Parameter Optimization of Fractional-Order PI Controller for Vector Control of Permanent Magnet Synchronous Motor Based on Improved SSA Algorithm

The speed loop of permanent magnet synchronous motor (PMSM) vector control system adopts PI controller, which is difficult to meet the requirements of fast dynamic response and strong robustness of the system. A fractional order proportional integral (FOPI) controller was proposed, and the parameters of the FOPI controller were optimized using improved sparrow search algorithm (ISSA). The SSA population is initialized through Piecewise chaotic mapping to improve the quality of the initial solution. The iterative update strategy of dynamic weight Gaussian-Cauchy mixture variation and sine and cosine distribution is used to solve the problem that SSA is prone to fall into local optimum. By searching for the sparrow's position with the best fit, the best setting parameters for the controller were obtained, and the time multiplied by the absolute value of the error integral was determined as the target fitness function. The motor speed regulation performance of improved SSA setting FOPI, SSA setting FOPI and WOA setting FOPI was experimentally compared. The results show that the FOPI optimized by the improved SSA has the advantages of enhancing robustness and reducing overshoot.