脉冲推力下多星协同搬运的预测博弈控制

doi:10.7527/S1000-6893.2021.26112

电子电气工程与控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

脉冲推力下多星协同搬运的预测博弈控制

柴源^1,2, 罗建军^1,2, 王明明^1,2

1. 西北工业大学航天学院, 西安 710072;
2. 西北工业大学航天飞行动力学技术重点实验室, 西安 710072

收稿日期:2021-07-15 修回日期:2021-08-12 发布日期:2021-09-22
通讯作者: 罗建军,E-mail:jjluo@nwpu.edu.cn E-mail:jjluo@nwpu.edu.cn
基金资助:
国家自然科学基金（12072269，61690210，61690211）；西北工业大学博士论文创新基金（CX202020）

Predictive game control for on-orbit transportation by multiple microsatellites with impulsive thrust

CHAI Yuan^1,2, LUO Jianjun^1,2, WANG Mingming^1,2

1. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi'an 710072, China

Received:2021-07-15 Revised:2021-08-12 Published:2021-09-22
Supported by:
National Natural Science Foundation of China (12072269, 61690210, 61690211);Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (CX202020)

摘要/Abstract

摘要： 在轨装配过程中，为了将装配结构运输到装配主体结构附近的期望位置，利用多个微小卫星进行协同搬运。针对多星协同搬运的轨道转移控制问题，为满足多种控制约束的同时减少星载燃料和通信资源消耗，研究了脉冲推力下的多星自主博弈控制方法。考虑到各个微小卫星的独立性和协同性，以相对轨道动力学为模型、以控制精度和能量消耗的二次型为局部目标函数构建多星博弈问题，个体能够通过局部目标函数的优化获得控制策略，避免了传统集中式方法所需的控制分配。鉴于微小卫星的控制能力以及通信能力，引入脉冲推力形式并将其与控制幅值约束合并描述为存在周期及幅值限制的力约束，与避免干扰姿态的力矩约束一起作为多星博弈问题的控制约束，相较于连续推力形式便于实施。在多约束博弈求解方面，设计了预测博弈控制算法来分布式地逼近纳什均衡策略，将计算负担分散在各个微小卫星之间的同时提高了方法的容错性。最后，数值仿真表明：所提出的脉冲推力下的预测博弈控制方法能够在满足多种控制约束条件下使得装配结构达到期望状态，在燃料消耗和通信压力等方面显著优于传统集中式方法。

关键词: 协同搬运, 微分博弈, 脉冲推力, 模型预测控制, 微小卫星

Abstract: During on-orbit assembly, multiple microsatellites are employed to transport the assembly structure collaboratively to the desired location near the main assembly structure. To meet several constraints of orbit transfer control during cooperative transportation and reduce consumption of onboard resources, the game-based control method for multiple microsatellites with impulse thrust is studied. Considering the independence and cooperativity of each microsatellite, a game model for cooperative transportation is constructed by taking relative orbital dynamics as the model and the quadratic form of control accuracy and energy consumption as the local objective function. Each microsatellite can optimize the local objective function to obtain the control strategy, avoiding the control allocation required by the traditional centralized method. In view of the control ability and communication ability of microsatellites, the impulse thrust is introduced, which is easier to implement than the continuous thrust. The impulse thrust is combined with the control amplitude constraint as a force constraint with periodic and amplitude restriction, and is taken, together with the torque constraint for avoiding disturbing the attitude, as the control constraints of the game model. To solve the multi-constraint game problem, a predictive game control algorithm is designed to approach the Nash equilibrium strategy in a distributed manner, which distributes the computational burden among microsatellites and improves fault tolerance of the method. Numerical simulation shows that the proposed control method can effectively deal with several control constraints, and is significantly better than the traditional centralized method in terms of fuel consumption and communication pressure.

Key words: collaborative transportation, differential game, impulse thrust, model predictive control, microsatellite

中图分类号:

V448.2

柴源, 罗建军, 王明明. 脉冲推力下多星协同搬运的预测博弈控制[J]. 航空学报, 2022, 43(12): 326112-326112.

CHAI Yuan, LUO Jianjun, WANG Mingming. Predictive game control for on-orbit transportation by multiple microsatellites with impulsive thrust[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(12): 326112-326112.

