合成信息物理系统建模

Georgios Bakirtzis, Christina N. Vasilakopoulou, C. Fleming
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引用次数: 9

摘要

确保网络物理系统的正确行为需要大量的建模工作,特别是在工程和设计过程的早期阶段,当系统还不能用于测试或验证正确的行为时。在这些早期设计阶段“把事情做好”的主要动机是,与硬件和软件已经开发出来相比,修改设计的成本要低得多,效率也高得多。工程信息物理系统需要构建几种不同类型的模型,每种模型代表不同的视图,其中包括涉众需求、系统行为和系统架构。此外,这些模型中的每一个都可以在不同的抽象层次上表示。在确保需求、行为和体系结构的正确性方面,形式推理提高了精度并扩展了可用的分析类型。然而,每一个通常都是用不同的形式和相应的工具建模的。目前,这种差异意味着系统设计人员必须手动检查不同的模型是否一致。手动编辑和检查模型容易出错,耗时,并且对模型本身设计中的任何更改都很敏感。接线图和相关理论为正式组织这些不同但相关的建模视图提供了一种方法,从而产生了用于网络物理系统的组合建模语言。这种分类语言可以使不同模型视图之间的关系具体化,从而管理复杂性,允许系统模型的分层分解,并正式证明模型之间的一致性。
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Compositional Cyber-Physical Systems Modeling
Assuring the correct behavior of cyber-physical systems requires significant modeling effort, particularly during early stages of the engineering and design process when a system is not yet available for testing or verification of proper behavior. A primary motivation for `getting things right' in these early design stages is that altering the design is significantly less costly and more effective than when hardware and software have already been developed. Engineering cyber-physical systems requires the construction of several different types of models, each representing a different view, which include stakeholder requirements, system behavior, and the system architecture. Furthermore, each of these models can be represented at different levels of abstraction. Formal reasoning has improved the precision and expanded the available types of analysis in assuring correctness of requirements, behaviors, and architectures. However, each is usually modeled in distinct formalisms and corresponding tools. Currently, this disparity means that a system designer must manually check that the different models are in agreement. Manually editing and checking models is error prone, time consuming, and sensitive to any changes in the design of the models themselves. Wiring diagrams and related theory provide a means for formally organizing these different but related modeling views, resulting in a compositional modeling language for cyber-physical systems. Such a categorical language can make concrete the relationship between different model views, thereby managing complexity, allowing hierarchical decomposition of system models, and formally proving consistency between models.
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