Improved PID search algorithm for multi-parameter identification of PMSM

Aiming at the problem that the parameter identification of permanent magnet synchronous motor (PMSM) can easily fall into the local optimum, resulting in low accuracy and slow identification speed, an improved PID search algorithm (IPSA) is proposed and applied to the parameter identification of PMSM. The algorithm adopts a good point set initialisation to increase the population diversity and homogenise the initial population distribution, and introduces the Weibull flight to enhance the global search capability of the algorithm, and finally introduces the strategy in the artemisinin optimisation algorithm to strengthen the ability of the algorithm to jump out of the local optimum. A vector control based permanent magnet synchronous motor model is constructed in dq-axis coordinates using Matlab/Simulink, and standard test function tests and simulation experiments are carried out. The simulation experiments show that compared with PSO and PSA algorithms, the IPSA algorithm has a significant improvement in convergence speed and optimality seeking performance.