引用本文: | 白宏阳,李伟明,孙瑞胜,等.航空时敏制导炸弹增程弹道组合优化设计.[J].国防科技大学学报,2014,36(6):100-105.[点击复制] |
BAI Hongyang,LI Weiming,SUN Ruisheng,et al.Trajectory combinatorial optimization design for airborne time sensitive guided bombs in extended range period[J].Journal of National University of Defense Technology,2014,36(6):100-105[点击复制] |
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航空时敏制导炸弹增程弹道组合优化设计 |
白宏阳1,2, 李伟明3, 孙瑞胜1, 熊舒望1 |
(1. 南京理工大学 能源与动力工程学院, 江苏 南京 210094;2.
2国防科技大学 航天科学与工程学院,湖南 长沙 410073;3.山东航天电子技术研究所,山东 烟台 264003)
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摘要: |
为增强航空时敏制导炸弹在中制导段的滑翔能力,将极小值原理与自适应进化粒子群算法相结合,提出了一种适用于航空时敏制导炸弹增程弹道的组合优化设计方法。基于纵向平面内质心运动模型,推导了性能指标泛函及各不等式约束函数。引入Lagrange乘子矢量并建立相应的Hamilton函数实现无约束泛函极值问题的转换,推导出兼顾各优化目标函数的满意优化模型。利用自适应进化粒子群算法对该段增程弹道进行了攻角与弹翼张合档位双设计变量的组合优化。数值仿真算例表明,在满足状态方程约束的条件下,双变量的增程效果比常规单变量控制时显著提高,其优化结果可为制导炸弹弹道规划设计的研究提供一定的理论参考。 |
关键词: 时敏制导炸弹 弹道组合优化 自适应进化粒子群 最优控制 |
DOI:10.11887/j.cn.201406018 |
投稿日期:2014-07-27 |
基金项目:国家自然科学基金资助项目(11176072);中国博士后基金(2014M562568) |
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Trajectory combinatorial optimization design for airborne time sensitive guided bombs in extended range period |
BAI Hongyang1,2, LI Weiming3, SUN Ruisheng1, XIONG Shuwang1 |
(1.School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;2.
2.College of Aerospace Science and Engineering,National University of Defense Technology,Changsha 410073,China;3.Shandong Institute of Aerospace Electronic Technology, Yantai 264003, China)
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Abstract: |
In order to improve the gliding ability in mid-course trajectory of the aerial time-sensitive guided bombs, a combinatorial optimization design method which can be applied to the extended-range project of aerial time-sensitive guided bombs was proposed by combining the minimum principle with the adaptive evolutionary particle swarm algorithm. In the base of the model of mass-centre motion in longitudinal plane, performance index function and inequality constraint functions were derived. Hamilton equation was established by introducing Lagrange multiplier vectors to convert the unconstrained functional extremum problem and deduce the satisfactory optimization model which gave consideration to all optimization object functions. By means of the adaptive evolutionary particle swarm algorithm, double design variables, attack angle and wing gears, of extended trajectory were optimized combinatorially. The simulation results indicate that the range of the guided bombs controlled by double variables is obviously more than that of bombs controlled by single variable as long as the constraint condition of state equation is satisfied. The optimization results have reference value for trajectory design of guided bombs. |
Keywords: time sensitive guided bombs trajectory combinatorial optimization adaptive evolutionary particle swarm optimal control |
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