Data-driven fault-tolerant control for nonlinear systems with output saturation

This paper is focused on data-driven fault-tolerant control for nonlinear systems with output saturation. A modified observer with measurement output is built to approximate sensor fault. According to this approximation, corresponding data-driven fault-tolerant controller is proposed by utilizing optimization criteria and adaptive dynamic programming method. Consequently, a triggering rule is constructed by employing instantaneous and average measurement output. Resorting to the Lyapunov method, the resulted error system is uniformly ultimately bounded. The effectiveness of the presented approach is demonstrated by an example comparison.