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

Anti-control of chaos based on fuzzy neural networks inverse system method

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

2 Author(s)
Hai-Peng Ren ; Xi''an Univ. of Technol., China ; Ding Liu

The problem considered in the paper is anti-control of chaos for a non-chaotic system via a fuzzy neural network inverse system (FNNIS) method. A Sugeno type fuzzy neural network (FNN) is trained to learn the kinetics of the non-chaotic system. The trained FNN model is employed in the inverse system method, thereby, the exact mathematic model of the system to be controlled is not necessary. The FNN model error upon control is studied and a related theorem is developed. Simulation results for continuous and discrete systems show the effectiveness of the method.

Published in:

Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on  (Volume:2 )

Date of Conference:

2002

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.