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A Novel Model Repair Approach of Timed Discrete-Event Systems With Anomalies

机译:具有时间异常的离散事件系统的新型模型修复方法

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In this paper, the model repair of timed discrete-event systems where anomalies may occur is considered. The nominal model is assumed to be known, and a set of observed timed sequences is given. The approach works with time Petri net models and is based on the formulation of a mixed-integer linear programming problem. The repaired model is obtained from the nominal one by adding fault transitions as well as by extending the firing interval of transitions. Note to Practitioners-The data collected from the observation of a discrete-event system are usually given in terms of behavioral sequences that may be fixed or may be increased in the course of the system operation (e.g., due to new experiments or simply to the system running). If this occurs, the nominal model of a system may reveal not consistent with these additional observations if they include anomalies. This paper presents an approach to repair the model of the system in order to make it able to also generate the observed timed faulty behavior. The repaired model can be used to perform fault diagnosis.
机译:在本文中,考虑了可能发生异常的定时离散事件系统的模型修复。假定标称模型是已知的,并给出了一组观察到的定时序列。该方法适用于时间Petri网模型,并且基于混合整数线性规划问题的表述。通过添加故障过渡以及延长过渡的触发间隔,可以从名义模型中获得修复后的模型。给从业者的注意-从离散事件系统的观察中收集的数据通常是按照行为顺序给出的,这些行为顺序可能是固定的,或者在系统运行过程中可能会增加(例如,由于进行了新的实验或仅仅是由于系统正在运行)。如果发生这种情况,则系统的标称模型可能会揭示出与这些其他观察结果(如果包含异常)不一致的情况。本文提出了一种修复系统模型的方法,以使其也能够生成观察到的定时故障行为。修复后的模型可用于执行故障诊断。

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