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Identification of the unobservable behaviour of industrial automation systems by Petri nets

机译:用Petri网识别工业自动化系统的不可观测行为。

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This paper addresses the problem of identifying the model of the unobservable behaviour of discrete event systems in the industrial automation sector. Assuming that the fault-free system structure and dynamics are known, the paper proposes an algorithm that monitors the system on-line, storing the occurred observable event sequence and the corresponding reached states. At each event observation, the algorithm checks whether some unobservable events have occurred on the basis of the knowledge of the Petri net (PN) modelling the nominal system behaviour and the knowledge of the current PN marking. By defining and solving some integer linear programming problems, the algorithm decides whether it is necessary to introduce some unobservable (silent) transitions in the PN model and provides a PN structure that is consistent with the observed event string. A case study describing an industrial automation system shows the efficiency and the applicability of the proposed algorithm.
机译:本文解决了确定工业自动化领域离散事件系统的不可观察行为模型的问题。假设无故障的系统结构和动力学是已知的,本文提出了一种在线监测系统的算法,该算法存储发生的可观察事件序列和相应的到达状态。在每次事件观察时,该算法基于对标称系统行为进行建模的Petri网(PN)的知识和当前PN标记的知识,检查是否发生了一些不可观察的事件。通过定义和解决一些整数线性规划问题,该算法确定是否有必要在PN模型中引入一些不可观察的(无声的)过渡,并提供与观察到的事件字符串一致的PN结构。案例研究描述了工业自动化系统,显示了所提出算法的效率和适用性。

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