Almost fast finite‐time adaptive tracking control for a class of full‐state constrained pure‐feedback nonlinear systems

Abstract

Summary In this article, a novel almost fast finite‐time adaptive tracking control scheme is proposed for a class of full‐state constrained pure‐feedback nonlinear systems based on barrier Lyapunov functions (BLFs). First, by employing the mean value theorem, the pure‐feedback systems are converted to the strict‐feedback structure with nonaffine terms. Then, by fusing adaptive backstepping technique and BLFs, the design difficulties caused by the nonaffine terms and full‐state constraints are overcome. Furthermore, according to the predeveloped almost fast finite‐time stability criterion, it is proved that the tracking error can converge to a small compact set and all signals of the closed‐loop system can be bounded in an almost fast finite time. Finally, a simulation example of a single‐link robot is presented to verify the effectiveness of the proposed control scheme.