Distributed LQR design for multi-agent formations

Huang Huang; Changbin Yu; Qinghe Wu

doi:10.1109/CDC.2010.5716988

Distributed LQR design for multi-agent formations

Huang Huang, Changbin Yu^*, Qinghe Wu

^*Corresponding author for this work

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

9 Citations (Scopus)

Abstract

In this paper we study the optimal formation control of multiple agents whose communication topology as well as the interaction parameters is tunable upon a cost function consisting of both control energy and formation indicator. The determination of interaction parameters is accompanied by the design of linear quadratic regulation(LQR) controllers which are distributed ones. When extending the results to systems with multiple agents, it is sufficient that the underlying graph of the cost matrix has an unrooted tree or the directed underlying graph is persistent. Numerical examples are provided to illustrate the effectiveness of the method.

Original language	English
Title of host publication	2010 49th IEEE Conference on Decision and Control, CDC 2010
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4535-4540
Number of pages	6
ISBN (Print)	9781424477456
DOIs	https://doi.org/10.1109/CDC.2010.5716988
Publication status	Published - 2010
Event	49th IEEE Conference on Decision and Control, CDC 2010 - Atlanta, United States Duration: 15 Dec 2010 → 17 Dec 2010

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	49th IEEE Conference on Decision and Control, CDC 2010
Country/Territory	United States
City	Atlanta
Period	15/12/10 → 17/12/10

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10.1109/CDC.2010.5716988

Cite this

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title = "Distributed LQR design for multi-agent formations",

abstract = "In this paper we study the optimal formation control of multiple agents whose communication topology as well as the interaction parameters is tunable upon a cost function consisting of both control energy and formation indicator. The determination of interaction parameters is accompanied by the design of linear quadratic regulation(LQR) controllers which are distributed ones. When extending the results to systems with multiple agents, it is sufficient that the underlying graph of the cost matrix has an unrooted tree or the directed underlying graph is persistent. Numerical examples are provided to illustrate the effectiveness of the method.",

author = "Huang Huang and Changbin Yu and Qinghe Wu",

year = "2010",

doi = "10.1109/CDC.2010.5716988",

language = "English",

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series = "Proceedings of the IEEE Conference on Decision and Control",

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pages = "4535--4540",

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note = "49th IEEE Conference on Decision and Control, CDC 2010 ; Conference date: 15-12-2010 Through 17-12-2010",

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Huang, H, Yu, C & Wu, Q 2010, Distributed LQR design for multi-agent formations. in 2010 49th IEEE Conference on Decision and Control, CDC 2010., 5716988, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 4535-4540, 49th IEEE Conference on Decision and Control, CDC 2010, Atlanta, United States, 15/12/10. https://doi.org/10.1109/CDC.2010.5716988

Distributed LQR design for multi-agent formations. / Huang, Huang; Yu, Changbin; Wu, Qinghe.
2010 49th IEEE Conference on Decision and Control, CDC 2010. Institute of Electrical and Electronics Engineers Inc., 2010. p. 4535-4540 5716988 (Proceedings of the IEEE Conference on Decision and Control).

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

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AU - Yu, Changbin

AU - Wu, Qinghe

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AB - In this paper we study the optimal formation control of multiple agents whose communication topology as well as the interaction parameters is tunable upon a cost function consisting of both control energy and formation indicator. The determination of interaction parameters is accompanied by the design of linear quadratic regulation(LQR) controllers which are distributed ones. When extending the results to systems with multiple agents, it is sufficient that the underlying graph of the cost matrix has an unrooted tree or the directed underlying graph is persistent. Numerical examples are provided to illustrate the effectiveness of the method.

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Distributed LQR design for multi-agent formations

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