Adaptive Fixed-Time Control of Error-Constrained Pure-Feedback Interconnected Nonlinear Systems
Qi Zhou, Peihao Du, Hongyi Li, Renquan Lu, Jun Yang
Abstract
This article addresses the problem of decentralized adaptive fuzzy fixed-time control for a class of pure-feedback interconnected nonlinear systems with full-state tracking error constraints. The fuzzy logic systems (FLSs) are adopted to model the unknown nonlinear functions. Combining the properties of the prescribed performance functions (PPFs) with barrier Lyapunov functions (BLFs), the predefined state tracking error dynamic performance and good tracking accuracy are guaranteed. Then, on the basis of the backstepping recursive design technique, a structurally simple adaptive fuzzy fixed-time controller is designed. Furthermore, by the fixed-time stability criterion and the Lyapunov stability theory, it is proven that the boundedness of system signals is guaranteed, and the full-state tracking errors can evolve within the prescribed performance regions within the fixed time. Finally, the effectiveness of the proposed control strategy is demonstrated by some simulation results.