Resilient filter of nonlinear network systems with dynamic event-triggered mechanism and hybrid cyber attack

In this paper, the problem of ?1 ,, resilient filter for nonlinear network systems with dy-namic event-triggered mechanism and hybrid cyber attack is discussed. The Takagi-Sugeno (T-S) fuzzy technique is applied to deal with the nonlinearity of network systems. For the obtained T-S fuzzy model, the system measurement output is assumed to transfer to the filter by network channels. A novel dynamic event-triggered communication scheme is proposed to improve the utilization of network resources. In addition, Bernoulli bino-mial distribution are used to simultaneously describe the phenomenon of deception and DoS attack. Multi-channel network delay is solved by the method of combining delay di-vision and segmented Lyapunov-Krasovskii functional. The co-design conditions of the ?1 ,, resilient filter based on dynamic event-triggered are given by the form of linear matrix inequalities (LMIs), and ensures that the error filtering system is stochastically stable un-der the ?1 ,, performance index. Finally, the effectiveness and superiority of the filter are verified by the joint simulation of Matlab and Carsim.(c) 2022 Published by Elsevier Inc.

Automated summary

This paper discusses the problem of resilient filter for nonlinear network systems with dynamic event-triggered mechanism and hybrid cyber attack. The Takagi-Sugeno fuzzy technique is applied to deal with the nonlinearity of network systems. A novel dynamic event-triggered communication scheme is proposed to improve the utilization of network resources. The effectiveness and superiority of the filter are verified through joint simulation.