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OverviewEvolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved. Full Product DetailsAuthor: Dimitris C. DracopoulosPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: phe05 Dimensions: Width: 15.50cm , Height: 1.20cm , Length: 23.50cm Weight: 0.360kg ISBN: 9783540761617ISBN 10: 3540761616 Pages: 211 Publication Date: 15 August 1997 Audience: College/higher education , Professional and scholarly , Undergraduate , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Active Availability: Out of stock ![]() The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsIntroduction.- Dynamic systems and control.- The attitude control problem.- Artificial neural networks.- Neuromodels of dynamic systems.- Current neurocontrol techniques.- Genetic algorithms.- Adaptive control architectures.- Conclusions and the future.- A. Euler equations solutions.- B. An attitude control simulator.- Bibliography.- Index.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |