dc.creator | Manzano Crespo, José María | es |
dc.creator | Limón Marruedo, Daniel | es |
dc.creator | Muñoz de la Peña Sequedo, David | es |
dc.creator | Calliess, Jan Peter | es |
dc.date.accessioned | 2021-05-13T12:07:33Z | |
dc.date.available | 2021-05-13T12:07:33Z | |
dc.date.issued | 2020-07 | |
dc.identifier.citation | Manzano, J.M., Limón, D., Muñoz de la Peña, D. y Calliess, J.-P. (2020). Robust learning-based MPC for nonlinear constrained systems. Automatica, 117, Art. number 108948. | |
dc.identifier.issn | 0005-1098 | es |
dc.identifier.uri | https://hdl.handle.net/11441/109011 | |
dc.description | Sherpa/Romeo: Versión aceptada en repositorios institucionales tras 24 meses de embargo https://v2.sherpa.ac.uk/id/publication/4278 | es |
dc.description.abstract | This paper presents a robust learning-based predictive control strategy for nonlinear systems subject to both input and output constraints, under the assumption that the model function is not known a priori and only input–output data are available. The proposed controller is obtained using a nonparametric machine learning technique to estimate a prediction model. Based on this prediction model, a novel stabilizing robust predictive controller without terminal constraint is proposed. The design procedure is purely based on data and avoids the estimation of any robust invariant set, which is in general a hard task. The resulting controller has been validated in a simulated case study. | es |
dc.format | application/pdf | es |
dc.format.extent | 7 p. | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Automatica, 117, Art. number 108948. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Predictive control | es |
dc.subject | Learning control | es |
dc.subject | Robust stability | es |
dc.subject | Nonlinear systems | es |
dc.subject | Lyapunov stability | es |
dc.title | Robust learning-based MPC for nonlinear constrained systems | 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://www.sciencedirect.com/science/article/pii/S0005109820301461 | es |
dc.identifier.doi | 10.1016/j.automatica.2020.108948 | es |
dc.contributor.group | Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control | es |
dc.journaltitle | Automatica | es |
dc.publication.volumen | 117 | es |
dc.publication.initialPage | Art. number 108948 | es |
dc.description.awardwinning | Premio Trimestral Publicación Científica Destacada de la US. Escuela Técnica Superior de Ingeniería | |