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2013 | OriginalPaper | Chapter

10. Discrete Neural Network Control

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 two kinds of adaptive discrete neural network controllers for discrete nonlinear system, including a direct RBF controller and an indirect RBF controller. For the two control laws, the adaptive laws are designed based on the Lyapunov stability theory; the closed-loop system stability can be achieved.

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previous chapter Digital RBF Neural Network Control
next chapter Adaptive RBF Observer Design and Sliding Mode Control
Appendix
Available only for authorised users
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Metadata
Title
Discrete Neural Network Control
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_10