Adaptive wavelet network controller design for nonlinear time delay systems in the presence of actuator failure

This paper presents an adaptive wavelet network controller for a class of strict-feedback uncertain nonlinear systems with unknown time delays and in the presence of external disturbances and actuator failure. The type of considered actuator failure is loss of effectiveness, in which the system input may lose unknown fraction of its effectiveness during the system operation. Wavelet networks are utilised to approximate unknown nonlinear functions and the proposed adaptive-neural controller is constructed based on dynamic surface control (DSC) design method. By applying the appropriate Lyapunov-Krasovskii functionals, the boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighbourhood of the origin. The performance of the proposed adaptive-neural control approach is illustrated by applying a theoretical system and a chemical reactor system. The simulation results indicate the effective capabilities of the proposed control algorithm.