Reference modification control DC-DC converter with neural network predictor

Reference modification control DC-DC converter with neural network predictor
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带神经网络预测器的参考修正控制 DC-DC 转换器

DOI:
10.1109/compel.2012.6251806
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发表时间:
2012
期刊:
2012 IEEE 13th Workshop on Control and Modeling for Power Electronics (COMPEL)
影响因子:
--
通讯作者:
F. Kurokawa
F. Kurokawa
中科院分区:
--
文献类型:
--
作者:
H. Maruta;M. Motomura;K. Ueno;F. Kurokawa

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提出一种新的基于神经网络预测器的直流-直流变换器数字控制方法。在所提出的方法中,在传统的PID控制的比例控制项的参考修改使用的神经网络预测器在过渡期间。神经网络被反复训练,以使用先前的预测数据来预测输出电压,以用于参考的修改。在训练之后,预测器修改P控制中的参考以改善瞬态响应。与传统方法相比,该方法输出电压的下冲被抑制到41%。与传统方法相比,该方法的收敛速度提高了48%。因此,它被证实,所提出的方法具有上级性能控制的dc-dc转换器。
The purpose of this paper is to present a new digital control method for dc-dc converters by reference modification with the neural network predictor. In the proposed method, the reference in the proportional control term of the conventional PID control is modified using the neural network predictor during the transient interval. The neural network is repeatedly trained to predict the output voltage using former predicted data for the modification of the reference. After the training, the reference in the P control is modified by the predictor to improve the transient response. By using the proposed method, the undershoot of output voltage is suppressed to 41% compared with the conventional method's one. The convergence time is also improved to 48% compared with the conventional method's one. Therefore, it is confirmed that the proposed method has the superior performance to control dc-dc converters.
一种新型基于预测的数字控制DC-DC变换器
DOI: --
发表时间: 2010
期刊:
影响因子: --
作者:
塚田尚樹;千葉明;朝間淳一;深尾正;牧田大河;嶺岸茂樹,川又憲,監修:高木相;黒川不二雄
通讯作者: 黒川不二雄