基于多目标优化的测控数传资源动态重调度方法

doi:10.12305/j.issn.1001-506X.2024.11.16

摘要/Abstract

摘要：

近年来，地面站资源测控数传任务的一体化调度方法受到了越来越多的关注。针对任务随遇处理条件下的测控数传资源调度问题，建立了面向多个优化目标的测控数传资源动态重调度数学模型，提出基于启发式规则和多目标非支配解排序遗传算法(non-dominated sorting genetic algorithm Ⅲ, NSGA-Ⅲ)的地面站测控数传资源一体化动态重调度算法，可生成侧重不同优化目标的多个规划方案供规划人员备选。实验结果表明该方法能有效解决测控数传资源多目标动态重调度问题。

关键词: 测控资源, 数传资源, 动态重调度, 多目标优化, 演化算法

Abstract:

In recent years, integrated scheduling methods for the telemetry, track and command (TT&C) tasks and data transmission (DT) tasks of ground stations have attracted more and more attention. To address the scheduling problem of station resources under the condition of random arrival of emergency TT&C and DT tasks, a multi-objective optimization model is established for the TT&C and DT tasks dynamic rescheduling. Then a rescheduling method based on heuristic rules and non-dominated sorting genetic algorithm Ⅲ (NSGA-Ⅲ) is designed, allowing to generate multiple alternative planning schemes focusing on different optimization objectives for users. The experimental results show that the proposed algorithm can effectively solve the multi-objective dynamic rescheduling proplem of measurment and control data transmission resources.

Key words: data transmission (DT) resource, telemetry, track and command (TT&C) resource, dynamic rescheduling, multi-objective optimization, evolutionary algorithm

中图分类号:

TP391

陈浩, 孙刚, 彭双, 伍江江. 基于多目标优化的测控数传资源动态重调度方法[J]. 系统工程与电子技术, 2024, 46(11): 3744-3753.

Hao CHEN, Gang SUN, Shuang PENG, Jiangjiang WU. Dynamic rescheduling method for TT&C and data transmission resources based on multi-objective optimization[J]. Systems Engineering and Electronics, 2024, 46(11): 3744-3753.

