Resilient Adaptive Event-Triggered $H_{\infty }$ Fuzzy Filtering for Cyber-Physical Systems Under Stochastic-Sampling and Denial-of-Service Attacks

作者：Xuhuan Xie, Songlin Hu, Yonggui Liu, Qinxue Li · 发表于：IEEE Transactions on Fuzzy Systems · 年份：2022 · DOI：10.1109/tfuzz.2022.3185500 · 被引用次数：58 · 研究领域：Network Security and Intrusion Detection、Smart Grid Security and Resilience、Neural Networks Stability and Synchronization

This article is concerned with resilient adaptive event-triggered$H_{\infty }$fuzzy filtering for a class of interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy-model-based cyber-physical systems (CPSs) under stochastic sampling and energy-constrained, nonperiodic denial-of-service (DoS) attacks. The nonlinear plant with parameter uncertainties is represented as a class of IT2 T–S fuzzy systems, and a novel resilient adaptive event-triggered scheme (AETS) against stochastic sampling and DoS attacks is proposed. In the designing process of the fuzzy filter, a novel resilient switched IT2 T–S fuzzy filter that switches according to the DoS attacks is applied. Then, the switched stochastic delayed systems model with a favorable form is established for the filtering-error-system. Based on the Lyapunov–Krasovskii stability theory and switched stochastic delayed systems theory, the relaxed stability condition is derived, which can ensure that the filtering-error-system is stochastically exponentially stable (SES) where the decay rate is indicated, the maximum frequency of DoS attacks is revealed, and an$H_{\infty }$disturbance attenuation performance is guaranteed. Also, the codesign algorithm is further developed to implement the codesign of fuzzy filter and resilient AETS. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed strategy.