Event Triggered Fault Tolerant Control for Nonlinear Systems Based on Adaptive Fault Estimation

In this paper, the problem of event triggered fault-tolerant control for nonlinear systems based on neural network learning technique is investigated. To achieve the main objective, a novel dynamic fault estimation method is proposed so that the fault mode of the system considered can be determined quickly. Then, one appropriate reference dynamics is selected. Based on the model reference control mechanism, the neural network is employed to learn the desired control policy when the event triggering condition is met. The stability of the closed-loop system is proved based on Lyapunov stability theory. Moreover, there does not exist the Zeno phenomenon using the proposed event triggered control method. Finally, the the effectiveness of the proposed method is verified on a single-joint manipulator system.