Abstract Matrix Converter (MC) has many advantages such as capability of bi-directional energy conversion, no need for DC bus and high value filters. However, modulation methods are very difficult and require high computational effort. Therefore, Multi-objective Finite Control Set Model Predictive Control (MFCS-MPC) has been implemented to simplify the complexity of this topology. However, the weakness of this control method is using mathematical model and affected by parameter mismatches due to the external disturbances, frequency and temperature variations. In this study, past errors of rotor current are added to the cost function and the weighting factors are adjusted with the Fuzzy Decision Making (FDM) approach. Due to the combination of these two methods, a robust system is obtained that can operate even in model-plant mismatch. The proposed algorithm is implemented using the TMS320F28335 Digital Signal Processor (DSP), a 32-bit floating-point processor operating at 150 MHz. Results obtained from simulation and experimental setup are compared with the current literature studies and the performance of the proposed method is confirmed.

中文翻译：

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基于多目标有限控制集模型预测控制的DFIG矩阵变换器误差最小化

摘要 矩阵变换器(MC)具有双向能量转换能力、无需直流母线和高值滤波器等优点。然而，调制方法非常困难并且需要大量的计算工作。因此，已实施多目标有限控制集模型预测控制 (MFCS-MPC) 以简化此拓扑的复杂性。然而，这种控制方法的弱点是使用数学模型，并且受外部扰动、频率和温度变化引起的参数不匹配的影响。在这项研究中，转子电流的过去误差被添加到成本函数中，并使用模糊决策 (FDM) 方法调整加权因子。由于这两种方法的结合，获得了一个鲁棒的系统，即使在模型与设备不匹配的情况下也能运行。所提出的算法是使用 TMS320F28335 数字信号处理器 (DSP) 实现的，该处理器是一种以 150 MHz 运行的 32 位浮点处理器。从模拟和实验设置中获得的结果与当前的文献研究进行了比较，并证实了所提出方法的性能。