DES可诊断性形式化模型的自动生成

Roberto Nardone, G. Tommasi, N. Mazzocca, A. Pironti, V. Vittorini
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引用次数: 1

摘要

本文旨在为离散事件系统的可诊断性分析定义一种模型驱动的方法。本文提出的方法可用于现代控制系统的设计中,这些控制系统采用了许多传感器和执行器,并且在一定的延迟内故障的可诊断性可能是一个问题。该建议代表了迈向自动模型驱动过程的第一步,该过程从完整的DESs高级规范中派生正式模型。我们方法的规范活动依赖于动态状态机(DSTM)形式,这是一种扩展状态机的新语言,具有动态实例化、中断和异步通信。本文将描述如何从高级DSTM规范中自动导出Petri网和Promela模型。前者可用于应用DES社区中提出的可诊断性分析方法,后者可用于应用模型检查技术。提出了一种模型驱动方法的应用,通过推导著名的铁路平交道口基准的PN和Promela模型来描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic generation of formal models for diagnosability of DES
This paper aims at defining a model-driven approach for the diagnosability analysis of discrete event systems (DES). The proposed approach can be adopted during the design of modern control systems, in which many sensors and actuators are employed and the diagnosability of faults within a certain delay could be an issue. The proposal represents a first step towards an automatic model-driven process which derive formal models from a complete high-level specification of DESs. The specification activity of our approach relies on the Dynamic STate Machine (DSTM) formalism, a new language that extends state machines with dynamic instantiation, interrupts and asynchronous communication. The paper will describe how we can automatically derive Petri net and Promela models from the high-level DSTM specification. The former model can be used to apply diagnosability analysis approaches proposed in the DES community, while the latter can be used to apply model checking techniques. An application of the proposed model-driven approach is described by deriving both a PN and a Promela model for the well-known railway level crossing benchmark.
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