摘要
轴对称飞行器在弹道设计与计算时的计算效率与计算精度难以兼顾,为了解决这一问题,提出了一种基于径向基函数(简称RBF)神经网络的轴对称飞行器弹道设计方法。该方法通过构建RBF神经网络来模拟复杂的弹道计算模型,在对该神经网络进行适当的学习训练之后,即可用来进行快速弹道设计与计算。仿真算例表明:该方法可行且运算效率较高,计算结果与工程实际结果吻合较好。
In order to solve the conflict between computing efficiency and computing precision in the trajectory design and computation of the axisymmetric vehicle, a new trajectory design method based on Radial Basis Function（RBF） is proposed. It simulates and approaches the complicated trajectory computing model by building RBF Neural Network, and it could be used for fast trajectory design and computation after the RBF Neural Network is trained properly. The example results show that the RBF Neural Network is applicable to the axisymmetric vehicle trajectory design and has great efficiency, and its computing results agree well with the actual engineering results.
出处
《导弹与航天运载技术》
北大核心
2014年第4期9-13,共5页
Missiles and Space Vehicles
关键词
弹道设计
径向基函数
神经网络
Trajectory design
Radial basis function
Neural Network
