Cart (Loading....) | Create Account
Close category search window

A robust adaptive sliding mode tracking control using an RBF neural network for robotic manipulators

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Man Zhihong ; Dept. of Comput. & Commun. Eng., Edith Cowan Univ., WA, Australia ; Yu, X.H. ; Eshraghian, K. ; Palaniswami, M.

A new robust adaptive sliding mode tracking control scheme using an RBF neural network is proposed for rigid robotic manipulators to achieve robustness and asymptotic error convergence. A key feature of this scheme is that the prior knowledge of the upper bound of the system uncertainties is not required. An adaptive RBF neural network is used to learn the upper bound of system uncertainties. The output of the neural network is then used as a compensator parameter in the sense that the effects of the system uncertainties can be eliminated and asymptotic error convergence can be obtained for the closed loop robotic control system

Published in:

Neural Networks, 1995. Proceedings., IEEE International Conference on  (Volume:5 )

Date of Conference:

Nov/Dec 1995

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.