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  Resilient Event-Triggered Control Strategies for Second-Order Consensus

Xu, W., Kurths, J., Wen, G., Yu, X. (2022): Resilient Event-Triggered Control Strategies for Second-Order Consensus. - IEEE Transactions on Automatic Control, 67, 8, 4226-4233.
https://doi.org/10.1109/TAC.2021.3122382

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 Urheber:
Xu, Wenying1, Autor
Kurths, Jürgen2, Autor              
Wen, Guanghui 1, Autor
Yu, Xinghuo 1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: This article investigates the second-order consensus issue for multiagent systems subject to both limited communication resources and replay attacks. First, an asynchronous dynamic edge event-triggered (DEET) communication scheme is developed to reduce the utilization of network resources in the absence of attacks. Then, we further consider the case of replay attacks launched by multiple adversaries, under which the transmitted information is maliciously replaced by a previous unnecessary message. To overcome the impact caused by replay attacks, a modified DEET scheme and an effective attack-resilient consensus protocol are well constructed, both of which successfully guarantee second-order consensus in the presence of replay attacks. In addition, internal dynamic variables are utilized in the proposed DEET schemes such that the triggering time sequence does not exhibit Zeno behavior. Finally, one numerical example is provided to illustrate our theoretical analysis.

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Sprache(n): eng - Englisch
 Datum: 2021-10-262022-08-01
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1109/TAC.2021.3122382
Research topic keyword: Complex Networks
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
Working Group: Network- and machine-learning-based prediction of extreme events
MDB-ID: No data to archive
 Art des Abschluß: -

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Titel: IEEE Transactions on Automatic Control
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 67 (8) Artikelnummer: - Start- / Endseite: 4226 - 4233 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/ieee-transactions-automatic-control
Publisher: Institute of Electrical and Electronics Engineers (IEEE)