Neural Networks-Based Active Fault-Tolerant Control for a Class of Switched Nonlinear Systems With Its Application to RCL Circuit

The active fault-tolerant control (FTC) problem for a class of switched nonlinear systems is investigated by using average dwell time method. First, an observer-based fault detection scheme is established. Because only the system output is assumed to be available, the threshold of fault detection only depends on the output error. Moreover, all the signals in the closed-loop system are bounded in fault-free case. After a fault has been detected, the fault estimation and FTC schemes are activated. Due to the existence of faults, unstable subsystems are allowed to exist. The fault-tolerant controllers of subsystems and a class of switching signals with average dwell time are designed such that all the signals in the closed-loop system remain bounded, and the system states can be estimated by the observer. Finally, in order to illustrate the effectiveness of the proposed method, we apply it to the switched RCL circuit system.