Idioma: Inglés
Publicado por Butterworth-Heinemann 2016-07-11, 2016
ISBN 10: 0128031360 ISBN 13: 9780128031360
Librería: Chiron Media, Wallingford, Reino Unido
EUR 103,11
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 114,73
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Añadir al carritoPaperback. Condición: Brand New. 1st edition. 282 pages. 8.75x6.00x0.50 inches. In Stock.
Idioma: Inglés
Publicado por Elsevier - Health Sciences Division, 2016
ISBN 10: 0128031360 ISBN 13: 9780128031360
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 126,08
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 162,98
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Añadir al carritoPaperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 93,30
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 150,00
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Englisch.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 156,09
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained.