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Data-Driven Optimal Output Tracking Control of Heterogeneous Multiagent Systems Under DoS Attacks

  • Yong Sheng Ma
  • , Jian Sun*
  • , Yong Xu*
  • *Corresponding author for this work
  • Beijing Institute of Technology

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

Abstract

This paper addresses the output tracking problem for heterogeneous multiagent systems (MASs) with unknown dynamics under denial-of-service (DoS) attacks. We propose a resilient distributed observer incorporating an attack compensator to estimate the leader’s state while mitigating the negative impact caused by network attacks. Additionally, we develop a data-driven learning algorithm circumventing the need for system dynamics knowledge. Compared with existing methods, the framework offers two key advantages: 1)the designed resilient distributed observer can dynamically reconstruct the system data lost during DoS attacks; 2)the developed learning algorithm eliminates the dependence of historical storage data. Finally, a numerical simulation is given to exemplify the effectiveness and superiority of the theoretical method.

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
Pages24-34
Number of pages11
ISBN (Print)9789819584345
DOIs
Publication statusPublished - 2026
Externally publishedYes
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

  • data-driven
  • DoS attacks
  • heterogeneous MASs

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