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NRRO Rejection using Online Iterative Control for High Density Data Storage on a PC-Based Spinstand Servo System

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5 Author(s)
Chee Khiang Pang ; A''STAR Data Storage Inst., Singapore ; Wai Ee Wong ; Guoxiao Guo ; Chen, B.M.
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In this paper, an OICA (online iterative control algorithm) by setting measured PES (position error signal) into the servo system to achieve high track densities through minimizing the square of the H2 -norm of the transfer function from NRRO (non-repeatable run-out) disturbance sources to true PES is proposed without having to solve any AREs (algebraic Riccati equations) and LMIs (linear matrix inequalities). An online RRO (repeatable run-out) estimator is constructed to extract NRRO components for gradient estimates, hence preventing the controller parameters from being trapped in a local minima. Experimental results on a PC-based servo system for a spinstand [12] show an improvement of 22% in 3sigma NRRO and suppression of baseline NRRO spectrum.

Published in:

American Control Conference, 2007. ACC '07

Date of Conference:

9-13 July 2007