Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 73,39
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Añadir al carritoPaperback. Condición: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.
Publicado por LAP LAMBERT Academic Publishing Feb 2016, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 39,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware -This book presents a research work towards the Identification and Control of Non-Linear Systems based on Fuzzy Models approach. A TS fuzzy model has been implemented successfully to a known benchmark problem of the identification of non-linear plant data. FCM Clustering based approach has been used for the classification of input ¿output data points. After clustering gradient descent method is used for the learning of parameters. It has also been implemented on a real data problem which is a model of an operator¿s control of a chemical plant and the accuracy was comparable to the results reported in the literature. The entire system has been modeled using MATLAB 7.0/Simulink toolbox.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: preigu, Osnabrück, Alemania
EUR 36,30
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Fuzzy Model Identification & Control of Non-Linear Systems | Sunil Gupta (u. a.) | Taschenbuch | 64 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659851148 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Publicado por LAP LAMBERT Academic Publishing Feb 2016, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 39,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a research work towards the Identification and Control of Non-Linear Systems based on Fuzzy Models approach. A TS fuzzy model has been implemented successfully to a known benchmark problem of the identification of non-linear plant data. FCM Clustering based approach has been used for the classification of input -output data points. After clustering gradient descent method is used for the learning of parameters. It has also been implemented on a real data problem which is a model of an operator's control of a chemical plant and the accuracy was comparable to the results reported in the literature. The entire system has been modeled using MATLAB 7.0/Simulink toolbox. 64 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 34,25
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gupta SunilMr.Sunil Gupta is working as a Reader in Maharaja Surajmal Institute of Technology,(GGSIP University), Janak Puri, New Delhi. He is pursuing Ph.D. degree in Electrical Engineering at Jamia Millia Islamia (A Central Univers.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659851140 ISBN 13: 9783659851148
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 39,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a research work towards the Identification and Control of Non-Linear Systems based on Fuzzy Models approach. A TS fuzzy model has been implemented successfully to a known benchmark problem of the identification of non-linear plant data. FCM Clustering based approach has been used for the classification of input -output data points. After clustering gradient descent method is used for the learning of parameters. It has also been implemented on a real data problem which is a model of an operator's control of a chemical plant and the accuracy was comparable to the results reported in the literature. The entire system has been modeled using MATLAB 7.0/Simulink toolbox.