文章基本信息

标题：Stochastic Model-based Analysis of Timing Errors for Mechatronic Systems with User-defined General Discrete-time Distributions
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作者：Thomas Mutzke ; Andrey Morozov ; Kai Ding 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：24
页码：1417-1424
DOI：10.1016/j.ifacol.2018.09.538
语种：English
出版社：Elsevier
摘要：AbstractThis paper introduces a new stochastic method for model-based analysis of the timing behavior for reliable design of mechatronic systems with distributed, concurrent processes. Given a baseline behavioral system model, e.g. a semi-formal UML activity diagram, which actions are annotated with timing properties specified with user-defined general discrete-time distributions and formalized timing requirements, this method helps to analyze the occurrence of timing errors. The method comprises a specific baseline model reduction, the mapping of the semi-formal model into a formal stochastic Petri net model, and the generation of a discrete-time Markov chain model. The results allow the design verification and the comparison of various design options regarding the timing behavior in early design phases. A concept study of a mobile medical patient table serves as a demonstrative example.
关键词：KeywordsPrognosisStochastic Timing AnalysisReliabilitySafety-Critical SystemsMechatronic Medical DevicesPetri net-based analysisNetworked Systems