Suboptimal Linear Distributed Control-Estimation Synthesis for Stochastic Multi-Agent System

被引:0
|
作者
Lee, Hojin [1 ]
Kwon, Cheolhyeon [1 ]
机构
[1] Ulsan Natl Inst Sci & Technol, Dept Mech Engn, Ulsan 44919, South Korea
来源
IEEE ACCESS | 2024年 / 12卷
基金
新加坡国家研究基金会;
关键词
Artificial neural networks; Decentralized control; Vectors; Multi-agent systems; Estimation; Costs; Network topology; Distributed control; optimal control; multi-agent systems; cooperative control; CONSENSUS; DESIGN; OBSERVABILITY; INVARIANCE; GRAPHS;
D O I
10.1109/ACCESS.2024.3449874
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers the distributed cooperative control problem for a linear stochastic multi-agent system (MAS). The optimal cooperative control design for each agent is challenging due to the limited neighboring information, contingent upon the MAS network topology. A synthesized distributed control-estimation framework is proposed to address the computationally tractable suboptimal solution. In particular, a distributed estimator extends MAS information beyond neighboring agents, allowing interactions with non-neighboring agents. The proposed control-estimation law is theoretically verified and further validated using numerical simulations.
引用
收藏
页码:119577 / 119588
页数:12
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