An Iterative Learning Control design for Self-ServoWriting in Hard Disk Drives

Abstract

This paper considers the modeling and compensator design for Self-ServoWriting (SSW) in disk drives. An Iterative Learning Control (ILC) based scheme is established to deal with radial error propagation and improve the quality of written tracks. In the proposed scheme, a feedback controller for track following is first designed to achieve good disturbance attenuation. Then, an ILC structure is applied to generate an external signal, which is injected into the feedback loop in order to compensate for the written-in errors in the previous track while the next track is written. As a result, the error propagation can be contained. The learning controller is synthesized by solving Linear Matrix Inequality (LMI) equations to ensure the stability and monotonic convergence of the control algorithm. Simulation results show the effectiveness of the proposed scheme on the error containment which results in good quality written tracks.

An Iterative Learning Control design for Self-Servowriting in Hard Disk Drives using L<inf>1</inf> optimal control

“…The general steps for SSW process were described by Melkote and McNab [3] and Wu and Tomizuka [4], among others.…”

“…6. This configuration is same as the one in Wu and Tomizuka [4]. are available for us to estimate i y k ( ).…”

“…See Ye et al [1], and Melkote et al [2] among others for further details. Iterative Learning Control (ILC) based control structure (Melkote and McNab [3], Wu and Tomizuka [4]) has been proved to be an effective approach to contain the radial error propagation.…”

Iterative learning control for nonlinear MIMO systems with unknown nonparametric uncertainties and input saturations

“…The key advantages of ILC is based on its simple structure and almost model-free nature. It is for this reason that ILC has been employed in many applications which include robots [1], hard disk drive [2], rapid thermal processing [3], rotary systems [4], and so on.…”

“…The contributions of the article are: (1) under the alignment condition, an ILC scheme for MIMO system is proposed; (2) in order to deal with the nonlinearities caused by the input saturations, an iterative learning controller consisting of a feedback law and a partially saturated learning law is proposed; (3) the proposed approach can address the nonparametric uncertainties; (4) unknown state-dependent input gain is considered; (5) the proposed scheme can address the unknown uncertainties which is local Lipschitz continuous.…”