Neural adaptive control of hypersonic aircraft with actuator fault using randomly assigned nodes

This paper investigates the fault-tolerant controller for hypersonic aircraft in case of actuator fault. The robust adaptive controller is designed using command filtered back-stepping scheme. The uncertainty caused by the fault is approximated by randomly assigning nodes of the RBF single-hidden layer feedforward network (SLFN). The output weight is updated based on the Lyapunov synthesis approach to guarantee the stability of the overall control system. The method is applied on the control-oriented model whose subsystems are written into the linearly parameterized form. Simulation results show that the proposed approach achieves good tracking performance.