• DocumentCode
    504711
  • Title

    Evolutionary modeling of a process system

  • Author

    Hayashi, Kayoko ; Kawada, Kazuo ; Yamamoto, Toru

  • Author_Institution
    Dept. of Technol. & Inf. Educ., Hiroshima Univ., Hiroshima, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    3268
  • Lastpage
    3273
  • Abstract
    In this paper, a genetic algorithm (GA) modeling system is proposed. The GA is an evolutionary computational method that simulates the mechanisms of heredity or evolution of living things, and it is utilized in optimization and in searching for optimized solutions. Most process systems have nonlinearities, so it is necessary to anticipate exactly such systems. However, it is difficult to make a suitable model for nonlinear systems, because most nonlinear systems have a complex structure. Therefore the newly proposed method of modeling for nonlinear systems uses GA. Then according to the newly proposed scheme, the optimal structure and parameters of the nonlinear model are automatically generated.
  • Keywords
    control nonlinearities; delays; genetic algorithms; nonlinear control systems; parameter estimation; search problems; complex structure; control nonlinearity; evolutionary computational method; genetic algorithm modeling system; nonlinear system modeling; optimal structure; optimization; parameter estimation; process system; search problem; time delay; Computational modeling; Genetic algorithms; Nonlinear systems; Optimization methods; GA; Nonlinear System; System Identification; the Evolutionary Computation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5334386