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

抜粋

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.

元の言語English
ページ762-766
ページ数5
DOI
出版物ステータス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
China
Harbin
期間13/8/1613/8/18

    フィンガープリント

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Education

これを引用

Sutrisno, I., Jami'In, M. A., & Hu, J. (2013). Implementation of Lyapunov learning algorithm for fuzzy switching adaptive controller modeled under Quasi-ARX Neural Network. 762-766. 論文発表場所 2013 2nd International Conference on Measurement, Information and Control, ICMIC 2013, Harbin, China. https://doi.org/10.1109/MIC.2013.6758071