Direct stable adaptive fuzzy neural model reference control of a class of nonlinear systems

Mojtaba Ahmadieh Khanesar, Mohammad Teshnehlab

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

Abstract

In this study, using a model reference adaptation law, a stable fuzzy neural control system is developed. Despite the advantages of Model reference control design technique, which is mainly its power to exactly set trajectories of the system under control, this method is designed for linear system. In this study using fuzzy neural systems, a stable model reference controller for nonlinear systems is developed. Lyapunov method is used to guarantee the stability of fuzzy neural training algorithm and model following of the system under control.

Original languageEnglish
Title of host publication3rd International Conference on Innovative Computing Information and Control, ICICIC'08
Publication date2008
Article number4603701
ISBN (Print)9780769531618
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event3rd International Conference on Innovative Computing Information and Control, ICICIC'08 - Dalian, Liaoning, China
Duration: 18 Jun 200820 Jun 2008

Conference

Conference3rd International Conference on Innovative Computing Information and Control, ICICIC'08
CountryChina
CityDalian, Liaoning
Period18/06/200820/06/2008

Keywords

  • Fuzzy neural control
  • Model reference control
  • Stable controller

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