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Artículo
Implementation of model predictive control for tracking in embedded systems using a sparse extended ADMM algorithm
dc.creator | Krupa García, Pablo | es |
dc.creator | Alvarado Aldea, Ignacio | es |
dc.creator | Limón Marruedo, Daniel | es |
dc.creator | Alamo, Teodoro | es |
dc.date.accessioned | 2022-02-24T12:43:32Z | |
dc.date.available | 2022-02-24T12:43:32Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Krupa García, P., Alvarado Aldea, I., Limón Marruedo, D. y Alamo, T. (2022). Implementation of model predictive control for tracking in embedded systems using a sparse extended ADMM algorithm. IEEE Transactions on Control Systems Technology | |
dc.identifier.issn | 1063-6536 | es |
dc.identifier.issn | 1558-0865 | es |
dc.identifier.uri | https://hdl.handle.net/11441/130207 | |
dc.description.abstract | This article presents a sparse, low-memory footprint optimization algorithm for the implementation of model predictive control (MPC) for tracking formulation in embedded systems. This MPC formulation has several advantages over standard MPC formulations, such as an increased domain of attraction and guaranteed recursive feasibility even in the event of a sudden reference change. However, this comes at the expense of the addition of a small amount of decision variables to the MPC's optimization problem that complicates the structure of its matrices. We propose a sparse optimization algorithm, based on an extension of the alternating direction method of multipliers, that exploits the structure of this particular MPC formulation. We describe the controller formulation and detail how its structure is exploited by means of the aforementioned optimization algorithm. We show closed-loop simulations comparing the proposed solver against other solvers and approaches from the literature. | es |
dc.format | application/pdf | es |
dc.format.extent | 8 p. | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers. IEEE | es |
dc.relation.ispartof | IEEE Transactions on Control Systems Technology | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Model predictive control | es |
dc.subject | Embedded optimization | es |
dc.subject | Embedded systems | es |
dc.subject | Extended ADMM | es |
dc.title | Implementation of model predictive control for tracking in embedded systems using a sparse extended ADMM algorithm | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9632418 | es |
dc.identifier.doi | 10.1109/TCST.2021.3128824 | es |
dc.contributor.group | Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control | es |
idus.validador.nota | Postprint. Peer Reviewed | es |
dc.journaltitle | IEEE Transactions on Control Systems Technology | es |
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