Adaptive fuzzy controller for a class of strict-feedback nonaffine nonlinear system

Abstract

A robust adaptive fuzzy control scheme is presented for a class of strict-feedback nonaffine nonlinear systems with modeling uncertainties and external disturbances by using Backstepping approach. Fuzzy logic systems (FLS) are employed to approximate the unknown parts of the desired virtual controls, the key assumption is that the norms of the approximation errors are bounded, and the bounds are unknown. A robust control algorithm was introduced to efficiently compensate the approximation error and external disturbances. The tracking error is guaranteed to be uniformly ultimately bounded. Finally, by taking the complexity of FLS, tracking error and control oscillation as object functions, an elitist preserved genetic algorithm (GA) is employed to search for the optimal parameters. The simulation results illustrate the effectiveness of the proposed scheme.