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2013 | OriginalPaper | Chapter

6. Adaptive RBF Control Based on Global Approximation

Author : Jinkun Liu

Published in: Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Publisher: Springer Berlin Heidelberg

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Abstract

This chapter introduces three kinds of adaptive neural mode control laws for n-link manipulators based on RBF, including adaptive neural network control law, adaptive neural network control law with sliding mode robust term, and adaptive neural network control law with HJI. The closed-loop system stability can be achieved based on the Lyapunov stability.

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previous chapter Neural Network Sliding Mode Control
next chapter Adaptive Robust RBF Control Based on Local Approximation
Appendix
Available only for authorised users
Literature
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Metadata
Title
Adaptive RBF Control Based on Global Approximation
Author
Jinkun Liu
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Print ISBN: 978-3-642-34815-0

Electronic ISBN: 978-3-642-34816-7

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-34816-7_6