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

In this paper, the problem of H∞ resilient filter for nonlinear network systems with dynamic 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 binomial 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 division and segmented Lyapunov-Krasovskii functional. The co-design conditions of the H∞ 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 under the H∞ performance index. Finally, the effectiveness and superiority of the filter are verified by the joint simulation of Matlab and Carsim.