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Guidance system for control periods under modelling threshold

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dc.contributor.authorViúdez Moreiras. Daniel
dc.contributor.authorMartín Sánchez, Juan M.
dc.date.accessioned2025-01-15T11:26:27Z
dc.date.available2025-01-15T11:26:27Z
dc.date.issued2016-07-27
dc.descriptionThe registered version of this article, first published in “International Journal of Automation and Control. 10(3), 215-233", is available online at the publisher's website: Inderscience, https://doi.org/10.1504/IJAAC.2016.077587
dc.descriptionLa versión registrada de este artículo, publicado por primera vez en “International Journal of Automation and Control. 10(3), 215-233", está disponible en línea en el sitio web del editor: Inderscience, https://doi.org/10.1504/IJAAC.2016.077587
dc.description.abstractThis paper presents a new guidance system for process control that can improve the control performance of model-based advanced controllers or optimised adaptive controllers, when their control periods have to be selected within a lower range of time values that may increase the sensitivity of the predictive model parameters to identification errors. The guidance system generates at each control instant a future desired trajectory for the process output variable under control, from which it computes a set point for the derivative variable of the process output variable. A predictive or adaptive predictive controller drives the derivative variable to its set point and, as a consequence, the process output converges towards said desired trajectory. The new guidance system is illustrated by its application to the level control of a MIMO nonlinear process, in the presence of noises and disturbances. The results show how the control performance of the guidance system is not affected by 'small' control periods that would deteriorate the performance of an adaptive predictive controller for the same application.en
dc.description.versionversión final
dc.identifier.citationViúdez-Moreiras, D. and Martín-Sánchez J.M. (2016) Guidance System for Control Periods under Modeling Threshold. International Journal of Automation and Control. 10(3), 215-233. 10.1504/IJAAC.2016.077587. https://doi.org/10.1504/IJAAC.2016.077587
dc.identifier.doihttps://doi.org/10.1504/IJAAC.2016.077587
dc.identifier.issn1740-7516 | eISSN 1740-7524
dc.identifier.urihttps://hdl.handle.net/20.500.14468/25308
dc.journal.issue3
dc.journal.titleInternational Journal of Automation and Control
dc.journal.volume10
dc.language.isoen
dc.page.final233
dc.page.initial215
dc.publisherInderscience
dc.relation.centerFacultades y escuelas::E.T.S. de Ingenieros Industriales
dc.relation.departmentIngeniería Eléctrica, Electrónica, Control, Telemática y Química Aplicada a la Ingeniería
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.es
dc.subject33 Ciencias Tecnológicas::3306 Ingeniería y tecnología eléctricas
dc.subject.keywordsoptimised adaptive controlen
dc.subject.keywordspredictive controlen
dc.subject.keywordsadaptive predictive controlen
dc.subject.keywordsderivative controlen
dc.subject.keywordsguidance systemsen
dc.subject.keywordsguidance strategyen
dc.subject.keywordsprocess controlen
dc.subject.keywordsmodelling thresholden
dc.subject.keywordsmodel-based controlen
dc.subject.keywordsMIMO nonlinear processesen
dc.subject.keywordscontrol performanceen
dc.titleGuidance system for control periods under modelling thresholden
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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