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Rotor Speed Identification of Doubly-Fed Generator System Based on Neural Network

机译:基于神经网络的双馈发电机系统转子转速辨识

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According to the mathematic model of doubly-fed induction generator, the adjustable model and reference model based on MRAS are found. The adjustable model of model reference adaptive system based on neural network is derived by backward differentiation method and the algorithm for magnetic flux linkage is determined using two-layer neural network . Besides, the speed identification of doubly-fed induction generator is obtained by training of two-layer neural network using error back propagation. Finally, the simulation results show that compared with the speed identification of model reference adaptive system, the rotor speed can be reflected actually, and the speed estimation precision is effectively improved when neural network speed estimator is applied.
机译:根据双馈感应发电机的数学模型,建立了基于MRAS的可调模型和参考模型。通过向后微分法推导了基于神经网络的模型参考自适应系统的可调模型,并采用两层神经网络确定了磁链的算法。此外,通过利用误差反向传播训练两层神经网络,获得了双馈感应发电机的速度识别。最后,仿真结果表明,与模型参考自适应系统的速度识别相比,转子速度可以得到实际反映,采用神经网络速度估计器可以有效提高速度估计精度。

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