Design and optimization of a space net capture system based on a multi-objective evolutionary algorithm

被引:15
|
作者
Chen, Qingquan [1 ]
Zhang, Qingbin [1 ]
Gao, Qingyu [1 ]
Feng, Zhiwei [1 ]
Tang, Qiangang [1 ]
Zhang, Guobin [1 ]
机构
[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, 109 Deya Rd, Changsha 410073, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Active debris removal; Net capture system; Multi-objective optimization; Lumped parameter method; Flexible dynamics;
D O I
10.1016/j.actaastro.2019.11.003
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Space net capture is an innovative concept for active debris removal that provides a prospective method for the removal of large, non-cooperative space targets. The design of a space net capture system must meet two basic requirements: maximizing the capture ability and minimizing the system cost. This paper presents an inexpensive multi-objective optimization framework to solve this design problem. In this framework, a design optimization approach using a lumped parameter modelling method as well as an improved inexpensive multi-objective optimization algorithm is proposed. The system mass and effective distance are chosen as objectives of this optimization problem. The simulation results reveal that the multi-objective optimization framework is feasible and effective for the design of a space net capture system, and the designer preferred solutions that enhance system design are reliably identified.
引用
收藏
页码:286 / 295
页数:10
相关论文
共 50 条
  • [21] An evolutionary algorithm for dynamic multi-objective optimization
    Wang, Yuping
    Dang, Chuangyin
    APPLIED MATHEMATICS AND COMPUTATION, 2008, 205 (01) : 6 - 18
  • [22] An evolutionary algorithm for constrained multi-objective optimization
    Jiménez, F
    Gómez-Skarmeta, AF
    Sánchez, G
    Deb, K
    CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2002, : 1133 - 1138
  • [23] An new evolutionary multi-objective optimization algorithm
    Mu, SJ
    Su, HY
    Chu, J
    Wang, YX
    CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 914 - 920
  • [24] Dynamic multi-objective optimization evolutionary algorithm
    Liu, Chun-an
    Wang, Yuping
    ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS, 2007, : 456 - +
  • [25] Dynamical multi-objective optimization evolutionary algorithm
    Xiong, SW
    Li, F
    Wang, W
    Feng, C
    THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 418 - 421
  • [26] Evolutionary multi-objective optimization algorithm with expert rules for mechanical design
    Wang, JW
    Zhang, JM
    Wei, XP
    Wang, J
    Proceedings of the International Conference on Mechanical Engineering and Mechanics 2005, Vols 1 and 2, 2005, : 179 - 182
  • [27] Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm
    Ming, Mengjun
    Wang, Rui
    Zha, Yabing
    Zhang, Tao
    ENERGIES, 2017, 10 (05)
  • [28] An orthogonal multi-objective evolutionary algorithm for multi-objective optimization problems with constraints
    Zeng, SY
    Kang, LSS
    Ding, LXX
    EVOLUTIONARY COMPUTATION, 2004, 12 (01) : 77 - 98
  • [29] A dynamic multi-objective evolutionary algorithm based on an orthogonal design
    Zeng, Sang-you
    Chen, Guang
    Zheng, Liang
    Shi, Hui
    de Garis, Hugo
    Ding, Lixin
    Kang, Lishan
    2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6, 2006, : 573 - +
  • [30] Ship hull-propeller system optimization based on the multi-objective evolutionary algorithm
    Ghassemi, Hassan
    Zakerdoost, Hassan
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2017, 231 (01) : 175 - 192