Adaptive and Sliding-Mode Fuzzy Control

Abstract

This chapter provides an overview of the issues and problems pertaining to fuzzy logic control systems based on adaptive fuzzy control and sliding-mode techniques . Initially, adaptive fuzzy control for a class of nonlinear systems with nonstrict-feedback structure is considered using fuzzy logic systems. A variable-separation approach is developed to overcome the difficulty from the nonstrict-feedback structure. Incorporating fuzzy approximation and backstepping techniques led to the design of a state feedback adaptive fuzzy tracking controller, which guarantees that all of the signals in the closed-loop system are bounded while the tracking error converges to a small neighborhood of the origin. In the next part, the main focus is centered around concepts of variable structure system with chattering free sliding modes. We study the design problem of dynamic event-triggered (ET) fuzzy control methodology for discrete-time Takagi–Sugeno (T–S) systems. The observed-state error is utilized to derive the event condition. Sufficient condition for the asymptotic stability of the closed-loop fuzzy and the observer error systems under the event-triggered fuzzy control is provided by linear matrix inequality (LMI). Moreover, the corresponding self-triggered (ST) fuzzy control is developed where the following control action is estimated in terms of the current sampled data. Furthermore, simulations are given to represent the feasibility and efficiency of the achieved results.