A modified distributed optimization method for both continuous-time and discrete-time multi-agent systems

被引：13
|
作者：
Wang, Dong [1 ]
Wang, Wei [1 ]
Liu, Yurong [1 ,2 ,3 ]
Alsaadi, Fuad E. [3 ]
机构：
[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[2] Yangzhou Univ, Dept Math, Yangzhou 225002, Jiangsu, Peoples R China
[3] King Abdulaziz Univ, Fac Engn, CSN Res Grp, Jeddah 21589, Saudi Arabia
来源：
NEUROCOMPUTING | 2018年 / 275卷
基金：
中国国家自然科学基金;
关键词：
Multi-agent systems; Cost function; Convex optimization; Convergence rate; Lyapunov method; TRACKING CONTROL; CONSTRAINED OPTIMIZATION; SWITCHING TOPOLOGIES; CONTAINMENT CONTROL; CONSENSUS; LEADER; COMMUNICATION; ALGORITHM; NETWORKS;
D O I：
10.1016/j.neucom.2017.09.016
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper discusses the distributed optimization problem for the continuous-time and discrete-time multi-agent systems. For such a problem, each agent possesses a local convex cost function only known by itself and all the agents converge to the optimizer of the sum of the local cost function through estimating the optimal states of the local cost function and exchanging states information between agents. Sufficient conditions for convergence to the optimizer of the continuous-time and discrete-time algorithms are provided by making use of the Lyapunov method. We also obtain the least convergence rate for the modified algorithm. Moreover, numerical simulations are supplied to testify the results we present. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码：725 / 732
页数：8
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