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Speed estimator in closed-loop scalar control using neural networks

机译:基于神经网络的闭环标量控制中的速度估计器

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This work proposes an artificial neural network approach to estimate the induction motor speed applied in a closed-loop scalar control. The induction motor speed is the important quantity in an industrial process. Thus, when the load coupled to the axis needs speed control, some of the drive and control strategies are based on the estimated axis speed of the motor. This paper proposes an alternative methodology for estimating the speed of a three phase induction motor driven by a voltage source inverter, using space vector modulation under the scalar control strategy and based on artificial neural networks. Experimental results are presented to validate the performance of the proposed method under motor load torque and speed reference set point variations.
机译:这项工作提出了一种人工神经网络方法来估计在闭环标量控制中应用的感应电动机速度。感应电动机的速度是工业过程中的重要量。因此,当耦合到轴的负载需要速度控制时,某些驱动和控制策略是基于估计的电动机轴速度。本文提出了一种替代方法,用于在标量控制策略下并基于人工神经网络,通过空间矢量调制来估算由电压源逆变器驱动的三相感应电动机的速度。提出了实验结果,以验证该方法在电动机负载转矩和速度参考设定值变化下的性能。

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