Recurrent fuzzy neural network using genetic algorithm for linear induction motor servo drive

F. J. Lin, P. K. Huang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

6 引文 斯高帕斯(Scopus)

摘要

A recurrent fuzzy neural network (RFNN) using genetic algorithm (GA) is proposed to control the mover of a linear induction motor (LIM) servo drive for periodic motion in this paper. First, the dynamic model of an indirect field-oriented LIM servo drive is derived. Then, an on-line training RFNN with backpropagation algorithm is introduced as the tracking controller. Moreover, to guarantee the global convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. In addition, a real-time GA is developed to search the optimal weights between the membership layer and the rule layer of RFNN on-line. The theoretical analyses for the proposed RFNN using GA controller are described in detail. Finally, experimental results show that the proposed controller provides high-performance dynamic characteristics and is robust with regard to plant parameter variations and external load disturbance.

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主出版物標題2006 1st IEEE Conference on Industrial Electronics and Applications
DOIs
出版狀態已出版 - 2006
事件2006 1st IEEE Conference on Industrial Electronics and Applications, ICIEA 2006 - Singapore, Singapore
持續時間: 24 5月 200626 5月 2006

出版系列

名字2006 1st IEEE Conference on Industrial Electronics and Applications

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???event.eventtypes.event.conference???2006 1st IEEE Conference on Industrial Electronics and Applications, ICIEA 2006
國家/地區Singapore
城市Singapore
期間24/05/0626/05/06

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