Automated estimator parameter selection for an IBM head/disk assembly
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Updated: Aug 16, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
May-Win L Thein1, Thomas Rendon, Eduardo A Misawa
1Department of Mechanical Engineering, University of New Hampshire, Durham, New Hampshire 03824-3591, USA. mthein@cisunix.unh.edu
Abstract:
This paper presents the application of a discrete adaptive observer (DAO) to an IBM head/disk assembly system. Because of the difficulties in tuning, a genetic algorithm is implemented off-line to obtain optimal observer parameters for the DAO. Simulations show that the genetic algorithm is successful in choosing appropriate observer gains. Furthermore, as a result of these optimal gains, the observer state and parameter estimates converge accurately and quickly.
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