Simulation-oriented model reuse in cyber-physical systems: A method based on constrained directed graph

Wenzheng Liu, Heming Zhang, Chao Tang, Shuangfei Wu, Hongguang Zhu
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引用次数: 1

Abstract

Modeling and Simulation of Cyber-Physical Systems (MSCPS) is demanding in terms of immediate response to dynamic and complex changes of CPS. Simulation-oriented model reuse can be used to build a whole CPS model by reusing developed models in a new simulation application, which avoid repeated modeling and thus reduce the redevelopment of submodels. Model composition, one of the important methods, enables model reuse by selecting and adopting diversified integration solutions of simulation components to meet the requirements of simulation application systems. In this paper, a real-time model integration approach for global CPS modeling is proposed, which reuses developed submodels by compositing submodel nodes. Specifically, a constrained directed graph of submodels for the whole system which can meet the simulation requirements is constructed by reverse matching. Submodel properties, including co-simulation distance between submodel nodes, reuse benefit and simulation performance of model nodes, are quantified. Based on the properties, the model-integrated solution for the whole CPS simulation is retrieved throughout the model constrained digraph by the Genetic Algorithm (GA). In the experiment, the proposed method is applied to a typical model integrated computing scenario containing multiple model-integration solutions, among which the Pareto optimal solutions are retrieved. Results show that the effectiveness of the model integration method proposed in this paper is verified.
面向仿真的网络物理系统模型复用:一种基于约束有向图的方法
信息物理系统建模与仿真对信息物理系统动态复杂变化的即时响应提出了更高的要求。面向仿真的模型重用可以通过在新的仿真应用中重用已开发的模型来构建完整的CPS模型,避免了重复建模,从而减少了子模型的再开发。模型组合是一种重要的方法,通过选择和采用多样化的仿真组件集成方案来实现模型复用,以满足仿真应用系统的需求。本文提出了一种面向全局CPS建模的实时模型集成方法,该方法通过组合子模型节点重用已开发的子模型。具体而言,通过反向匹配,构建了整个系统满足仿真要求的约束子模型有向图。量化子模型属性,包括子模型节点间的协同仿真距离、模型节点的复用效益和仿真性能。基于这些特性,利用遗传算法在整个模型约束有向图中检索整个CPS仿真的模型集成解。在实验中,将该方法应用于包含多个模型集成解的典型模型集成计算场景,并从中检索出Pareto最优解。结果表明,本文提出的模型集成方法的有效性得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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