Skip to main content
SpringerLink
Log in

Adaptive trajectory tracking of magnetostrictive actuator based on preliminary hysteresis compensation and further adaptive filter controller

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

The magnetostrictive actuator is a widely used precision smart actuator; however, the micro-positioning and tracking performance of it is limited due to the inherent dynamic nonlinearities. In order to improve the tracking performance of actuator, a hybrid control strategy comprising a preliminary rate-independent hysteresis compensation and a further adaptive filter controller is developed. The generalized Prandtl–Ishlinskii model that has analytical inversion is used to preliminarily compensate the rate-independent hysteresis. A modified coral reef optimization algorithm is utilized to identify the model parameter and accordingly enhance the compensation accuracy. In addition, considering the input current and output displacement of magnetostrictive actuator are always positive, a one-side generalized play operator is adopted. Further, the adaptive finite impulse response controller is applied to eliminate the preliminary compensation error which is owing to the dynamic effect of nonlinearities. In order to validate the hybrid control strategy, some simulations and experiments are conducted. Compared with the feedforward inverse controller, the hybrid control strategy is of better accuracy and adaptivity. The results demonstrate that the hybrid control strategy is capable of precisely tracking step and multiple-frequency sinusoidal trajectory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Tan, X., Baras, J.S.: Modeling and control of hysteresis in magnetostrictive actuators. Automatica 40(9), 1469–1480 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  2. Zhang, T., Jiang, C., Zhang, H., Xu, H.: Giant magnetostrictive actuators for active vibration control. Smart Mater. Struct. 13(3), 473–477 (2004). ISSN 0964-1726 1361-665X

    Article  Google Scholar 

  3. Yang, B., Meng, G., Feng, Z.-Q., Yang, D.: Giant magnetostrictive clamping mechanism for heavy-load and precise positioning linear inchworm motors. Mechatronics 21(1), 92–99 (2011)

    Article  Google Scholar 

  4. Visintin, A.: Differential Models of Hysteresis. Springer, Berlin (1994)

    Book  MATH  Google Scholar 

  5. Jiles, D.C., Atherton, D.L.: Theory of ferromagnetic hysteresis (invited). J. Appl. Phys. 61(1–2), 48–60 (1986)

    Google Scholar 

  6. Oh, J.H., Bernstein, D.S.: Piecewise linear identification for the rate-independent and rate-dependent Duhem hysteresis models. IEEE Trans. Autom. Control 52(3), 576–582 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  7. Kuhnen, K., Krejci, P.: Compensation of complex hysteresis and creep effects in piezoelectrically actuated systems—a new Preisach modeling approach. IEEE Trans. Autom. Control 54(3), 537–550 (2009). ISSN 0018-9286

    Article  MathSciNet  MATH  Google Scholar 

  8. Brokate, M., Sprekels, J.: Hysteresis and Phase Transitions, vol. 121. Springer, Berlin (1996)

    MATH  Google Scholar 

  9. Meng, A., Yang, J., Li, M., Jiang, S.: Research on hysteresis compensation control of GMM. Nonlinear Dyn. 83(1), 161–167 (2016)

    Article  MathSciNet  Google Scholar 

  10. Kuhnen, K.: Modeling, identification and compensation of complex hysteretic nonlinearities: a modified Prandtl–Ishlinskii approach. Eur. J. Control 9(4), 407–418 (2003). ISSN 09473580

    Article  MATH  Google Scholar 

  11. Al Janaideh, M., Rakheja, S., Su, C.: An analytical generalized Prandtl–Ishlinskii model inversion for hysteresis compensation in micropositioning control. IEEE-ASME Trans. Mech. 16(4), 734–744 (2011). ISSN 1083-4435

    Article  Google Scholar 

  12. Aljanaideh, O., Al Janaideh, M., Rakheja, S., Su, C.Y.: Compensation of rate-dependent hysteresis nonlinearities in a magnetostrictive actuator using an inverse Prandtl–Ishlinskii model. Smart Mater. Struct. 22(2), 025027 (2013). ISSN 0964-1726 1361-665X

    Article  Google Scholar 

  13. Aljanaideh, O., Rakheja, S., Su, C.: Experimental characterization and modeling of rate-dependent asymmetric hysteresis of magnetostrictive actuators. Smart Mater. Struct. 23(3), 035002 (2014). ISSN 0964-1726 1361-665X

