Sampled-data based distributed convex optimization with event-triggered communication

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• 作者：Jiayun Liu ; Weisheng Chen ; Hao Dai
• 关键词：Distributed convex optimization ; event ; triggered scheme ; multi ; agent systems ; sampled ; data control ; zero ; gradient ; sum (ZGS) algorithm
• 刊名：International Journal of Control, Automation and Systems
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：14
• 期：6
• 页码：1421-1429
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Control, Robotics, Mechatronics;
• 出版者：Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
• ISSN：2005-4092
• 卷排序：14

文摘

This paper studies the distributed convex optimization problem for multi-agent systems over undirected and connected networks. Motivated by practical considerations, we propose a new distributed optimization algorithm with event-triggered communication. The proposed event detection is decentralized, sampled-data and not requires periodic communications among agents to calculate the threshold. Based on Lyapunov approaches, we show that the proposed algorithm is asymptotically converge to the unknown optimizer if the design parameters are chosen properly. We also give an upper bound on the convergence rate. Finally, we illustrate the effectiveness of the proposed algorithm by a numerical simulation.