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基于多目标优化的深空探测器姿态组合规划方法

王卓 徐瑞

王卓, 徐瑞. 基于多目标优化的深空探测器姿态组合规划方法[J]. 深空探测学报(中英文). doi: 10.15982/j.issn.2096-9287.2021.20200069
引用本文: 王卓, 徐瑞. 基于多目标优化的深空探测器姿态组合规划方法[J]. 深空探测学报(中英文). doi: 10.15982/j.issn.2096-9287.2021.20200069
WANG Zhuo, XU Rui. Combination Planning for Attitude Maneuver of Deep Space Probes based on Multi-objective Optimization[J]. Journal of Deep Space Exploration. doi: 10.15982/j.issn.2096-9287.2021.20200069
Citation: WANG Zhuo, XU Rui. Combination Planning for Attitude Maneuver of Deep Space Probes based on Multi-objective Optimization[J]. Journal of Deep Space Exploration. doi: 10.15982/j.issn.2096-9287.2021.20200069

基于多目标优化的深空探测器姿态组合规划方法

doi: 10.15982/j.issn.2096-9287.2021.20200069
基金项目: 国家重点研发计划资助项目(2019YFA0706500);国家自然科学基金资助项目(61976020)
详细信息
    作者简介:

    王卓(1994– ),男,博士研究生,主要研究方向:航天器任务规划、自主导航、智能控制。通讯地址:北京理工大学宇航学院22号信(100081)E-mail:54168870@qq.com通信作者:

    徐 瑞(1975– ),男,教授,博士生导师,主要研究方向:航天器任务规划、自主导航、智能控制。本文通讯作者。通讯地址:北京市海淀区中关村南大街5号 北京理工大学宇航学院22号信箱(100081)E-mail: xurui@bit.edu.cn

  • ● Multi-objective optimization of time and energy for attitude maneuver of deep space probe is studied. ● The multi-objective optimization is transformed into single objective programming to replace fitness function as the population selection criterion of differential evolution. ● The initial attitude path obtained by the fast Euler maneuver is added to the variation formula with the set probability to improve the variation process of differential evolution. ● The combined differential evolution algorithm is designed to improve the convergence rate and the efficiency of the program.
  • 中图分类号: V467.3

Combination Planning for Attitude Maneuver of Deep Space Probes based on Multi-objective Optimization

  • 摘要: 深空探测器在执行姿态机动任务中,通常需要优化多个性能指标参数。此外,姿态指向约束和有界约束的存在显著减小了姿态机动路径的可行空间。在复杂的多约束条件下,多目标姿态机动优化对深空探测器系统是一个极大的挑战。提出多目标组合的概念,通过物理规划方法将多目标优化转换为单目标规划问题。考虑到欧拉路径的低能量特性,提出一种多目标组合规划方法,通过欧拉路径改进差分进化算法的变异过程,实现多约束多目标姿态机动路径组合规划。最后,对深空探测器大角度姿态机动进行多目标组合规划数值仿真,验证了该方法的可行性和有效性。
    Highlights
    ● Multi-objective optimization of time and energy for attitude maneuver of deep space probe is studied. ● The multi-objective optimization is transformed into single objective programming to replace fitness function as the population selection criterion of differential evolution. ● The initial attitude path obtained by the fast Euler maneuver is added to the variation formula with the set probability to improve the variation process of differential evolution. ● The combined differential evolution algorithm is designed to improve the convergence rate and the efficiency of the program.
  • 图  1  深空探测器指向约束示意图

    Fig.  1  Schematic diagram of pointing constraint of deep space probe

    图  2  深空探测器姿态四元数曲线

    Fig.  2  Attitude maneuver quaternion curve of deep space probe

    图  3  深空探测器控制力矩曲线

    Fig.  3  Attitude maneuver control torque curve of deep space probe

    图  4  深空探测器角速度曲线

    Fig.  4  Attitude maneuver angular velocity curve of deep space probe

    图  5  探测器在天球坐标系下姿态机动路径

    Fig.  5  Attitude maneuver path of deep space probe in celestial coordinate system

    图  6  天球坐标系下深空探测器可见光相机空间姿态机动路径

    Fig.  6  Space attitude maneuver path of visible camera of deep space detector in celestial coordinate system

