Decentralized Dynamic Event-Triggered Adaptive Fuzzy Control for Switched Nonlinear Systems With Unstable Inverse Dynamics
Fenglan Wang, Lijun Long
Abstract
In this article, the problem of decentralized dynamic event-triggered (ET) adaptive fuzzy control for a class of strong interconnected switched uncertain nonlinear systems with unstable inverse dynamics and unknown control gains is studied. By utilizing the adaptive backstepping technique and new fuzzy logic systems, decentralized ET adaptive fuzzy controllers for subsystems and a new type of switching decentralized dynamic event-triggering mechanisms are constructed. Then, the asynchronous switching problem between candidate controllers and subsystems is addressed, and the upper bound of asynchronous time is not directly restricted. Meanwhile, by ensuring that the interexecution times are lower bounded by a positive constant, Zeno behavior is avoided. Furthermore, it is proved by the multiple Lyapunov functions method that all signals in the switched closed-loop system are bounded under a new class of slow switching signals. The validity of the derived result is illustrated using two examples which include a two inverted pendulum system.