• DocumentCode
    3114145
  • Title

    Position Control of a Intelligent Module based on Neural Network Sliding Mode Control

  • Author

    Chen, Weihai ; Yong, Gao ; Lu, Zhen ; Yuan, Xue Ming

  • Author_Institution
    Singapore Inst. of Manuf. Technol., Singapore
  • fYear
    2006
  • fDate
    16-18 Aug. 2006
  • Firstpage
    990
  • Lastpage
    994
  • Abstract
    Based on the standard intelligent module of the modular robot, a kind of neural network sliding mode control method is put forward. The neural network is used to approach to the function between the state hyperplane of the system and the reaching law. A hyperbolic tangent function is applied to replace the saturated function in order to realize the boundary method design of the sliding mode control. Simulation results show that system owns quick response and strong antijamming capability. Moreover, the chattering of neural network sliding mode control is weakened effectively, and problems that cannot be solved with the traditional PID control method under complicated environment and conditions such as variable load etc can be solved.
  • Keywords
    intelligent robots; neurocontrollers; position control; three-term control; variable structure systems; PID control method; antijamming capability; boundary method design; hyperbolic tangent function; intelligent module; modular robot; neural network sliding mode control; position control; state hyperplane; Automatic voltage control; Intelligent control; Intelligent networks; Neural networks; Position control; Robot sensing systems; Service robots; Servomotors; Sliding mode control; Torque control; Robot control; actuator; neural network control; sliding-mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics, 2006 IEEE International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    0-7803-9700-2
  • Electronic_ISBN
    0-7803-9701-0
  • Type

    conf

  • DOI
    10.1109/INDIN.2006.275732
  • Filename
    4053524