Resilience-driven cooperative reconfiguration strategy for unmanned weapon system-of-systems

doi:10.23919/JSEE.2024.000088

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (4): 932-944.doi: 10.23919/JSEE.2024.000088

• SYSTEMS ENGINEERING • Previous Articles

Resilience-driven cooperative reconfiguration strategy for unmanned weapon system-of-systems

Qin SUN(), Hongxu LI(), Yifan ZENG(), Yingchao ZHANG()

School of Systems Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China

Received:2022-02-21 Online:2024-08-18 Published:2024-08-06
Contact: Yingchao ZHANG E-mail:sunq56@mail2.sysu.edu.cn;lihx79@mail2.sysu.edu.cn;zengyf29@mail2.sysu.edu.cn;zhangych68@mail.sysu.edu.cn
About author:
SUN Qin was born in 1991. He received his M.E. degree in power electronics and power drives, in 2016, from Harbin University of Science and Technology, Harbin, China. He is currently working toward his Ph.D. degree in information and communication engineering at Sun Yat-sen University, Guangzhou, China. His current research interests include resilient system-of-systems (SoS) modeling and resilience enhancement for unmanned systems. E-mail: sunq56@mail2.sysu.edu.cn

LI Hongxu was born in 1994. He received his M.E. degree in management science and engineering, in 2020, from Hebei University of Engineering, Handan, China. He is currently working toward his Ph.D. degree in information and communication engineering at Sun Yat-sen University, Guangzhou, China. His current research interests include resilience assessment and optimization of unmanned systems. E-mail: lihx79@mail2.sysu.edu.cn

ZENG Yifan was born in 1996. He received his B.E. degree in electrical engineering and automation from Liaoning University, Shenyang, China, in 2018, and M.E. degree in electronic engineering from the University of Florida in 2021. He is currently pursuing his Ph.D. degree at Sun Yat-sen University. His research interests include complex network information systems, digital twins, decision-making support systems with artificial intelligence, and information system analysis and design. E-mail: zengyf29@mail2.sysu.edu.cn

ZHANG Yingchao was born in 1977. He received his Ph.D. degree in management science and engineering from the National University of Technology, China, in 2004, with a focus on high-performance information integration in the virtual organization. He is a professor and doctoral supervisor in the School of System Science and Engineering at Sun Yat-sen University, China. His research interests include information system of systems engineering, and intelligent decision support system and strategy. E-mail: zhangych68@mail.sysu.edu.cn
Supported by:
This work was supported by Ph.D. Intelligent Innovation Foundation Project (201-CXCY-A01-08-19-01) and Science and Technology on Information System Engineering Laboratory (05202007).

Abstract

Abstract:

As the unmanned weap system-of systems (UWSoS) becomes complex, the inevitable uncertain interference gradually increases, which leads to a strong emphasis on the resilience of UWSoS. Hence, this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS. First, a unified resilience-driven cooperative reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement. Subsequently, a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence, combining the cooperative pair resilience contribution index (CPRCI) and cooperative pair importance index (CPII). At last, the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include different attack modes and intensities. The analysis results can provide a reference for decision-makers to manage UWSoS.

Key words: resilience strategy, unmanned weapon system-of-systems (UWSoS), cooperative reconfiguration, unmanned confrontation

Qin SUN, Hongxu LI, Yifan ZENG, Yingchao ZHANG. Resilience-driven cooperative reconfiguration strategy for unmanned weapon system-of-systems[J]. Journal of Systems Engineering and Electronics, 2024, 35(4): 932-944.

Figures/Tables 14

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Number	Mode	Attacked node
Number	Mode	$ {G'_1} $	$ {G''_1} $
1	MA-MA	44,38,29,27	44,38,29,27,26,25,14,11
2	SA-SA	18,14,12,11	18,14,12,11,10,5,8,2
3	DA-DA	29,27,26,25	29,27,26,25,24,22,21,20
4	IA-IA	44,38,39,37	44,38,39,37,35,43,36,41
5	SA-DA	18,14,12,11	29,27,26,25,24,22,21,20
6	SA-IA	18,14,12,11	44,38,39,37,35,43,36,41
7	DA-IA	29,27,26,25	44,38,39,37,35,43,36,41
8	DA-SA	29,27,26,25	18,14,12,11,10,5,8,2
9	IA-SA	44,38,39,37	18,14,12,11,10,5,8,2
10	IA-DA	44,38,39,37	29,27,26, 25,24,22,21,20

Resilience-driven cooperative reconfiguration strategy for unmanned weapon system-of-systems

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Name	Network	$ V $	$ {V^S} $	$ {V^D} $	$ {V^I} $	$ {V^T} $
Swarm 1	$ {G_1} $	50	20	10	15	5
Swarm 2	$ {G_2} $	50	20	15	10	5
Swarm 3	$ {G_3} $	50	15	10	20	5

Network	$ E $	$ S \to S $	$ S \to D $	$ D \to D $	$ D \to S $	$ D \to I $	$ I \to T $	$ T \to S $	$ {f_0}\left( G \right) $
$ {G_1} $	200	40	43	6	12	23	22	23	18.657
$ {G_2} $	209	31	48	21	17	30	16	29	31.250
$ {G_3} $	204	33	33	9	3	31	26	19	11.750