Traditional model predictive control has difficulty in achieving satisfactory control performance when parameter identification is inaccurate or when a parameter changes. To solve this problem, this article proposed a new model-free predictive current control (MFPCC) scheme for a doubly fed induction generator (DFIG), which combines an ultra-local model with predictive current control (PCC). This method replaces the mathematical model of a DFIG with an ultra-local model and has strong parameter robustness. In addition, this method is suitable for the synchronization and power regulation processes of a DFIG, and it is also easy to apply to a DFIG with uncertain parameters. The proposed method is compared to traditional model-based deadbeat control with space vector modulation (SVM), and the presented experimental results confirm its superiority and effectiveness.

中文翻译：

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使用用于电网同步和功率调节的超局部模型对 DFIG 进行无模型预测电流控制

当参数辨识不准确或参数发生变化时，传统的模型预测控制难以获得令人满意的控制性能。为了解决这个问题，本文针对双馈感应发电机 (DFIG) 提出了一种新的无模型预测电流控制 (MFPCC) 方案，该方案将超局部模型与预测电流控制 (PCC) 相结合。该方法用超局部模型代替DFIG的数学模型，具有很强的参数鲁棒性。此外，该方法适用于双馈电机的同步和功率调节过程，也易于应用于参数不确定的双馈电机。将所提出的方法与传统的基于模型的无差拍控制与空间矢量调制 (SVM) 进行比较，