Model Predictive Current Control for PMSM Drives Based on Nonparametric Prediction Model

To essentially solve that the control performance of model predictive current control (MPCC) is affected by the accuracy of model parameters, an MPCC of permanent magnet synchronous motors (PMSMs) based on the nonparametric prediction model (NPM-MPCC) is proposed. First, the control principle of MPCC method is introduced, and the influence of model parameter errors on the control performance under the conventional prediction model is analyzed. Then, an NPM for PMSM prediction control is proposed, which consists of
$d$
-axis current prediction model and
$q$
-axis current prediction model. The proposed model does not include any motor parameters and has a real-time model updating mechanism. The accurate current prediction can be achieved, only by using current prediction difference, sampling, and storing information, and the control performance of the system can get rid of the dependence on the precision of model motor parameters. Finally, the effectiveness of the MPCC method based on NPM is verified by the experimental results.