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dc.contributor.author Νίνος, Κωνσταντίνος Δ. el
dc.contributor.author Γιαννακάκης, Χαράλαμπος el
dc.contributor.author Κομπογιάννης, Ιωάννης el
dc.contributor.author Σταύρακας, Ηλίας el
dc.contributor.author Αλεξανδρίδης, Αλέξανδρος Π. el
dc.date.accessioned 2015-06-03T19:25:25Z
dc.date.issued 2015-06-03
dc.identifier.uri http://hdl.handle.net/11400/15008
dc.rights Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.source http://ieeexplore.ieee.org/ en
dc.subject Fuzzy Means
dc.subject Intelligent Control
dc.subject Neural Controller
dc.subject Neural networks
dc.subject Radial Basis Function
dc.subject Ασαφή μέσα
dc.subject Ευφυής Έλεγχος
dc.subject Νευρωνικός ελεγκτής
dc.subject Νευρωνικά Δίκτυα
dc.subject Ακτινική συνάρτηση βάσης
dc.title Nonlinear control of a DC-motor based on radial basis function neural networks en
heal.type conferenceItem
heal.classification Technology
heal.classification Electrical engineering
heal.classification Τεχνολογία
heal.classification Ηλεκτρολογία Μηχανολογία
heal.classificationURI http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI http://zbw.eu/stw/descriptor/18426-4
heal.classificationURI **N/A**-Τεχνολογία
heal.classificationURI **N/A**-Ηλεκτρολογία Μηχανολογία
heal.keywordURI http://zbw.eu/stw/descriptor/19808-6
heal.identifier.secondary DOI: 10.1109/INISTA.2011.5946168
heal.dateAvailable 10000-01-01
heal.language en
heal.access forever
heal.publicationDate 2011
heal.bibliographicCitation Ninos, K.D., Giannakakis, C., Kompogiannis, I., Stavrakas, I. & Alexandridis, A.P. (2011) Nonlinear control of a DC-motor based on radial basis function neural networks, In: Proceedings of the 2011 International Symposium on INnovations in Intelligent SysTems and Applications. Istanbul-Kadikoy, Turkey. 15-18 June, 2011. [online]. p. 611-615, 5946168. Available from: http://ieeexplore.ieee.org/ en
heal.abstract This paper presents a nonlinear controller based on an inverse neural network model of the system under control. The neural controller is implemented as a Radial Basis Function (RBF) network trained with the powerful fuzzy means algorithm. The resulting controller is tested on a nonlinear DC motor control problem and the results illustrate the advantages of the proposed approach. en
heal.publisher IEEE en
heal.fullTextAvailability false
heal.conferenceName 2011 International Symposium on INnovations in Intelligent SysTems and Applications en
heal.conferenceItemType poster


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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες Except where otherwise noted, this item's license is described as Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες