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Optimized Distributed Field-Based Sensing for Control of Voice Coil Motor

[+] Author Affiliations
Shaohui Foong, Xianmin Chen, Kok-Meng Lee

Georgia Institute of Technology, Atlanta, GA

Paper No. DSCC2011-5999, pp. 145-151; 7 pages
doi:10.1115/DSCC2011-5999
From:
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control
  • ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Volume 2
  • Arlington, Virginia, USA, October 31–November 2, 2011
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5476-1
  • Copyright © 2011 by ASME

abstract

A magnetic field-based sensing system utilizing statistically optimized concurrent multi-sensor outputs for non-contact precise field-position association is presented. The rationale and principle of capitalizing on simultaneous spatial field measurements to induce unique correspondence between field and position to achieve accurate translational motion over large travel distances for feedback control is illustrated using a single-source-multi-sensor configuration. Principal component analysis (PCA) is used as a pseudo filter to optimally reduce the dimension of the multi-sensor output space for field-position mapping with artificial neural networks (ANNs). The effects of PCA on the sensing accuracy and closed-loop tracking performance are experimentally investigated using a voice-coil motor and a 9 sensor network with an optical encoder as a comparison.

Copyright © 2011 by ASME
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