• DocumentCode
    2930781
  • Title

    Intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks for a ball-riding robot

  • Author

    Cheng-Kai Chan ; Ching-Chih Tsai

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung Hsing Univ., Taichung, Taiwan
  • fYear
    2012
  • fDate
    16-18 Nov. 2012
  • Firstpage
    169
  • Lastpage
    174
  • Abstract
    This paper presents an intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks (RIT2FNN) for motion control of a ball-riding robot. After brief description of the dynamic model of the robot with viscous and Coulomb frictions, a backstepping sliding-mode control using hierarchical aggregated sliding control method and RIT2FNN is proposed to accomplish robust trajectory tracking of the robot in the presence of mass variations, terrain-dependent viscous and Coulomb frictions. Computer simulations are conducted to illustrate the effectiveness of the proposed control method.
  • Keywords
    friction; fuzzy neural nets; mobile robots; motion control; neurocontrollers; position control; recurrent neural nets; robot dynamics; variable structure systems; Coulomb friction; RIT2FNN; ball-riding robot; hierarchical aggregated sliding control method; intelligent backstepping sliding-mode control; mass variation; motion control; recurrent interval type 2 fuzzy neural network; robot dynamic model; robot trajectory tracking; viscous friction; Backstepping; Equations; Mathematical model; Mobile robots; Sliding mode control; Vectors; backstepping; ball-riding robot; recurrent interval type 2 fuzzy neural networks (RIT2FNN); sliding-mode control; trajectory tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on
  • Conference_Location
    Taichung
  • Print_ISBN
    978-1-4673-2057-3
  • Type

    conf

  • DOI
    10.1109/iFUZZY.2012.6409695
  • Filename
    6409695