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Distributed LQR Design for Multi-Agent Formations

Huang, Huang; Yu, Changbin (Brad); Wu, Qinghe

Description

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...[Show more]

dc.contributor.authorHuang, Huang
dc.contributor.authorYu, Changbin (Brad)
dc.contributor.authorWu, Qinghe
dc.coverage.spatialAtlanta USA
dc.date.accessioned2015-12-10T22:58:13Z
dc.date.createdDecember 15-17 2010
dc.identifier.isbn9781424477449
dc.identifier.urihttp://hdl.handle.net/1885/60761
dc.description.abstractIn 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.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE Conference on Decision and Control 2010
dc.sourceIEEE Conference on Decision and Control 2010 Proceedings
dc.subjectKeywords: Communication topologies; Control energy; Cost matrices; Formation control; Interaction parameters; Linear quadratic regulations; Multi-Agent; Multiple agents; Numerical example; Underlying graphs; Numerical methods; Trees (mathematics)
dc.titleDistributed LQR Design for Multi-Agent Formations
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2010
local.identifier.absfor080101 - Adaptive Agents and Intelligent Robotics
local.identifier.ariespublicationu4334215xPUB561
local.type.statusPublished Version
local.contributor.affiliationHuang, Huang, College of Engineering and Computer Science, ANU
local.contributor.affiliationYu, Changbin (Brad), College of Engineering and Computer Science, ANU
local.contributor.affiliationWu, Qinghe, Beijing Institute of Technology
local.description.embargo2037-12-31
local.bibliographicCitation.startpage4535
local.bibliographicCitation.lastpage4540
local.identifier.doi10.1109/CDC.2010.5716988
local.identifier.absseo890199 - Communication Networks and Services not elsewhere classified
dc.date.updated2016-02-24T11:01:55Z
local.identifier.scopusID2-s2.0-79953150915
CollectionsANU Research Publications

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