永磁同步电机(PMSM)是一种具有很强非线性的动态系统,在工业驱动应用中发挥着重要作用。实时辨识转动惯量对于高精度PMSM系统控制和稳定性状态监测具有重要意义,但传统转动惯量识别方法精度较低。在传统离散模型参考自适应理论基础之上,用柯西变异粒子群优化(CMPSO)算法代替待辨识参数自适律设计环节,以实现PMSM转动惯量识别。该转动惯量辨识方法充分利用了CMPSO算法的快速高效收敛性,仿真结果和试验结果表明了可行性、正确性和准确性。

Permanent magnet synchronous motor (PMSM) was a highly nonlinear dynamic system, which played an important role in industrial driving applications. Real time identification of moment of inertia was of great significance to the control and stability monitoring of high precision PMSM systems. However, traditional identification methods lacked accuracy. Based on the traditional discrete model reference adaptive theory, the Cauchy mutation particle swarm optimization (CMPSO) algorithm was used to replace the adaptive law design of parameters to be identified to realize the identification of PMSM moment of inertia. This method made full use of the fast and efficient convergence of CMPSO algorithm. The simulation and experimental results proved the feasibility, correctness and accuracy of the method.

TM 351