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The Direct Torque Control System Using the Artificial Neural Network Observer

机译:基于人工神经网络观测器的直接转矩控制系统

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In this paper, we propose a new method for direct identifying the stator flux linkage and electromagnetic torque of induction motors, which uses artificial neural networks. Because the multilayer feedforward network has the good capability of approximating any linear or nonlinear function, which is trained using the back propagation (BP) algorithm, it can observe the stator flux linkage and electro-magnetic torque of induction motors accurately. Based on this principle, we built a new direct torque control (DTC) system. With simulation experiment, the results show that this method can observe accurately the stator flux linkage and electro-magnetic torque of induction motors, and the system has good dynamic and static performance.
机译:在本文中,我们提出了一种使用人工神经网络直接识别感应电动机的定子磁链和电磁转矩的新方法。由于多层前馈网络具有很好的逼近任何线性或非线性函数的能力,并且使用反向传播(BP)算法对其进行了训练,因此它可以准确地观察感应电动机的定子磁链和电磁转矩。基于此原理,我们构建了一个新的直接转矩控制(DTC)系统。通过仿真实验,结果表明,该方法可以准确地观察感应电动机的定子磁链和电磁转矩,具有良好的动,静性能。

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