• DocumentCode
    1795332
  • Title

    Sensor fault detection and isolation in small-scale autonomous helicopters

  • Author

    Erzhuo Niu ; Minwen Wang ; Zixia Wen ; Jia Li

  • Author_Institution
    AVIC Xi´an Flight Autom. Control Res. Inst., Xi´an, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    2397
  • Lastpage
    2400
  • Abstract
    This paper deals with the problem of Fault detection and isolation for a small-scale autonomous helicopter. By using the unobservable and unobservability subspace concept, the smallest unobservability subspace is constructed to describe the fault characteristics. The residual designed by geometric approach is only sensitive to single sensor. Our proposed method is then applied to an autonomous helicopter. The component of the gyroscope angular velocity sensor has been used as representative case of sensor fault detection and isolation for three fault types (stuck with constant bias, additive type and multiplicative type). Numerical examples for sensor faults are given to show the validness of our proposed fault detection and isolation algorithm.
  • Keywords
    angular velocity control; autonomous aerial vehicles; fault diagnosis; gyroscopes; helicopters; sensors; additive fault; constant bias; fault characteristics; fault types; gyroscope angular velocity sensor; multiplicative type; sensor fault detection and isolation; small-scale autonomous helicopters; stuck fault; unobservability subspace; Additives; Aerospace control; Fault detection; Gyroscopes; Helicopters; Robustness; Vectors; FDI; Geometric approach; Sensor fault; Unobserservability subspace;
  • 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.2014.7007544
  • Filename
    7007544