基于性能的多智能体系统分布式控制:一种双阶段方法

Performance-Based Distributed Control of Multiagent Systems: A Dual Phase Approach

IEEE Transactions on Cybernetics · 2023
被引 12
ABS 3

中文导读

针对有向拓扑下具有未知时变增益的不确定非线性严格反馈系统,提出一种双阶段性能保证的分布式跟踪控制方法,使输出跟踪误差收敛到任意预设残差集并具有任意预设收敛速度。

Abstract

In this article, we investigate the distributed tracking control problem for networked uncertain nonlinear strict-feedback systems with unknown time-varying gains under a directed interaction topology. A dual phase performance-guaranteed approach is established. In the first phase, a fully distributed robust filter is constructed for each agent to estimate the desired trajectory with prescribed performance such that the control directions of all agents are allowed to be nonidentical. In the second phase, by establishing a novel lemma regarding Nussbaum function, a new adaptive control protocol is developed for each agent based on backstepping technique, which not only steers the output to track the corresponding estimated signal asymptotically with arbitrarily prescribed transient response but also extends the application scope of the proposed control scheme largely since the unknown control gains are allowed to be time-varying and even state-dependent. In such a way, the underlying problem is tackled with the output tracking error converging into an arbitrarily preassigned residual set exhibiting an arbitrarily predefined convergence rate. Besides, all the internal signals are ensured to be semi-globally ultimately uniformly bounded (SGUUB). Finally, two examples are provided to illustrate the effectiveness of the co-designed scheme.

多智能体系统分布式控制自适应控制非线性系统