| 基于神经网络的太阳电池阵热真空试验外热流模拟系统辨识 |
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| 引用本文： | 马 昆,崔俊峰,张晓丽,王 涛.基于神经网络的太阳电池阵热真空试验外热流模拟系统辨识[J].航天器环境工程,2012,29(2):150-153. |
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| 作者姓名： | 马 昆 崔俊峰 张晓丽 王 涛 |
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| 作者单位： | 北京卫星环境工程研究所,北京100094 |
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| 摘 要： | 文章针对太阳电池阵热真空试验非线性的特点,引入一种基于神经网络的系统辨识方法。该方法采用BP网络作为模型辨识器,而辨识器又采用L-M(Levenberg-Marquart)算法进行训练。仿真结果表明,该方法具有较高的训练速度与精度,可以对太阳电池阵热真空试验测点温度响应做出较为精确的预测。
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| 关 键 词： | 热真空试验 BP神经网络 L-M算法 太阳电池阵 |
| 收稿时间： | 2011/11/14 0:00:00 |
| 修稿时间： | 4/1/2012 12:00:00 AM |
The solar battery array thermal vacuum test model identification based on neural network |
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| Ma Kun,Cui Junfeng,Zhang Xiaoli and Wang Tao.The solar battery array thermal vacuum test model identification based on neural network[J].Spacecraft Environment Engineering,2012,29(2):150-153. |
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| Authors: | Ma Kun Cui Junfeng Zhang Xiaoli and Wang Tao |
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| Institution: | (Beijing Institute of Spacecraft Environment Engineering,Beijing 100094,China) |
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| Abstract: | In view of the nonlinear characteristics of the solar cell array in thermal vacuum tests,an identification method based on the neural network is proposed.The neural network is trained by the Levenberg-Marquart algorithm.The simulation results show that the system can achieve a fast identification and with a high precision,and the temperature response at the measurement point on the solar array can be predicted. |
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| Keywords: | thermal vacuum test BP neural network Levenberg-Marquart algorithm solar cell array |
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