Robust iterative learning controller design using H infinity approach for optical disk drive track-following servo control

Abstract

Optical disk drive systems require high tracking performance to comply with stricter specifications that are imposed by increasing data density on optical disks and faster access time. The major disturbance encountered in optical disk drive system is the result of eccentric disk rotation in combination with track shape irregularities. These periodic signals can be regarded as reference trajectories, which are repetitive in nature but not exactly known except the frequencies. Tight specifications on track-following and disturbance attenuation of the optical disk drive system can be achieved by applying the iterative learning control (ILC) strategy. The aim of the DLC is to asymptotically track (and reject) the periodic reference (and disturbance). The main focus of this thesis is to discuss the analysis and synthesis of learning controllers, considering the trade-off between robustness and performance of the system and finally attenuating the tracking disturbance error.