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Erschienen in: Neural Computing and Applications 7-8/2014

01.06.2014 | Original Article

Petri net-based modeling and control of the multi-elevator systems

verfasst von: Farooq Ahmad, Ilyas Fakhir, Sher Afzal Khan, Yaser Daanial Khan

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2014

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Abstract

This paper extends the Petri net (PN)-based modeling of multi-elevator control system for M floors and N elevators which provides the generic PN model of the system. A new class of Petri nets is introduced known as elevator control Petri net (ECPN) for such purpose. The model of the multi-elevator control system is developed through components, whereas the model of each elevator is defined as a component. The interaction between these elevators is implemented through control places (CPs) of its PN model. A bottom-up modeling approach is adopted by adding the CPs and using the arc-addition operator to the single-elevator modules. Mixture of collective and selective approaches, that is, collective-selective/up–down approach, is used for the control. The proposed Petri net class in the paper resolves the bunching problem among multiple elevators. The bunching problem is tackled by introducing the request places with the capacity of one in the ECPN. A case study of ECPN is also presented by taking the two elevators and four-floor model, and it is analyzed by the incidence matrix–based invariant method.

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Metadaten
Titel
Petri net-based modeling and control of the multi-elevator systems
verfasst von
Farooq Ahmad
Ilyas Fakhir
Sher Afzal Khan
Yaser Daanial Khan
Publikationsdatum
01.06.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7-8/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-013-1391-1

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