基于改进鸽群算法的气动捕获轨道优化

吴爱国; 巩志浩

doi:10.7527/S1000-6893.2020.24292

航空学报 >

2020 , Vol. 41 >Issue 9: 324292 - 324292

DOI: https://doi.org/10.7527/S1000-6893.2020.24292

电子电气工程与控制

基于改进鸽群算法的气动捕获轨道优化

吴爱国 ,
巩志浩

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哈尔滨工业大学(深圳), 机电工程与自动化学院, 深圳 518055

收稿日期: 2020-05-20

修回日期: 2020-05-30

网络出版日期: 2020-06-18

基金资助

国家自然科学基金优秀青年科学基金（61822305）；中央高校基本科研业务费专项资金（HIT.BRETIV.201907）；深圳市基础研究学科布局项目（JCYJ20180507183437860，JCYJ20170811160715620）；广东省自然科学基金（2020A1515011091，2019A151-5011576）

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Optimization of aerocapture orbit based on improved pigeon inspired optimization algorithms

WU Aiguo ,
GONG Zhihao

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School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China

Received date: 2020-05-20

Revised date: 2020-05-30

Online published: 2020-06-18

Supported by

National Natural Science Foundation of China for Excellent Young Scholars (61822305);the Fundamental Research Funds for the Central Universities (HIT.BRETIV.2019); Shenzhen Municipal Project for Discipline Layout (JCYJ20180507183437860, JCYJ20170811160715620); Natural Science Foudation of Guangdong Province (2020A1515011091, 2019A1515011576)

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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

本文引用格式

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

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.

Key words： Mars explorers; aerocapture orbital; orbital optimization; improved pigeon inspired optimization algorithm; multi-parameter optimization

参考文献

[1] HOWARD S. Change of satellite orbit plane by aerodynamic maneuvering[J]. Journal of the Aerospace Sciences, 1962, 29(3):323-332.
[2] AI Y H, CUI H T, ZHENG Y Y. Identifying method of entry and exit conditions for aerocapture with near Minimum fuel consumption[J]. Aerospace Science and Technology, 2016, 58:582-593.
[3] BETTS J T. Survey of numerical methods for trajectory optimization[J]. Journal of Guidance, Control, and Dynamics, 1998, 21(2):193-207.
[4] JORRIS T R, COBB R G. Multiple method 2-D trajectory optimization satisfying waypoints and nofly zone constraints[J]. Journal of Guidance, Control, and Dynamics, 2008, 31(3):543-553.
[5] 周浩, 周韬, 陈万春, 等. 高超声速滑翔飞行器引入段弹道优化[J]. 宇航学报, 2006, 27(5):970-973. ZHOU H, ZHOU T, CHEN W C, et al. Trajectory optimization in injection phase for hypersonic gliding vehicle[J]. Journal of Astronautics, 2006, 27(5):970-973(in Chinese).
[6] 陈功, 傅瑜, 郭继峰. 飞行器轨迹优化方法综述[J]. 飞行力学, 2011, 29(4):1-5. CHEN G, FU Y, GUO J F. Survey of aircraft trajectory optimization methods[J]. Flight Dynamics, 2011, 29(4):1-5(in Chinese).
[7] HARGRAVES C, JOHNSON F, PARIS S, et al. Numerical computation of optimal atmospheric trajectories[J]. Journal of Guidance, Control and Dynamics, 1981, 4(4):406-414.
[8] HARGRAVES C, JOHNSON F, PARIS S, et al. Direct trajectory optimization using nonlinear programming and collocation[J]. Journal of Guidance, Control, and Dynamics, 1987, 10(4):338-342.
[9] TIAN B L, ZONG Q. Optimal guidance for reentry vehicles based on indirect legendre pseudospectral method[J]. Acta Astronautica, 2011, 68(7-8):1176-1184.
[10] HARGRAVES C, JOHNSON F, PARIS S, et al. Numerical computation of optimal atmospheric trajectories[J]. Journal of Guidance, Control and Dynamics, 1981, 4(4):406-414.
[11] 王铀, 赵辉, 惠百斌, 等. 利用Radau伪谱法求解UCAV对地攻击轨迹研究[J]. 电光与控制, 2012, 19(10):50-53. WANG Y, ZHAO H, HUI B B, et al. Air-to-ground trajectory planning for UCAVs using a radau pseudo-spectral method[J]. Electronics Optics & Control, 2012, 19(10):50-53(in Chinese).
[12] RAHIMI A, DEV K K, ALIGHANBARI, et al. Swarm optimization applied to spacecraft reentry trajectory[J]. Journal of Guidance, Control, and Dynamics, 2012, 36(1):307-310.
[13] PONTANI M, CONWAY B A. Particle swarm optimization applied to space trajectories trajectory[J]. Journal of Guidance, Control, and Dynamics, 2010, 33(5):1429-1441.
[14] YOKOYAMA N, SUZUKI S. Modifled genetic algorithm for constrained trajectory optimization[J]. Journal of Guidance, Control, and Dynamics, 2005, 28(1):139-144.
[15] LI Y T, WU Y, QU X J. Chicken swarm-based method for ascent trajectory optimization of hypersonic vehicles[J]. Journal of Aerospace Engineering, 2017, 30(5):04017043.
[16] DUAN H B, QIAO P X. Pigeon-inspired optimization:A new swarm intelligence optimizer for air robot path planning[J]. International Journal of Intelligence Computing and Cybernetics, 2014, 7:24-37.
[17] 段海滨, 邱华鑫, 范彦铭. 基于捕食逃逸鸽群优化的无人机紧密编队协调控制[J]. 中国科学:技术科学, 2015, 45(6):559-572. DUAN H B, QIU H X, FAN Y M. Unmanned aerial vehicle close formation cooperative control based on predatory escaping pigeon-inspired optimization[J]. Scientia Sinica Technologica, 2015, 45(6):559-572(in Chinese).
[18] 华冰, 刘睿鹏, 孙胜刚, 等. 一种基于自适应种群变异鸽群优化的航天器集群轨道规划方法[J]. 中国科学:技术科学, 2020, 50(4):453-460. HUA B, LIU R P, SUN S G, et al. Spacecraft cluster orbit planning method based on adaptive population mutated pigeon group optimization[J]. Scientia Sinica Technologica, 2020, 50(4):453-460(in Chinese).
[19] SUSHNIGDHA G, JOSHI A. Trajectory design of re-entry vehicles using combined pigeon inspired optimization and orthogonal collocation method[J]. IFAC Papers OnLine, 2018, 51(1):656-662.
[20] 徐博, 张大龙. 基于量子行为鸽群优化的无人机紧密编队控制[J]. 航空学报, 2020, 41(8):323722. XU B,ZHANG D L. Close formation control of UAV Based on pigeon group optimization of quantum behavior[J].Acta Aeronautica et Astronautica Sinica, 2020, 41(8):323722(in Chinese).
[21] VINH N X, BUSEMANN A, CULP R D. Hypersonic and planetary entry flight mechanics:NASA STI/RECON Technical Report A[R].Wshington, D.C.:NASA, 1980.

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