Identification of industrial automation systems: Building compact and expressive Petri Net models from observable behavior

Abstract

Abstract-The paper deals with black-box identification of industrial automated discrete manufacturing systems. The problem of obtaining Petri net (PN) models from the observable behavior, expressed as a sequence of input-output vectors, is addressed. First the problem is stated: important issues to handle in systems automated by Programmable Logic Controllers that cannot be dealt by other methods are detailed. Then a novel method is presented; it focuses on building a compact and expressive representation of the observable part of the model which allows consequently the construction of a reduced complete Interpreted PN describing both observable and unobservable behavior.

Generación Determinística de Lenguajes Legales para Sistemas de Eventos Discretos

“…Respecto a la utilización de PN para identificación y diagnóstico, varias propuestas de modelado se han generado utilizando PN extendidas como: PN interpretadas en Cabasino et al (2011);Dotoli et al (2008a); Estrada-Vargas et al (2012) o como PN temporizadas en Basile et al (2011).…”

Identification of discrete event systems unobservable behaviour by petri nets using language projections

“…This work is located in the continuation of [6]. The authors of [6] provide a statistical approach to discover the observable behaviour as IPN fragments from an input/output observed sequence.…”

“…The authors of [6] provide a statistical approach to discover the observable behaviour as IPN fragments from an input/output observed sequence. This sequence is also converted into a firing sequence on the alphabet of observable transition.…”

“…Section 2 recalls the notions of Petri nets. Section 3 states the problem based on the previous results of [6], and gives an overview of the method. Section 4 establishes the relationship between transitions to be discovered using projections of the sequence, and how they can lead to the discovery of unobservable places.…”

Identificación y Diagnóstico de Fallos en Sistemas de Eventos Discretos Estocásticos.

“…Respecto a la utilización de PN para identificación y diagnóstico varias propuestas de modelado se han generado utilizando PN extendidas como PN interpretadas (IPN), [53,54,55], PN temporizadas [56], algunas de estas propuestas se presentan a continuación.…”