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A Novel Implementation of Neural Network and Multi-Fuzzy Controllers for Permanent Magnet Synchronous Motor Direct Torque Controlled Drive

机译:用于永磁同步电动机直接扭矩控制驱动的神经网络和多模糊控制器的新颖实现

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To reduce torque ripples and improve dynamic performance, a novel implementation of neural network and multi-fuzzy controller for permanent magnet synchronous motor (PMSM) direct torque controlled (DTC) drive is presented, which replaces the conventional hystersis controller with fuzzy controller (FC1) and includes a neural network speed controller (NC). To tune the weights and biases of the neural networks online, another fuzzy controller (FC2) is adopted. It combines the capability of fuzzy reasoning in handling uncertain information and the capability of neural network in learning from processes. Results of simulation are provided to demonstrate that the proposed drive has low flux linkage and torque ripples, and has quick response performance even under the occurrence of parameter variations and external disturbance.
机译:为了减少扭矩涟漪并提高动态性能,提出了一种新颖的永磁同步电动机(PMSM)直接控制(DTC)驱动器的神经网络和多模糊控制器的新颖实现,其替换了具有模糊控制器(FC1)的传统氢干控制器并包括神经网络速度控制器(NC)。为了调整神经网络在线的权重和偏差,采用另一个模糊控制器(FC2)。它结合了模糊推理在处理不确定信息和神经网络从过程中学习中的能力的能力。提供了模拟结果以证明所提出的驱动器具有低通量连杆和扭矩波纹,即使在发生参数变化和外部干扰的情况下也具有快速的响应性能。

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