Position Sensorless Control for PMSM Based on Diagonal Recurrent Neural Network
The rotor position observers were designed based on diagonal recurrent neural network (DRNN). The neural rotor position estimation process is separated into two neural observers, a stator current estimator, and a angular velocity estimator. The angle estimation block generates rotor angle by integrating the estimated angular velocity, with adjustment derived from the current estimation error. Through experimentation, 12 neurons in the hidden recurrent layer were found to produce good results for the neural current observer. The output layer contains two neurons: one for each the direct and quadrature axis current estimates. The simulation results show the estimated rotor angle error is small, and the robust property is good when step load changes.
DRNN current estimator velocity estimator
SUN Fanjin LIU Yancheng CHEN Yang
Department of Marine Engineering, Dalian Maritime University Dalian, LiaoNing, 116026
国际会议
北京
英文
2007-08-05(万方平台首次上网日期,不代表论文的发表时间)