Distributed optimization problem for double-integrator systems with the presence of the exogenous disturbances

被引:29
|
作者
Ngoc-Tu Tran [1 ,2 ]
Wang, Yan-Wu [1 ,2 ,3 ]
Yang, Wu [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, Minist Educ, Key Lab Image Proc & Intelligent Control, Wuhan, Hubei, Peoples R China
[3] China Three Gorges Univ, Hubei Prov Collaborat Innovat Ctr New Energy Micr, Yichang, Peoples R China
基金
中国国家自然科学基金;
关键词
Second-order multi-agent systems; Distributed optimization; Gradient-based algorithm; External disturbance; Internal model principle; CONVEX-OPTIMIZATION; MULTIAGENT SYSTEMS; ALGORITHMS; CONSENSUS;
D O I
10.1016/j.neucom.2017.07.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The aim of this paper is to study the distributed optimization problem for continuous-time multi-agent systems with the existence and the interference of external disturbance, therein each agent is described as double-integrator dynamic. To reject the exogenous disturbance, the distributed algorithm is proposed for each agent based on the internal model principle. The proposed algorithm only utilizes the position information of each agent from its neighbors subject to the undirected graph, which can reduce communication costs and energy consumptions in applications. Moreover, the algorithm only needs the cost functions of the agent itself, which can greatly protect the privacy of other agents. The optimal solution of the problem is thus obtained with the design of Lyapunov function and the help of convex analysis, LaSallel's Invariance Principle. Finally, two numerical simulation examples and the comparison of proposed algorithm with other previous research are presented to illustrate the persuasive effectiveness of the theoretical result. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:386 / 395
页数:10
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