• DocumentCode
    569704
  • Title

    Robust adaptive neural network control of aircraft braking system

  • Author

    Bihua Chen ; Zongxia Jiao ; Shuzhi Sam Ge ; Chengwen Wang

  • Author_Institution
    Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    740
  • Lastpage
    745
  • Abstract
    This paper addresses the nonlinear robust braking control of aircraft. We consider the unknown aerodynamic forces and moments which will degrade the brake performance significantly. Moreover, for the transport or commercial air-crafts, weight variation will influence the braking control torque calculation. In this paper, robust adaptive control is proposed for aircraft braking system. By integrating a neural network (NN) estimator to approximate unknown aerodynamic forces and moments, the proposed control can effectively suppress the aerodynamic uncertainties and weight variation. The brake torque input constraint is also discussed in this paper. Simulation results clearly demonstrate the advantages and effectiveness of the proposed method.
  • Keywords
    adaptive control; aerodynamics; aircraft control; brakes; braking; force control; neurocontrollers; nonlinear control systems; robust control; torque control; uncertain systems; vehicle dynamics; aerodynamic uncertainty suppression; aircraft braking system; braking control torque calculation; neural network estimator; nonlinear robust braking control; robust adaptive neural network control; unknown aerodynamic forces; unknown aerodynamic moments; weight variation; Aerodynamics; Aerospace control; Aircraft; Force; Friction; Gears; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-0312-5
  • Type

    conf

  • DOI
    10.1109/INDIN.2012.6301235
  • Filename
    6301235