摘要
大气制动技术是减少深空探测任务燃耗的重要手段.本文面向火星大气制动轨迹优化问题,提出了一种高精度火星大气制动轨迹快速优化方法.首先,构建了全维度非球形引力摄动动力学方程,并基于此完成了火星大气制动轨迹参数的敏感性分析,结果表明近火点高度在高精度模型下存在波动现象.然后,应用深度神经网络发展了大气制动轨迹参数快速估算方法,提出了受控火星大气制动轨迹优化模型,并采用遗传算法进行优化.数值仿真结果表明,本文所提方法较传统简化动力学方法在计算效率和精度方面优势明显.
Aerobraking technology is a significant way to save fuel for interplanetary missions,and has been employed several times for Mars missions.A novel intelligent optimization method is proposed in this study to achieve high-fidelity aerobraking trajectory for Mars missions.First,a full-dimensional,nonspherical gravitational perturbation dynamic model is derived;this model is employed to analyze the sensitivity of the Mars aerobraking trajectory.The results indicate that the periapsis altitude of the aerobraking trajectory is volatile rather than being a constant value under the high-fidelity dynamic model.Then,two deep neural networks are applied to replace the complex dynamic equations for efficiently approximating the parameters of the aerobraking trajectory.Finally,a controlled aerobraking trajectory optimization approach is introduced for Mars missions,and the genetic algorithm is used to optimize the control variables.The numerical simulation results verify the effectiveness of the proposed method and show its outstanding advantages with respect to efficiency and accuracy.
作者
杨彬
李爽
刘旭
黄旭星
黄翔宇
YANG Bin;LI Shuang;LIU Xu;HUANG XuXing;HUANG XiangYu(College of Astronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Advanced Space Technology Laboratory,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Beijing Institute of Control Engineering,Beijing 100190,China)
出处
《中国科学:技术科学》
EI
CSCD
北大核心
2020年第9期1185-1199,共15页
Scientia Sinica(Technologica)
基金
国家自然科学基金(批准号:11672126,61273051,61525301,61673057)
南京航空航天大学博士论文创新与创优基金(编号:BCXJ19-12)
空间智能控制技术实验室开放基金课题(编号:KGJZDSYS-2018-11)资助项目。
关键词
火星探测
大气制动
轨迹优化
神经网络
非球形引力摄动
Mars exploration
aerobraking
trajectory optimization
neural networks
nonspherical gravitational perturbation