This paper presents a new algorithm based on the combination of fuzzy logic control with M5 decision tree algorithm for doubly fed induction generator active and reactive power control. The M5 model tree is a machine learning algorithm that uses the extracted dataset from fuzzy logic for the aim of control performance enhancement. Because the fuzzy logic provides high design and implementation complexity, the new control approach is proposed to reduce its complexity and to achieve fast dynamic control by translating the fuzzy logic algorithm into simple if‐then instructions using M5 model tree. The obtained model shows good agreement with fuzzy logic in rotor side control. The effectiveness of the proposed control approach is investigated through Matlab/Simulink software. Furthermore, a cosimulated through processor in the loop testing is performed as an experimental verification using a low‐cost STM32F407 discovery board.

中文翻译：

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风能转换系统中双馈感应发电机的新型M5P模型树控制

本文提出了一种基于模糊逻辑控制与M5决策树算法相结合的新算法，用于双馈感应发电机的有功和无功控制。M5模型树是一种机器学习算法，使用从模糊逻辑中提取的数据集来提高控制性能。由于模糊逻辑提供了较高的设计和实现复杂度，因此提出了一种新的控制方法，即通过使用M5模型树将模糊逻辑算法转换为简单的if-then指令，从而降低其复杂度并实现快速动态控制。所获得的模型与转子侧控制中的模糊逻辑吻合良好。通过Matlab / Simulink软件研究了所提出的控制方法的有效性。此外，