1998
DOI: 10.1109/20.663429
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An overview of the PES Pareto Method for decomposing baseline noise sources in hard disk position error signals

Abstract: This paper gives an overview of the PES Pareto Method, a useful tool for identifying and eliminating key contributors to uncertainty in the Position Error Signal (PES) of a magnetic disk drive servo system [1, 2, 3]. Once identified and ranked according to their overall effect on PES, the top-ranking sources can be worked on first, either by finding ways to reduce their magnitude or by altering system components to reduce sensitivity to the contributors.

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Cited by 52 publications
(14 citation statements)
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“…Therefore, we first have to consider reducing the position error signal (PES). Abramovitch et al investigated the PES Pareto method to identify disturbance sources and found that windage and PES baseline noise were the two most significant sources [1]. Then Yamaguchi et al proposed a design tool for evaluating track misregistration (TMR) for disk drives [2].…”
Section: Introductionmentioning
confidence: 98%
“…Therefore, we first have to consider reducing the position error signal (PES). Abramovitch et al investigated the PES Pareto method to identify disturbance sources and found that windage and PES baseline noise were the two most significant sources [1]. Then Yamaguchi et al proposed a design tool for evaluating track misregistration (TMR) for disk drives [2].…”
Section: Introductionmentioning
confidence: 98%
“…The requirement of higher TPI demands more precise and smaller motion of the actuator arm, which exerts more difficulties on track following and single-track seeking. Consequently, it has posted a great challenge to the design of servo controllers for the moving parts of the information storage devices, as the current industrial servo design techniques may no longer be able to deliver the required accuracy and speed, which is due to either the fundamental performance limitations coming from the artificial constraint of using only linear controller structures [16,17,18,19]. In order to capture effects of these nonlinearities, certain nonlinear models are needed.…”
Section: Introductionmentioning
confidence: 99%
“…This means that servo control needs to perform well in both low and middle frequency range. Conventionally loop shaping or disturbance observer [1,2] is used to improve the disturbance rejection, but the performance in the middle or high frequency range is sacrificed due to the water-bed effect [3,4]. Fig.…”
Section: Introductionmentioning
confidence: 99%