Skip to main content
Log in

Extended-state-observer-based robust torsional vibration suppression for rolling mill main drive system with input saturation

  • Original Paper
  • Published:
Journal of Iron and Steel Research International Aims and scope Submit manuscript

Abstract

A robust torsional vibration suppression strategy is proposed for the main drive system of the rolling mill subject to uncertainties, disturbances and input saturation. With given model information incorporated into observer design, an extended state observer that relies only on roller speed measurements is developed to estimate the system states and lumped uncertainties of the rolling mill main drive system. To handle the motor torque saturation, an auxiliary signal system with the same order as the plant is constructed. The error between the control input and plant input is taken as the input of the constructed auxiliary system, and a number of signals are generated to compensate for the effect of the motor torque saturation. Furthermore, a robust output feedback controller is introduced to obtain better transient and steady-state performance of the rolling mill main drive system and the stability of the closed-loop system is strictly proved via Lyapunov theory. Finally, comparative simulations are performed to verify the effectiveness and superiority of the proposed control strategy.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Y.F. Zhang, X.Q. Yan, Q.H. Lin, Chin. J. Mech. Eng. 29 (2016) 180–187.

    Article  Google Scholar 

  2. P.M. Shi, J.Z. Li, J.S. Jiang, B. Liu, D.Y. Han, J. Iron Steel Res. Int. 20 (2013) No. 1, 7–12.

    Article  Google Scholar 

  3. M. Zhang, Y. Peng, J.L. Sun, H.R. Li, J. Iron Steel Res. Int. 26 (2019) 953–961.

    Article  Google Scholar 

  4. L.P. Wang, Y.L. Zhao, Q.Y. Zhu, Y. Liu, Q.K. Han, ISIJ Int. 60 (2020) 1237–1244.

    Article  Google Scholar 

  5. X.G. Liu, Z.Y. Wu, J. Lu, J.L. Xu, J. Adv. Mech. Des. Syst. Manuf. 13 (2019) 0079.

    Article  Google Scholar 

  6. P.M. Shi, K.W. Xia, B. Liu, J.S. Jiang, Journal of Mechanical Engineering 48 (2012) No. 17, 57–64.

    Article  Google Scholar 

  7. D.Y. Han, P.M. Shi, D.W. Zhao, Shock Vibration 35 (2016) No. 12, 1–6.

    Google Scholar 

  8. B. Liu, S. Liu, Y.K. Zhang, Y. Wen, Journal of Mechanical Engineering 46 (2010) No. 8, 160–166.

    Article  Google Scholar 

  9. D.X. Hou, L. Xu, P.M. Shi, J. Iron Steel Res. Int. 28 (2021) 574–585.

    Article  Google Scholar 

  10. X. Yang, K.X. Peng, C.N. Tong, Abstract Appl. Anal. 2013 (2013) 387890.

    Google Scholar 

  11. U.M. Nath, C. Dey, R.K. Mudi, IEEE Control Syst. Lett. 5 (2021) 1255–1260.

    Article  MathSciNet  Google Scholar 

  12. J. Hao, G.S. Zhang, W.Q. Liu, Y.Q. Zheng, L. Ren, IEEE Trans. Ind. Electron. 68 (2020) 21051678.

    Google Scholar 

  13. K. Erenturk, IET Control Theory Appl. 2 (2008) 635–642.

    Article  Google Scholar 

  14. K. Tsuda, T. Sakuma, K. Umeda, S. Sakaino, T. Tsuji, IEEJ J. Ind. Appl. 6 (2017) 320–327.

    Google Scholar 

  15. J.Q. Han, IEEE Trans. Ind. Electron. 56 (2009) 900–906.

    Article  Google Scholar 

  16. J.Y. Yao, Z.X. Jiao, D.W. Ma, IEEE Trans. Ind. Electron. 61 (2014) 3630–3637.

    Article  Google Scholar 

  17. Q. Guo, Y. Zhang, B.G. Celler, S.W. Su, IEEE Trans. Ind. Electron. 63 (2016) 6909–6920.

    Article  Google Scholar 

  18. W.Z. Shi, J.H. Wei, J.H. Fang, IEEE Access 6 (2018) 64503–64514.

    Article  Google Scholar 

  19. R.X. Cui, L.P. Chen, C.G. Yang, M. Chen, IEEE Trans. Ind. Electron. 64 (2017) 6785–6795.

    Article  Google Scholar 

  20. Z.H. Peng, J. Wang, IEEE Trans. Syst. Man Cybern. 48 (2018) 535–544.

    Article  Google Scholar 

  21. D. Lin, X.Y. Wang, Y. Yao, Nonlinear Dynam. 67 (2012) 2889–2897.

    Article  Google Scholar 

  22. K.N. Yong, M. Chen, Y. Shi, Q.X. Wu, Automatica 122 (2020) 109268.

    Article  Google Scholar 

  23. X.Y. Zhu, D.D. Li, Mech. Syst. Signal Process. 149 (2021) 107209.

    Article  Google Scholar 

  24. C. Qian, C.C. Hua, L.L. Zhang, Z.H. Bai, J. Franklin Inst. 17 (2020) 12886–12903.

    Article  Google Scholar 

  25. R. Zhang, W. Yang, W. Liang, Y. Zhang, Control Engineering of China 25 (2018) No. 12, 16–21.

    Google Scholar 

  26. H. Khalil, L. Praly, Int. J. Robust Nonlin. 24 (2014) 991–1015.

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. U20A20187 and 61933009) and the Top talents of Hebei provincial Education Department (Grant No. BJ2019047).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shu-zong Chen.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Jq., Chen, Sz., Hua, Cc. et al. Extended-state-observer-based robust torsional vibration suppression for rolling mill main drive system with input saturation. J. Iron Steel Res. Int. 30, 985–993 (2023). https://doi.org/10.1007/s42243-023-00933-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42243-023-00933-5

Keywords

Navigation