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参考文献 29

1	CHEN H , ZHAI B R , WU J J , et al. A satellite observation data transmission scheduling algorithm oriented to data topics[J]. International Journal of Aerospace Engineering, 2020, 2020, 1- 16.
2	LI Y Q , WANG R X , LIU Y , et al. Satellite range scheduling with the priority constraint: an improved genetic algorithm using a station ID encoding method[J]. Chinese Journal of Aeronautics, 2015, 28 (3): 789- 803. doi: 10.1016/j.cja.2015.04.012
3	ANTONIOU M, PETELIN G, PAPA G. On formulating the ground scheduling problem as a multi-objective bilevel problem[C]// Proc. of the International Conference on Bioinspired Methods and Their Applications, 2020: 177-188.
4	XHAFA F , IP A . Optimisation problems and resolution methods in satellite scheduling and space-craft operation: a survey[J]. Enterprise Information Systems, 2021, 15 (8): 1022- 1045. doi: 10.1080/17517575.2019.1593508
5	WU G H , LUO Q Z , ZHU Y Q , et al. Flexible task scheduling in data relay satellite networks[J]. IEEE Trans.on Aerospace and Electronic Systems, 2021, 58 (2): 1055- 1068.
6	CUI J T , ZHANG X . Application of a multi-satellite dynamic mission scheduling model based on mission priority in emergency response[J]. Sensors, 2019, 19 (6): 1430. doi: 10.3390/s19061430
7	CHEN H , YANG S , LI J , et al. Exact and heuristic methods for observing task-oriented satellite cluster agent team formation[J]. Mathematical Problems in Engineering, 2018, 2018, 2103625.
8	陈浩, 李军, 杜春, 等. 对地观测卫星任务规划与调度技术[M]. 北京: 国防工业出版社, 2021.
	CHEN H , LI J , DU C , et al. Task planning and scheduling technology for earth observation satellite[M]. Beijing: National Defense Industry Press, 2021.
9	习婷, 李菊芳. 面向动态需求的成像卫星滚动式重调度方法研究[J]. 中国管理科学, 2015, (S1): 269- 274.
	XI T , LI J F . The rolling horizon method for EOS scheduling with dynamic requests[J]. Chinese Journal of Management Science, 2015, (S1): 269- 274.
10	WANG J , ZHU X , YANG L T , et al. Towards dynamic real-time scheduling for multiple earth observation satellites[J]. Journal of Computer and System Sciences, 2015, 81 (1): 110- 124. doi: 10.1016/j.jcss.2014.06.016
11	DENG B Y, JIANG C X, KUANG L L, et al. Preemptive dynamic scheduling algorithm for data relay satellite systems[C]// Proc. of the IEEE International Conference on Communications, 2017.
12	SUN H Q , XIA W , HU X X , et al. Earth observation satellite scheduling for emergency tasks[J]. Journal of Systems Engineering and Electronics, 2019, 30 (5): 931- 945. doi: 10.21629/JSEE.2019.05.11
13	LI Y Q , WANG R X , XU M Q . Rescheduling of observing spacecraft using fuzzy neural network and ant colony algorithm[J]. Chinese Journal of Aeronautics, 2014, 27 (3): 678- 687. doi: 10.1016/j.cja.2014.04.027
14	LI J , CHEN H , JING N . A data transmission scheduling algorithm for rapid-response earth-observing operations[J]. Chinese Jour-nal of Aeronautics, 2014, 27 (2): 349- 364. doi: 10.1016/j.cja.2014.02.014
15	ZHENG Z , GUO J , GILL E . Onboard autonomous mission re-planning for multi-satellite system[J]. Acta Astronautica, 2018, 145 (4): 28- 43.
16	CHEN H, ZHOU Y R, DU C, et al. A satellite cluster data transmission scheduling method based on genetic algorithm with rote learning operator[C]//Proc. of the IEEE Congress on Evolutionary Computation, 2016: 5076-5083.
17	林鹏, 晏坚, 费立刚, 等. 中继卫星系统的多星多天线动态调度方法[J]. 清华大学学报, 2015, 55 (5): 491-496, 502.
	LING P , YAN J , FEI L G , et al. Multi-satellite and multi-antenna TDRSS dynamic scheduling method[J]. Journal of Tsinghua University, 2015, 55 (5): 491-496, 502.
18	WANG C, CHEN H, ZHAI B R, et al. Satellite observing mission scheduling method based on case-based learning and a genetic algorithm[C]//Proc. of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016: 627-634.
19	WANG H J , ZHEN Y , ZHOU W G , et al. Online scheduling of image satellites based on neural networks and deep reinforcement learning[J]. Chinese Journal of Aeronautics, 2019, 32 (4): 1011- 1019. doi: 10.1016/j.cja.2018.12.018
20	罗棕, 杜春, 陈浩, 等. 基于Transformer层次预测的多星应急观测任务规划方法[J]. 航空学报, 2021, 42 (4): 524271.
	LUO Z , DU C , CHEN H , et al. Multi-satellite cheduling approach for emergency scenarios based on hierarchical forecasting with transformer network[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42 (4): 524271.
21	孙刚, 陈浩, 彭双, 等. 一种基于偏好MOEA的卫星地面站资源多目标优化算法[J]. 航空学报, 2021, 42 (4): 524475.
	SUN G , CHEN H , PENG S , et al. Multi-objective optimization algorithm for satellite range scheduling based on preference MOEA[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42 (4): 524475.
22	孙刚, 彭双, 陈浩, 等. 面向测控数传资源一体化场景的卫星地面站资源多目标优化方法[J]. 航空学报, 2022, 43 (9): 326114.
	SUN G , PENG S , CHEN H , et al. Multi-objective optimization method oriented to integrated scenario of TT&C resources and data transmission resources[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43 (9): 326114.
23	孙刚, 伍江江, 陈浩, 等. 一种基于切比雪夫距离的隐式偏好多目标进化算法[J]. 计算机科学, 2022, 49 (6): 297- 304.
	SUN G , WU J J , CHEN H , et al. A hidden preference-based multi-objective evolutionary algorithm based on Chebyshev distance[J]. Computer Science, 2022, 49 (6): 297- 304.
24	DU Y , XING L , ZHANG J , et al. MOEA based memetic algorithms for multi-objective satellite range scheduling problem[J]. Swarm and Evolutionary Computation, 2019, 50, 100576. doi: 10.1016/j.swevo.2019.100576
25	DEB K , JAIN H . An evolutionary many-objective optimization algorithm using reference point-based nondominated sorting approach, Part Ⅰ: solving problems with box constraints[J]. IEEE Trans.on Evolutionary Computation, 2014, 18 (4): 577- 601. doi: 10.1109/TEVC.2013.2281535
26	MACCORMICK J . What can be computed?: a practical guide to the theory of computation[M]. Princeton: Princeton University Press, 2018.
27	LI L M, CHEN H, WU J J, et al. Preference-based evolutionary algorithms for many-objective mission planning of agile earth observation satellites[C]//Proc. of the Genetic and Evolutionary Computation Conference Companion, 2018.
28	HADKA D. MOEAFramework[EB/OL]. [2022-6-16]. http://moeaframework.org/.
29	Analytical Graphics Inc. Satellite tool kit 10.1.3[EB/OL]. [2022-6-16]. https://www.agi.com/.

ID	\|F^init\|	\|new_R^TTC\|	\|new_R^DT\|
S₁	330	50(10)	100(20)
S₂	397	40(10)	80(20)
S₃	471	30(10)	60(15)
S₄	532	20(5)	40(15)
S₅	599	10(5)	20(5)

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