Observer-based adaptive neural fault-tolerant control for nonlinear systems with prescribed performance and input dead-zone

This article investigates the adaptive fault-tolerant tracking control problem for nonlinear systems with prescribed performance and input dead-zone. First, a new composite variable is constructed by using the characteristics of actuator fault and input dead-zone for the modeling purpose. Second, an adaptive neural network observer is designed to estimate the system states in the presence of inaccurate feedback information. Third, the proposed control strategy effectively counteracts the effects of sensor failure and unknown nonlinear functions, which makes the tracking error confined within the performance boundary and all the signals of the closed-loop system semi-globally uniformly ultimately bounded. Finally, an application oriented example is provided to demonstrate the effectiveness of the proposed control algorithm.