Title :
Nonrepeatable Run-out Rejection Using Online Iterative Control for High-Density Data Storage
Author :
Pang, Chee Khiang ; Wong, Wai Ee ; Guo, Guoxiao ; Chen, Ben M. ; Lee, Tong Heng
Author_Institution :
Data Storage Inst., Nat. Univ. of Singapore
fDate :
5/1/2007 12:00:00 AM
Abstract :
The spectra of disturbances and noises affecting precise servo positioning for ultrahigh-density storage in future hard disk drives are time-varying and remain unknown. In this paper, we propose an online iterative control algorithm that sets the measured position error signal (PES) into the servo system to achieve high track densities by minimizing the square of the H2-norm of the transfer function from nonrepeatable run-out (NRRO) disturbances to the true PES. It is not necessary to solve any algebraic Riccati equations and linear matrix inequalities. The algorithm constructs an online repeatable run-out estimator to extract NRRO components for gradient estimates, thereby preventing the controller parameters from being trapped in a local minima. Experimental results on a PC-based servo system for a spinstand show an improvement of 22% in 3sigma NRRO and suppression of baseline NRRO spectrum
Keywords :
Riccati equations; adaptive control; control engineering computing; disc drives; hard discs; iterative methods; linear matrix inequalities; position control; servomechanisms; transfer functions; algebraic Riccati equations; hard disk drives; high-density data storage; linear matrix inequalities; nonrepeatable run-out rejection; online iterative control; position error signal; servo positioning; servo system; transfer function; Control systems; Density measurement; Error correction; Hard disks; Iterative algorithms; Memory; Position measurement; Riccati equations; Servomechanisms; Transfer functions; Hard disk drives; NRRO; PES; iterative control; self servotrack writing (SSW); servo track writing (STW);
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2006.890242
