期刊
INTERNATIONAL JOURNAL OF CONTROL
卷 95, 期 5, 页码 1363-1370出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207179.2020.1854866
关键词
Distributed convex optimisation; event-triggered; zero-gradient-sum algorithm; minimum inter-event time
资金
- National Natural Science Foundation of China [61673344, 61873235, 61976215]
This study investigates the distributed convex optimisation problem of a multi-agent system over an undirected network. Two zero-gradient-sum algorithms with state-based dynamic event-triggered mechanism are designed to address the problem.
In this study, we investigate the distributed convex optimisation problem of the multi-agent system over an undirected network, in which the global objective function is the sum of all the local cost functions and the local cost function of each agent is only known by itself. In order to save the computation and communication resources, the above optimisation problem is addressed by designing two zero-gradient-sum algorithms with state-based dynamic event-triggered mechanism, where the information communication only occurs at some discrete triggering time instants. The Zeno behaviour of the above event-triggered control scheme is excluded by the existence of the positive minimum inter-event time (MIET). The convergence is proved based on the Lyapunov method. Finally, we illustrate and evaluate the effectiveness of the proposed event-triggered algorithms through numerical experiments on simulated.
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