• DocumentCode
    620451
  • Title

    Identification and assessment for landing action adjustment

  • Author

    Li Yingzhen ; Xia Guihua ; Li Jinlong ; Zhang Zhi

  • Author_Institution
    Acad. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    4159
  • Lastpage
    4161
  • Abstract
    Landing action adjustment is an important part of the flight. Operation of the landing process is very complex. Assessing the landing action adjustment with recording flight parameters using recording system is very important to guarantee security of pilots. However, assessing landing action adjustment was based on identification method. The use of fuzzy neural network theory determine the structure of the fuzzy neural network in lateral and longitudinal, then MATLAB is used to obtain landing adjustment of fuzzy neural network structure. The Alopex algorithm with landing adjustment simulation data and experts´ data is used to correct the value of neural network. The value of neural network sent to the program of the fuzzy neural network, which can realize adjustment action identification in every moment. Then we got every period of adjustment action with clustering. Finally, it is turn out that the fuzzy neural network was valid.
  • Keywords
    aerospace computing; aerospace safety; fuzzy neural nets; stochastic programming; vehicle dynamics; Alopex algorithm; MATLAB; flight parameters; fuzzy neural network theory; landing action adjustment assessment; landing action adjustment identification; landing adjustment simulation data; landing process operation; pilot security; recording system; Algorithm design and analysis; Educational institutions; Fuzzy neural networks; Heuristic algorithms; Neural networks; Neurons; Vectors; Alopex; action adjustment; clustering; fuzzy neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561680
  • Filename
    6561680