    表  1  仿真条件

    Table  1  Simulation conditions

    变量
    J/(kg·m2diag(100,100,100)
    q0[0.646,0.034,0.722,0.241]T
    ω0/(rad•s–1[0,0,0]
    qf[0.733,0.362,–0.544,0.181]T
    ωf/(rad•s–1[0,0,0]
    ${ {{\gamma} } _\omega } //(rad•s-1)$0.05 rad/s
    $ { {{\gamma} } _u} / {\rm Nm}$0.1
    θ1/(°)40
    θ2/(°)30
    θ3/(°)30°
    θ4/(°)25
    rgI[0,0,1]T
    rI1 [–0.76,0,0.64]T
    rI2 [0.49,0.85,0.17]T
    rI3 [0.64,–0.76,0]T
    rI4 [0.76,0,0.64]T
    下载: 导出CSV
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  • 收稿日期:  2020-10-20
  • 修回日期:  2020-12-10
  • 网络出版日期:  2021-05-12

基于多目标优化的深空探测器姿态组合规划方法

doi: 10.15982/j.issn.2096-9287.2021.20200069
    基金项目:  国家重点研发计划资助项目(2019YFA0706500);国家自然科学基金资助项目(61976020)
    作者简介:

    王卓(1994– ),男,博士研究生,主要研究方向:航天器任务规划、自主导航、智能控制。通讯地址:北京理工大学宇航学院22号信(100081)E-mail:54168870@qq.com通信作者:

    徐 瑞(1975– ),男,教授,博士生导师,主要研究方向:航天器任务规划、自主导航、智能控制。本文通讯作者。通讯地址:北京市海淀区中关村南大街5号 北京理工大学宇航学院22号信箱(100081)E-mail: xurui@bit.edu.cn

  • ● Multi-objective optimization of time and energy for attitude maneuver of deep space probe is studied. ● The multi-objective optimization is transformed into single objective programming to replace fitness function as the population selection criterion of differential evolution. ● The initial attitude path obtained by the fast Euler maneuver is added to the variation formula with the set probability to improve the variation process of differential evolution. ● The combined differential evolution algorithm is designed to improve the convergence rate and the efficiency of the program.
  • 中图分类号: V467.3

摘要: 深空探测器在执行姿态机动任务中,通常需要优化多个性能指标参数。此外,姿态指向约束和有界约束的存在显著减小了姿态机动路径的可行空间。在复杂的多约束条件下,多目标姿态机动优化对深空探测器系统是一个极大的挑战。提出多目标组合的概念,通过物理规划方法将多目标优化转换为单目标规划问题。考虑到欧拉路径的低能量特性,提出一种多目标组合规划方法,通过欧拉路径改进差分进化算法的变异过程,实现多约束多目标姿态机动路径组合规划。最后,对深空探测器大角度姿态机动进行多目标组合规划数值仿真,验证了该方法的可行性和有效性。

注释:
1)  ● Multi-objective optimization of time and energy for attitude maneuver of deep space probe is studied. ● The multi-objective optimization is transformed into single objective programming to replace fitness function as the population selection criterion of differential evolution. ● The initial attitude path obtained by the fast Euler maneuver is added to the variation formula with the set probability to improve the variation process of differential evolution. ● The combined differential evolution algorithm is designed to improve the convergence rate and the efficiency of the program.

English Abstract

王卓, 徐瑞. 基于多目标优化的深空探测器姿态组合规划方法[J]. 深空探测学报(中英文). doi: 10.15982/j.issn.2096-9287.2021.20200069
引用本文: 王卓, 徐瑞. 基于多目标优化的深空探测器姿态组合规划方法[J]. 深空探测学报(中英文). doi: 10.15982/j.issn.2096-9287.2021.20200069
WANG Zhuo, XU Rui. Combination Planning for Attitude Maneuver of Deep Space Probes based on Multi-objective Optimization[J]. Journal of Deep Space Exploration. doi: 10.15982/j.issn.2096-9287.2021.20200069
Citation: WANG Zhuo, XU Rui. Combination Planning for Attitude Maneuver of Deep Space Probes based on Multi-objective Optimization[J]. Journal of Deep Space Exploration. doi: 10.15982/j.issn.2096-9287.2021.20200069
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