• DocumentCode
    1795311
  • Title

    System identification of quadrotor UAV based on genetic algorithm

  • Author

    Jinpeng Yang ; Zhihao Cai ; Qing Lin ; Dongyao Zhang ; Yingxun Wang

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    2336
  • Lastpage
    2340
  • Abstract
    Quadrotor helicopter is an increasingly popular rotorcraft platform for unmanned aerial vehicle (UAV) study. Development of a mathematical model with accurate model parameters for quadrotor is extremely beneficial to control the system. But accurate measurement of numerous vehicle parameters would be especially challenging. In this paper, a system identification method for the quadrotor model parameter identification based on genetic algorithm is proposed. Using the real flight input and output information, the genetic algorithm can identify the model parameters. And the results show that the identified parameters with genetic algorithm have an acceptable accuracy.
  • Keywords
    genetic algorithms; helicopters; identification; genetic algorithm; quadrotor UAV; quadrotor helicopter; quadrotor model parameter identification; system identification method; unmanned aerial vehicle; Accuracy; Educational institutions; Genetic algorithms; Mathematical model; Parameter estimation; System identification; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4799-4700-3
  • Type

    conf

  • DOI
    10.1109/CGNCC.2014.7007533
  • Filename
    7007533