基于输入和误差补偿的PMSM迭代学习控制

Iterative learning control on PMSM based on input and error compensation

针对永磁同步电机(PMSM)在运行过程中受到扰动影响的问题,在分析其数学模型的基础上,采用矢量控制方法,构建了Matlab/Simulink环境下的永磁同步电机仿真模型,介绍了基于迭代学习的输入和误差补偿的控制方法,利用先前误差信息以及误差的变化趋势,对误差提前进行了预测补偿;最后对整个控制系统进行了仿真。仿真结果表明,与传统的PI控制相比较,该控制方法扰动抑制效果明显,提高了系统运行性能,证明了迭代学习控制可用于有效抑制系统干扰。

Aiming at the disturbance of the permanent magnet synchronous motor（PMSM） during running, on the basis of analysis of the mathematical model of PMSM, the simulation model was established by using vector control methods under Matlab/Simulink environment. Input and error compensation based on iterative learning control （ILC）was introduced. Error could be compensated and forecasted in advance utilizing previous error information and error change trend. Finally, the whole control system was simulated. The simulation results show that compared with the traditional PI control, disturbance rejection effect of proposed method is more obvious, which demonstrates that iterative learning control can restrain interference and improve system performance.