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Probing and diagnosis of slider–disk interactions in nanometer clearance regime using artificial neural network

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Abstract

This paper addresses the issue of system identification for an active-head slider used to form a stable and reliable head–disk interface with a spacing of sub 3 nm. A new identification method is proposed to fit the highly non-stationary and highly nonlinear slider dynamics. The estimated model can be used for design of a model based nonlinear controller to control the flying height within the desired range. The effectiveness of the proposed system identification method is verified with simulation examples.

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Authors and Affiliations

  1. University of Alaska, Fairbanks, AK, 99775, USA

    Gang Sheng

  2. Auckland University of Technology, Auckland, New Zealand

    Loulin Huang

  3. Western Digital Corporation, 5863 Rue Ferrari, San Jose, CA, 95138, USA

    Jianfeng Xu

  4. National Tsing Hua University, Hsinchu, 30013, Taiwan

    Jen-Yuan Chang

Authors
  1. Gang Sheng
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  2. Loulin Huang
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  3. Jianfeng Xu
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  4. Jen-Yuan Chang
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Corresponding author

Correspondence to Loulin Huang.

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Sheng, G., Huang, L., Xu, J. et al. Probing and diagnosis of slider–disk interactions in nanometer clearance regime using artificial neural network. Microsyst Technol 18, 1255–1259 (2012). https://doi.org/10.1007/s00542-012-1501-5

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  • DOI: https://doi.org/10.1007/s00542-012-1501-5

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