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- Title
Dynamic Event-Based Asynchronous and Resilient Dissipative Filtering for T–S Fuzzy Markov Jump Singularly Perturbed Systems Against Deception Attacks.
- Authors
Zhang, Shuyu; Wang, Yanqian; Zhuang, Guangming; Song, Gongfei
- Abstract
In the paper, we endeavor to study the asynchronous and resilient dissipative filtering issue for T–S fuzzy Markov jump singularly perturbed systems (MJSPSs) involving the dynamic event-triggered transmission protocol, partly known conditional probabilities, and deception attacks. A novel dynamic event-triggered transmission protocol is firstly offered to further decrease the data transmission percentage over the communication channels. To better depict the practical communication situations, the mutually independent random variables that subject to the Bernoulli distribution are adopted to formulate the occurrence of deception attacks. And an asynchronous and resilient filter is properly constructed, which yields that the filtering error systems are converted into the T–S fuzzy MJSPSs with time-varying delays. Then, the criteria of stochastically stable for the filtering error systems are presented concerning a group of linear matrix inequalities (LMIs). By solving the LMIs, the nonsynchronous and resilient dissipative filter, the weighting matrix of dynamic event-triggered transmission protocol can be concurrently determined. Eventually, an example is provided to verify the validity of the developed theoretical results. Further, for the prescribed dissipative performance, state trajectoires, filter trajectories, and filter errors are presented for MJSPSs involving deception attacks under different transmission protocols, which illustrate that both of them almost have the same decay rates. However, for the prescribed dissipative performance, the transmission rates are so different for two transmission protocols that the dynamic event-triggered transmission protocol is much lower than that of the static one.
- Subjects
KALMAN filtering; LINEAR matrix inequalities; DECEPTION; ASYNCHRONOUS learning; BINOMIAL distribution; RANDOM variables; CONDITIONAL probability
- Publication
International Journal of Fuzzy Systems, 2022, Vol 24, Issue 3, p1491
- ISSN
1562-2479
- Publication type
Article
- DOI
10.1007/s40815-021-01204-9