High performance speed tracking of induction motor drives using an adaptive fuzzy-neural network control
by Mokhtar Zerikat, Soufyane Chekroun
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Vol. 2, No. 3, 2010

Abstract: This paper relates an adaptive speed control of hybrid fuzzy-neural network for high-performance induction motor drives. The speed control performance of induction motors is affected by parameter variations and non-linearities in the induction motor. The aim of the proposed control scheme is to improve the performance and robustness of the induction motor drives under non-linear loads and parameter variations. Both the design of the fuzzy controller and its integration with neural networks in a global control system are discussed. The simulation results showed excellent tracking performance of the proposed control system, and have convincingly demonstrated the usefulness of the hybrid fuzzy-neural controller in high-performance drives with uncertainty.

Online publication date: Thu, 17-Feb-2011

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Artificial Intelligence and Soft Computing (IJAISC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com