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dc.creatorChevet, T.es
dc.creatorStoica Maniu, Cristinaes
dc.creatorVlad, C.es
dc.creatorZhang, Y.es
dc.creatorCamacho, E.es
dc.creatorCamacho, Eduardo F.es
dc.date.accessioned2021-09-06T16:00:27Z
dc.date.available2021-09-06T16:00:27Z
dc.date.issued2020
dc.identifier.citationChevet, T., Stoica Maniu, C., Vlad, C., Zhang, Y., Camacho, E. y Camacho, E.F. (2020). Chance-constrained MPC for voronoi-based multi-agent system deployment. En 21st IFAC World Congress 2020, vol. 53, issue 2, Article number 145388, (6969-6974), Berlín: Elsevier B.V. ; IFAC-PapersOnLine.
dc.identifier.issn2405-8963es
dc.identifier.urihttps://hdl.handle.net/11441/125473
dc.descriptionCuenta con otro ed.: IFAC-PapersOnLine Inluída en vol.53, Issue 2 Article number: 145388es
dc.description.abstractThis paper proposes a new chance-constrained model predictive control (CCMPC) algorithm with state estimation applied to the two-dimensional deployment of a multi-vehicle system where each agent is subject to process noise and measurement noise. The bounded convex area of deployment is partitioned into time-varying Voronoi cells defined by the position of each agent. Due to the presence of noise in the system model, stochastic constraints appear in the model predictive control problem. The proposed decentralized robust CCMPC algorithm drives the multi-agent system into a static Chebyshev configuration where each agent lies on the Chebyshev center of its Voronoi cell. Simulation results show the effectiveness of the proposed control strategy on a fleet of quadrotors subject to wind perturbations and measurement noise.es
dc.description.sponsorshipMinisterio de Economía y Competitividad ( España) DPI2016- 76493-C3-1-Res
dc.description.sponsorshipFeder (UE) 789051es
dc.formatapplication/pdfes
dc.format.extent6 p.es
dc.language.isoenges
dc.publisherElsevier B.V.es
dc.relation.ispartof21st IFAC World Congress 2020 (2020), pp. 6969-6974.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDecentralized controles
dc.subjectModel predictive controles
dc.subjectMulti-agent systemses
dc.titleChance-constrained MPC for voronoi-based multi-agent system deploymentes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.relation.projectIDDPI2016- 76493-C3-1-Res
dc.relation.projectID789051es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2405896320307072es
dc.identifier.doi10.1016/j.ifacol.2020.12.417es
dc.publication.initialPage6969es
dc.publication.endPage6974es
dc.eventtitle21st IFAC World Congress 2020es
dc.eventinstitutionBerlínes

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