Exponential Stability of Stochastic Takagi–Sugeno Fuzzy Systems Under Intermittent Dynamic Event-Triggered Control
Yongbao Wu, Sai Hu, Wenxue Li
Abstract
This article discusses the exponential stability in mean square of Takagi–Sugeno fuzzy systems (T-SFSs) under the stochastic case. Moreover, stochastic factors are taken into account to make the model more general. Different from traditional time-triggered control, we introduce event-triggered control strategy into intermittent control and then intermittent dynamic event-triggered control (IDE-TC) is developed, which can reduce updates of the controller and save resources. Besides, we eliminate Zeno phenomena, which is independent of mathematical expectation. Furthermore, the minimum interexecution time by the IDE-TC can be obtained directly for T-SFSs under the stochastic case. In addition, in order to illustrate the theoretical results, an application about double-link robot arm model is given. Meanwhile, we exhibit some numerical simulations.