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dc.contributor.authorBarreiro Gómez, Julián
dc.contributor.authorObando, Germán
dc.contributor.authorOcampo-Martínez, Carlos
dc.contributor.authorQuijano Silva, Nicanor
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2020-02-28T16:55:21Z
dc.date.available2020-02-28T16:55:21Z
dc.date.issued2019
dc.identifier.citationBarreiro, J. [et al.]. Evolutionary-games approach for distributed predictive control involving resource allocation. "IET control theory and applications", 2019, vol. 13, núm. 6, p. 772-782.
dc.identifier.issn1751-8644
dc.identifier.urihttp://hdl.handle.net/2117/178896
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractThis paper proposes a distributed model predictive control (DMPC) scheme based on population games for a system formed by a set of sub-systems. In addition to considering independent operational constraints for each sub-system, the controller addresses a coupled constraint that involves the sum of all control inputs. This constraint models an upper bound on the total amount of energy supplied to the plant. The proposed approach does not need a centralized coordinator when having a coupled constraint involving all the decision variables. The proposed methodology, which takes advantage of evolutionary game theory concepts, provides an optimal solution for the described problem. Moreover, it is shown that the methodology has plug-and-play features, i.e., for each already designed local MPC controller nothing changes when more sub-systems are added/removed to/from the global constrained control problem. Furthermore, the stability analysis of the proposed DMPC scheme is presented.
dc.format.extent11 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.otherEvolutionary game theory
dc.subject.otherpredictive control
dc.subject.otherdistributed control schemes
dc.titleEvolutionary-games approach for distributed predictive control involving resource allocation
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.identifier.doi10.1049/iet-cta.2018.5716
dc.subject.inspecClassificació INSPEC::Control theory::Predictive control
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8692328
dc.rights.accessOpen Access
local.identifier.drac25152001
dc.description.versionPostprint (author's final draft)
local.citation.authorBarreiro, J.; Obando, G.; Ocampo-Martinez, C.; Quijano, N.
local.citation.publicationNameIET control theory and applications
local.citation.volume13
local.citation.number6
local.citation.startingPage772
local.citation.endingPage782


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