• DocumentCode
    501123
  • Title

    Knowledge-increasable Neural Network Group and its Control Application

  • Author

    Lv Jin ; Fan Hai-wei ; Zhao Xiang-mo

  • Author_Institution
    Sch. of Inf. Eng., Chang´an Univ., Xi´an, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    362
  • Lastpage
    365
  • Abstract
    Aiming at the complex dynamic feature of large ship, an intelligent control structure based on library-similar knowledge-increasable neural network group is presented. This compounded control structure using the dynamic knowledge-increasable learning capability of the neural network groups, solve the problems of online identification and online design of the controller, so that the high precise output tracking control of uncertain nonlinear large ship can be realized. Simulating results show that it is feasible and effective.
  • Keywords
    control system synthesis; motion control; neurocontrollers; nonlinear control systems; ships; vehicle dynamics; complex dynamic feature; compounded control structure; intelligent control structure; library-similar knowledge-increasable neural network group; online design; online identification; tracking control; uncertain nonlinear large ship; Adaptive control; Artificial intelligence; Artificial neural networks; Electronic mail; Intelligent control; Marine vehicles; Motion control; Neural networks; Nonlinear control systems; Organizing; artificial neural network; intelligence control; knowledge-increasable neural network; ship motion control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.9
  • Filename
    5231125