Adaptive disturbance observer-based event-triggered fuzzy control for nonlinear system

This paper investigates the issue of tracking control of nonlinear system with external disturbance, an event-triggered fuzzy backstepping sliding-mode control strategy is proposed. Firstly, a fuzzy state estimator is designed to estimate the unmeasurable state, and a sliding-mode disturbance observer is presented on the estimation error. In which, consider the conservativeness of the observer parameter, a parameter adaptation law with a double nested structure is proposed to mitigate chattering problems caused by parameter conservativeness. Then an event-triggered mechanism along with backstepping control and sliding-mode strategy is designed to achieve tracking control and save the network resources, and the Zeno phenomenon can be avoided. Furthermore, the backstepping law combines with Lyapunov theory is used to prove that the tracking error can converge to a small bounded set and all the signals of closed-loop plant are bounded. Finally, simulation results are carried out to illustrate the potential of designed approaches.