Optimal Control of Wind Energy Systems, Iulian Munteanu; Antoneta Iuliana Bratcu; Nicolaos

Автор: Sul
Название: Control of Electric Machine Drive Systems
ISBN: 0470590793 ISBN-13(EAN): 9780470590799
Издательство: Wiley
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Цена: 20901.00 р.
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Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.

Автор: Dikai Liu; Lingfeng Wang; Kay Chen Tan (Eds.)
Название: Design and Control of Intelligent Robotic Systems
ISBN: 3540899324 ISBN-13(EAN): 9783540899327
Издательство: Springer
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Цена: 36570.00 р.
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Описание: With the increasing applications of intelligent robotic systems in various ?elds, the - sign and control of these systems have increasingly attracted interest from researchers.

Автор: Norgaard M., Ravn O., Poulsen N.K., Hansen L.K.
Название: Neural Networks for Modelling and Control of Dynamic Systems / A Practitioner`s Handbook
ISBN: 1852332271 ISBN-13(EAN): 9781852332273
Издательство: Springer
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Цена: 11179.00 р.
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Описание: The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.