Overview
- Presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
Similar content being viewed by others
Keywords
Table of contents (8 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Discrete-Time High Order Neural Control
Book Subtitle: Trained with Kalman Filtering
Authors: Edgar N. Sanchez, Alma Y. Alanís, Alexander G. Loukianov
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-78289-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-78288-9Published: 29 April 2008
Softcover ISBN: 978-3-642-09695-2Published: 22 November 2010
eBook ISBN: 978-3-540-78289-6Published: 24 June 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 110
Topics: Mathematical and Computational Engineering, Artificial Intelligence, Complex Systems, Control, Robotics, Mechatronics, Systems Theory, Control, Statistical Physics and Dynamical Systems