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This paper investigates the problem of non-fragile dissipative filtering for discrete-time nonlinear networked systems with dynamic quantization, a dynamic event-triggered mechanism and stochastic cyber attacks. The nonlinear networked system under investigation is described by an uncertain Takagi–Sugeno (T-S) fuzzy model. In this work, a novel fuzzy-dependent dynamic event-triggered communication scheme and the dynamic quantization strategy, integrated with an online adjustment rule, are introduced to reduce the frequency and volume of data transmission, thus realizing more rational utilization of the limited communication resources. In addition, the stochastic cyber attacks are characterized by a random variable obeying the Bernoulli distribution. The core focus of this paper is to design a non-fragile filter such that the resulting filtering error system is stochastically stable and meets the prescribed dissipative filtering performance. Based on the matrix inequality decoupling technique, the design conditions of the desired filter are derived and presented in the form of linear matrix inequalities (LMIs). Finally, the effectiveness and superiority of the proposed filter design approach is verified via two simulation examples.
Cheng et al. (Thu,) studied this question.