Predictive Control Methods for MultiModel Systems

dc.coverage.spatialNacionales_ES
dc.creatorPipino, Hugo
dc.creatorBernardi, Emanuel
dc.creatorCappelletti, Carlos Alberto
dc.creatorAdam, Eduardo J.
dc.creator.orcid0000-0003-4937-6685es_ES
dc.creator.orcid0000-0001-5248-9352es_ES
dc.creator.orcid0009-0009-7416-6955es_ES
dc.creator.orcid0000-0003-0156-9832es_ES
dc.date.accessioned2024-08-05T18:44:54Z
dc.date.available2024-08-05T18:44:54Z
dc.date.issued2020-12-04
dc.description.abstractThis paper explores the design of three different approaches of robust predictive control formulations for the case of multi-model system representations. The first one is an optimum multi-objective regulator with variable gain matrix that considers a continuous time multi-model system representation and an infinite horizon; the second one is a sub-optimal linear parameter varying model predictive controller based on a discrete time multi-model system representation with finite horizon and a sequence of contractive terminal set constraint; and, at last, an adaptive model predictive controller that considers a discrete time multi-model system representation, with finite horizon and a terminal invariant set, in common to all models within the system’s polytope. Finally, these proposed methods are applied to a continuously-stirred tank reactor (CSTR) system, whose dynamic characteristics are well known and strongly non-linear. Through the simulation results, discussions are established on the design procedure, the online computational effort, the performance indexes and the application difficulties.es_ES
dc.description.affiliationFil: Pipino, Hugo A. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina.es_ES
dc.description.affiliationFil: Bernardi, Emanuel. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina.es_ES
dc.description.affiliationFil: Cappelletti, Carlos A. Universidad Tecnológica Nacional. Facultad Regional Paraná; Argentina.es_ES
dc.description.affiliationFil: Adam, Eduardo J. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina.es_ES
dc.description.peerreviewedPeer Reviewedes_ES
dc.formatpdfes_ES
dc.identifier.citation2020 IEEE Congreso Bienal de Argentina (ARGENCON)es_ES
dc.identifier.doi10.1109/ARGENCON49523.2020.9505546
dc.identifier.isbn978-1-7281-5957-7
dc.identifier.urihttp://hdl.handle.net/20.500.12272/11239
dc.language.isoenges_ES
dc.language.isoenges_ES
dc.rightsembargoedAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.uriAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.use.es_ES
dc.subjectPredictive controles_ES
dc.subjectMulti-modeles_ES
dc.subjectCSTRes_ES
dc.titlePredictive Control Methods for MultiModel Systemses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versionpublisherVersiones_ES

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