• DocumentCode
    425342
  • Title

    Intelligent automatic landing system using fuzzy neural networks and genetic algorithm

  • Author

    Juang, Jih-Gau ; Chin, Kuo-Chih ; Chio, Jem-Zuin

  • Author_Institution
    Dept. of Commun. & Guidance Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
  • Volume
    6
  • fYear
    2004
  • fDate
    June 30 2004-July 2 2004
  • Firstpage
    5790
  • Abstract
    In this paper, an intelligent automatic landing system using fuzzy neural networks and genetic algorithms is developed to improve the performance of the conventional automatic landing systems. This study uses a functional fuzzy neural network as the controller. Control gains are selected by a combination method of a nonlinear control design and genetic algorithm. The simulation results are described for the automatic landing system of a commercial airplane. Tracking performance and robustness are demonstrated through software simulations. Simulation results show that the proposed scheme can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments.
  • Keywords
    aerospace simulation; air safety; aircraft landing guidance; control system synthesis; fuzzy control; fuzzy neural nets; genetic algorithms; intelligent control; neurocontrollers; nonlinear control systems; robust control; aircraft safety; control gains; fuzzy neural networks; genetic algorithm; intelligent automatic landing system; nonlinear control design; robustness; software simulation; wind disturbance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2004. Proceedings of the 2004
  • Conference_Location
    Boston, MA, USA
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-8335-4
  • Type

    conf

  • Filename
    1384780