    Article  Google Scholar 

  14. Guo, Y., Mao, J., Zhou, K.: Rate-dependent modeling and robust control of GMA based on Hammerstein model with Preisach operator. IEEE Trans. Control Syst. Technol. 23(6), 2432–2439 (2015). ISSN 1063-6536

    Article  Google Scholar 

  15. Li, Z., Zhang, X., Gu, G.Y., Chen, X.: A comprehensive dynamic model for magnetostrictive actuators considering different input frequencies with mechanical loads. IEEE Trans. Ind. Inf. 12(3), 980–990 (2016)

    Article  Google Scholar 

  16. Vörös, J.: Recursive identification of discrete-time nonlinear cascade systems with time-varying output hysteresis. Nonlinear Dyn. 87(2), 1427–1434 (2017)

    Article  Google Scholar 

  17. Papoulis, E.V., Stathaki, T.: A normalized robust mixed-norm adaptive algorithm for system identification. IEEE Signal Process. Lett. 11(1), 56–59 (2004)

    Article  Google Scholar 

  18. George, N.V., Panda, G.: Advances in active noise control: a survey, with emphasis on recent nonlinear techniques. Signal Process. 93(2), 363–377 (2013)

    Article  Google Scholar 

  19. Shah, S.M., Samar, R., Khan, N.M., Raja, M.A.Z.: Fractional-order adaptive signal processing strategies for active noise control systems. Nonlinear Dyn. 85(3), 1363–1376 (2016)

    Article  MathSciNet  Google Scholar 

  20. Salcedo-Sanz, S., Del Ser, J., Landa-Torres, I., Gil-Lpez, S., Portilla-Figueras, J.A.: The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems. Sci World J, 2014, 739768–739768 (2014)

  21. Salcedo-Sanz, S., Pastor-Sánchez, A., Del Ser, J., Prieto, L., Geem, Z.W.: A coral reefs optimization algorithm with harmony search operators for accurate wind speed prediction. Renew Energy 75, 93–101 (2015)

    Article  Google Scholar 

  22. Li, M., Miao, C., Leung, C.: A coral reef algorithm based on learning automata for the coverage control problem of heterogeneous directional sensor networks. Sensors 15(12), 30617–30635 (2015)

    Article  Google Scholar 

  23. Yang, Y., Yang, B., Niu, M.: Parameter identification of Jilesc–Atherton model for magnetostrictive actuator using hybrid niching coral reefs optimization algorithm. Sens. Actuators A Phys. 261, 184–195 (2017)

    Article  Google Scholar 

  24. Li, J., Mourelatos, Z.P.: Time-dependent reliability estimation for dynamic problems using a niching genetic algorithm. J. Mech. Des. 131(7), 1119–1133 (2009)

    Article  Google Scholar 

  25. Kang, F., Li, J., Ma, Z.: Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions. Inf. Sci. 181(16), 3508–3531 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  26. Haykin, S.: Adaptive Filter Theory, vol. 2, pp. 478–481. Prentice Hall, Englewood Cliffs (2002)

    Google Scholar 

  27. Shin, H.C., Sayed, A.H., Song, W.J.: Variable step-size NLMS and affine projection algorithms. IEEE Signal Process. Lett. 11(2), 132–135 (2004)

    Article  Google Scholar 

Download references

Acknowledgements

The work is supported by National Natural Science Foundation of China (Grant No. 51775349), National key R&D program of China (No. 2017YFF0108000) and SJTU-CASC Advanced Space Technology Fund (Nos. USCAST 2015-05, USCAST 2016-13), for which the authors are most grateful.

Author information

Authors and Affiliations

  1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, 200240, China

    Yikun Yang, Bintang Yang & Muqing Niu

Authors
  1. Yikun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bintang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Muqing Niu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bintang Yang.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Y., Yang, B. & Niu, M. Adaptive trajectory tracking of magnetostrictive actuator based on preliminary hysteresis compensation and further adaptive filter controller. Nonlinear Dyn 92, 1109–1118 (2018). https://doi.org/10.1007/s11071-018-4112-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-018-4112-6

Keywords

Search

Navigation