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REQUIRED CONDITIONS TO IDENTIFY PETRI NET MODELS BASED ON AN ASYMPTOTIC IDENTIFICATION APPROACH

机译:基于渐近识别法的Petri网模型识别的必要条件

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The aim of this paper is to present the conditions underrnwhich a Discrete Event System (DES) can be identifiedrnusing an asymptotic identification approach.rnThe asymptotic identification problem consists inrncompute an Interpreted Petri Net (IPN) model inrnproportion as new output sequences of the system arernobserved. Given this problem, the identificationrnconditions are related with: 1) the possibility to detect arnchange of state from the output signal, 2) the structure ofrnthe system to be identified and 3) the input signal given tornthe system to generate the output sequences required.
机译:本文的目的是提出使用渐近识别方法可以识别离散事件系统(DES)的条件。渐进识别问题包括将解释Petri网(IPN)模型比例不正确作为系统的新输出序列。给定这个问题,识别条件与以下方面有关:1)从输出信号中检测状态变化的可能性,2)要识别的系统的结构,以及3)给系统的输入信号,以生成所需的输出序列。

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