dc.creator | Chaouach, Lotfi Mustapha | es |
dc.creator | Fiacchini, Mirko | es |
dc.creator | Alamo, Teodoro | es |
dc.date.accessioned | 2023-02-08T09:49:17Z | |
dc.date.available | 2023-02-08T09:49:17Z | |
dc.date.issued | 2022 | |
dc.identifier.issn | 2405-8963 | es |
dc.identifier.uri | https://hdl.handle.net/11441/142531 | |
dc.description | -Part of special issue: 10th IFAC Symposium on Robust Control Design ROCOND 2022: Online (Kyoto, Japan), 30 August – 2 September 2022
-Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) | es |
dc.description.abstract | In this paper, the problem of stability, recursive feasibility and convergence conditions of stochastic model predictive control for linear discrete-time systems affected by a large class of correlated disturbances is addressed. A stochastic model predictive control that guarantees convergence, average cost bound and chance constraint satisfaction is developed. The results rely on the computation of probabilistic reachable and invariant sets using the notion of correlation bound. This control algorithm results from a tractable deterministic optimal control problem with a cost function that upper-bounds the expected quadratic cost of the predicted state trajectory and control sequence. The proposed methodology only relies on the assumption of the existence of bounds on the mean and the covariance matrices of the disturbance sequence. | es |
dc.format | application/pdf | es |
dc.format.extent | 6 p. | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Stochastic MPC | es |
dc.subject | Probabilistic reachability | es |
dc.subject | Probabilistic invariance | es |
dc.title | Stochastic model predictive control for linear systems affected by correlated disturbances | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | 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.projectID | ANR-11-LABX-0025-01 | es |
dc.relation.projectID | 10.13039/501100011033 | es |
dc.relation.projectID | PID2019-106212RB-C41 | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S2405896322015890 | es |
dc.identifier.doi | 10.1016/j.ifacol.2022.09.336 | es |
dc.contributor.group | Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control | es |
dc.publication.initialPage | 133 | es |
dc.publication.endPage | 138 | es |
dc.eventtitle | 10th IFAC Symposium on Robust Control Design, ROCOND 2022, IFAC PapersOnLine 55, 25 | es |
dc.eventinstitution | Kyoto | es |
dc.contributor.funder | Secretaría general de inversiones. Francia | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | es |
dc.contributor.funder | Agencia Estatal de Investigación | |