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Control of a chain pendulum: A fuzzy logic approach

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dc.contributor.authorAranda Escolástico, Ernesto
dc.contributor.authorGuinaldo Losada, María
dc.contributor.authorSantos, Matilde
dc.contributor.authorDormido Canto, Sebastián
dc.date.accessioned2024-10-07T08:48:33Z
dc.date.available2024-10-07T08:48:33Z
dc.date.issued2016-02-12
dc.descriptionThe registered version of this article, first published in International Journal of Computational Intelligence Systems, is available online at the publisher's website: Taylor and Francis Group, https://doi.org/10.1080/18756891.2016.1150001
dc.descriptionLa versión registrada de este artículo, publicado por primera vez en International Journal of Computational Intelligence Systems, está disponible en línea en el sitio web del editor: Taylor and Francis Group, https://doi.org/10.1080/18756891.2016.1150001
dc.description.abstractIn this paper, we present a real application of computational intelligence. Fuzzy control of a non-linear rotary chain pendulum is proposed and implemented on real prototypes. The final aim is to obtain a larger region of attraction for the stabilization of this complex system, that is, a more robust controller. As it is well-known, fuzzy logic exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost when dealing with complex systems. In this case, the control strategy is based on a Takagi-Sugeno fuzzy model of the strongly non-linear multivariable system. Simulation and experimental results on the real plant have been obtained and tested in a rotary inverted pendulum and in a double rotary inverted pendulum. They have been compared to other feedback control strategies such as Full State Feedback or Linear Quadratic Regulator with encouraging results. Fuzzy control allows to enlarge the stability region of control. Indeed, the region of attraction and therefore the stabilization has been enlarged up to over 17% for the real system.en
dc.description.versionversión final
dc.identifier.citationAranda-Escolástico, E., Guinaldo, M., Santos, M., & Dormido, S. (2016). Control of a Chain Pendulum: A fuzzy logic approach. International Journal of Computational Intelligence Systems, 9(2), 281–295. https://doi.org/10.1080/18756891.2016.1150001
dc.identifier.doihttps://doi.org/10.1080/18756891.2016.1150001
dc.identifier.issn1875-6883
dc.identifier.urihttps://hdl.handle.net/20.500.14468/23931
dc.journal.issue2
dc.journal.titleInternational Journal of Computational Intelligence Systems
dc.journal.volume9
dc.language.isoen
dc.page.final295
dc.page.initial281
dc.publisherTaylor and Francis Group
dc.relation.centerFacultades y escuelas::E.T.S. de Ingeniería Informática
dc.relation.departmentIngeniería de Software y Sistemas Informáticos
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject33 Ciencias Tecnológicas
dc.subject.keywordsintelligent controlen
dc.subject.keywordsfuzzy logicen
dc.subject.keywordsrotary inverted pendulumen
dc.subject.keywordsstabilizationen
dc.subject.keywordsTakagi-Sugeno modelen
dc.subject.keywordsregion of attractionen
dc.subject.keywordsrobustnessen
dc.titleControl of a chain pendulum: A fuzzy logic approachen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery19c0c538-4e7e-4de5-afd9-6ff1a8bbf88e
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