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Título
A Novel Method to Prevent Control System Instability Based on a Soft Computing Knowledge System
dc.contributor.authorCalvo Rolle, José L.
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorFerreiro García, Ramón
dc.contributor.authorLaham, Amer
dc.contributor.authorSánchez Sánchez, María Araceli 
dc.contributor.authorGil González, Ana Belén 
dc.date.accessioned2017-09-06T09:14:33Z
dc.date.available2017-09-06T09:14:33Z
dc.date.issued2011
dc.identifier.citationSoft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011 Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 87, pp. 427-436.
dc.identifier.isbn978-3-642-19643-0 (Print) / 978-3-642-19644-7 (Online)
dc.identifier.issn1867-5662(Print)/ 1867-5670(Online)
dc.identifier.urihttp://hdl.handle.net/10366/134889
dc.description.abstractThe aim of this study is to present a novel soft computing method to assure PID tuning parameters place the system into a stable region by applying the gain scheduling method. First the system is identified for each significant operation point. Then using transfer functions solid structures of stability are calculated to program artificial neural networks, whose object is to prevent system from transitioning to instability. The method is verified empirically under a data set obtained by a pilot plant.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleA Novel Method to Prevent Control System Instability Based on a Soft Computing Knowledge System
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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