Advertisement

Nonlinear Dynamics

, Volume 84, Issue 4, pp 2363–2375 | Cite as

Backlash identification for PMSM servo system based on relay feedback

  • Yong Han
  • Chao Liu
  • Jianhua Wu
Original Paper
  • 376 Downloads

Abstract

This paper presents a novel method of backlash identification for PMSM servo system based on a relay feedback technique. We develop this method by analyzing the motor velocity signal in time domain under a strong assumption that the speed signal can be viewed as piecewise segments. The proposed approach takes a dead-zone model to describe the backlash and adopts an elastic two-mass model to represent the servo system. In view of response speed and differential noise, the motor velocity has been chosen to be the feedback signal. It should be pointed that particular attention ought to be paid to the choices of the parameters of the delay element and the relay component. This is because undervalued choices may lead to system chaos and thus the failure of identification. Since little knowledge is available about the potential backlash size, the identification procedure is performed iteratively until the identified value converges to its true value. This new strategy only requires one encoder on the motor side, from which the position and speed signals can be acquired. To complete the identification process, however, knowledge of both the motor’s moment of inertia and the load’s moment of inertia is needed. Simulation and experimental results validate that this new strategy is easy and fast to execute with good accuracy.

Keywords

Backlash identification Servo system Relay feedback Dead-zone model Nonlinearity 

Notes

Acknowledgments

This research was supported in part by National Natural Science Foundation of China under Grant 51575355, National Key Basic Research Program of China under Grant 2013CB035804 and China Postdoctoral Science Foundation under Grant 2015M80325.

Supplementary material

Supplementary material 1 (mp4 43074 KB)

