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Multi-agent-based failure modeling for uncrewed swarm systems considering cross-layer diffusion characteristics

Author

Listed:
  • Guo, Xing
  • Feng, Qiang
  • Wu, Zeyu
  • Liu, Meng
  • Ren, Yi
  • Yang, Chao
  • Wang, Zili

Abstract

Uncrewed swarm systems (USSs) are injecting renewed vigor into societal development and economic growth, and their failure modeling is crucial for ensuring the safety and stability of system operations. However, traditional modeling methods are insufficient for describing the cross-layer diffusion characteristics of USS failure. In this context, proposed here is a multi-agent-based failure modeling approach to establish the groundwork for analyzing USS failure. A failure modeling framework grounded in agent-based modeling methodology is developed to efficiently capture and organize the multi-layer failure information of a USS. Expanding on this framework, the interaction mechanism of agents is designed to delineate the operational processes and failure propagation paths of the USS. A dynamic clock failure model, structural functions, and functional constraint matrices are integrated effectively to describe the cross-layer failure behaviors of the components, subsystems, and nodes of the USS. Furthermore, a unified modeling approach is proposed to describe the failure propagation within and between nodes. Finally, a case study of a USS comprising 16 uncrewed aerial vehicles and eight satellites is conducted to validate the effectiveness of the proposed approach. The simulation results reveal that the electric distribution board, voltage stabilizer, and flight control board significantly influence the mission completion.

Suggested Citation

  • Guo, Xing & Feng, Qiang & Wu, Zeyu & Liu, Meng & Ren, Yi & Yang, Chao & Wang, Zili, 2025. "Multi-agent-based failure modeling for uncrewed swarm systems considering cross-layer diffusion characteristics," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
  • Handle: RePEc:eee:reensy:v:257:y:2025:i:pa:s0951832025000341
    DOI: 10.1016/j.ress.2025.110831
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