The Parameter Identification of PMSM Based on Improved Cuckoo Algorithm

摘要

In view of the multi-parameter identification problem of permanent magnet synchronous motor, a kind of parameter identification method was proposed based on an improved cuckoo search algorithm. Cuckoo search algorithm has the advantages of simple, less parameters, fast convergence etc., but it also has the defects of premature convergence and low computation accuracy. In view of the deficiency of cuckoo search algorithm, the fuzzy reasoning based on the cloud membership was designed to adjust the probability of an alien egg being discovered by host birds and adaptive variable step method was used to adjust the step size of Lévy flights. The improved algorithm can accelerate the convergence speed and improve the local and global optimizing ability by increasing the diversity of the population. The multi-parameter identification results of permanent magnet synchronous motor show that the improved cuckoo algorithm can effectively identify the motor parameters, and compared with the traditional cuckoo algorithm, the effectiveness and superior performance are tested.