Probability-based event-triggered asynchronous control for fuzzy jump systems

Abstract

This study investigates asynchronous control strategies for a specific class of nonlinear semi-Markov jump systems using the T-S fuzzy model. The primary objective is to overcome bandwidth constraints and enhance system performance. A novel probabilistic event-triggered protocol is introduced, aimed at reducing the frequency of packet transmissions efficiently. Unlike conventional static event-triggered protocols, this developed probabilistic event-triggered protocol adeptly harnesses the dynamic nature of network-induced delays. Moreover, by incorporating probabilistic delay division, a novel control law associated with the delay probability segmentation variable is skillfully designed. Discrepancies between system and controller modes are addressed by adopting a hidden semi-Markov model. This approach leads to the derivation of comprehensive criteria ensuring the stochastic stability of the closed-loop system. Finally, a practical example is presented, demonstrating the efficacy and practicality of the proposed theoretical results.