• DocumentCode
    58842
  • Title

    Fuzzy Neural-Network Friction Compensation-Based Singularity Avoidance Energy Swing-Up to Nonequilibrium Unstable Position Control of Pendubot

  • Author

    Deyin Xia ; Tianyou Chai ; Liangyong Wang

  • Author_Institution
    State Key Lab. of Synthetical Autom. for Process Ind., Northeastern Univ., Shenyang, China
  • Volume
    22
  • Issue
    2
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    690
  • Lastpage
    705
  • Abstract
    This paper mainly researches the swing-up control of Pendubot. Comparing with the uppermost unstable equilibrium position, it is more difficult to make the Pendubot swing up to the unstable nonequilibrium position. In order to complete the control target, the energy-based controller incorporated with fuzzy neural network compensation (ECFNNC) is designed in this paper. In addition, numerical simulations and experimental results of the Pendubot actuated by a dc servo motor are given in this paper. By comparing the results with other algorithms, it is found that the ECFNNC proposed in this paper has better performance under the same conditions.
  • Keywords
    DC motors; compensation; control system synthesis; friction; fuzzy control; manipulator dynamics; neurocontrollers; numerical analysis; position control; power control; servomotors; ECFNNC; Pendubot control; dc servo motor; drive-arm friction model; fuzzy neural-network friction compensation; nonequilibrium unstable position control; numerical simulations; singularity avoidance energy swing-up control; DC servo motor; energy-based controller; fuzzy neural network; numerical simulations and experimental results; the unstable nonequilibrium position;
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/TCST.2013.2255290
  • Filename
    6515604