Double Update Intelligent Strategy for Permanent Magnet Synchronous Motor Parameter Identification

The parameters of permanent magnet synchronous motor (PMSM) affect the performance vector control servo system. Because complexity nonlinear model PMSM, it is very difficult to identify PMSM. Aiming at problems large amount data calculation, low identification accuracy and poor robustness in process multi parameter motor, this paper proposes a weighted differential evolutionary particle swarm optimization algorithm based on double update strategy. By introducing adaptive judgment factor proportion difference evolution (WDE) (PSO) each iteration process, consider using PSO or WDE individuals according probability law. obtained from operation are used guide individual through information exchange mechanism. proposed WDEPSO can ensure diversity effectiveness population. applied PMSM drive simulation results show that has better convergence strong robustness, method does not need rely more sheet design value, stator resistance same time, rotor flux linkage, d/q-axis inductance electrical parameters, effectively track value.