A Bi-event-Triggered Multi-agent System for Distributed Optimization

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Scopus Citations
View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1074-1084
Number of pages11
Journal / PublicationIEEE Transactions on Network Science and Engineering
Volume10
Issue number2
Online published14 Dec 2022
Publication statusPublished - Mar 2023

Abstract

In this paper, we propose a continuous-time multiagent system via event-triggered communication among agents for distributed optimization. We develop a dynamic bi-event triggering rule based on both local decision variables and auxiliary variables to reduce communication costs. We design a bi-event triggered multi-agent system based on the Karush-Kuhn-Tucker conditions, which allows initializing auxiliary variables arbitrarily and hence relaxing the existing zero-sum condition on the initial values of auxiliary variables. We prove the exponential convergence of the multi-agent system to the optimal solution and derive a lower bound of the convergence rate. In addition, we prove the capability of the triggering rule for precluding Zeno behavior. We also elaborate on two numerical examples to illustrate the effectiveness and characteristics of the theoretical results.

Research Area(s)

  • Bandwidth, Behavioral sciences, Convergence, Distributed optimization, Eigenvalues and eigenfunctions, event-triggered communication, Linear programming, multi-agent systems, Optimization, Protocols, Zeno behavior

Citation Format(s)

A Bi-event-Triggered Multi-agent System for Distributed Optimization. / Huang, Banghua; Liu, Yang; Xia, Zicong et al.
In: IEEE Transactions on Network Science and Engineering, Vol. 10, No. 2, 03.2023, p. 1074-1084.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review