Robust Predictive Flux Control Based on Generalized Proportional Integral Observer for PMSM

The traditional finite control set-model predicting flux control (FCS-MPFC) suffers from the problem of system parameter dependence. When the parameters used in the controller deviate from the actual value, it will lead to serious deviation of the control, which will lead to instability of the system. Therefore, in order to improve the robustness of predictive control, based on the analysis of the influence of parameter deviation on the control effect, the generalized proportional integral (GPI) observer is used to construct the flux observer, to compensation observation error caused by motor parameter deviation. The proposed observer can accurately observe the flux linkage when there is a deviation in the motor parameters. In addition, the GPI observer is used to improve the prediction model. Finally, simulation results show that the proposed scheme has excellent parameter robustness.