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dc.contributor.author | Reynoso Meza, Gilberto![]() |
es_ES |
dc.contributor.author | Sanchís Saez, Javier![]() |
es_ES |
dc.contributor.author | Blasco, Xavier![]() |
es_ES |
dc.contributor.author | Freire, Roberto Z.![]() |
es_ES |
dc.date.accessioned | 2017-05-31T11:11:39Z | |
dc.date.available | 2017-05-31T11:11:39Z | |
dc.date.issued | 2016-06-01 | |
dc.identifier.issn | 0957-4174 | |
dc.identifier.uri | http://hdl.handle.net/10251/82090 | |
dc.description.abstract | Multi-objective optimisation design procedures have shown to be a valuable tool for control engineers. They enable the designer having a close embedment of the tuning process for a wide variety of applica- tions. In such procedures, evolutionary multi-objective optimisation has been extensively used for PI and PID controller tuning; one reason for this is due to their flexibility to include mechanisms in order to en- hance convergence and diversity. Although its usability, when dealing with multi-variable processes, the resulting Pareto front approximation might not be useful, due to the number of design objectives stated. That is, a vast region of the objective space might be impractical or useless a priori, due to the strong degradation in some of the design objectives. In this paper preference handling techniques are incorpo- rated into the optimisation process, seeking to improve the pertinency of the approximated Pareto front for multi-variable PI controller tuning. That is, the inclusion of preferences into the optimisation process, in order to seek actively for a pertinent Pareto front approximation. With such approach, it is possible to tune a multi-variable PI controller, fulfilling several design objectives, using previous knowledge from the designer on the expected trade-off performance. This is validated with a well-known benchmark exam- ple in multi-variable control. Control tests show the usefulness of the proposed approach when compared with other tuning techniques. | es_ES |
dc.description.sponsorship | This work was partially supported by the fellowship BJT-304804/2014-2 from the National Council of Scientific and Technologic Development of Brazil (CNPq) and by EVO-CONTROL project (ref. PROMETEO/2012/028, Generalitat Valenciana - Spain). | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Expert Systems with Applications | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Multi-objective optimisation | es_ES |
dc.subject | Controller tuning | es_ES |
dc.subject | PI tuning | es_ES |
dc.subject | Evolutionary multi-objective optimisation | es_ES |
dc.subject | Preference handling | es_ES |
dc.subject | Many-objective optimisation | es_ES |
dc.subject.classification | INGENIERIA DE SISTEMAS Y AUTOMATICA | es_ES |
dc.title | Evolutionary multi-objective optimisation with preferences for multivariable PI controller tuning | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.eswa.2015.11.028 | |
dc.relation.projectID | info:eu-repo/grantAgreement/CNPq//BJT-304804%2F2014-2/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//PROMETEO%2F2012%2F028/ES/EVO-CONTROL: CONTROL Y OPTIMIZACION DE PROCESOS INDUSTRIALES BASADO EN ALGORITMOS EVOLUTIVOS/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.description.bibliographicCitation | Reynoso Meza, G.; Sanchís Saez, J.; Blasco, X.; Freire, RZ. (2016). Evolutionary multi-objective optimisation with preferences for multivariable PI controller tuning. Expert Systems with Applications. 51:120-133. https://doi.org/10.1016/j.eswa.2015.11.028 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://doi.org/10.1016/j.eswa.2015.11.028 | es_ES |
dc.description.upvformatpinicio | 120 | es_ES |
dc.description.upvformatpfin | 133 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 51 | es_ES |
dc.relation.senia | 300383 | es_ES |
dc.identifier.eissn | 1873-6793 | |
dc.contributor.funder | Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brasil | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |