Composite Learning Based Fuzzy Control for Nonlinear Systems with Unknown Dead Zone

This paper investigates the disturbance observer based composite fuzzy control for a class of uncertain nonlinear systems. With fuzzy logic system (FLS) approximating the unknown nonlinearities, composite learning is constructed on the basis of a serial-parallel identifier. By introducing the intermediate signal, the disturbance observer is developed to provide efficient learning of the compounded disturbance which includes the effect of time-varying disturbance, fuzzy approximation error and unknown dead zone. Based on the disturbance estimation and fuzzy approximation, the adaptive fuzzy controller is synthesized with novel updating law. The stability analysis of the closed-loop system is rigorously established via Lyapunov approach. The performance of the proposed controller is verified via simulation that faster convergence and higher precision are obtained.