控制理论(社会学)
控制器(灌溉)
计算机科学
弹道
积分器
多智能体系统
Lyapunov稳定性
观察员(物理)
李雅普诺夫函数
内部模型
指数稳定性
自适应控制
图层(电子)
控制工程
控制(管理)
工程类
带宽(计算)
人工智能
非线性系统
物理
化学
有机化学
天文
生物
量子力学
计算机网络
农学
出处
期刊:IEEE transactions on systems, man, and cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2022-06-01
卷期号:52 (6): 3556-3567
被引量:36
标识
DOI:10.1109/tsmc.2021.3071307
摘要
This article investigates a distributed optimization problem of double-integrator multiagent systems with unmatched constant disturbances. Instead of involving an internal model or a disturbance observer to deal with the disturbances as in existing works, a two-layer control framework is presented based on state-integral feedback control (SIFC) and adaptive control techniques. The upper layer uses a virtual system to generate a global optimal consensus trajectory which is shared by the agents via a communication network. The lower layer includes an SIFC controller to guarantee asymptotic tracking of the given trajectory. Also in this layer, a model reference adaptive controller is introduced to enhance the dynamic tracking performance of the SIFC controller. This framework enables distributed optimization with time-triggered communication and mild requirements on the team objective. The method yields an interesting co-design algorithm of the control parameters and the communication intervals, which is proved to be convergent using Lyapunov stability theory. The effectiveness and advantages of the method are illustrated by numerical simulations.
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