• DocumentCode
    295891
  • Title

    The application of neural networks to anti-skid brake system design

  • Author

    Mazumdar, Sanjay K. ; Chew Lim, Cheng

  • Author_Institution
    Weapons Syst. Div., Defence Sci. & Technol. Organ., Salisbury, SA, Australia
  • Volume
    5
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2409
  • Abstract
    A neural network based model reference adaptive control approach to anti-skid brake system (ABS) design is investigated in this paper. The principal benefit of using neural networks in an ABS is their ability to adapt to changes in the environmental conditions without significant degradation in performance. In the proposed approach, the controller neural network is designed to produce a braking torque which regulates the wheel slip for the vehicle-brake system to a prespecified level. Simulation studies are performed to demonstrate the effectiveness of the proposed neural network based anti-skid brake system (NN-ABS)
  • Keywords
    brakes; model reference adaptive control systems; neurocontrollers; road vehicles; anti-skid brake system; braking torque; controller neural network; environmental conditions; neural network based model reference adaptive control; vehicle-brake system; wheel slip; Australia; Control systems; Friction; Neural networks; Roads; Tires; Torque control; Vehicle dynamics; Vehicles; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487739
  • Filename
    487739