Operator-Based Robust Nonlinear Control for Ionic Polymer Metal Composite with Uncertainties and Hysteresis

  • Aihui Wang
  • Mingcong Deng
  • Dongyun Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6424)


The ionic polymer metal composite (IPMC) belongs to the category electroactive polymers (EAP), many potential applications for low-mass high-displacement actuators in biomedical and robotic systems have been shown. But identification of some physical parameters for nonlinear IPMC models is still a difficult issue. Moreover, hysteretic behavior exists in IPMCs and affects the performance of actuators, even makes the system with these actuators exhibit undesirable oscillations and instability. In this paper, a new nonlinear model of the IPMC with uncertainties and hysteresis is obtained. According to hysteresis and uncertainties for the proposed model, a nonlinear robust control using operator-based robust right coprime factorization is designed for the IPMC. The effectiveness of the proposed method is confirmed through simulation and experiment.


IPMC Uncertainties Hysteresis Nonlinear Control Right Coprime Factorization Robust Stability 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Shahinpoor, M., Kim, K.: Ionic polymer-metal composites: I. Fundamentals. Smart Materials and Structures 10, 819–833 (2001)CrossRefGoogle Scholar
  2. 2.
    Shahinpoor, M.: Ionic polymer-conductor composites as biomimetic sensors, robotic actuators and artificial muscles-a review. Electrochimica Acta 48, 2343–2353 (2003)CrossRefGoogle Scholar
  3. 3.
    Chen, Z., Tan, X.: A control-oriented and physics-based model for ionic polymer-metal composite actuators. IEEE/ASME Transactions on Mechatronics 13, 519–529 (2008)CrossRefGoogle Scholar
  4. 4.
    Bhat, N., Kim, W.: Precision position control of ionic polymer metal composite. In: Proc. of the 2004 American Control Conference, Boston, MA, pp. 740–745 (2004)Google Scholar
  5. 5.
    Oh, S., Kim, H.: A study on the control of an IPMC actuator using an adaptive fuzzy algorithm. Journal of Mechanical Science and Technology 18, 1–11 (2004)Google Scholar
  6. 6.
    Bhat, N., Kim, W.: Precision force and position control of ionic polymer metal composite. Journal of Systems and Control Engineering 218, 421–432 (2004)Google Scholar
  7. 7.
    Hao, L., Li, Z.: Modeling and adaptive inverse control of hysteresis and creep in ionic polymer-metal composite actuators. Smart Materials and Structures 19, 14–25 (2010)CrossRefGoogle Scholar
  8. 8.
    Deng, M., Inoue, A., Ishikawa, K.: Tracking of perturbed nonlinear plants using robust right coprime factorization approach. In: Proc. of the 2004 American Control Conference, Boston, MA, pp. 3666–3670 (2004)Google Scholar
  9. 9.
    Figueiredo, R., Chen, G.: Nonlinear Feedback Control System: an Operator Theory Approach. Academic Press Inc., New York (1993)zbMATHGoogle Scholar
  10. 10.
    Deng, M., Inoue, A., Ishikawa, K.: Operator-based nonlinear feedback control design using robust right coprime factorization. IEEE Transactions on Automatic Control 51, 645–648 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Chen, G., Han, Z.: Robust right coprime factorization and robust stabilization of nonlinear feedback control systems. IEEE Transactions on Automatic Control 43, 1505–1510 (1998)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Deng, M., Bi, S., Inoue, A.: Robust nonlinear control and tracking design for multi-input multi-output nonlinear perturbed plants. IET Control Theory & Applications 3, 1237–1248 (2009)CrossRefGoogle Scholar
  13. 13.
    Wen, S., Deng, M.: Experimental study of robust control to a nonlinear MIMO process using robust right coprime factorization. ICIC Express Letters 3, 1061–1066 (2009)Google Scholar
  14. 14.
    Deng, M., Wang, A., Minami, M., Yanou, A.: Operator-based Modeling for Nonlinear Ionic Polymer Metal Composite with Uncertainties. In: Proc. of 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, Okayama, Japan (2010) (submitted)Google Scholar
  15. 15.
    Saito, S., Deng, M., Inoue, A., Jiang, C.: Vivration control of a fiexible arm experimental system with hysteresis of piezoelectric actuator. International Journal of Innovative Computing, Information and Control 6, 2965–2975 (2010)Google Scholar
  16. 16.
    Jiang, C., Deng, M., Inoue, A.: Robust stability of nonlinear plants with a non-symmetric Prandtl-Ishlinskii hysteresis model. International Journal of Automation and Computing 7, 213–218 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Aihui Wang
    • 1
    • 2
  • Mingcong Deng
    • 1
    • 2
  • Dongyun Wang
    • 1
    • 2
  1. 1.School of Electronic InformationZhongyuan University of TechnologyZhengzhouChina
  2. 2.Graduate School of Natural Science and TechnologyOkayama UniversityOkayamaJapan

Personalised recommendations