Abstract
The authors have developed a low-cost, high-performance magneto-optical (MO) disk drive whose track-following mechanism is implemented as a linear positioner driven by a voice coil motor (VCM), that is, a single-stage tracking mechanism. In this tracking mechanism, Coulomb friction disturbance caused by the slide bearings of the positioner is a critical problem preventing precise track following.
To solve this problem, we developed a learning controller, which automatically estimates and generates an ideal VCM current signal to perfectly compensate for the friction disturbance. The estimated signal pattern is approximated as the weighted sum of time-shifted rectangular functions, and the weight for each rectangular function is updated online using a simple learning algorithm during track following control. Simultaneously, the latest updated signal is added to the output of a feedback controller and fed to the VCM driver.
We evaluated the efficiency of our controller both in a simulation and an experiment. In the experiment, the tracking error peaks caused by Coulomb friction were drastically lowered by using the learning controller, and a tracking error of less than 0.02μm was confirmed during operation of an MO disk rotating at 4, 500rpm with a radial track runout of 77μm peak to peak.
