Distributed multi-step subgradient projection algorithm with adaptive event-triggering protocols: a framework of multiagent systems

Wenjing An, Peifeng Zhao, Hongjian Liu and Jun Hu

International Journal of Systems Science, 2022, vol. 53, issue 13, 2758-2772

Abstract: This paper discusses a convex optimisation problem with a common set of constraints in the framework of multi-agent systems. Each agent only exchanges information with its neighbours and collaboratively searches for the optimal solution of the global function. To this addressed problem, a distributed multi-step subgradient projection algorithm is developed, where an adaptive event-triggering protocol is designed to govern the information exchange. It is disclosed that the state of each agent representing the estimate of the optimal solution asymptotically converges to one of the optimal solutions under suitably chosen stepsizes and momentum parameters. Simulation results verify that the proposed algorithm has better convergence performance than the standard event-triggered subgradient projection algorithm. In addition, the communication frequency between agents can be effectively reduced to save communication resource consumption.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2022.2063967 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:53:y:2022:i:13:p:2758-2772

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2022.2063967

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().