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Diagnosability and online diagnosis of discrete-event systems modeled by acyclic labeled Petri nets

机译:用无环标记Petri网建模的离散事件系统的可诊断性和在线诊断

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We address in this paper the problems of online diagnosis and verification of language diagnosability of discrete event systems (DES) modeled by acyclic labeled Petri nets, in which, different transitions can be labeled by the same event (observable, unobservable and failure). The proposed diagnoser makes its decision regarding the failure occurrence by storing the sequence of observed events and, after each occurrence of observable event, it verifiers if two sets of inequalities are satisfied; the first set accounts for the normal whereas the second one accounts for the faulty behavior of the system. We also consider the problem of diagnosability verification by creating new sets of inequalities that, when satisfied, allow us to decide whether the language generated by the Petri net is diagnosable. Our method for online diagnosis has the advantage over previously ones for relying only on the verification of set of inequalities. Regarding language diagnosability, our verification algorithm does not require any knowledge of automaton theory, being self-contained within the Petri net formalism.
机译:我们在本文中解决了在线诊断和验证以无环标记Petri网为模型的离散事件系统(DES)的语言可诊断性的问题,其中,相同事件可以标记不同的过渡(可观察,不可观察和失败)。拟议的诊断程序通过存储观察事件的顺序来决定故障的发生,并在每次可观察事件发生后验证是否满足两组不等式;第一组解释正常,而第二组解释系统的错误行为。我们还通过创建新的不等式集来考虑可诊断性验证的问题,当不等式满足时,这些不等式将使我们能够确定Petri网络生成的语言是否可诊断。我们的在线诊断方法相对于以前的方法具有优势,仅依赖于一组不等式的验证。关于语言的可诊断性,我们的验证算法不需要任何自动机理论的知识,因为它在Petri网形式主义中是独立的。

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