基于CRC-MATE的体系架构方案选择

doi:10.12305/j.issn.1001-506X.2021.08.16

Abstract

Abstract:

The modern warfare is moving towards system-of-systems (SoS) confrontation. In order to achieve the joint combat capability via successful system integration, it is necessary to select optimized architecture alternatives that are often considered as system composition and their connections at the early design phase. The selection and decision of SoS architecture alternative are the critical part of weapon SoS concept design, the foundation of weapon SoS development and the initial step towards the integrated capability of SoS for future warfare. The SoS architecture can be considered as system composition and the interdependency between the systems. To address the problems of non-linear relationship between SoS capability and component system capability, SoS capability degradation risks due to uncertainties, and cost constraint, a SoS capability evaluation method based on functional dependency network, SoS risk analysis method based upon conditional value-at-risk, and SoS cost assessment method based on the entire systems engineering process are proposed. The three perspectives result in a capability-risk-cost multi-attribute tradespace exploration model. An application to a naval air and missile defense SoS demonstrates the implementation process of method as well as the feasibility and effectiveness of the method. Overall, the proposed method provides a new idea for the selection of architecture alternatives in the process of combat SoS development.

Key words: system-of-systems (SoS) architecture, multi-attribute tradespace exploration, capability-risk-cost

CLC Number:

TP202

Liupengcheng YUAN, Zhemei FANG, Jianbo WANG, Xiaozhen QIN. CRC-MATE based method for system-of-systems architecture alternative selection[J]. Systems Engineering and Electronics, 2021, 43(8): 2146-2153.

