Finite-time adaptive tracking control for unknown nonlinear systems with a novel barrier Lyapunov function

Abstract

This paper focuses on the issue of adaptive finite-time tracking control for uncertain strict-feedback nonlinear systems with full state constraints. For the first time, a new finite-time adjustable barrier function is introduced, whose design parameters can be regulated dynamically in real time with the change of tracking error. It cannot only converge to a preset region in a finite settling time with a faster convergent barrier, but it further optimizes the system transient performance. By embedding the proposed barrier function, a novel barrier Lyapunov function (BLF) is used for the design of an adaptive finite-time tracking controller, which guarantees that the output tracking error converges to a small region in finite time without violation of the constraint, and then tends to zero. All of the signals in the closed-loop system are bounded. A simulation verifies the effectiveness of the proposed control scheme.