Use of an artificial neural network for current derivative estimation
Use of an artificial neural network for current derivative estimation
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使用人工神经网络进行电流导数估计
DOI：
10.1109/epe.2013.6634327
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
C. Gerada
中科院分区：
文献类型：
--
作者：
D. Hind;M. Sumner;C. Gerada
基于显着跟踪的无传感器（无编码器）电机控制的基本 PWM 技术使用电流导数测量来计算转子位置。然而，当逆变器的 IGBT 开关时，驱动器、电机和电缆中的寄生阻抗会导致电流出现高频振荡。当新的电压施加到电机上时，这会阻止立即测量电流导数，并导致强制执行最小 PWM 矢量时间限制，从而允许电流响应中的振荡在进行电流导数测量之前充分衰减。在这项工作中，提出了一种新方法，通过使用神经网络在存在此类振荡的情况下估计电流导数来减少这种最小 PWM 矢量时间限制。神经网络的训练是离线执行的，神经网络配置（权重和偏差）存储在可移动存储介质上。这可以通过允许保存和调用网络配置来减轻培训负担，从而可能为以前遇到的驱动器设置提供“即插即用”解决方案。所提出的解决方案的另一个好处是，电流导数是根据使用标准工业电流传感器而不是专用电流导数传感器捕获的数据来估计的。讨论了所提出的方法及其实现，并给出了在线实验结果，验证了所提出技术的可行性和性能。
The Fundamental PWM technique for saliency tracking based sensorless (encoderless) motor control uses current derivative measurements to calculate the rotor position. However parasitic impedances in the drive, motor and cabling cause high frequency oscillations in the current, when the inverter's IGBTs switch. This prevents the immediate measurement of the current derivative when a new voltage is imposed on the motor and has led to an enforced minimum PWM vector time restriction that allows the oscillations in the current response to decay sufficiently before current derivative measurements are made. In this work a new method is proposed to reduce this minimum PWM vector time restriction by estimating the current derivative in the presence of such oscillations using a neural network. Training of the neural network is performed off-line with the neural network configuration (weights and biases) being stored on removable storage media. This can reduce the training burden by allowing network configurations to be saved and recalled, potentially offering a “plug and play” solution for previously encountered drive setups. An additional benefit of the proposed solution is that the current derivative is estimated from data captured using standard industrial current sensors instead of dedicated current derivative sensors. The proposed method and its implementation are discussed and on-line experimental results are presented which validate the feasibility and performance of the proposed technique.
使用递归最小二乘算法进行新型电流导数测量，用于永磁同步电机的无传感器控制
DOI：
10.1109/ipemc.2012.6259005
发表时间：
2012
期刊：
--
影响因子：
--
作者：
Yu Duan
通讯作者：
Yu Duan