Model predictive control of induction motor drives: Flux control versus torque control

Yongchang Zhang, Haitao Yang
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引用次数: 17

Abstract

Recently, model predictive torque control (MPTC) has been introduced as a powerful control method for induction motor (IM) drives. However, the weighting factor for stator flux must be tuned carefully to obtain satisfactory performance at different operation points. Unfortunately, so far the tuning of weighting factor in MPTC is mostly based on empirical procedure. This paper solves this problem by proposing a model predictive flux control (MPFC), which uses the stator flux vector as the control variable. As a result, the weighting factor in conventional MPTC is eliminated and the control complexity is significantly reduced. Both MPTC and MPFC are tested and compared in detail, including steady state performance, dynamic response and low speed operation. The experimental results prove that, the performance of conventional MPTC is dependent on the weighting factor and improper weighting factor would lead to significant performance deterioration. On the contrary, the proposed MPFC achieves similar or even better overall performance over a wide speed range with very low tuning work. Hence, it is concluded that the proposed MPFC is more practical than conventional MPTC.
感应电机驱动的模型预测控制:磁链控制与转矩控制
模型预测转矩控制(MPTC)是近年来引入的一种有效的异步电动机控制方法。但是,必须仔细调整定子磁链的权重因子,才能在不同的工作点获得满意的性能。遗憾的是,到目前为止,MPTC中权重因子的调整大多是基于经验过程的。本文提出了一种以定子磁链矢量为控制变量的模型预测磁链控制(MPFC)。因此,消除了传统MPTC中的权重因素,显著降低了控制复杂度。对MPTC和MPFC进行了详细的测试和比较,包括稳态性能、动态响应和低速运行。实验结果表明,传统MPTC的性能依赖于权重因子,权重因子设置不当会导致性能显著下降。相反,所提出的MPFC在宽速度范围内以非常低的调谐工作实现了类似甚至更好的整体性能。因此,我们得出结论,所提出的MPFC比传统的MPTC更实用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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