Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs

Wenyan Hu; Quanyi Liang

doi:10.1109/CCDC65474.2025.11091153

Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs

Wenyan Hu
, Quanyi Liang^*

^*Corresponding author for this work

School of Mathematical Sciences

Beihang University

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

Abstract

This paper investigates the consensus control problem in leaderless multi-agent systems (MASs) with unknown nonlinear dynamics. To address this challenge, we apply a data-driven model-free adaptive control (MFAC) approach. Specifically, by the dynamic linearization and pseudo-partial derivatives (PPD) approximation, we can solely use input-output (I/O) data to design consensus algorithm. Under this algorithm, consensus is achieved when the parameter ? is smaller than reciprocal of greatest diagonal entry of the Laplacian matrix L. Furthermore, simulation results for both homogeneous and heterogeneous MAS validate the effectiveness of the approach.

Original language	English
Title of host publication	Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4557-4562
Number of pages	6
ISBN (Electronic)	9798331510565
DOIs	https://doi.org/10.1109/CCDC65474.2025.11091153
State	Published - 2025
Event	37th Chinese Control and Decision Conference, CCDC 2025 - Xiamen, China Duration: 16 May 2025 → 19 May 2025

Publication series

Name	Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025

Conference

Conference	37th Chinese Control and Decision Conference, CCDC 2025
Country/Territory	China
City	Xiamen
Period	16/05/25 → 19/05/25

Keywords

Model-free adaptive control (MFAC)
consensus control
data-driven control
dynamic linearization
leaderless multi-agent systems

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10.1109/CCDC65474.2025.11091153

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Hu, W., & Liang, Q. (2025). Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs. In Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025 (pp. 4557-4562). (Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC65474.2025.11091153

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title = "Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs",

abstract = "This paper investigates the consensus control problem in leaderless multi-agent systems (MASs) with unknown nonlinear dynamics. To address this challenge, we apply a data-driven model-free adaptive control (MFAC) approach. Specifically, by the dynamic linearization and pseudo-partial derivatives (PPD) approximation, we can solely use input-output (I/O) data to design consensus algorithm. Under this algorithm, consensus is achieved when the parameter ? is smaller than reciprocal of greatest diagonal entry of the Laplacian matrix L. Furthermore, simulation results for both homogeneous and heterogeneous MAS validate the effectiveness of the approach.",

keywords = "Model-free adaptive control (MFAC), consensus control, data-driven control, dynamic linearization, leaderless multi-agent systems",

author = "Wenyan Hu and Quanyi Liang",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 37th Chinese Control and Decision Conference, CCDC 2025 ; Conference date: 16-05-2025 Through 19-05-2025",

year = "2025",

doi = "10.1109/CCDC65474.2025.11091153",

language = "英语",

series = "Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4557--4562",

booktitle = "Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025",

address = "美国",

}

Hu, W & Liang, Q 2025, Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs. in Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025. Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025, Institute of Electrical and Electronics Engineers Inc., pp. 4557-4562, 37th Chinese Control and Decision Conference, CCDC 2025, Xiamen, China, 16/05/25. https://doi.org/10.1109/CCDC65474.2025.11091153

Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs. / Hu, Wenyan; Liang, Quanyi.
Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025. Institute of Electrical and Electronics Engineers Inc., 2025. p. 4557-4562 (Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025).

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

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T1 - Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs

AU - Hu, Wenyan

AU - Liang, Quanyi

PY - 2025

Y1 - 2025

N2 - This paper investigates the consensus control problem in leaderless multi-agent systems (MASs) with unknown nonlinear dynamics. To address this challenge, we apply a data-driven model-free adaptive control (MFAC) approach. Specifically, by the dynamic linearization and pseudo-partial derivatives (PPD) approximation, we can solely use input-output (I/O) data to design consensus algorithm. Under this algorithm, consensus is achieved when the parameter ? is smaller than reciprocal of greatest diagonal entry of the Laplacian matrix L. Furthermore, simulation results for both homogeneous and heterogeneous MAS validate the effectiveness of the approach.

AB - This paper investigates the consensus control problem in leaderless multi-agent systems (MASs) with unknown nonlinear dynamics. To address this challenge, we apply a data-driven model-free adaptive control (MFAC) approach. Specifically, by the dynamic linearization and pseudo-partial derivatives (PPD) approximation, we can solely use input-output (I/O) data to design consensus algorithm. Under this algorithm, consensus is achieved when the parameter ? is smaller than reciprocal of greatest diagonal entry of the Laplacian matrix L. Furthermore, simulation results for both homogeneous and heterogeneous MAS validate the effectiveness of the approach.

KW - Model-free adaptive control (MFAC)

KW - consensus control

KW - data-driven control

KW - dynamic linearization

KW - leaderless multi-agent systems

UR - https://www.scopus.com/pages/publications/105013969264

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DO - 10.1109/CCDC65474.2025.11091153

M3 - 会议稿件

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T3 - Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025

SP - 4557

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BT - Proceedings of the 37th Chinese Control and Decision Conference, CCDC 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 37th Chinese Control and Decision Conference, CCDC 2025

Y2 - 16 May 2025 through 19 May 2025

ER -

Data-Driven Model-Free Adaptive Control for Consensus of Leaderless MASs

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Keywords

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