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Event-Triggered Distributed Aggregative Optimization of Heterogeneous High-Order Systems

  • Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article investigates the event-triggered distributed aggregative optimization problem for heterogeneous higher-order integrator systems. A novel distributed event-triggered algorithm ETDAO is proposed that integrates the dynamic average consensus technique with the gradient descent method to efficiently solve the aggregative optimization problem. Under the event-triggered scheme, continuous communication between agents is avoided. The exponential convergence of the algorithm is established through rigorous stability analysis. Finally, the efficiency of the algorithm is verified by numerical simulations.

Original languageEnglish
Title of host publicationProceedings of 2025 9th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Control Technologies
EditorsQing Wang, Xiwang Dong, Peng Song
PublisherSpringer Science and Business Media Deutschland GmbH
Pages413-424
Number of pages12
ISBN (Print)9789819584345
DOIs
StatePublished - 2026
Event9th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2025 - Shanghai, China
Duration: 31 Oct 20253 Nov 2025

Publication series

NameLecture Notes in Electrical Engineering
Volume1604 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference9th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2025
Country/TerritoryChina
CityShanghai
Period31/10/253/11/25

Keywords

  • Distributed aggregative optimization
  • Event-triggered strategy
  • Heterogeneous higher-order dynamics

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