Recurrent functional-link-based fuzzy neural network controller with improved particle swarm optimization for a linear synchronous motor drive

Faa Jeng Lin*, Syuan-Yi Chen, Li Tao Teng, Hen Chu

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

47 引文 斯高帕斯(Scopus)

摘要

A recurrent functional link (FL)-based fuzzy neural network (FNN) controller is proposed in this study to control the mover of a permanent-magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, a recurrent FL-based FNN controller is proposed in this study to control the PMLSM. Moreover, the online learning algorithms of the connective weights, means, and standard deviations of the recurrent FL-based FNN are derived using the back-propagation (BP) method. However, divergence or degenerated responses will result from the inappropriate selection of large or small learning rates. Therefore, an improved particle swarm optimization (IPSO) is adopted to adapt the learning rates of the recurrent FL-based FNN online. Finally, the control performance of the proposed recurrent FL-based FNN controller with IPSO is verified by some simulated and experimental results.

原文英語
文章編號5170216
頁(從 - 到)3151-3165
頁數15
期刊IEEE Transactions on Magnetics
45
發行號8
DOIs
出版狀態已發佈 - 2009 八月

ASJC Scopus subject areas

  • 電子、光磁材料
  • 電氣與電子工程

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