Switching Event-Triggered Protocol for Fuzzy Singularly Perturbed Systems Under Random Sampling Periods

The study focuses on the problem of switching event-triggered protocol control for fuzzy singularly perturbed systems under random sampling. The non-uniform sampling of the model is characterized by introducing a random variable obeying the Markov process. Nextly, to reduce the network transmission burden, a novel switching event-triggered protocol is proposed, which can dynamically adjust the triggering parameters based on the time interval between the current sampling instant and the previous sampling instant. Meanwhile, a switching fuzzy event triggered controller is devised, by jointly triggering state information. Additionally, a set of sufficient conditions is derived to ensure the finite-time stability of the closed-loop system. The effectiveness and advantages of the proposed methodology are validated through both a numerical simulation and a practical example, demonstrating its feasibility and superiority.