Dynamic Event-Triggered Filtering for Nonlinear MJSs With Application to Tunnel Diode Circuits

In this brief, a dissipative filtering algorithm that integrates dynamic event-triggered control and IT2 fuzzy model is developed for nonlinear discrete-time Markov jump systems (MJSs). Firstly, the plant with partially unknown transition probabilities is modeled as an interval type-2 (IT2) fuzzy MJSs by using IT2 fuzzy set and membership functions, where the premise variables are not required full measurable. Secondly, a dynamic event-triggered scheme (DETS) is developed to conserve communication resources, wherein the triggering parameter can be tuned as data changes instead of a traditional event-triggered with a fixed triggering parameter. Thirdly, an IT2 fuzzy dynamic event-triggered filtering approach is proposed, utilizing the Lyapunov theory. Finally, the effectiveness of the proposed algorithms is verified through experiments conducted on tunnel diode circuits (TDC).