Weighting-Factorless Sequential Model Predictive Torque Control of a Six-Phase AC Machine

J. Rodas, O. González, Margarita Norambuena, J. Doval‐Gandoy, O. Gomis‐Bellmunt, R. Gregor, M. Ayala, José Raúl Rodríguez Rodríguez, C. Romero
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Abstract

Model predictive control is an exciting control technique that has been applied successfully to multiphase induction machines. The possibility to include several constraints by using only the cost function is one of its main attractive characteristics. However, this latter implies the nontrivial task of adequately tuning the weighting factors to fulfil multiple control objectives properly. This paper proposes a sequential model predictive torque control of a six-phase induction machine that avoids using the weighting factor. Simulation studies are provided to show the effectiveness of this proposal showing good reference tracking of the torque, flux and stator $\alpha-\beta$ and $x-y$ currents.
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六相交流电机的无权重因子序贯模型预测转矩控制
模型预测控制是一种已成功应用于多相感应电机的激励控制技术。通过仅使用成本函数来包含几个约束的可能性是其主要吸引人的特征之一。然而,后者意味着适当调整权重因子以适当地实现多个控制目标的重要任务。本文提出了一种避免使用权重因子的六相感应电机序贯模型预测转矩控制方法。仿真研究表明了该方法的有效性,对转矩、磁链、定子$\alpha-\beta$和$x-y$电流有良好的参考跟踪。
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