Abstract:For linear systems with nonlinear terms and faults, a fault diagnosis and fault-tolerant control method based on adaptive neural networks is proposed by using RBF neural networks and adaptive laws. First, an adaptive neural network observer is designed to approximate the fault, and an adaptive law is designed to adjust the neural network weight vector and center vector online with a regulator introduced. Second, the adaptive neural network controller was designed, and the compensating control input is designed in conjunction with the neural network. Then, the proposed method is proved to achieve asymptotic stability of the system using the Lyapunov stability theorem. Finally, the simulation experimental results verify that the proposed method has good observation performance, control accuracy, and response speed for the faulty system.