This dissertation presents an adaptive controller for nonlinear systems with unknown parameters, bounded time varying delays and in the presence of time varying actuator failures. The type of the considered actuator failure is that some unknown inputs may be stuck at some unknown time varying values where the values, times and patterns of the failures are unknown. The considered actuator failure can cover most failures that may occur in actuators of the systems. The proposed adaptive state feedback control scheme is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. Furthermore, the proposed adaptive controller is extended for uncertain Multi Input Multi Output nonlinear time delay systems and uncertain large scale systems with time varying delays and in the presence of time varying actuator failures. To prevent the problem of “explosion of complexity” that exists in the backstepping design method, the adaptive control scheme is proposed by combining the backstepping design method and Dynamic surface Control (DSC) approach. In the latter approach, the uncertainties are approximated by using Gaussian Neural Networks. Key words Actuator failure, Compensation, Time varying delay, Backstepping, Dynamic Surface Control, Neural Networks
