Optimization and simulation of asynchronous motor vector control parameter based on adapted genetic algorithm

FENG Xinghui, FANG Jianan, XV Honglei, WU Ruiyan
(School of Information Science & Technology, Donghua University, Shanghai 201620, China)

Abstract: PID parameters tuning is an extremely important issue in the control field. Accoding to the engineers experience, it is always very hard to find the optimal solution of asynchronous machine speed controllers parameter. In order to solve the problem, punitive measures and adapted genetic algorithm were applied to optimize the asynchronous machine speed controllers parameter and then it was slinulated using rate error integral as the objective function. By comparing with the speed curve that use conventional PID parameter, the experimental results show that the optimized parameters can improve the control precision and dynamic performance.
Key words: asynchronous motor; vector control; adapted genetic algorithm