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dc.contributor.authorMatous, Josef
dc.contributor.authorVaragnolo, Damiano
dc.contributor.authorPettersen, Kristin Ytterstad
dc.contributor.authorPaliotta, Claudio
dc.date.accessioned2022-09-19T08:14:13Z
dc.date.available2022-09-19T08:14:13Z
dc.date.created2022-09-15T09:08:51Z
dc.date.issued2022
dc.identifier.citationIFAC-PapersOnLine. 2022, 55 (13), 85-90.en_US
dc.identifier.issn2405-8963
dc.identifier.urihttps://hdl.handle.net/11250/3018745
dc.description.abstractThe paper considers the problem of formation path-following of multiple vehicles and proposes a solution based on combining distributed model predictive control with parametrizations of the trajectories of the vehicles using polynomial splines. Introducing such parametrization leads indeed to two potential benefits: a) reducing the number of optimization variables, and b) enabling enforcing constraints on the vehicles in a computationally efficient way. Moreover, the proposed solution formulates the formation path-following problem as a distributed optimization problem that may then be solved using the alternating direction method of multipliers (ADMM). The paper then analyzes the effectiveness of the proposed method via numerical simulations with surface vehicles and differential drive robots.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleDistributed MPC for Formation Path-Following of Multi-Vehicle Systemsen_US
dc.title.alternativeDistributed MPC for Formation Path-Following of Multi-Vehicle Systemsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber85-90en_US
dc.source.volume55en_US
dc.source.journalIFAC-PapersOnLineen_US
dc.source.issue13en_US
dc.identifier.doihttps://doi.org/10.1016/j.ifacol.2022.07.240
dc.identifier.cristin2051861
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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