Adaptive NN fault-tolerant control for discrete-time systems in triangular forms with actuator fault

This paper investigates the adaptive actuator fault compensation control for a class of uncertain multi-input single-out discrete-time systems with triangular forms. The considered actuator faults contain both loss of effectiveness and lock-in-place. With the help of radial basis function neural networks to approximate the unknown nonlinear functions, an adaptive fault tolerant control scheme is designed. Compared with some existing methods, one of features of the proposed method is that we introduce the backstepping technique to achieve the fault-tolerant control task. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop systems are uniformly ultimately bounded and that the output can track a reference signal in the presence of the actuator faults. Finally, three simulation results are provided to confirm the effectiveness of the fault-tolerant control approach.