参考文献

[1] OEGERLE W R, PURVES L R, BUDINOFF J G, et al. Concept for a large scalable space telescope:In-space assembly[C]//SPIE Astronomical Telescopes + Instrumentation. Proc SPIE 6265, Space Telescopes and Instrumentation I:Optical, Infrared, and Millimeter, 2006:755-766.
[2] DATASHVILI L, ENDLER S, WEI B, et al. Study of mechanical architectures of large deployable space antenna apertures:From design to tests[J]. CEAS Space Journal, 2013, 5(3):169-184.
[3] 郭继峰, 王平, 崔乃刚. 大型空间结构在轨装配技术的发展[J]. 导弹与航天运载技术, 2006(3):28-35. GUO J F, WANG P, CUI N G. Development of on-orbit assembly of large space structures[J]. Missiles and Space Vehicles, 2006(3):28-35(in Chinese).
[4] LILLIE C F. On-orbit assembly and servicing of future space observatories[C]//SPIE Astronomical Telescopes + Instrumentation. Proc SPIE 6265, Space Telescopes and Instrumentation I:Optical, Infrared, and Millimeter, 2006:767-778.
[5] JAEGER T, MIRCZAK W. Phoenix and the new satellite paradigm created by HISat:SSC14 VII-6[R]. Logan:Utah State University, 2014
[6] KORTMANN M, SCHERVAN T A, SCHMIDT H, et al. Building block-based "iBOSS" approach:Fully modular systems with standard interface to enhance future satellites[C]//66nd International Astronautical Congress, Jerusalem. Aachen:RWTH Aachen University, 2015:1-11.
[7] LIU G P, ZHANG S J. A survey on formation control of small satellites[J]. Proceedings of the IEEE, 2018, 106(3):440-457.
[8] CHEN Z Y, EMAMI M R, CHEN W C. Connectivity preservation and obstacle avoidance in small multi-spacecraft formation with distributed adaptive tracking control[J]. Journal of Intelligent & Robotic Systems, 2021, 101(1):16.
[9] HAN N, LUO J J, MA W H, et al. Integrated identification and control for nanosatellites reclaiming failed satellite[J]. Acta Astronautica, 2018, 146:387-398.
[10] CHANG H T, HUANG P F, ZHANG Y Z, et al. Distributed control allocation for spacecraft attitude takeover control via cellular space robot[J]. Journal of Guidance, Control, and Dynamics, 2018, 41(11):2499-2506.
[11] ABOUHEAF M I, LEWIS F L, VAMVOUDAKIS K G, et al. Multi-agent discrete-time graphical games and reinforcement learning solutions[J]. Automatica, 2014, 50(12):3038-3053.
[12] LIN W. Distributed UAV formation control using differential game approach[J]. Aerospace Science and Technology, 2014, 35:54-62.
[13] MYLVAGANAM T, SASSANO M, ASTOLFI A. A differential game approach to multi-agent collision avoidance[J]. IEEE Transactions on Automatic Control, 2017, 62(8):4229-4235.
[14] 王雨琪, 宁国栋, 王晓峰, 等. 基于微分对策的临近空间飞行器机动突防策略[J]. 航空学报, 2020, 41(S2):724276. WANG Y Q, NING G D, WANG X F, et al. Maneuver penetration strategy of near space vehicle based on differential game[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S2):724276(in Chinese).
[15] 柴源, 罗建军, 韩楠, 等. 失效航天器姿态接管的SDRE微分博弈控制[J]. 宇航学报, 2020, 41(2):191-198. CHAI Y, LUO J J, HAN N, et al. Attitude takeover control of failed spacecraft using SDRE based differential game approach[J]. Journal of Astronautics, 2020, 41(2):191-198(in Chinese).
[16] VAMVOUDAKIS K G, MODARES H, KIUMARSI B, et al. Game theory-based control system algorithms with real-time reinforcement learning:How to solve multiplayer games online[J]. IEEE Control Systems Magazine, 2017, 37(1):33-52.
[17] ZHANG Q C, ZHAO D B, ZHU Y H. Data-driven adaptive dynamic programming for continuous-time fully cooperative games with partially constrained inputs[J]. Neurocomputing, 2017, 238:377-386.
[18] 罗建军, 韩楠, 柴源. 基于微小卫星合作博弈的失效航天器姿态接管控制[J]. 飞控与探测, 2019, 2(3):1-9. LUO J J, HAN N, CHAI Y. Taking over attitude control of failed spacecraft through cooperative game among multiple microsatellites[J]. Flight Control & Detection, 2019, 2(3):1-9(in Chinese).
[19] 韩楠. 多星协同作业的博弈控制研究[D]. 西安:西北工业大学,2021:39-54. HAN N. Study on game control for coordinated operation of multiple microsatellites[D]. Xi'an:Northwestern Polytechnical University, 2021:39-54(In Chinese).
[20] YANG X B, YU J Y, GAO H J. An impulse control approach to spacecraft autonomous rendezvous based on genetic algorithms[J]. Neurocomputing, 2012, 77(1):189-196.
[21] VAMVOUDAKIS K G, LEWIS F L. Multi-player non-zero-sum games:Online adaptive learning solution of coupled Hamilton-Jacobi equations[J]. Automatica, 2011, 47(8):1556-1569.
[22] LI Q, YUAN J P, ZHANG B, et al. Model predictive control for autonomous rendezvous and docking with a tumbling target[J]. Aerospace Science and Technology, 2017, 69:700-711.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

