Distributed Optimization for Multi-Agent Systems With Time Delay

被引：11
|
作者：
Yang, Zhengquan [1 ]
Pan, Xiaofang [1 ]
Zhang, Qing [1 ]
Chen, Zengqiang [2 ]
机构：
[1] Civil Aviat Univ China, Coll Sci, Tianjin 300300, Peoples R China
[2] Nankai Univ China, Coll Artificial Intelligence, Tianjin 300350, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Distributed optimization; multi-agent systems; time delay; Lyapunov-Krasovskii function; zero-gradient-sum algorithm; CONVEX-OPTIMIZATION; SUBGRADIENT METHODS; CONSENSUS; GRADIENT; ALGORITHMS; NETWORKS;
D O I：
10.1109/ACCESS.2020.3007731
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The distributed optimization for multi-agent systems with time delay and first-order is investigated in this paper. The objective of the distributed optimization is to optimize the objective function composed of the sum of local objective functions, which can only be known by its corresponding agents. Firstly, a distributed algorithm for time-delay systems is proposed to solve the optimization problem that each agent depends on its own state and the state between itself and its neighbors. Secondly, Lyapunov-Krasovskii function is used to prove that the states of each agent can be asymptotically the same, and the states are optimal. Finally, an example is given for illustrating the analytical results and a comparison is also gave to illustrate the differences between the algorithm of this paper and other results.
引用
收藏
页码：123019 / 123025
页数：7
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