Adaptive finite-time fault-tolerant control for switched nonlinear systems with actuator fault and dead-zone via prescribed performance

Abstract

In this work, an adaptive finite-time fault-tolerant control (FTC) technique for a class of switched nonlinear systems in strict-feedback form is presented. The switched nonlinear systems are considered under the influence of actuator fault, input-dead zone, and external disturbances. A prescribed performance function is used to ensure transient and steady-state control performance. To approximate unknown functions and minimize the negative effect of faults, radial basis function neural networks (RBFNNs) are used. With the help of neural networks and the backstepping method, an adaptive finite-time tracking controller is constructed. For the stability analysis of the proposed approach, the common Lyapunov function (CLF) is employed. Based on the Lyapunov function method, it has been shown that all the signals in the closed-loop system are semi-globally practically finite-time (SGPF)-stable. Also, the tracking error converges to a small residual set with the prescribed performance bounds. Finally, two simulation examples show the effectiveness of the presented control method, one of which is an application to a continuous stirred tank reactor (CSTR).