Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems

Xiaoxu Lv; Yuqing Hao; Tao Xu; Zhisheng Duan

doi:10.1109/DOCS55193.2022.9967735

Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems

Xiaoxu Lv
, Yuqing Hao
, Tao Xu
, Zhisheng Duan^*

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

Abstract

This paper investigates the cooperative adaptive environment identification and the force control problems for heterogeneous Euler-Lagrange systems. A distributed adaptive control law is designed to identify the external environment, and the parameter convergence and the parameter consensus are achieved. The cooperative control law is easier to satisfy the persistently exciting condition. Using the containment control approach, a distributed control law is proposed to guarantee that the trajectory error and the parameter errors are uniformly ultimately bounded. The effectiveness of the proposed adaptive control laws is demonstrated by some simulation examples.

Original language	English
Title of host publication	2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665459822
ISBN (Print)	9781665459839
DOIs	https://doi.org/10.1109/DOCS55193.2022.9967735
Publication status	Published - 5 Dec 2022
Externally published	Yes
Event	4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022 - Chengdu, China Duration: 28 Oct 2022 → 30 Oct 2022

Publication series

Name	2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022

Conference

Conference	4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022
Country/Territory	China
City	Chengdu
Period	28/10/22 → 30/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

heterogeneous multi-agent systems
parameter consensus
distributed control
Euler-Lagrange systems

Access to Document

10.1109/DOCS55193.2022.9967735

Cite this

Lv, X., Hao, Y., Xu, T., & Duan, Z. (2022). Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems. In 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022 Article 9967735 (2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DOCS55193.2022.9967735

Lv, Xiaoxu ; Hao, Yuqing ; Xu, Tao et al. / Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems. 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022).

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title = "Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems",

abstract = "This paper investigates the cooperative adaptive environment identification and the force control problems for heterogeneous Euler-Lagrange systems. A distributed adaptive control law is designed to identify the external environment, and the parameter convergence and the parameter consensus are achieved. The cooperative control law is easier to satisfy the persistently exciting condition. Using the containment control approach, a distributed control law is proposed to guarantee that the trajectory error and the parameter errors are uniformly ultimately bounded. The effectiveness of the proposed adaptive control laws is demonstrated by some simulation examples.",

keywords = "heterogeneous multi-agent systems, parameter consensus, distributed control, Euler-Lagrange systems",

author = "Xiaoxu Lv and Yuqing Hao and Tao Xu and Zhisheng Duan",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022 ; Conference date: 28-10-2022 Through 30-10-2022",

year = "2022",

month = dec,

day = "5",

doi = "10.1109/DOCS55193.2022.9967735",

language = "English",

isbn = "9781665459839",

series = "2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022",

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Lv, X, Hao, Y, Xu, T & Duan, Z 2022, Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems. in 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022., 9967735, 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022, Institute of Electrical and Electronics Engineers Inc., 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022, Chengdu, China, 28/10/22. https://doi.org/10.1109/DOCS55193.2022.9967735

Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems. / Lv, Xiaoxu; Hao, Yuqing; Xu, Tao et al.
2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 9967735 (2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems

AU - Lv, Xiaoxu

AU - Hao, Yuqing

AU - Xu, Tao

AU - Duan, Zhisheng

PY - 2022/12/5

Y1 - 2022/12/5

N2 - This paper investigates the cooperative adaptive environment identification and the force control problems for heterogeneous Euler-Lagrange systems. A distributed adaptive control law is designed to identify the external environment, and the parameter convergence and the parameter consensus are achieved. The cooperative control law is easier to satisfy the persistently exciting condition. Using the containment control approach, a distributed control law is proposed to guarantee that the trajectory error and the parameter errors are uniformly ultimately bounded. The effectiveness of the proposed adaptive control laws is demonstrated by some simulation examples.

AB - This paper investigates the cooperative adaptive environment identification and the force control problems for heterogeneous Euler-Lagrange systems. A distributed adaptive control law is designed to identify the external environment, and the parameter convergence and the parameter consensus are achieved. The cooperative control law is easier to satisfy the persistently exciting condition. Using the containment control approach, a distributed control law is proposed to guarantee that the trajectory error and the parameter errors are uniformly ultimately bounded. The effectiveness of the proposed adaptive control laws is demonstrated by some simulation examples.

KW - heterogeneous multi-agent systems

KW - parameter consensus

KW - distributed control

KW - Euler-Lagrange systems

UR - https://www.scopus.com/pages/publications/85144624018

U2 - 10.1109/DOCS55193.2022.9967735

DO - 10.1109/DOCS55193.2022.9967735

M3 - Conference Paper published in a book

AN - SCOPUS:85144624018

SN - 9781665459839

T3 - 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022

BT - 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022

Y2 - 28 October 2022 through 30 October 2022

ER -

Lv X, Hao Y, Xu T, Duan Z. Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems. In 2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. 9967735. (2022 4th International Conference on Data-Driven Optimization of Complex Systems, DOCS 2022). doi: 10.1109/DOCS55193.2022.9967735

Cooperative Adaptive Identification and Force Control for Networked Euler-Lagrange Systems

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Keywords

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