Figures/Tables 13

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Fig.6

Fig.7

Table 2

Table 3

Fig.8

Table 4

Table 5

References 34

1	U.S. Department of Defense, National Defense Research Institute. Portfolio-analysis methods for assessing capability options[R]. Santa Monica: Rand Corporation, 2008.
2	POOLE B H. A methodology for the robustness-based evaluation of systems-of-systems alternatives using regret analysis[D]. Atlanta: Georgia Institute of Technology, 2008.
3	DAVENDRALINGAM N , DELAURENTIS D . A robust portfolio optimization approach to system of system architectures[J]. Systems Engineering, 2015, 18 (3): 269- 283. doi: 10.1002/sys.21302
4	ROSS A M. Multi-attribute tradespace exploration with concurrent design as a value-centric framework for space system architecture and design[D]. Cambridge: Massachusetts Institute of Technology, 2003.
5	RICHARDS M G , ROSS A M , SHAH N B , et al. Metrics for evaluating survivability in dynamic multi-attribute tradespace exploration[J]. Journal of Spacecraft & Rockets, 2009, 46 (5): 1049- 1064.
6	张骁雄. 武器装备多能力领域组合选择与决策方法研究[D]. 长沙: 国防科技大学, 2018.
	ZHANG X X. Multi-capability areas weapon system portfolio selection and decision making methods[D]. Changsha: National University of Defense Technology, 2018.
7	ZHANG X X , HIPEL K W , TAN Y . Project portfolio selection and scheduling under a fuzzy environment[J]. Memetic Computing, 2019, 11, 391- 406. doi: 10.1007/s12293-019-00282-5
8	ZHANG X X , FANG L P , HIPEL K W , et al. A hybrid project portfolio selection procedure with historical performance consideration[J]. Expert Systems with Applications, 2020, 142, 113003. doi: 10.1016/j.eswa.2019.113003
9	周宇, 杨克巍, 姜江, 等. 面向武器装备体系组合规划的集成决策优化框架[J]. 国防科技大学学报, 2013, 35 (3): 36- 41. doi: 10.3969/j.issn.1001-2486.2013.03.007
	ZHOU Y , YANG K W , JIANG J , et al. An integrated decision making and optimization framework for system of armament systems portfolio planning[J]. Journal of National University of Defense Technology, 2013, 35 (3): 36- 41. doi: 10.3969/j.issn.1001-2486.2013.03.007
10	夏博远, 赵青松, 张骁雄, 等. 基于动态能力需求的鲁棒性武器系统组合决策[J]. 系统工程与电子技术, 2017, 39 (6): 1280- 1286.
	XIA B Y , ZHAO Q S , ZHANG X X , et al. Robust weapon system portfolio decision based on dynamic capability requirements[J]. Systems Engineering and Electronics, 2017, 39 (6): 1280- 1286.
11	WEI H C , XIA B Y , YANG Z W , et al. Model and data-driven system portfolio selection based on value and risk[J]. Applied Sciences, 2019, 9 (8): 1657- 1675. doi: 10.3390/app9081657
12	李瑞阳, 王智学, 禹明刚, 等. 基于鲁棒能力的体系多目标组合优化[J]. 系统工程与电子技术, 2019, 41 (5): 1034- 1042.
	LI R Y , WANG Z X , YU M G , et al. Multi-objective portfolio optimization of system-of-systems based on robust capabilities[J]. Systems Engineering and Electronics, 2019, 41 (5): 1034- 1042.
13	陶智刚, 徐浩, 易侃, 等. 基于权衡空间探索分析的C4ISR系统韧性研究[C]//第四届中国指挥控制大会, 2016: 110-115.
	TAO Z G, XU H, YI K, et al. C4ISR system resilience research based on tradespace exploration analysis[C]//Proc. of the 4th China Conference on Command and Control, 2016: 110-115.
14	张旺勋, 侯洪涛, 王维平. 基于MATE的卫星导航系统安全防护设计[J]. 系统工程与电子技术, 2013, 35 (6): 1231- 1235.
	ZHANG W X , HOU H T , WANG W P . MATE based design for protection of GNSS[J]. Systems Engineering and Electro-nics, 2013, 35 (6): 1231- 1235.
15	DAVENDRALINGAM N , DELAURENTIS D . An analytic portfolio approach to system of systems evolutions[J]. Procedia Computer Science, 2014, 28, 711- 719. doi: 10.1016/j.procs.2014.03.085
16	GARVEY P R, PINTO C A. Introduction to functional dependency network analysis[C]//Proc. of the 2nd International Symposium on Engineering Systems Massachusetts Institute of Technology, 2009
17	GUARINIELLO C, GRANDE M, BRAND C, et al. Quantify-ing the impact of systems interdependencies in space systems architectures[C]//Proc. of the 70th International Astronautical Congress, 2019: 21-25.
18	GUARINIELLO C , RAZ A K , FANG Z , et al. System-of-systems tools and techniques for the analysis of cyber-physical systems[J]. Systems Engineering, 2020, 23 (4): 480- 491. doi: 10.1002/sys.21539
19	LUO A M, YI S H, LIU J X, et al. An improved functional dependency network model for information systems effectiveness analysis[C]//Proc. of the International Conference on Wireless Communication and Sensor Networks, 2020: 56-59
20	舒佳康. 基于权衡空间探索的体系韧性分析[D]. 武汉: 华中科技大学, 2019.
	SHU J K. Evaluating system of systems resilience based on tradespace exploration[D]. Wuhan: Huazhong University of Science and Technology, 2019.
21	钟庆, 周剑雄, 秦肖臻, 等. 体系效能的功能依赖网络分析[J]. 兵工自动化, 2017, 36 (6): 52- 55. doi: 10.7690/bgzdh.2017.06.015
	ZHONG Q , ZHOU J X , QIN X Z , et al. FDNA of SoS effectiveness[J]. Ordnance Industry Automation, 2017, 36 (6): 52- 55. doi: 10.7690/bgzdh.2017.06.015
22	陈宽, 李元元, 罗云峰, 等. 基于功能依赖网络的体系韧性分析[J]. 指挥与控制学报, 2016, 2 (3): 256- 260.
	CHEN K , LI Y Y , LUO Y F , et al. Evaluating system of systems resilience based on functional dependency network analysis[J]. Journal of Command and Control, 2016, 2 (3): 256- 260.
23	殷加玞, 赵冬梅. 基于全概率风险度量的电力系统备用风险评估方法[J]. 电力自动化设备, 2020, 40 (1): 156- 162.
	YIN J F , ZHAO D M . Reserve risk assessment method of power system based on total probability risk measure[J]. Electric Power Automation Equipment, 2020, 40 (1): 156- 162.
24	ROCKAFELLAR R T , URYASEV S . Optimization of conditional value-at-risk[J]. Journal of Risk, 2000, 2 (3): 1071- 1074.
25	PAUL S , PADHY N P . Resilient scheduling portfolio of residential devices and plug-in electric vehicle by minimizing conditional value at risk[J]. IEEE Trans.on Industrial Informatics, 2019, 15 (3): 1566- 1578. doi: 10.1109/TII.2018.2847742
26	ARASTEH H , VAHIDINASAB V , SEPASIAN M S , et al. Stochastic system of systems architecture for adaptive expansion of smart distribution grids[J]. IEEE Trans.on Industrial Informatics, 2019, 15 (1): 377- 389. doi: 10.1109/TII.2018.2808268
27	SHAH P, DAVENDRALINGAM N, DELAURENTIS D A. A conditional value-at-risk approach to risk management in system-of-systems architectures[C]//Proc. of the 10th System of Systems Engineering Conference, 2015: 457-462.
28	郭红霞, 高瑞, 杨苹. 基于条件风险价值的微电网现货市场两阶段调度[J]. 电网技术, 2019, 43 (8): 2665- 2673.
	GUO H X , GAO R , YANG P . Two-stage dispatch of microgrid based on CVaRtheory under electricity spot market[J]. Power System Technology, 2019, 43 (8): 2665- 2673.
29	URYASEV S. Conditional value-at-risk: optimization algorithms and applications[C]//Proc. of the IEEE/IAFE/INFORMS Confe-rence on Computational Intelligence for Financial Engineering, 2000.
30	李天照. 舰艇作战系统全寿命费用估算研究[D]. 北京: 中国舰船研究院, 2016.
	LI T Z. The research of LCC estimation of ship combat system[D]. Beijing: China Ship Research and Development Academy, 2016.
31	VALERDI R. The constructive systems engineering cost model (COSYSMO)[D]. Los Angeles: University of Southern California, 2005.
32	VALERDI R, BOEHM B W, REIFER D J. COSYSMO: a constructive systems engineering cost model coming of age[C]//Proc. of the International Council on Systems Engineering International Symposium, 2003: 70-82.
33	DOMERCANT J C. ARC-VM: an architecture real options complexity-based valuation methodology for military systems-of-systems acquisitions[D]. Atlanta: Georgia Institute of Technology, 2011.
34	PAPKE B, PAVALKIS S, WANG G. Enabling repeatable SE cost estimation with COSYSMO and MBSE[C]// Proc. of the 27th Annual International Council on Systems Engineering International Symposium, 2017.

