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Edge-Based Event-Triggered Consensus Control for Multi-Agent Systems Under False Data Injection Attacks

  • Hangwu He
  • , Yang Liu*
  • , Rong Sun
  • *Corresponding author for this work
  • Beihang University
  • Beijing Institute of Astronautical Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This article focuses on the security control for general linear multi-agent systems (MASs) against false data injection attacks (FDIAs). A dynamic edge-based event-triggered mechanism is proposed, which reduces bandwidth consumption, saves communication resources and avoids continuous communication between agents. First, a neighbor information estimator is designed for each agent to match the asynchronous information generated by the dynamic edge-based event-triggered mechanism. A state estimator is designed to monitor and quantify the impact of FDIAs, while a feedback compensation mechanism is implemented in the control loop to mitigate attack-induced disturbances. Further, it is proved that the consensus control can be realized without Zeno behavior. Finally, a numerical simulation example is used to prove the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of 2025 Chinese Intelligent Systems Conference - Volume I
EditorsYingmin Jia, Yang Liu, Weicun Zhang, Yongling Fu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages505-513
Number of pages9
ISBN (Print)9789819568123
DOIs
StatePublished - 2026
Event21st Chinese Intelligent Systems Conference, CISC 2025 - Beijing, China
Duration: 25 Oct 2025 → 26 Oct 2025

Publication series

NameLecture Notes in Electrical Engineering
Volume1545 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference21st Chinese Intelligent Systems Conference, CISC 2025
Country/TerritoryChina
CityBeijing
Period25/10/25 → 26/10/25

Keywords

  • False data injection attack (FDIA)
  • consensus control
  • dynamic event-triggered mechanism
  • edge-based event-triggered
  • multi-agent system (MAS)

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