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An Integrated Modeling, Simulation and Analysis Framework for Engineering Complex Systems
DOI:10.1109/ACCESS.2019.2917652.png)
摘要
En 中文
The discipline of component-based modeling and simulation offers promising gains in reducing cost, time, and the complexity of model development through the (re) use of modular components. Model-driven development suggests 1) the realization of a complex system using a conceptual model; 2) its automatic transformation into an executable form using transformation rules, and; 3) its automatic verification using a formal analysis technique for an accurate assessment of its correctness. Both approaches have numerous complementary benefits in rapid prototyping of complex systems using model reuse. In this paper, we propose a framework grounded in a combination of component-based and model-driven approaches to promote rapid prototyping of complex systems through the effective reuse of the simulation models. Our proposed process allows developers to 1) build or select existing components and compose them to formulate the conceptual models of complex systems; 2) automatically transform the conceptual models for the rapid implementation and simulation, and; 3) automatically verify them as per the requirement specifications. We propose the use of the extended finite-state machine (EFSM) as conceptual modeling formalism, anylogic simulation platform for the implementation, and probabilistic model checking technique using communicating sequential process (CSP) formalism for the verification. Finally, we present a case study of a real-time adaptive cruise control system to demonstrate the functionality of our framework. Our proposed component-based model-driven approach facilitates rapid prototyping and effective meaningful reuse of complex system models, which further accelerates the modeling, simulation, and analysis process of real-time systems and aids in complex engineering designs and implementations.
Keyword:
Component-based development
model driven engineering
complex systems
anylogic simulation
probabilistic model checking
adaptive cruise control system
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
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