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OverviewControl theory of nonlinear systems, in which either the linear part is known but the relevant nonlinearities in place, kind or parameters are unknown, or both the linear and the nonlinear parts are partially or even most unknown, is a new, demanding and highly interesting field. This book treats the problem by focussing on the role of learning. Intelligent learning techniques are able to determine the unknown components of nonlinear systems. These processes are always stable and convergent. The methods presented can be used both on-line and off-line. They have applications in mechatronics, hydraulics and combustion engines. Full Product DetailsAuthor: Dierk Schröder , D. Schröder , U. Lenz , M. BeuschelPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: 2000 ed. Dimensions: Width: 15.50cm , Height: 2.00cm , Length: 23.50cm Weight: 1.500kg ISBN: 9783540636397ISBN 10: 3540636390 Pages: 339 Publication Date: 18 November 1999 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction — Control Aspects.- 2 Motion Control.- 3 Learning in Control Engineering.- 4 Nonlinear Function Approximators.- 5 Systematic Intelligent Observer Design.- 6 Identification of Separable Nonlinearities.- 7 Identification and Compensation of Friction.- 8 Detection and Identification of Backlash.- 9 Identification of Isolated Nonlinearities in Rolling Mills.- 10 Input-Output Linearization: an Introduction.- 11 Stable Model Reference Neurocontrol.- 12 Dynamic Neural Network Compositions.- 13 Further Strategies for Nonlinear Control with Neural Networks.- List of Figures.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |