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
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
Ma Kun, Cui Junfeng, Zhang Xiaoli, Wang Tao. The solar battery array thermal vacuum test model identification based on neural network[J]. Spacecraft Environment Engineering, 2012, 29(2): 150-153.
Citation: Ma Kun, Cui Junfeng, Zhang Xiaoli, Wang Tao. The solar battery array thermal vacuum test model identification based on neural network[J]. Spacecraft Environment Engineering, 2012, 29(2): 150-153.

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

The solar battery array thermal vacuum test model identification based on neural network

  • 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。

     

    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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