• DocumentCode
    2728038
  • Title

    Research of RBF neural network PID control algorithm for longitudinal channel control of small UAV

  • Author

    Shichao Wang ; Baokui Li ; Qingbo Geng

  • Author_Institution
    Sch. of Autom., Beijing Inst. of Technol., Beijing, China
  • fYear
    2013
  • fDate
    12-14 June 2013
  • Firstpage
    1824
  • Lastpage
    1827
  • Abstract
    An intelligent PID controller based on RBF neural network was designed for longitudinal attitude control of a small unmanned aerial vehicle (UAV) according to the feature of complexity and nonlinear; RBF neural network is used to real-time update the PID parameters on line by its learning function for achieving the longitudinal channel control of the UAV; Simulation results show that the design of the RBF neural network PID controller has better control performance and it better satisfies the requirements of the longitudinal channel flight control of small UAV.
  • Keywords
    attitude control; autonomous aerial vehicles; control system synthesis; neurocontrollers; radial basis function networks; three-term control; RBF neural network PID control algorithm; RBF neural network PID controller design; intelligent PID controller; learning function; longitudinal attitude control; longitudinal channel control; longitudinal channel flight control; small UAV; small unmanned aerial vehicle; Aerospace control; Automation; Equations; Mathematical model; Neural networks; PD control; Simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation (ICCA), 2013 10th IEEE International Conference on
  • Conference_Location
    Hangzhou
  • ISSN
    1948-3449
  • Print_ISBN
    978-1-4673-4707-5
  • Type

    conf

  • DOI
    10.1109/ICCA.2013.6565086
  • Filename
    6565086