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Predictive Control Methods for MultiModel Systems
dc.coverage.spatial | Nacional | es_ES |
dc.creator | Pipino, Hugo | |
dc.creator | Bernardi, Emanuel | |
dc.creator | Capelletti, Carlos A. | |
dc.creator | Adam, Eduardo J. | |
dc.date.accessioned | 2024-08-05T18:44:54Z | |
dc.date.available | 2024-08-05T18:44:54Z | |
dc.date.issued | 2020-12-04 | |
dc.identifier.citation | 2020 IEEE Congreso Bienal de Argentina (ARGENCON) | es_ES |
dc.identifier.isbn | 978-1-7281-5957-7 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12272/11239 | |
dc.description.abstract | This 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.format | es_ES | |
dc.language.iso | eng | es_ES |
dc.language.iso | eng | es_ES |
dc.rights | embargoedAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.rights.uri | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.subject | Predictive control | es_ES |
dc.subject | Multi-model | es_ES |
dc.subject | CSTR | es_ES |
dc.title | Predictive Control Methods for MultiModel Systems | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.description.affiliation | Fil: Pipino, Hugo A. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina. | es_ES |
dc.description.affiliation | Fil: Bernardi, Emanuel. Universidad Tecnológica Nacional. Facultad Regional San Francisco; Argentina. | es_ES |
dc.description.affiliation | Fil: Cappelletti, Carlos A. Universidad Tecnológica Nacional. Facultad Regional Paraná; Argentina. | es_ES |
dc.description.affiliation | Fil: Adam, Eduardo J. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentina. | es_ES |
dc.description.peerreviewed | Peer Reviewed | es_ES |
dc.type.version | publisherVersion | es_ES |
dc.rights.use | . | es_ES |
dc.identifier.doi | 10.1109/ARGENCON49523.2020.9505546 | |
dc.creator.orcid | 0000-0003-4937-6685 | es_ES |
dc.creator.orcid | 0000-0001-5248-9352 | es_ES |
dc.creator.orcid | 0009-0009-7416-6955 | es_ES |
dc.creator.orcid | 0000-0003-0156-9832 | es_ES |