CAJ | 학술논문

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。
축대칭비행기재탄도설계여계산시적계산효솔여계산정도난이겸고，위료해결저일문제，제출료일충기우경향기함수（간칭RBF）신경망락적축대칭비행기탄도설계방법。해방법통과구건RBF신경망락래모의복잡적탄도계산모형，재대해신경망락진행괄당적학습훈련지후，즉가용래진행쾌속탄도설계여계산。방진산례표명：해방법가행차운산효솔교고，계산결과여공정실제결과문합교호。
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.