Distributed finite-time optimisation for multi-agent systems via event-triggered aperiodically intermittent communication

Abstract

In this paper, the finite-time distributed optimisation problem for multi-agent systems (MASs) is investigated by proposing a kind of new event-based aperiodically intermittent communication strategy. Firstly, the distributed optimisation problem with the sum of local objective functions is considered. A novel finite-time event-triggered intermittent control protocol is proposed over undirected networks, and some sufficient conditions are obtained to ensure the finite-time consensus of MASs and the asymptotical solvability of the optimisation problem. Secondly, a more general distributed optimisation problem, in which the optimisation objective is the convex combination of local objective functions, is considered and we also prove that MASs can achieve consensus in finite-time and asymptotically reach the optimal solution under the proposed protocol over directed networks. Finally, two numerical examples are given to demonstrate the effectiveness of the theoretical results.

Keywords:

• Multi-agent systems (MASs)
• distributed optimisation
• event-triggered
• finite-time
• aperiodically intermittent communication

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 62003289], in part by the China Postdoctoral Science Foundation [grant number 2021M690400], in part by the Tianshan Youth Program [grant number 2018Q068], and in part by the Tianshan Innovation Team Program [grant number 2020D14017].

Notes on contributors

Feiyang Yang

Feiyang Yang was born in Zhejiang, China, in 1997. She received the B.S. degree in mathematics and applied mathematics from Zhejiang Gongshang University, Zhejiang, in 2019. She is currently pursuing the M.S. degree in mathematics from Xinjiang University, Xinjiang, China. Her current research interests include consensus and distributed optimisation problems in multi-agent systems.

Zhiyong Yu

Zhiyong Yu was born in Gansu, China, in 1991. He received the B.S. degree in mathematics and applied mathematics from Tianshui Normal University, Gansu, in 2012, the M.S. degree in mathematics and the Ph.D. degree in operations research and control theory from the College of Mathematics and System Sciences, Xinjiang University, Xinjiang, China, in 2015 and 2018, respectively. His current research interests include nonlinear dynamics and control, multi-agent systems and distributed optimisation.

Haijun Jiang

Haijun Jiang was born in Hunan, China, in 1968. He received the B.S. degree from the Department of Mathematics, Yili Teacher College, Xinjiang, China, in 1990, the M.S. degree from the Department of Mathematics, East China Normal University, Shanghai, China, in 1994, and the Ph.D. degree from the College of Mathematics and System Sciences, Xinjiang University, Xinjiang, in 2004. He was a Post-Doctoral Research Fellow with the Department of Southeast University, Nanjing, China, from 2004 to 2006. He is a Professor and a Doctoral Advisor of Mathematics and System Sciences with Xinjiang University. His current research interests include nonlinear dynamics, delay differential equations, dynamics of neural networks, and mathematical biology.