Robustness Improvement of Predictive Current Control Using Prediction Error Correction for Permanent-Magnet Synchronous Machines

The predictive control method deals with the prediction of the motor behavior based on a mathematical model of the motor. This model is dependent on the motor parameters. However, these parameters may not match with their actual values due to the measurement error or they may change during the operation of the motor. All these uncertainties and model inexactitude lead to inaccurate prediction of the motor behavior and deteriorate the performance of the predictive algorithm. This paper presents an extension of the predictive current control (PCC) method to improve the prediction accuracy for a permanent-magnet synchronous motor (PMSM). The proposed strategy not only reduces the current ripple but also improves the robustness of the system against parameter uncertainties. Simulation and experimental results that confirm the good performance of the proposed method are presented.