Observer-based robust adaptive fuzzy controller for strict-feedback nonlinear uncertain systems

An observer-based robust adaptive fuzzy sliding mode control algorithm is proposed in this paper for the tracking control problem of a class of single-input single-output (SISO) strict-feedback nonlinear uncertain systems in the presence of uncertainties. Because all the states of the original nonlinear systems are not available for measurement, the high-gain observer is applied for estimating all states in the equivalent system. Moreover, fuzzy logic systems and some adaptive laws are used to approximate unknown nonlinear functions and the unknown bounds of uncertainties. Based on the Lyapunov stability theorem, the proposed robust adaptive fuzzy sliding mode controller can achieve the asymptotic stabilization and the output tracking performance of the whole closed-loop system. Finally, an example and simulation results are illustrated to show the effectiveness of the proposed control scheme.