The conventional five-phase finite-control-set model predictive control (FCS-MPC) suffers from heavy computational burden. Meanwhile, the control set with finite vectors inevitably leads to deteriorated operation performance. This article proposes a novel FCS model predictive current control (MPCC) with continued modulation. A cascaded optimization procedure is proposed, which includes main virtual voltage vector (VV) selection, determination of optimal combination of adjacent two VVs, and amplitude optimization. In this cascaded optimization procedure, the phase angle and the amplitude of the synthesized vector can be obtained in different steps. Also, there are two duty cycles calculated in different steps independently, which avoid overflow. By using this cascaded procedure, the continued modulation can be realized without using a modulator. Meanwhile, a vector selection method is introduced to reduce computational burden. This vector selection method avoids evaluation of all the candidate vectors without any negative effects. Moreover, the merits of conventional FCS-MPCC can be preserved. The experimental results verify the effectiveness and superiority of the proposed FCS-MPCC method.

中文翻译：

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一种新型的连续调制五相永磁电机有限控制集模型预测电流控制

传统的五相有限控制集模型预测控制 (FCS-MPC) 承受着沉重的计算负担。同时，有限向量的控制集不可避免地导致运行性能恶化。本文提出了一种具有连续调制的新型 FCS 模型预测电流控制 (MPCC)。提出了一种级联优化程序，包括主虚拟电压矢量(VV)选择、相邻两个VV最佳组合的确定和幅度优化。在这个级联优化过程中，合成矢量的相位角和幅度可以在不同的步骤中获得。此外，在不同的步骤中独立计算了两个占空比，避免了溢出。通过使用这种级联程序，可以在不使用调制器的情况下实现连续调制。同时，引入向量选择方法以减少计算负担。这种向量选择方法避免了对所有候选向量的评估而没有任何负面影响。此外，可以保留传统 FCS-MPCC 的优点。实验结果验证了所提出的 FCS-MPCC 方法的有效性和优越性。