Description: Discrete-Time High Order Neural Control Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Trained with Kalman Filtering Author(s): Edgar N. Sanchez, Alma Y. Alanis, Alexander G. Loukianov Format: Paperback Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Germany Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K ISBN-13: 9783642096952, 978-3642096952 Synopsis Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.
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Book Title: Discrete-Time High Order Neural Control
Number of Pages: 110 Pages
Language: English
Publication Name: Discrete-Time High Order Neural Control: Trained with Kalman Filtering
Publisher: Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG
Publication Year: 2010
Subject: Engineering & Technology, Computer Science, Physics
Item Height: 235 mm
Item Weight: 197 g
Type: Textbook
Author: Alexander G. Loukianov, Edgar N. Sanchez, Alma Y. Alanis
Subject Area: Material Science, Mechanical Engineering
Series: Studies in Computational Intelligence
Item Width: 155 mm
Format: Paperback
