Dynamic Event-Triggered Asynchronous Filter for T-S Fuzzy Markov Jump Systems with Packet Losses
Mingshuai Jiang, Huiying Chen, Weijun Liu · 2024
This paper investigates the problem of dynamic event-triggered asynchronous filtering for Takagi-Sugeno fuzzy Markov jump systems in the context of packet losses. The dynamic event-triggered mechanism is employed to alleviate communication load. Compared with the static event triggering mechanism, it has less triggering times, thus obtaining better communication performance. Packet losses occurring between the trigger and the filter are addressed by the Bernoulli model which can avoid zero input of the filter. In view of the asynchronous influence in practical engineering, the asynchronism between the filter and the plant is modeled using a hidden Markov model. Under this framework, a filtering error dynamic system model is built. By constructing Lyapunov functions, sufficient conditions for stochastic mean-square stability and H∞performance are derived. The design of an appropriate filter is achieved by the adoption of the slack matrix method and the Projection lemma. The practical efficacy of the proposed scheme is confirmed by the tunnel-diode circuit system.