• DocumentCode
    2926983
  • Title

    Genetic adaptive state estimation for a jet engine compressor

  • Author

    Gremling, James R. ; Passino, Kevin M.

  • Author_Institution
    Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
  • fYear
    1997
  • fDate
    16-18 Jul 1997
  • Firstpage
    131
  • Lastpage
    136
  • Abstract
    A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. In this paper we develop a GA that can perform online adaptive state estimation. First, we show how to construct a genetic adaptive state estimator where a GA evolves the model in a state estimator in real time so that the state estimation error is driven to zero. Next, we show how to use a genetic adaptive state estimator for predicting when surge and stall occur in a nonlinear jet engine compressor model
  • Keywords
    adaptive estimation; aerospace engines; aircraft; compressors; genetic algorithms; search problems; state estimation; adaptive state estimation; genetic algorithm; jet engine compressor; parallel search; Economic forecasting; Game theory; Genetic algorithms; Genetic engineering; Jet engines; Observers; Parameter estimation; Predictive models; State estimation; Surges;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1997. Proceedings of the 1997 IEEE International Symposium on
  • Conference_Location
    Istanbul
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-4116-3
  • Type

    conf

  • DOI
    10.1109/ISIC.1997.626431
  • Filename
    626431