Development of genetic-PI based controller for interior permanent magnet synchronous motor drive over wide speed range

Abstract

This paper develops a genetic-PI based controller for interior permanent magnet synchronous motor (IPMSM) drive. An artificial neural network (ANN) is used for on-line tuning of the PI controller. Genetic algorithm (GA) has been used in this work in order to obtain the optimized values of the PI controller parameters for precise speed control under different operating conditions over wide speed range. The performance index which has been utilized as GA objective function is zero steady-state error, minimum speed deviation, and minimum settling time of the IPMSM drive. The optimal behavior of drive can be achieved by considering two control strategics: maximum torque per ampere (MTPA) control strategy in constant torque region and flux-weakening control strategy in constant power region. In developing the proposed controller, the PI controller parameters are optimized by GA at all operating conditions, in a closed loop vector control scheme. By obtaining the parameters at a number of points in the possible operating region, a look-up table approach has been completed. Then an ANN is trained by this look-up table. Ultimately, the well-trained ANN is utilized for on-line tuning of the PI controller parameters to ensure optimum drive performance under different disturbances and operating conditions over wide speed range.