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空射近空间飞行器助推弹道规划方法
引用本文:杨 明,,刘 明,,郑 伟,高 兴,陈志刚.空射近空间飞行器助推弹道规划方法[J].弹道学报,2019,31(3):7-11.
作者姓名:杨 明    刘 明    郑 伟  高 兴  陈志刚
作者单位:1.国防科技大学 空天科学学院,湖南 长沙 410073; 2.空间物理重点实验室,北京 100076
摘    要:为研究空射近空间飞行器低弹道快速入轨弹道规划问题,将空射近空间飞行器助推弹道分为投放段、一级飞行段、无动力滑行段、二级飞行段。一级飞行段采用最大可用过载快速拉起; 二级飞行段纵向剖面采用基于分段多项式的参数化控制方法,二级飞行段横向剖面设计了基于三角函数的参数化能量管理; 形成了多段多约束参数化助推弹道规划模型,采用改进粒子群算法对该问题进行求解。仿真结果表明:规划弹道满足过载、控制及分离等各类约束条件; 该方法具有很高的求解精度和较快的求解速度,能获得满足不同交班需求的参考弹道。

关 键 词:空中发射  近空间飞行器  助推弹道  粒子群算法

Ascent Trajectory Planning for Air-launched Near Space Vehicle
YANG Ming,' target="_blank" rel="external">,LIU Ming,' target="_blank" rel="external">,ZHENG Wei,GAO Xing,CHEN Zhigang.Ascent Trajectory Planning for Air-launched Near Space Vehicle[J].Journal of Ballistics,2019,31(3):7-11.
Authors:YANG Ming  " target="_blank">' target="_blank" rel="external">  LIU Ming  " target="_blank">' target="_blank" rel="external">  ZHENG Wei  GAO Xing  CHEN Zhigang
Affiliation:1.College of Aerospace Science and Engineering,National University of Defense Technology,Changsha 410073,China; 2.Science and Technology on Space Physics Laboratory,Beijing 100076,China
Abstract:To study the planning approach of low-altitude rapid ascent trajectory for air-launched near-space vehicle,the ascent trajectory was divided into four phases such as dropping phase,the first powered phase,gliding phase and the second powered phase. To climb rapidly after the dropping,the maximum normal load was applied during the first powered phase. In order to satisfy the terminal constraints of the second powered phase,the time-varying longitudinal control variable was parameterized as a piece-wise polynomial,with a lateral energy management scheme based on triangle function. A parameter-programming problem with multiple phases and constraints was formulated,and the modified particle swarm optimization was employed to solve it. The simulation results show that the constraints of load,control and separation were well satisfied; this method can provide reference trajectories with high accuracy and computational efficiency for different constraints.
Keywords:air launching  near space vehicle  ascent trajectory  particle swarm optimization
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