Fuzzy Adaptive Fault-Tolerant Control for Uncertain Nonlinear Systems With Unknown Dead-Zone and Unmodeled Dynamics

This paper investigates the problem of adaptive fault-tolerant tracking control for uncertain nonlinear systems subject to input dead-zone and full state constraints. First, an error transformation approach is introduced to guarantee that all states do not violate their constraint bounds. Then, to avoid the issue of "explosion of complexity" in handling the derivative computation for the virtual control laws and improve the robust control performance, a novel nonlinear filter is proposed together with designing adaptive laws to compensate the bounded layer errors. In addition, the saturation function is employed to handle the difficulty caused by obtaining the explicit bounds for virtual signals at each step. By utilizing fuzzy logic systems to approximate unknown compound nonlinear functions, a novel fault-tolerant control scheme is proposed subject to online estimation technique. Finally, according to Lyapunov stability theory, it is concluded that all signals in the resulting closed-loop system are bounded and the tracking error satisfies the desired performance in presence of input dead-zone and actuator failures. Simulation results verify the effectiveness of the proposed control scheme.