Performance-Constraint-Based Adaptive Fuzzy Prescribed-Time Containment Control for Nonlinear Multi-Agent Systems
Kewen Li, Xiao Liu, Yongming Li
Abstract
In this article, a fuzzy adaptive prescribed-time performance constrain containment control issue is researched for nonlinear multi-agent systems (MASs). The original system’s prescribed time control issue will be converted into the corresponding controlled system’s asymptotic tracking control issue by using the time-domain mapping technique. Fuzzy logic systems (FLSs) are ultilized to identify the unknown dynamics. Combining prescribed-performance control and time-domain mapping techniques, a fuzzy adaptive prescribed-time performance constraint containment control algorithm is proposed, which can demonstrate that all signals in controlled system are bound within prescribed-time, and followers can converge to the convex hull created by the leaders by using Lyapunov stability theory. Furthermore, the virtual errors and local containment error asymptotically converge to a preset region. Finally, the simulations are provided to illustrate the effectiveness and feasibility of the developed control method. Note to Practitioners—This article investigates a fuzzy adaptive prescribed-time containment control issue for nonlinear multi-agent systems (MASs). The time-domain mapping technique can be used to convert the prescribed time control issue of the original system in finite horizon into the asymptotic tracking control issue of the corresponding controlled system in infinite horizon. In contrast to previous similar works, this article proposes a prescribed-time control algorithm, where the convergence time can be set offline and it does not rely on any design parameters. Moreover, this study can guarantee containment and virtual errors converge to the prescribed region by using the prescribed performance function and the barrier Lyapunov function.