Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms

Na Wang; Yang Liu; Xinxi Lu

doi:10.1007/978-981-99-6886-2_16

Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms

Na Wang
, Yang Liu^*
, Xinxi Lu

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

CAS - Institute of Automation
Beihang University

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

1 Scopus citations

Abstract

In this paper, The resilient consensus problem of heterogeneous multi-agent systems (MASs) composed of first and second order agents under malicious attacks is studied. To achieve consensus, an event-triggered mean subsequence reduced (E-MSR) control protocol is designed for first-order and second-order agents, respectively. Specifically, in the input generation of an agent based on local information, some neighbor nodes’ extreme values will be deleted, which could be malicious. Under the event-triggered strategy, an agent sends its information to the neighbor only when its own triggering condition is met, which effectively reduces the communication burden. Simulations show the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III
Editors	Yingmin Jia, Weicun Zhang, Yongling Fu, Jiqiang Wang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	173-187
Number of pages	15
ISBN (Print)	9789819968855
DOIs	https://doi.org/10.1007/978-981-99-6886-2_16
State	Published - 2023
Event	19th Chinese Intelligent Systems Conference, CISC 2023 - Ningbo, China Duration: 14 Oct 2023 → 15 Oct 2023

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1091 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	19th Chinese Intelligent Systems Conference, CISC 2023
Country/Territory	China
City	Ningbo
Period	14/10/23 → 15/10/23

Keywords

Event-triggered control
Malicious attacks
Multi-agent systems (MASs)
Resilient consensus

Access to Document

10.1007/978-981-99-6886-2_16

Cite this

Wang, N., Liu, Y., & Lu, X. (2023). Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms. In Y. Jia, W. Zhang, Y. Fu, & J. Wang (Eds.), Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III (pp. 173-187). (Lecture Notes in Electrical Engineering; Vol. 1091 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-6886-2_16

Wang, Na ; Liu, Yang ; Lu, Xinxi. / Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms. Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III. editor / Yingmin Jia ; Weicun Zhang ; Yongling Fu ; Jiqiang Wang. Springer Science and Business Media Deutschland GmbH, 2023. pp. 173-187 (Lecture Notes in Electrical Engineering).

@inproceedings{87ed7c7efdd74c2e89546cfa73a9ea9e,

title = "Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms",

abstract = "In this paper, The resilient consensus problem of heterogeneous multi-agent systems (MASs) composed of first and second order agents under malicious attacks is studied. To achieve consensus, an event-triggered mean subsequence reduced (E-MSR) control protocol is designed for first-order and second-order agents, respectively. Specifically, in the input generation of an agent based on local information, some neighbor nodes{\textquoteright} extreme values will be deleted, which could be malicious. Under the event-triggered strategy, an agent sends its information to the neighbor only when its own triggering condition is met, which effectively reduces the communication burden. Simulations show the effectiveness of the proposed method.",

keywords = "Event-triggered control, Malicious attacks, Multi-agent systems (MASs), Resilient consensus",

author = "Na Wang and Yang Liu and Xinxi Lu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 19th Chinese Intelligent Systems Conference, CISC 2023 ; Conference date: 14-10-2023 Through 15-10-2023",

year = "2023",

doi = "10.1007/978-981-99-6886-2\_16",

language = "英语",

isbn = "9789819968855",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

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booktitle = "Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III",

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Wang, N, Liu, Y & Lu, X 2023, Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms. in Y Jia, W Zhang, Y Fu & J Wang (eds), Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III. Lecture Notes in Electrical Engineering, vol. 1091 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 173-187, 19th Chinese Intelligent Systems Conference, CISC 2023, Ningbo, China, 14/10/23. https://doi.org/10.1007/978-981-99-6886-2_16

Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms. / Wang, Na; Liu, Yang; Lu, Xinxi.
Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III. ed. / Yingmin Jia; Weicun Zhang; Yongling Fu; Jiqiang Wang. Springer Science and Business Media Deutschland GmbH, 2023. p. 173-187 (Lecture Notes in Electrical Engineering; Vol. 1091 LNEE).

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

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AB - In this paper, The resilient consensus problem of heterogeneous multi-agent systems (MASs) composed of first and second order agents under malicious attacks is studied. To achieve consensus, an event-triggered mean subsequence reduced (E-MSR) control protocol is designed for first-order and second-order agents, respectively. Specifically, in the input generation of an agent based on local information, some neighbor nodes’ extreme values will be deleted, which could be malicious. Under the event-triggered strategy, an agent sends its information to the neighbor only when its own triggering condition is met, which effectively reduces the communication burden. Simulations show the effectiveness of the proposed method.

KW - Event-triggered control

KW - Malicious attacks

KW - Multi-agent systems (MASs)

KW - Resilient consensus

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Wang N, Liu Y, Lu X. Resilient Consensus of Heterogeneous Multi-agent Systems Based on E-MSR Algorithms. In Jia Y, Zhang W, Fu Y, Wang J, editors, Proceedings of 2023 Chinese Intelligent Systems Conference - Volume III. Springer Science and Business Media Deutschland GmbH. 2023. p. 173-187. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-99-6886-2_16