Implementation of Lyapunov learning algorithm for fuzzy switching adaptive controller modeled under Quasi-ARX Neural Network

Imam Sutrisno, Mohammad Abu Jami'In, Jinglu Hu

研究成果: Paper査読

抄録

This paper presents a fuzzy adaptive controller applied to a non linear system modeled under a Quasi-linear ARX Neural Network, with stability proof by using the Lyapunov approach. This work exploits the new idea to use Lyapunov function to train multi-input multi-output neural network on the core-part sub-model. The proposed controller is designed between a non linear controller and linear controller based on fuzzy switching algorithm. Finally improving performances of the Lyapunov learning algorithm are stable in the learning process, fast convergence of error, and able to increase the accuracy of the controller.

本文言語English
ページ762-766
ページ数5
DOI
出版ステータスPublished - 2013 1 1
イベント2013 2nd International Conference on Measurement, Information and Control, ICMIC 2013 - Harbin, China
継続期間: 2013 8 162013 8 18

Conference

Conference2013 2nd International Conference on Measurement, Information and Control, ICMIC 2013
国/地域China
CityHarbin
Period13/8/1613/8/18

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 教育

フィンガープリント

「Implementation of Lyapunov learning algorithm for fuzzy switching adaptive controller modeled under Quasi-ARX Neural Network」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル