Improved Command-Filtering-Based Fixed-Time Fuzzy Adaptive Control for Uncertain Nonlinear Systems With Full State Constraints

Abstract

In this article, the improved command-filteringbased fixed-time fuzzy adaptive control of strict-feedback uncertain nonlinear systems with full state constraints is studied. Firstly, a new filtering approach is designed to improve the convergence speed and solve the “explosion of complexity” problem. And the filtering error can be effectively eliminated by a novel compensating mechanism. Then, barrier Lyapunov function with the filtering approach handles full state constraints in the system, so that the states will not violate the specified ranges. The proposed method ensures the tracking error converges to the neighborhood of the origin rapidly in a fixed time. Finally, the effectiveness and advantages of the proposed method is verified through simulation of a single link robot system.