Enhancing the Time Petri Nets for Automatic Hybrid Control Synthesis

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Letia:2014:ICSTCC,
  author =       "Tiberiu S. Letia and Ors Kilyen",
  booktitle =    "18th International Conference System Theory, Control
                 and Computing (ICSTCC 2014)",
  title =        "Enhancing the Time Petri Nets for Automatic Hybrid
                 Control Synthesis",
  year =         "2014",
  month =        oct,
  pages =        "621--626",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICSTCC.2014.6982486",
  abstract =     "Hybrid control refers to applications having a
                 discrete event part and a continuous one that involves
                 the interactions of different model types. Their
                 control synthesis is difficult due to the fact that
                 they contain models that belong to different
                 approaches. In the current study the Time Petri Nets
                 (TPNs) are used for discrete event controlled part
                 model. For the continuous plant model is used a
                 discrete time system (DTS) and the Fuzzy Logic Control
                 (FLC) for its control. A new proposed method links the
                 TPN models with FLC models. The formal Time Petri Net
                 based Language (TPNL) (used for TPNs description) is
                 enhanced to comprise the FLC functions and thus the
                 entire hybrid control system can be described. The
                 hybrid control descriptions constructed with the
                 extended TPNL are transformed into trees that are
                 further processed by Genetic Programming for control
                 structure synthesis. The controller's parameters are
                 improved by Genetic Algorithm (GA). The evolutionary
                 individuals are organised in species taking into
                 account the isomorphic distance between them. The
                 species evolution implemented by GP is alternated by
                 its adaptation performed by GA. New methods are used
                 for the bloat control leading to a higher speed of
                 solution search.",
  notes =        "Dept. of Autom., Tech. Univ. of Cluj-Napoca,
                 Cluj-Napoca, Romania Also known as \cite{6982486}",
}

Genetic Programming entries for Tiberiu S Letia Ors Kilyen

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