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A Conceptual Framework for Refining Influence Knowledge from Simulation Evidence in Cyber-Physical Systems
RSS 官方收录 · 可信分层展示
关键摘要
提出新概念框架,用‘Influences’提升网络物理系统仿真结果的理解与利用
- 针对CPS仿真中环境介导交互建模不足问题
- 引入‘Influences’概念支持仿真活动迭代精化
- 通过Simulink/Gazebo移动机器人案例验证框架有效性
AI 摘要 · 来源可核验
正文提要
arXiv:2608.11221v1 Announce Type: new Abstract: Cyber-physical systems (CPS) are typically developed by multiple stakeholders who produce artefacts tailored to their specific domains of expertise. The behaviour of these systems emerges from the interaction between those artefacts and their operational environment. Simulation and co-simulation have become essential approaches for analysing CPS behaviour and, through simulation campaigns, developers can explore system responses under changing conditions, including interactions with the environment. However, the lack of details and understanding of some environmentmediated interactions (typically the ones beyond direct sensing and actuation), which remain unmodelled due to their complexity, a lack of time, or a lack of domain experience, hinders the proper comprehension and exploitation of simulation results. To address these limitations, we propose a conceptual framework leveraging the novel concept of Influences to support the iterative and incremental refinement of simulation campaigns and deepen the understanding of the system behaviour. We demonstrate the proposed approach through a case study involving a mobile robot implemented using Simulink/Gazebo co-simulation.