Optimal Control Method of Motor Torque Loading Based on Genetic Algorithm

This paper designs an automatic calibration method and system of motor torque for the problem of low loading accuracy of motor torque. The system uses genetic algorithm to optimize PID parameters and load control and measurement of the motor. The genetic algorithm is realized in the simulation platform, and the iterative operation is carried out by setting different cross probability and mutation probability parameters. The results are substituted into the motor model to analyze the response speed and anti-interference ability of the motor to the given random signal, and the optimal PID parameters are obtained as the configuration parameters of the motor torque automatic calibration system. The experimental results show that compared with the traditional motor torque calibration loading control, the accuracy of the system torque calibration error is improved and the error range is controlled within +/- 0.003N . m, which verifies the effectiveness and feasibility of this method.