再入体气动参数的神经网络辨识方法

Identifiction Method with Neural Network For Dynamic Parameter of a Reentry Body

以某弹头六自由度数学模型为基础 ,介绍了飞行数据的产生及神经网络算法选择和学习步骤 .采用RBF网络增长型结构训练算法对某型号弹头再入段动力学模型的气动参数进行了辨识 ,用优化初始化权值的方法解决了训练时间长的问题 .

Producing flight data,selecting neural network algorithm and learning step are presented,based on six degree of freedom mathematical model of a warhead. The aerodynamic parameter of a reentry body’s dynamic model is identified by using the adding architecture with RBF network,and the long time training is short by optimizing the initial weights.The simulated results show that this method is workable well.