空气动力学学报2024，Vol.42Issue(3)：92-101,10.DOI:10.7638/kqdlxxb-2023.0087
考虑强风干扰的固定翼飞行器"神经元"飞行气动建模
Aerodynamic modeling of"Neural"-Fly for fixed-wing aircraft considering strong wind interference
周晓雨 1黄江涛 1章胜 1刘刚2
作者信息
- 1. 中国空气动力研究与发展中心空天技术研究所,绵阳 621000
- 2. 中国空气动力研究与发展中心,绵阳 621000
- 折叠
摘要
Abstract
The strong and unsteady wind imposes severe challenges to the safe flight and aerodynamic prediction of the fixed-wing aircraft.Traditional aerodynamic models established in the wind-oriented coordinate system have a clear physical meaning but cannot be readily applied to unsteady windy environments.This paper proposes an innovative"neural"-fly aerodynamic modeling method based on deep meta-learning to accurately predict the aerodynamic forces and moments online for fixed-wing aircraft subjected to strong and unsteady wind.Based on variables in a coordinate system relative to the ground,this method decomposes the aerodynamic forces and moments into the sum of polynomial multiplication and constructs the common aerodynamic base functions by a three-step deep meta-learning algorithm using the Generative Adversarial Network.The application of the method for the fixed-wing aircraft F-18 demonstrates that the method can accurately predict the aerodynamic forces and moments under unknown wind conditions,laying a good foundation for real-time aerodynamic modeling.关键词
固定翼飞行器/气动力建模/神经元飞行/生成对抗网络/共性基函数Key words
fixed-wing aircraft/aerodynamic modeling/neural-fly/generative adversarial network/generic base分类
航空航天引用本文复制引用
周晓雨,黄江涛,章胜,刘刚..考虑强风干扰的固定翼飞行器"神经元"飞行气动建模[J].空气动力学学报,2024,42(3):92-101,10.
