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Establishment and experimental verification of a prandtl–ishlinskii hysteresis model for tri-layer conducting polymer actuators

Conference Paper


Abstract


  • In this paper, a Prandtl–Ishlinskii hysteresis

    model (PI) is used to build a rate-independent hysteresis model

    for a class of conducting polymer actuators typified by tri-layer

    conjugated polymer actuators. Firstly, an off-line method is

    proposed to identify a discretization density function for the

    hysteresis model, and then a linear transfer function for the

    actuator is identified using the PI inverse model. Secondly, a

    neural network approach is proposed to realize an adaptive

    on-line identification method for the density function of the PI

    hysteresis model. In the back propagation (BP) algorithm for

    the neural network, the discretization PI operator is considered

    as an operational function of the neural network and the density

    function is considered as the power value. Finally, the

    simulation and experimental results are presented to

    demonstrate the validity of the model identification method and

    the actuator model.

UOW Authors


  •   Wang, Xiangjiang (external author)
  •   Alici, Gursel
  •   Nguyen, Chuc Huu (external author)

Publication Date


  • 2013

Citation


  • Wang, X., Alici, G. & Nguyen, C. H. (2013). Establishment and experimental verification of a prandtl–ishlinskii hysteresis model for tri-layer conducting polymer actuators. 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) (pp. 1217-1221). United States: IEEE.

Scopus Eid


  • 2-s2.0-84883718113

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1261

Start Page


  • 1217

End Page


  • 1221

Place Of Publication


  • United States

Abstract


  • In this paper, a Prandtl–Ishlinskii hysteresis

    model (PI) is used to build a rate-independent hysteresis model

    for a class of conducting polymer actuators typified by tri-layer

    conjugated polymer actuators. Firstly, an off-line method is

    proposed to identify a discretization density function for the

    hysteresis model, and then a linear transfer function for the

    actuator is identified using the PI inverse model. Secondly, a

    neural network approach is proposed to realize an adaptive

    on-line identification method for the density function of the PI

    hysteresis model. In the back propagation (BP) algorithm for

    the neural network, the discretization PI operator is considered

    as an operational function of the neural network and the density

    function is considered as the power value. Finally, the

    simulation and experimental results are presented to

    demonstrate the validity of the model identification method and

    the actuator model.

UOW Authors


  •   Wang, Xiangjiang (external author)
  •   Alici, Gursel
  •   Nguyen, Chuc Huu (external author)

Publication Date


  • 2013

Citation


  • Wang, X., Alici, G. & Nguyen, C. H. (2013). Establishment and experimental verification of a prandtl–ishlinskii hysteresis model for tri-layer conducting polymer actuators. 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) (pp. 1217-1221). United States: IEEE.

Scopus Eid


  • 2-s2.0-84883718113

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1261

Start Page


  • 1217

End Page


  • 1221

Place Of Publication


  • United States