• DocumentCode
    1886737
  • Title

    A Fuzzy-Neural Network Sliding Mode Control for Flexible Spacecraft

  • Author

    Chen, Yu ; Dong, Chaoyang

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A fuzzy-neural network sliding mode control (FNNSMC) is proposed for the attitude stabilization of flexible spacecraft during large angle slew maneuver. The dynamic model of the spacecraft with flexible appendages is derived by Lagrange equation. To make the system state reach sliding mode surface in finite time, a sliding mode controller is designed, so the system is robustness against uncertainties and disturbances during the sliding phase. A fuzzy-neural network system is used to approximate the strong coupling nonlinear dynamics between rigid hub and flexible appendages, so that the elastic vibration of flexible spacecraft during maneuver is suppressed and the attitude of flexible spacecraft is stabilized. Simulation results show that not only high-precision attitude stabilization of flexible spacecraft is achieved, but also the elastic vibration of flexible spacecraft during maneuver is suppressed effectively.
  • Keywords
    control system synthesis; fuzzy control; neurocontrollers; space vehicles; stability; variable structure systems; vehicle dynamics; vibrations; Lagrange equation; angle slew maneuver; attitude stabilization; coupling nonlinear dynamics; elastic vibration; flexible appendages; flexible spacecraft; fuzzy-neural network sliding mode control; rigid hub; Approximation methods; Attitude control; Fuzzy control; Fuzzy neural networks; Mathematical model; Sliding mode control; Space vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5677732
  • Filename
    5677732