Overview
Part of the book series: The International Series on Asian Studies in Computer and Information Science (ASIS, volume 12)
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About this book
Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks.
Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.
Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.
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Table of contents (8 chapters)
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Front Matter
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A Review of Nonlinear Adaptive Neural Control Schemes
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Nonlinear System Identification and Indirect Adaptive Control Schemes
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Front Matter
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Direct Adaptive Control Strategy and Fighter Aircraft Applications
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Fully Tuned Radial Basis Function Neural Networks for Flight Control
Authors: N. Sundararajan, P. Saratchandran, Yan Li
Series Title: The International Series on Asian Studies in Computer and Information Science
DOI: https://doi.org/10.1007/978-1-4757-5286-1
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2002
Hardcover ISBN: 978-0-7923-7518-0Published: 30 November 2001
Softcover ISBN: 978-1-4419-4915-8Published: 07 December 2010
eBook ISBN: 978-1-4757-5286-1Published: 09 March 2013
Series ISSN: 1566-0710
Edition Number: 1
Number of Pages: XVI, 158
Topics: Complex Systems, Calculus of Variations and Optimal Control; Optimization, Artificial Intelligence, Automotive Engineering, Statistical Physics and Dynamical Systems