Model Identification and Synthesis of Discrete‐Event Systems

Zhou, MengChu; Li, Han-Xiong; Weijnen, Margot

doi:10.1002/9781119036821.ch10

Cited by 28 publications

(20 citation statements)

References 46 publications

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“…This difference is pointed out in [10]. Both problems have been treated in several works, surveyed in [4]. Notable contributions to solve these problems, notably the synthesis one, are Region Theory [11] or the resolution of Integer Linear Programs [12], later used for fault diagnosis by identifying faulty nets [13] [14].…”

Section: A Related Workmentioning

confidence: 99%

“…When lacking knowledge about an existing system, modelling can be performed by identification, provided Input Output data collected from the system. Several methods identifying DES are surveyed in [4], most being devoted to fault diagnosis. A few approaches are instead focused on reverseengineering of closed-loop DES by various classes of Petri nets [5] [6] [7].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automated Partitioning of Concurrent Discrete-Event Systems for Distributed Behavioral Identification

Saives¹,

Faraut²,

Lesage³

2018

IEEE Trans. Automat. Sci. Eng.

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The aim of behavioural identification of Discrete Event Systems is to build, from a sequence of observed inputs/outputs events, an understandable model that exhibits both the direct relations between inputs and outputs events (i.e. the observable behaviour of the system) and the internal state evolutions (i.e. the unobservable behaviour). Since parallelism hinders the construction of monolithic models, distributed identification builds instead models of subsystems. This paper proposes an automated partitioning of the system, optimal regarding the readability of the identified distributed models, thus fitting reverse-engineering purposes. To solve the optimization problem, a first solution is extracted from the observable behaviour, then additional solutions are computed by agglomerative clustering. The approach is applied to a benchmark, resulting in an adequate functional partition.Note to Practitioners-Identification is an approach to obtain models of an existing closed-loop Discrete Event System from an observed I/O sequence, discovering both sequential and concurrent processes within a same system. The result is an understandable and compact model, that approximates the observed behaviour and can be used for reverse-engineering. To get better insight on the behaviour of the system, splitting it into subsystems and studying distributed models might be easier. Besides, identifying smaller subsystems reduces the computational cost. The main contribution of this article is therefore a partitioning approach for distributed DES identification. Only the knowledge of the I/Os and the observed I/O sequence are required to provide a partitioning adapted to reverse-engineering and compact distributed models, in reasonable computation times.

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Section: A Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated Partitioning of Concurrent Discrete-Event Systems for Distributed Behavioral Identification

Saives¹,

Faraut²,

Lesage³

2018

IEEE Trans. Automat. Sci. Eng.

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“…Remark The problem of fault diagnosis of DESs belongs to the identification problem, just like the problem of model identification of DESs . The former focuses on detecting whether a fault (usually modeled by an unobservable transition) has occurred according to the behavior generated by a DES.…”

Section: Problem Statement and Assumptionsmentioning

confidence: 99%

Fault Diagnosis for Discrete Event Systems Modeled By Bounded Petri Nets

Ran

Wang

et al. 2017

Asian Journal of Control

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Fault diagnosis is an important problem in the manufacturing industry. It has been extensively studied in the past few decades both in time‐driven systems and discrete event systems. This paper presents a Petri net diagnoser for online fault diagnosis of discrete event systems modeled by bounded labeled Petri nets. First, we present the concept and some properties of an extended basis reachability graph. Next, based on such a graph, we construct a Petri net diagnoser that is used to determine if a fault has occurred. Finally, an example is given to illustrate the application of the proposed diagnoser.

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“…Given a finite observed language and considering any nonobserved word as a counter-example, the authors of [8] or [4] propose to solve an Integer Linear Problem to discover a generalized, possibly unbounded PN reproducing exactly every word of the language up to a length k. Works such as [1] based on the region theory propose to compute a PN whose reachability graph isomorphic to a given transition system. An extensive literature review of identification and synthesis methods can be found in [2].…”

Section: Introductionmentioning

confidence: 99%

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

Saives

Faraut

Lesage

2015

2015 European Control Conference (ECC)

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Abstract-The aim of behavioural identification of Discrete Event Systems is to build, from a sequence of observed inputs/outputs events, a model that exhibits both the direct relations between inputs and outputs events (i.e. the reactive or observable behaviour of the system) and the internal state evolutions (i.e. the unobservable behaviour). Once the observable behaviour has been modelled by an Interpreted Petri net, the method proposed in this paper aims at discovering the unobservable part from a firing sequence of previously discovered observable transitions. The principle is to project the firing sequence on subalphabets to discover specific patterns that are characteristic of dependancy relationships between the transitions. These relationships can be translated into Petri net structure fragments that will be assembled to form the final model. A parametric algorithm is proposed to conduct the discovery, the choice of the minimal degree of places as a parameter being motivated by the reduction of the search space and the fitness of the final model.

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Model Identification and Synthesis of Discrete‐Event Systems

Cited by 28 publications

References 46 publications

Automated Partitioning of Concurrent Discrete-Event Systems for Distributed Behavioral Identification

Automated Partitioning of Concurrent Discrete-Event Systems for Distributed Behavioral Identification

Fault Diagnosis for Discrete Event Systems Modeled By Bounded Petri Nets

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

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