PI parameter optimization of Asynchronous motor vector control based on MIGA

Abstract

In motor control, the stable control of motor speed and the stability in the face of sudden torque are two important indicators to evaluate the quality of the control system. This paper proposes a multi-island genetic algorithm (MIGA) and fuzzy PI vector control algorithm. Combined with the asynchronous motor control method, the simulation test and bench test are carried out. Taking the Integral Time Multiplied by the Absolute Value of Error (ITAE) minimum as the optimization goal, the MIGA optimization algorithm is used to obtain the optimal solution for the quantization factors ke0, kec0 , proportional factors kup, kui of the fuzzy PI controller. The optimal parameters are imported into the asynchronous motor control model for simulation verification and bench test verification. The simulation test shows that the fuzzy PI control method optimized by MIGA can effectively reduce the speed rise time, overshoot and steady-state error. When the load is suddenly applied, the speed drop is 5.16 r/min, and the adjustment time is 0.015s. The bench test shows that: under the changing load, the change trend of the speed curve of the simulation and the test is basically the same, which proves the correctness and effectiveness of the algorithm proposed in this paper.