Neural-network-based adaptive fault-tolerant tracking control of uncertain nonlinear time-delay systems under output constraints and infinite number of actuator faults

In this paper, the problem of NN-based adaptive fault-tolerant tracking control for a class of uncertain nonlinear time-varying delay systems under output constraints and infinite number of actuator faults is considered. By constructing Lyapunov-Krasovskii functions, introducing a bound estimation approach and using dynamic surface control technique, a novel adaptive fault-tolerant control scheme is designed to compensate actuator faults and unknown time-delay uncertain functions as well as the output constraint is not violated. Compared with the existing results, the proposed controller can be implemented easily. Furthermore, via Lyapunov theory, it is proven that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded. Finally, two illustrative examples are used for verifying effectiveness of the proposed approach.