FPGA-based recurrent wavelet neural network control system for linear ultrasonic motor

Ying Chih Hung, Faa Jeng Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM) in this study. First, the structure and operating principles of the LUSM are introduced. Since the dynamic characteristics and motor parameters of the LUSM are nonlinear and time-varying, an RWNN controller is designed to improve the control performance for the precision tracking of various reference trajectories. The network structure and its on-line learning algorithm using delta adaptation law of the RWNN are described in detail. Moreover, an FPGA chip is adopted to implement the developed control algorithm for possible low-cost and high-performance industrial applications. Finally, the effectiveness of the proposed control system is verified by some experimental results.

Original languageEnglish
Title of host publicationISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications
Pages1290-1295
Number of pages6
DOIs
StatePublished - 2009
Event9th International Conference on Intelligent Systems Design and Applications, ISDA 2009 - Pisa, Italy
Duration: 30 Nov 20092 Dec 2009

Publication series

NameISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

Conference

Conference9th International Conference on Intelligent Systems Design and Applications, ISDA 2009
Country/TerritoryItaly
CityPisa
Period30/11/092/12/09

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