A goal-based approach for modeling and simulation of different types of system-of-systems

doi:10.23919/JSEE.2023.000084

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (3): 627-640.doi: 10.23919/JSEE.2023.000084

• COMPLEX SYSTEMS THEORY AND PRACTICE • Previous Articles

A goal-based approach for modeling and simulation of different types of system-of-systems

Yimin FENG¹(), Chenchu ZHOU²(), Qiang ZOU¹^,*(), Yusheng LIU¹(), Jiyuan LYU³(), Xinfeng WU³()

¹ State Key Lab of CAD&CG, Zhejiang University, Hangzhou 310027, China
² Xi’an Aerospace Propulsion Institute, Xi’an 710100, China
³ China Astronaut Research and Trainning Center, Beijing 100094, China

Received:2022-03-15 Online:2023-06-15 Published:2023-06-30
Contact: Qiang ZOU E-mail:yiminfengmy@zju.edu.cn;zhouchenchu@126.com;qiangzou@cad.zju.edu.cn;ysliu@cad.zju.edu.cn;lvjiyuan@139.com;wxf.134@163.com
About author:
FENG Yimin was born in 1995. He received his B.E. degree in computer science from Northwestern Polytechnical University, Xi ’an, China, in 2017. He is currently pursuing his Ph.D. degree in computer science at the State Key Laboratory of Computer Aided Design and Computer Graphics, Zhejiang University. His research interests include system-of-systems engineering, model-based system engineering, and computer-aided design. E-mail: yiminfengmy@zju.edu.cn

ZHOU Chenchu was born in 1990. He received his master ’s degree from Beijing University of Aeronautics and Astronautics in 2015. He is currently an engineer at Xi’an Aerospace Propulsion Institute. His research interests include engine dynamics simulation, aerospace propulsion theory and engineering. E-mail: zhouchenchu@126.com

ZOU Qiang was born in 1990. He received his Ph.D. degree in mechanical engineering from University of British Columbia, Vancouver, Canada, in 2019. He is currently an associate professor at the State Key Laboratory of Computer Aided Design and Computer Graphics and the College of Computer Science, Zhejiang University. His research interests include design modeling and manufacturing simulation. E-mail: qiangzou@cad.zju.edu.cn

LIU Yusheng was born in 1970. He received his B.E. degree in mechanical engineering and Ph.D. degree in computer science from Zhejiang University, Hangzhou, Zhejiang, China, in 1995 and 2000, respectively. He is currently a professor and a researcher at the State Key Laboratory of Computer Aided Design and Computer Graphics and the College of Computer Science, Zhejiang University. His research interests include model based system engineering, computer aided design and manufacturing, product innovation design, and model retrieval. E-mail: ysliu@cad.zju.edu.cn

LYU Jiyuan was born in 1984. He received his B.E. and Ph.D. degrees from Northwestern Polytechnical University in 2008 and 2012, respectively. He is currently an engineer at China Astronaut Research and Trainning Center, Beijing, China. His research interests are guidance and control engineering, manned space mission analysis and simulation. E-mail: lvjiyuan@139.com

WU Xinfeng was born in 1983. He received his Ph.D. degree from National University of Defense Technology. He is currently an engineer at China Astronaut Research and Trainning Center, Beijing, China. His research interests include aircraft design engineering, and manned space mission analysis. E-mail: wxf.134@163.com
Supported by:
This work was supported by the National Key Research and Development Program of China (61873236), the Natural Science Foundation of Zhejiang Province (LZ21F020003; LY18F030001), and the Civil Aerospace Pre-research Project (D020101)

Abstract

Abstract:

A system of systems (SoS) composes a set of independent constituent systems (CSs), where the degree of authority to control the independence of CSs varies, depending on different SoS types. Key researchers describe four SoS types with descending levels of central authority: directed, acknowledged, collaborative and virtual. Although the definitions have been recognized in SoS engineering, what is challenging is the difficulty of translating these definitions into models and simulation environments. Thus, we provide a goal-based method including a mathematical baseline to translate these definitions into more effective agent-based modeling and simulations. First, we construct the theoretical models of CS and SoS. Based on the theoretical models, we analyze the degree of authority influenced by SoS characteristics. Next, we propose a definition of SoS types by quantitatively explaining the degree of authority. Finally, we recognize the differences between acknowledged SoS and collaborative SoS using a migrating waterfowl flock by an agent-based model (ABM) simulation. This paper contributes to the SoS body of knowledge by increasing our understanding of the degree of authority in an SoS, so we may identify suitable SoS types to achieve SoS goals by modeling and simulation.