References

  1. 1.
    Brouri, A., Giri, F., Rochdi, Y., Chaoui, F.Z.: Frequency identification of nonparametric Hammerstein systems with backlash nonlinearity. In: American Control Conference (ACC). Proceedings of the American Control Conference, pp. 657–662. IEEE, New York (2011)Google Scholar
  2. 2.
    Chen, H.F.: Recursive identification for Wiener model with discontinuous piece-wise linear function. IEEE Trans. Automat. Contr. 51(3), 390–400 (2006)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Chen, J., Lu, X.L., Ding, R.F.: Gradient-based iterative algorithm for Wiener systems with saturation and dead-zone nonlinearities. J. Vib. Control 20(4), 634–640 (2014)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Chen, S.L., Tan, K.K., Huang, S.N.: Friction modeling and compensation of servomechanical systems with dual-relay feedback approach. IEEE Trans. Contr. Syst. Technol. 17(6), 1295–1305 (2009)CrossRefGoogle Scholar
  5. 5.
    Chen, X.D., Fang, F., Luo, X.: A friction identification approach based on dual-relay feedback configuration with application to an inertially stabilized platform. Mechatronics 24(8), 1120–1131 (2014)CrossRefGoogle Scholar
  6. 6.
    Gebler, D., Holtz, J.: Identification and compensation of gear backlash without output position sensor in high-precision servo systems. In: IEEE Industrial Electronics Society, Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society, pp. 662–666. AACHEN, GERMANY (1998)Google Scholar
  7. 7.
    Huang, X.Y., Zhang, H., Zhang, G.G., Wang, J.M.: Robust weighted gain-scheduling h-infinity vehicle lateral motion control with considerations of steering system backlash-type hysteresis. IEEE Trans. Contr. Syst. Technol. 22(5), 1740–1753 (2014)CrossRefGoogle Scholar
  8. 8.
    Jukic, T., Peric, N.: Model based backlash compensation. American Control Conference (ACC). In: Proceedings of the American Control Conference, pp. 775–780. IEEE, New York (2001)Google Scholar
  9. 9.
    Lee, T.H., Tan, K.K., Lim, S.Y., Dou, H.F.: Iterative learning control of permanent magnet linear motor with relay automatic tuning. Mechatronics 10(1–2), 169–190 (2000)CrossRefGoogle Scholar
  10. 10.
    Liu, C., Wu, J.H., Liu, J., Xiong, Z.H.: High acceleration motion control based on a time-domain identification method and the disturbance observer. Mechatronics 24(6), 672–678 (2014)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Liu, J., Wu, J.H., Xiong, Z.H., Zhu, X.Y.: Servo system identification using relay feedback: A time-domain approach. J. Manuf. Sci. Eng. ASME 134(6), 061012 (2012)Google Scholar
  12. 12.
    Liu, Z.C., Dong, X.M., Xue, J.P., Chen, Y.: Adaptive neural control for a class of time-delay systems in the presence of backlash or dead-zone non-linearity. IET Control Theoty A 8(11), 1009–1022 (2014)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Malas, A., Chatterjee, S.: Generating self-excited oscillation in a class of mechanical systems by relay-feedback. Nonlinear Dyn. 76(2), 1253–1269 (2014)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Nordin, M., Galic, J., Gutman, P.O.: New models for backlash and gear play. Int. J. Adapt. Control 11(1), 49–63 (1997)MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Panda, R.C.: Estimation of parameters of under-damped second order plus dead time processes using relay feedback. Comput. Chem. Eng. 30(5), 832–837 (2006)CrossRefGoogle Scholar
  16. 16.
    Pupeikis, R.: On recursive parametric identification of wiener systems. Inf. Technol. Control 40(1), 21–28 (2011)Google Scholar
  17. 17.
    Reyland, J., Bai, E.W.: Generalized wiener system identification: general backlash nonlinearity and finite impulse response linear part. Int. J. Adapt. Control 28(11), 1174–1188 (2014)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Sander-Tavallaey, S., Saarinen, K.: Backlash identification in transmission unit. In: IEEE International Conference on Control Applications/International Symposium on Intelligent Control. IEEE International Conference on Control Applications, pp. 1325–1331. IEEE, New York (2009)Google Scholar
  19. 19.
    Selmic, R.R., Lewis, F.L.: Backlash compensation in nonlinear systems using dynamic inversion by neural networks. Asian J. Control 2(2), 76–87 (2000)CrossRefGoogle Scholar
  20. 20.
    Shen, Q.Y., Ding, F.: Iterative estimation methods for Hammerstein controlled autoregressive moving average systems based on the key-term separation principle. Nonlinear Dyn. 75(4), 709–716 (2014)CrossRefMATHGoogle Scholar
  21. 21.
    Tan, K.K., Lee, T.H., Huang, S.N., Xi, J.: Friction modeling and adaptive compensation using a relay feedback approach. IEEE Trans. Ind. Electron. 48(1), 169–176 (2001)Google Scholar
  22. 22.
    Tong, S.C., Li, Y.M.: Adaptive fuzzy output feedback control of MIMO nonlinear systems with unknown dead-zone inputs. IEEE Trans. Fuzzy Syst. 21(1), 134–146 (2013)CrossRefGoogle Scholar
  23. 23.
    Villwock, S., Pacas, M.: Time-domain identification method for detecting mechanical backlash in electrical drives. IEEE Trans. Ind. Electron. 56(2), 568–573 (2009)CrossRefGoogle Scholar
  24. 24.
    Voros, J.: Modeling and identification of nonlinear cascade and sandwich systems with general backlash. J. Electr. Eng. Slovak. 65(2), 104–110 (2014)Google Scholar
  25. 25.
    Voros, J.: Iterative identification of nonlinear dynamic systems with output backlash using three-block cascade models. Nonlinear Dyn. 79(3), 2187–2195 (2015)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Wang, D.Q., Ding, F., Liu, X.M.: Least squares algorithm for an input nonlinear system with a dynamic subspace state space model. Nonlinear Dyn. 75(1–2), 49–61 (2014)MathSciNetCrossRefMATHGoogle Scholar
  27. 27.
    Wang, H.Q., Chen, B., Liu, K.F., Liu, X.P., Lin, C.: Adaptive neural tracking control for a class of nonstrict-feedback stochastic nonlinear systems with unknown backlash-like hysteresis. IEEE Trans. Neural Netw. 25(5), 947–958 (2014)CrossRefGoogle Scholar
  28. 28.
    Wang, Q.G., Hang, C.C., Bi, Q.: Process frequency response estimation from relay feedback. Control Eng. Pract. 5(9), 1293–1302 (1997)MathSciNetCrossRefGoogle Scholar
  29. 29.
    Wu, Y.F., Wang, Z.H., Li, Y.Y., Chen, W., Du, R.H., Chen, Q.W.: Characteristic modeling and control of servo systems with backlash and friction. Math. Pro. Eng. 2014, 328–450 (2014)Google Scholar
  30. 30.
    Yu, C.P., Zhang, C.S., Xie, L.H.: A new deterministic identification approach to hammerstein systems. IEEE Trans. Signal Process. 62(1), 131–140 (2014)MathSciNetCrossRefGoogle Scholar
  31. 31.
    Zhang, Z.Q., Shen, H., Li, Z., Zhang, S.Z.: Zero-error tracking control of uncertain nonlinear systems in the presence of actuator hysteresis. Int. J. Syst. Sci. 46(15), 2853–2864 (2015)MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.State Key Laboratory of Mechanical System and Vibration, School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

Personalised recommendations