a M.S. candidate at the School of Electrical and Information Engineering, Anhui University of Technology, China. His current research interests include singular systems, Markov jump systems, networked control systems, fuzzy control, robust control and filtering.
Feng Li
Feng Li received the M.S. degree in Electrical Engineering from Anhui University of Technology, Ma'anshan, China, in 2017, and the Ph.D. degree in Control Science and Engineering from Nanjing University of Science and Technology, Nanjing, China, in 2021. He is currently a lecturer with the School of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan, China. From April 2019 to November 2020, he was a visiting fellow with the School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, NSW, Australia. His current research interests include Markov jump systems, singularly perturbed systems, neural networks, networked control systems, robust control and filtering, and their applications.
Yan Wang
Yan Wang received the Ph.D. degree in Intelligent Monitoring and Control from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2008. She is currently a professor with the School of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan China. From July 2014 to July 2015, she worked as a visiting scholar in Missouri University of Science and Technology, USA. Her current research interests include intelligent monitoring and control, structural health monitoring and modern control theory.
Jing Wang
Jing Wang received the Ph.D. degree in Electric Power System and Automation from Hohai University in 2019. She is currently an associate professor with the School of Electrical and Information Engineering, Anhui University of Technology, Ma'anshan, China. Her current research interests include Markov jump nonlinear systems, singularly perturbed systems, power systems, and nonlinear 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.