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基于改进鸽群算法的气动捕获轨道优化
引用本文:吴爱国,巩志浩. 基于改进鸽群算法的气动捕获轨道优化[J]. 航空学报, 2020, 41(9): 324292-324292. DOI: 10.7527/S1000-6893.2020.24292
作者姓名:吴爱国  巩志浩
作者单位:哈尔滨工业大学(深圳), 机电工程与自动化学院, 深圳 518055
基金项目:广东省自然科学基金;中央高校基本科研业务费专项资金;国家自然科学基金优秀青年科学基金;深圳市基础研究学科布局项目
摘    要:针对火星探测器的气动捕获轨道,提出了一种改进的鸽群算法对气动捕获轨道进行优化。首先,考虑成功进行气动捕获所要求的终端约束和过程约束,根据从捕获轨道进行轨道转移进入目标轨道所需的速度增量,提出了进行捕获轨道优化的最优性能指标。然后,针对原始鸽群算法存在的一些不足,提出一种改进算法,并对改进算法的参数取值进行了分析。最后,基于大气内飞行的动力学方程,将气动捕获轨道优化问题转化为多参数优化问题,利用所提出的改进鸽群算法对气动捕获轨道进行优化,并通过仿真实例验证该算法的有效性。

关 键 词:火星探测器  气动捕获轨道  轨道优化  改进鸽群算法  多参数优化  
收稿时间:2020-05-20
修稿时间:2020-05-30

Optimization of aerocapture orbit based on improved pigeon inspired optimization algorithms
WU Aiguo,GONG Zhihao. Optimization of aerocapture orbit based on improved pigeon inspired optimization algorithms[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(9): 324292-324292. DOI: 10.7527/S1000-6893.2020.24292
Authors:WU Aiguo  GONG Zhihao
Affiliation:School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
Abstract:An improved pigeon-inspired algorithm is proposed to optimize the aerocapture orbits of Mars explorers. The terminal and process constraints imposed by successful aerocapture are first analyzed, followed by the introduction of an appropriate performance index for the optimization of the capture orbit according to the speed increment required by the orbit transfer from the capture orbit to the target orbit. Then, to overcome the shortcomings of the original pigeon-inspired algorithm, an improved version is proposed by introducing an exponential function. The functions of the parameters in the improved algorithm are analyzed. Finally, based on the dynamic equations of flight in the atmosphere, the aerocapture orbital optimization problem is transformed into a multi-parameter optimization problem which is solved by the proposed improved pigeon inspired algorithm. The effectiveness of this algorithm is verified by a simulation example.
Keywords:Mars explorers  aerocapture orbital  orbital optimization  improved pigeon inspired optimization algorithm  multi-parameter optimization  
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