Indirect Adaptive Fuzzy Control of SISO Nonlinear Systems With Input–Output Nonlinear Relationship

Abstract

In this paper, a design method of indirect adaptive fuzzy controller is proposed for a class of single-input single-output (SISO) nonlinear systems with input–output nonlinear relationship. In this method, fuzzy systems are utilized to approximate unknown nonlinear functions, and a state observer is designed to estimate the unmeasured state. Under the given constraint conditions of the system parameters, the adaptive law is given. Meanwhile, the stability of the closed-loop system is proven with all state variables being uniformly bounded in the Lyapunov sense. Moreover, the convergence of the fuzzy control system is analyzed. The simulation results show the feasibility, effectiveness, and universality of the designed method.