Automatic Learning of Hybrid Fuzzy Controller for the Optical Data Storage Device

Abstract

A hybrid track seeking fuzzy controller for the optical data storage device is proposed in this paper. It will be shown that the proposed hybrid fuzzy controller smoothes the applied voltage to the sled motor and improves the track seeking efficiency. The proposed hybrid fuzzy controller consists of two subsystems including parking time controller and driving force controller. Both subsystems are designed based on fuzzy inference. The hybrid fuzzy controller will on one hand drive the pickup as fast as possible to the neighborhood of target track, and on the other hand smoothly park the pickup so that the fine seek controller can take over the control of pickup. An automatic learning approach based on GA is proposed learning both fuzzy rules of parking time controller and driving force controller. To improve GA's learning efficiency, modulated orthogonal membership functions are utilized in both fuzzy controllers. Various experiments are made to justify the performance comparison.