FPGA-based elman neural network control system for linear ultrasonic motor

Faa Jeng Lin, Ying Chih Hung

研究成果: 雜誌貢獻期刊論文同行評審

35 引文 斯高帕斯(Scopus)

摘要

A field-programmable gate array (FPGA)-based Elman neural network (ENN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM) in this study. First, the structure and operating principle of the LUSM are introduced. Because the dynamic characteristics and motor parameters of the LUSM are nonlinear and time-varying, an ENN control system is designed to achieve precision position control. The network structure and online learning algorithm using delta adaptation law of the ENN are described in detail. Then, a piecewise continuous function is adopted to replace the sigmoid function in the hidden layer of the ENN to facilitate hardware implementation. In addition, an FPGA chip is adopted to implement the developed control algorithm for possible low-cost and high-performance industrial applications. The effectiveness of the proposed control scheme is verified by some experimental results.

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文章編號4775268
頁(從 - 到)101-113
頁數13
期刊IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
56
發行號1
DOIs
出版狀態已出版 - 1月 2009

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