• DocumentCode
    3101808
  • Title

    Study on Preview Control Theory for Trajectory Tracking Control

  • Author

    Liu Xiao-feng ; Tian Mu-Qin ; Lv Yong-Wei ; Wang Shu-Hua

  • Author_Institution
    Taiyuan Univ. of Technol., Taiyuan, China
  • fYear
    2010
  • fDate
    26-28 Sept. 2010
  • Firstpage
    445
  • Lastpage
    447
  • Abstract
    Trajectory tracking is popularity in industrial procession, such as machining parts control, high automatic control for a roller of shearer cutting in memory mode, etc. In these cases, trajectory tracked was often artificially pre-determined, and essentially belongs to the fields of predictable control. There are still some shortages in the respect of tracking accuracy and responsiveness among the existing control methods. Therefore, the application of predicted control theory, with the neural network and genetic algorithm identifying the dynamic object model, gives new vigor and vitality to the traditional trajectory tracking.
  • Keywords
    genetic algorithms; neural nets; position control; predictive control; dynamic object model; genetic algorithm; industrial process; neural network; predictable control; preview control theory; trajectory tracking control; Artificial neural networks; Equations; Function approximation; Mathematical model; Target tracking; Training; Trajectory; Auto-adjusting of height for CaiMeiJi; memory cutting; neural network; previewing control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Aspects of Social Networks (CASoN), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-8785-1
  • Type

    conf

  • DOI
    10.1109/CASoN.2010.105
  • Filename
    5636609