A novel training method based on variable structure systems theory for fuzzy neural networks

Ozkan Cigdem*, Erdal Kayacan, Mojtaba Ahmadieh Khanesar, Okyay Kaynak, Mohammad Teshnehlab

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Uncertainty is an inevitable problem in real-time industrial control systems and, to handle this problem and the additional one of possible variations in the parameters of the system, the use of sliding mode control theory-based approaches is frequently suggested. In this paper, instead of using a conventional sliding mode controller, a sliding mode control theory-based learning algorithm is proposed to train the fuzzy neural networks in a feedback-error-learning structure. The parameters of the fuzzy neural network are tuned by the proposed algorithm not to minimize the error function but to ensure that the error satisfies a stable equation. The parameter update rules of the fuzzy neural network are derived, and the proof of the learning algorithm is verified by using the Lyapunov stability method. The proposed method is tested on a real-time servo system with time-varying and nonlinear load conditions.

Original languageEnglish
Title of host publicationIEEE SSCI 2011 - Symposium Series on Computational Intelligence - CICA 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation
Number of pages8
Publication date2011
Pages44-51
Article number5945757
ISBN (Print)9781424499038
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011 - Paris, France
Duration: 11 Apr 201115 Apr 2011

Conference

ConferenceSymposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2011
CountryFrance
CityParis
Period11/04/201115/04/2011
SponsorIEEE

Keywords

  • Feedback error learning
  • Fuzzy neural networks
  • Servo system
  • Variable structure systems

Fingerprint Dive into the research topics of 'A novel training method based on variable structure systems theory for fuzzy neural networks'. Together they form a unique fingerprint.

Cite this