Intermittent Event-Triggered Exponential Stabilization for State-Dependent Switched Fuzzy Neural Networks With Mixed Delays
Xiaofan Li, Nikhil R. Pal, Huiyuan Li, Tingwen Huang
Abstract
In this article, the issue of intermittent event-triggered exponential stabilization for state-dependent switched fuzzy neural networks with mixed delays is discussed and resolved. By combining event-triggered control with intermittent control, an intermittent event-triggered control strategy is proposed, which only focuses on events during control time. Consequently, compared with some existing event-triggered control strategies, it greatly reduces the amount of samplings and saves control costs. Based on the fuzzy intermittent event-triggered controller designed in this article, two event-triggering mechanisms are proposed to determine the trigger instants. In this context, some easily testified algebraic conditions are obtained for the exponential stabilization of the state-dependent switched fuzzy neural networks with mixed delays. In addition, a positive lower bound for the inter-event time is given. The results of theoretical analysis are verified through a simulation example.