Adaptive Zero-Error Finite-Time Tracking Control of Switched Nonlinear Systems With Prescribed Performance

This paper considers the adaptive finite-time tracking control problem for a class of switched nonlinear systems. Based on neural networks, the influence of unknown nonlinear functions is offset. A performance function is proposed to guarantee the transient performance of the tracking error. Moreover, a novel-type Lyapunov function is constructed that relaxes the constraints on virtual control functions. It is shown by Lyapunov stability analysis that the finite-time convergence and zero-error tracking performance can be ensured simultaneously. Finally, the effectiveness of the proposed method is verified by a simulation example.