A Robust Predictive Torque and Flux Control for IPM Motor Drives Without a Cost Function

Abstract

Finite control set model predictive torque and flux control of ac motor drives commonly selects optimum inverter switching states through a cost function with a required weighting factor. The weighting factor should be well-tuned in accordance with the motor specifications and operating points. Additionally, the control performance of the drive is degraded under the parametric uncertainties. In this article, a predictive torque and flux control method is proposed for interior permanent magnet synchronous motor drives without a cost function. As a result, the tuning of the weighting factor is avoided. Besides, an estimation scheme based on a data-driven model is adopted, which enhances the robustness of the drive against parametric uncertainties. Instead of directly using the motor parameters, the input and output data of the control system, i.e., voltage and current, are used for estimating three new coefficients employed in the predictions. The performance of an interior permanent magnet synchronous motor drive under the proposed control method is evaluated and compared with those under the conventional predictive torque control method and a recently developed predictive torque control method without a weighting factor. The results confirm the effectiveness of the proposed control method and its superiority over the other two methods.