Key words: simulation, systems agent-based modeling, systems-of-systems (SoS), systems thinking

Yimin FENG, Chenchu ZHOU, Qiang ZOU, Yusheng LIU, Jiyuan LYU, Xinfeng WU. A goal-based approach for modeling and simulation of different types of system-of-systems[J]. Journal of Systems Engineering and Electronics, 2023, 34(3): 627-640.

Figures/Tables 8

Fig 1

Fig 2

Table 1

Fig 3

Table 2

Summary of ODD protocol for ABM"

Overview	Design concepts	Details
Purpose: to verify the simulation results when different types of the same SoS are used. Entities: fixed number of agents is 30; fixed time step duration of 0.1 s; fixed speed increase/decrease rate is 20%; fixed rotation angle per step is 4°. State variables: Facing north/not north; whether the four agent rules are satisfied. Scales: 70×70 grids. Process overview and scheduling: Collaborative SoS: Each bird starts at a random position and goes out into the world. If the bird cannot see another bird within a limited range of vision, it will continue to fly straight at its normal basic speed. If another bird can be seen, the following four basic rules are followed, given by that order of priority. (i) If it is too far from the nearest visible bird, it will turn toward that bird and approach it at an increased speed. (ii) Once it is close enough to another bird, it randomly moves to one side or the other until its view is no longer obscured. (iii) If it gets too close to another bird, it will slow down. (iv) Once the preceding three conditions are met (the bird has an unobstructed view and is close enough but not too close to another bird), the bird will set its speed and the forward direction of its closest visible neighbor. Acknowledged SoS: Rule 1 and Rule 4 disabled.	Basic principles: the model represents a simplified behavior based on natural physical phenomena. Objectives: different types of the same SoS. Stochasticity: initialized random number of seeds. Interaction: agents will acquire traction from other agents in the vicinity. Adaptation: agents try to occupy a favorable position and avoid an unfavorable one. Sensing: sensing distance of agents is 15-patch; sensing angle of agents is 120° cone range in front of it; obstruction cone of agents is 45°; obstruction distance of agents is 10-patch. Prediction: collision point prediction. Emergence: flock geometry; SoS goals. Observation: the heading of each agent after forming a flight formation.	Initialization: the initial position and initial heading are random. Input data: no external data. Submodel 1(solo): the default state of a bird agent is to be solo. When no other birds are in vision to provide an updraft, a bird cruises towards its destination. Submodel 2(Alignment as Rule 4): a bird tends to turn, moving in the same direction as nearby birds. Submodel 3(Separation as Rule 3): a bird will turn to avoid another bird that gets too close. Submodel 4(Cohesion as Rule 1 and Rule 2): a bird will move towards other nearby birds (unless another bird is too close).

Table 2

Fig 4

Fig 5

Fig 6

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SoS classification		SoS goal dimension
SoS classification		$ \mathrm{\Delta }{G}^{*} > 0 $	$ \mathrm{\Delta }{G}^{*}=0 $
CS goal dimension	$ \mathrm{\Delta }{G}_{i} > 0 $	Collaborative	Collaborative
	$ \mathrm{\Delta }{G}_{i}=0 $	Collaborative	−
	$ \mathrm{\Delta }{G}_{i} < 0, $ $\mathrm{\Delta }{G}_{i}=-{P'_{i}}$	Acknowledged	−
	$ \mathrm{\Delta }{G}_{i} < 0, $ $ \mathrm{\Delta }{G}_{i}=-\mathrm{c}\mathrm{o}\mathrm{s}t $	Directed	−

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A goal-based approach for modeling and simulation of different types of system-of-systems

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