Event-Triggered Robust Adaptive Fuzzy Control for a Class of Nonlinear Systems

Abstract

This paper considers a robust adaptive fuzzy control problem for a class of uncertain nonlinear systems via an event-triggered control strategy. Fuzzy logic systems are used to approximate the unknown nonlinear functions in the nonlinear system. A novel robust adaptive control scheme together with a novel event-triggering mechanism (ETM) is proposed to reduce communication burden. It should be noted that both the control signal and the adaptive parameters are updated only at the triggering time instants in the proposed scheme, which further saves the system energy and resources. It is shown that with the proposed event-triggered robust adaptive control scheme, all the signals in the closed-loop system are guaranteed to be semiglobally bounded, and the output of the system converges to a small neighborhood of the origin. Moreover, with the proposed ETM, Zeno behavior can be strictly excluded. Finally, a one-link manipulator system is used to demonstrate the effectiveness of the proposed control scheme.