A novel neural network based control method with adaptive on-line training for dc-dc converters
A novel neural network based control method with adaptive on-line training for dc-dc converters
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一种基于神经网络的新型 DC-DC 转换器自适应在线训练控制方法
DOI：
10.1109/icmla.2012.152
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
M. Motomura and F. Kurokawa
中科院分区：
文献类型：
--
作者：
H. Maruta;M. Motomura and F. Kurokawa
本研究提出了一种基于神经网络的 DC-DC 转换器的新型自适应控制。控制方法需要适应条件的变化以获得高性能的dc-dc变换器。在本研究中，采用神经网络控制来改善dc-dc转换器的瞬态响应。它与传统的PID控制相配合，实现了高度自适应的方法。神经网络使用在线获得的数据进行训练。因此，神经网络控制可以动态适应输入的变化。自适应是通过修改PID控制中的给定来实现的。所提出方法的效果在模拟中得到了证实。结果表明，所提出的方法有助于实现这种自适应控制。
This study presents a novel adaptive control based on a neural network for dc - dc converters. The control method is required to adapt to changes of conditions to obtain high performance dc-dc converters. In this study, the neural network control is adopted to improve the transient response of dc-dc converters. It woks in coordination with a conventional PID control to realize a high adaptive method. The neural network is trained with data which is obtained on-line. Therefore, the neural network control can adapt dynamically to change of input. The adaptation is realized by the modification of the reference in the PID control. The effect of the presented method is confirmed in simulations. Results show the presented method contributes to realize such adaptive control.