Nonrepeatable Run-out Rejection Using Online Iterative Control for High-Density Data Storage

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