Adaptive NFTSM-Based Fault Tolerant Control for a Class of Nonlinear System With Actuator Fault and Saturation

In this paper, an adaptive fault-tolerant control (FTC) strategy is proposed for a class of nonlinear systems in the presence of actuator fault, actuator saturation, and unknown external disturbance. The mathematical model of a second-order nonlinear system with actuator fault is first given, and a fault estimation observer is designed to estimate the occurred time-varying actuator fault. On this basis, the adaptive FTC strategy is proposed using both nonsingular fast terminal sliding mode (NFTSM) and radial basis function neural networks (RBFNNs) techniques to compensate for the negative effects caused by time-varying actuator fault and external disturbance. Another adaptive FTC scheme is further presented under actuator saturation case, and the Lyapunov stability analysis demonstrates that the designed FTC approach could guarantee that the trajectory of sliding mode dynamics could converge to a small neighborhood of the origin within a finite time. Compared with some existing results, the FTC approach proposed in this paper has better fault acceptability. Finally, the proposed adaptive FTC approach is applied to the attitude control of rigid spacecraft, and the simulation results illustrate the advantages of the designed control scheme.