Parameter estimation of disk drive servo system using a hybrid simplex differential evolution algorithm

Abstract

To accurately maintain the head position along the center of the track, determining the optimal parameters of the disk drive servo control system is one of most important works. In this paper, a hybrid optimization algorithm incorporated Nelder & Mead (NM) simplex method into the differential evolution (DE) algorithm was presented to the optimum parameter estimation of a disk drive servo system. This hybrid procedure performed the exploration with DE and the exploitation with the NM simplex method. Three experiments under the different conditions of command signal, sampling period and measuring noises were used to test the effectiveness of the proposed approach. The experiment results demonstrate that the hybrid optimization algorithm is superior to the two original search techniques (i.e. NM and DE) in terms of solution quality and convergence rate, and is an effective method for the parameter estimation of a control system.