Authors:
- COMPLEX NONLINEAR SYSTEMS ARE WIDESPREAD - THE READER WILL BE ABLE TO TREAT THEM AS SIMPLER LINEAR SYSTEMS.
- THESE ARE EASIER AND LESS EXPENSIVE TO DEAL WITH.
- THE READER WILL BE MADE AWARE OF THE MOST UP-TO-DATE RESEARCH IN THE APPLICATION OF NEURAL NETWORKS TO NONLINEAR CONTROL SYSTEMS.
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Industrial Control (AIC)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Department of Cybernetics, University of Reading, UK
Freddy Garces, Victor M. Becerra, Kevin Warwick
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Department of Computer Science, The University of Hull, UK
Chandrasekhar Kambhampati
Bibliographic Information
Book Title: Strategies for Feedback Linearisation
Book Subtitle: A Dynamic Neural Network Approach
Authors: Freddy Garces, Victor M. Becerra, Chandrasekhar Kambhampati, Kevin Warwick
Series Title: Advances in Industrial Control
DOI: https://doi.org/10.1007/978-1-4471-0065-2
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 2003
Hardcover ISBN: 978-1-85233-501-4Published: 20 November 2002
Softcover ISBN: 978-1-4471-1095-8Published: 30 January 2012
eBook ISBN: 978-1-4471-0065-2Published: 06 December 2012
Series ISSN: 1430-9491
Series E-ISSN: 2193-1577
Edition Number: 1
Number of Pages: XV, 171
Topics: Control and Systems Theory, Artificial Intelligence, Systems Theory, Control, Industrial and Production Engineering