脉冲推力下多星协同搬运的预测博弈控制

Predictive game control for on-orbit transportation by multiple microsatellites with impulsive thrust

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	颜黎明, 郭鑫, 赵冬冬. 基于新型权重解析法的永磁电机预测转矩控制[J]. 航空学报, 2022, 43(12): 327785-327785.
[2]	颜黎明, 赵冬冬, 焦宁飞. 基于鲁棒模型的航空交流感应电机预测转矩控制[J]. 航空学报, 2021, 42(9): 324700-324700.
[3]	赵冬冬, 赵国胜, 夏磊, 方淳, 马睿, 皇甫宜耿. 无人机用燃料电池阴极供气系统建模与控制[J]. 航空学报, 2021, 42(7): 324659-324659.
[4]	韩楠, 罗建军, 马卫华. 失效卫星姿态接管的并行学习合作博弈控制[J]. 航空学报, 2021, 42(3): 324307-324307.
[5]	董凯凯, 罗建军, 马卫华, 高登巍, 谭龙玉. 非合作目标交会的双层MPC全局轨迹规划控制[J]. 航空学报, 2021, 42(11): 524903-524903.
[6]	王子安, 龚正, 陈永亮, 史志伟, 徐锦法. 混合动力复合翼应急迫降在线航迹规划与制导[J]. 航空学报, 2019, 40(10): 323105-323105.
[7]	唐清君, 陈厚磊, 梁惊涛, 蔡京辉. 空间微小脉冲管制冷机研制[J]. 航空学报, 2018, 39(S1): 722321-722321.
[8]	聂雪媛, 杨国伟. 基于CFD降阶模型的阵风减缓主动控制研究[J]. 航空学报, 2015, 36(4): 1103-1111.
[9]	刘刚, 李传江, 马广富. 应用非线性模型预测控制的绳系卫星Halo轨道保持控制[J]. 航空学报, 2014, 35(9): 2605-2614.
[10]	王超, 张胜修, 郑建飞, 张超. 基于气动特性辨识的飞行器抗饱和自适应控制[J]. 航空学报, 2013, 34(12): 2645-2657.
[11]	王健康, 张海波, 黄向华, 陆波. 基于直升机/涡轴发动机综合仿真平台的发动机非线性模型预测控制[J]. 航空学报, 2012, (3): 402-411.
[12]	付健, 岑继文, 徐进良, 黄元东, 赖喜锐. 微推进系统中微型喷嘴结构参数的实验研究[J]. 航空学报, 2011, 32(4): 608-616.
[13]	苏抗, 周建江. 微小卫星低可观测外形飞行姿态规划[J]. 航空学报, 2011, 32(4): 720-728.
[14]	苏抗;周建江. 有限姿控能力的低RCS微小卫星姿态实时规划[J]. 航空学报, 2010, 31(9): 1841-1848.
[15]	彭辉;沈林成;朱华勇. 基于分布式模型预测控制的多UAV协同区域搜索[J]. 航空学报, 2010, 31(3): 593-601.