Please use this identifier to cite or link to this item: https://doi.org/10.1109/ACC.2007.4282238
Title: NRRO rejection using online iterative control for high density data storage on a PC-based spinstand servo system
Authors: Pang, C.K. 
Wong, W.E.
Guo, X.
Chen, B.M. 
Lee, T.H. 
Keywords: HDD (Hard-Disk Drives)
Iterative control
NRRO
PES
SSW (Self Servotrack Writing)
STW (Servo Track Writing)
Issue Date: 2007
Citation: Pang, C.K.,Wong, W.E.,Guo, X.,Chen, B.M.,Lee, T.H. (2007). NRRO rejection using online iterative control for high density data storage on a PC-based spinstand servo system. Proceedings of the American Control Conference : 1514-1520. ScholarBank@NUS Repository. https://doi.org/10.1109/ACC.2007.4282238
Abstract: 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 3σ NRRO and suppression of baseline NRRO spectrum. ©2007 IEEE.
Source Title: Proceedings of the American Control Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/84027
ISBN: 1424409888
ISSN: 07431619
DOI: 10.1109/ACC.2007.4282238
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