SGKW轨道在线生成技术研究  

Research on technique of onboard trajectory generation for SGKW

作　　者：胡正东[1,2] 沈荟萍[2] 张士峰[2] 蔡洪[2] 

机构地区：[1]陆军武器装备体系研究国防科技重点实验室,北京100012 [2]国防科技大学航天与材料工程学院,长沙410073

出　　处：《固体火箭技术》2009年第6期591-595,共5页Journal of Solid Rocket Technology

基　　金：教育部新世纪优秀人才支持计划项目(NCET-05-0901);国防科技大学优秀研究生创新资助项目(B070103)

摘　　要：天基对地打击动能武器(SGKW)用于从太空对地面高价值战略目标进行快速、准确的打击。针对作战实时性要求,探讨了SGKW的轨道在线生成技术。首先,利用庞特里亚金极大值原理将时间最短打击轨道的最优控制问题转化为两点边值问题。由于约束条件中存在优化参数,一种基于"遗传算法+序列二次规划"的组合优化算法被用于求解伴随变量初值和再入点参数。为了提高轨道生成的速度,在大量离线优化数据的基础上建立了BP神经网络预测模型,其预测值通过序列二次规划算法稍加修正,即可满足相应任务的落点精度要求。仿真结果验证了上述方案的有效性。The space-to-ground kinetic weapon （SGKW）is mainly used to strike the ground strategic target with high worth rapidly and exactly from space. According to the combat requirement of reahime capability, a method of onboard trajectory generation for SGKW was discussed. Firstly the optimal control problem of minimum-time strike trajectory was translated into two-point-boundaryvalue problem by using Pontryagin maximum principle. Because optimization parameters were involved in the constraint conditions, a combined optimization algorithm based on genetic algorithm and sequential quadratic programming was used to calculate the initial value of costates and reentry parameters. To improve the rapidity of trajectory generation, BP neural networks were founded as predictive models based on abundant samples from offline optimization. Then the predictive results were corrected slightly by using sequential quadratic programming so that the falling precision of corresponding task could be achieved. Simulation results show effectiveness of the method presented.

关 键 词：天基对地打击动能武器 轨道在线生成 庞特里亚金极大值原理 时间最短打击轨道 遗传算法 序列二次规 划 BP神经网络 

分 类 号：V474.28[航空宇航科学与技术—飞行器设计]