系统关键指标	类型1	类型2	类型3	类型4
预警机雷达探测距离/km	450	500	550	600
驱逐舰雷达探测距离/km	350	400	450	500
战斗机探测距离/km	80	100	120	140
电子战飞机干扰成功率/%	50	60	70	80
航母雷达探测距离/km	200	250	300	350
中远程导弹射程/km	800	1 000	1 500	2 000

系统	类型1	类型2	类型3	类型4
预警机	1.45	1.81	2.17	2.61
驱逐舰	15.34	17.04	18.74	20.62
战斗机	1.15	1.28	1.54	1.84
电子战飞机	0.68	0.75	0.83	0.99
航母	168.99	187.77	197.16	207.02
中远程导弹	0.07	0.08	0.09	0.10

序号	能力	风险	成本/亿美元
1	83.31	9.62	292.63
2	85.1	20.13	293.63
3	84.89	32.89	294.63
4	84.96	46.01	295.63
$ \vdots $	$ \vdots $	$ \vdots $	$ \vdots $
4 093	83.08	12.74	389.64
4 094	84.86	21.38	390.64
4 095	85.35	33.56	391.64
4 096	84.87	43.78	392.64

系统	方案1	方案2	方案3	方案4
预警机	类型1	类型1	类型1	类型1
驱逐舰	类型1	类型1	类型1	类型1
战斗机	类型1	类型1	类型1	类型1
电子战飞机	类型2	类型3	类型4	类型2
航母	类型1	类型1	类型1	类型1
中远程导弹	类型1	类型2	类型4	类型2

方案	能力	风险	成本/亿美元
方案1	83.32	9.48	292.91
方案2	85.07	22.59	294.23
方案3	85.65	40.97	296.87
方案4	85.17	21.68	293.91

CRC-MATE based method for system-of-systems architecture alternative selection

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 34

Related Articles 5

Recommended Articles

Metrics

Comments

[1]	Shuguang SUN, Qixin WEN. Aircraft height optimization algorithm of integrated navigation in terminal area based on height anomaly compensation [J]. Systems Engineering and Electronics, 2021, 43(9): 2612-2619.
[2]	Xinhao DONG, Zhijie ZHOU, Youmin ZHANG, Zhichao FENG, You CAO. Forecasting method of the error coefficient for SIMU based on belief rule base [J]. Systems Engineering and Electronics, 2020, 42(12): 2867-2874.
[3]	YIN Yong, ZHOU Zu-de, LIU Quan, LUO Xing, WANG Ji-hong. Design of DC-DC chopper based on sliding mode control theory [J]. Journal of Systems Engineering and Electronics, 2009, 31(9): 2177-2180.
[4]	LUO Hang, HUANG Jian-guo, LONG Bing, WANG Hou-jun. Research on failure distribution of samples based on correlation coefficient method [J]. Journal of Systems Engineering and Electronics, 2009, 31(7): 1776-1781.
[5]	SONG De-qiang, DUAN Cheng-hua, HUANG Qing-ming. Resource-constrained LB-ACO algorithm for functional pipelines in behavioral synthesis [J]. Journal of Systems Engineering and Electronics, 2009, 31(2): 384-389.