Identification of Petri net models based on an asymptotic approach

dc.contributorMeda-Campaña, M.E., Information Systems Department, University of Guadalajara, Zapopan, Jal, Mexico; Lopez-Lopez, F.J., Information Systems Department, University of Guadalajara, Zapopan, Jal, Mexico; Lopez-Martin, C., Information Systems Department, University of Guadalajara, Zapopan, Jal, Mexico; Chavoya, A., Information Systems Department, University of Guadalajara, Zapopan, Jal, Mexico
dc.creatorMeda-Campana, M.E.
dc.creatorLopez-Lopez, F.J.
dc.creatorLopez-Martin, C.
dc.creatorChavoya, A.
dc.date.accessioned2015-11-19T18:50:20Z
dc.date.accessioned2022-11-02T15:21:59Z
dc.date.available2015-11-19T18:50:20Z
dc.date.available2022-11-02T15:21:59Z
dc.date.created2015-11-19T18:50:20Z
dc.date.issued2009
dc.identifierhttp://hdl.handle.net/20.500.12104/65412
dc.identifier10.1109/ISDA.2009.244
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-77949538732&partnerID=40&md5=853ac848e6b5e19c8bfaebf37fbbdda4
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5012951
dc.description.abstractThe identification problem considered in this work consists in compute an Interpreted Petri Net (IPN) model, in proportion as new output signals of the system are observed. The identification problem becomes complex when the complete state of the system cannot be fully measured. The state information that is not observed is inferred during the identification process allowing the computed model represents the observed system behavior. As the system evolves new information is revealed and the wrong dependencies are eliminated in order to update the computed model. Given this problem, in this paper are presented the needed algorithms to identify a class of Petri Nets (PN) known as state machines. © 2009 IEEE.
dc.relationISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications
dc.relation749
dc.relation754
dc.relationScopus
dc.titleIdentification of Petri net models based on an asymptotic approach
dc.typeConference Paper


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