• DocumentCode
    678954
  • Title

    Feedback control of outer rotor spherical actuator using adaptive neuro-fuzzy inference system

  • Author

    Junghyun Chu ; Niguchi, Noboru ; Hirata, Kazufumi

  • Author_Institution
    Dept. of Adaptive Machine Syst., Osaka Univ., Suita, Japan
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    401
  • Lastpage
    405
  • Abstract
    Adaptive neuro-fuzzy inference systems (ANFIS) has the advantage of expert knowledge of the fuzzy inference system (FIS) and learning capabilities of the neural networks (NN) for control of a nonlinear system. The membership function parameters are tuned using a combination of the least squares estimation and back propagation. So, a control method using ANFIS will produce more accurate results compared to other control methods. In this paper, we propose a feedback control method using the adaptive neuro-fuzzy inference system (ANFIS) for the outer rotor spherical actuator. Outer rotor spherical actuators are a type of multi-DOF actuator that can produce a high torque. In order to verify the ANFIS, experiments using a prototype of the outer rotor spherical actuator are conducted using a dSPACE controller with MATLAB/Simulink.
  • Keywords
    actuators; adaptive control; backpropagation; feedback; fuzzy control; least mean squares methods; neurocontrollers; nonlinear control systems; rotors; ANFIS; MATLAB; Simulink; adaptive neuro-fuzzy inference system; back propagation; dSPACE controller; expert knowledge; feedback control; least squares estimation; membership function parameter; multiDOF actuator; neural network; nonlinear system control; outer rotor spherical actuator; Artificial intelligence; Conferences; Sensors; adaptive neuro-fuzzy inference system; feedback control; spherical actuator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sensing Technology (ICST), 2013 Seventh International Conference on
  • Conference_Location
    Wellington
  • ISSN
    2156-8065
  • Print_ISBN
    978-1-4673-5220-8
  • Type

    conf

  • DOI
    10.1109/ICSensT.2013.6727684
  • Filename
    6727684