Enhanced Model Predictive Control for PMSM Based on Reference Voltage Predictive Model

Model predictive torque control (MPTC) for permanent magnet synchronous motor (PMSM) suffers from multiparameter sensitivities and complicated weighting factors tuning. To solve the above problems, an enhanced model predictive control based on the reference voltage predictive model (RVPM) is proposed in this article. In the proposed RVPM, the parameters of inductance and flux are eliminated, and the effect of mismatched resistance parameters is suppressed by introducing the current increment multiplied by resistance. Therefore, the ability of the system to resist parameter mismatches is effectively strengthened without using parameter identification or disturbance estimation. Then, the reference voltage vectors (RVVs) can be directly obtained in the RVPM to design a cost function without the weighting factor. In addition, the traditional speed controller applying the linear proportional-integral (PI) control has poor performance in the face of uncertain disturbances. A discrete-time disturbance observer (DDOB) serves as the speed controller to restrain the influence of lump disturbances and improves the system's dynamic response performance. Finally, the experimental results confirm the superiority of the proposed method.

Automated summary

This article proposes an enhanced model predictive control method for permanent magnet synchronous motors, which addresses the issues of parameter sensitivities and control performance by introducing a reference voltage predictive model and a discrete-time disturbance observer.