Log in

Robust-optimal control design for current-controlled electromagnetic levitation system with unmatched input uncertainty

  • Published:
International Journal of Dynamics and Control Aims and scope Submit manuscript

Abstract

This article introduces the robust-optimal control design for the current-controlled electromagnetic levitation system (CC-EMLS). Because of the uncertain nature of the electromagnetic levitation system, it is essential to propose a robust regulator such that it will handle the system’s uncertainties. The dynamics of CC-EMLS are transformed in terms of the unmatched input uncertainty. The robust control issue in terms of uncertainties is reflected in the cost function, which is translated and solved using the optimal control problem. The controller developed using the optimal control method for the electromagnetic levitation system becomes the solution to the robust control problem to handle the uncertainties of the system. The Lyapunov stability theorem is used to establish the required stability proof. A simulation results demonstrates the proposed controller’s effectiveness, robustness, and efficiency. The integral error indices such as integral absolute error, integral square error, integral time absolute error, and integral time square error, are calculated to validate the effectiveness of the designed regulator.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

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

Similar content being viewed by others

Availability of data and materials

Not applicable.

References

  1. Wai RJ, Lee JD (2008) Robust levitation control for linear maglev rail system using fuzzy neural network. IEEE Trans Control Syst Technol 17(1):4–14

    Google Scholar 

  2. Sun Y, Xu J, Qiang H, Lin G (2019) Adaptive neural-fuzzy robust position control scheme for maglev train systems with experimental verification. IEEE Trans Industr Electron 66(11):8589–99

    Article  Google Scholar 

  3. Zhai M, Long Z, Li X (2019) A new strategy for improving the tracking performance of magnetic levitation system in maglev train. Symmetry 11(8):1053

    Article  ADS  Google Scholar 

  4. Li G, Wang X, Cui P, Li J (2019) Analysis of superconducting linear synchronous motor for electromagnetic propulsion. Clust Comput 22:2709–17

    Article  Google Scholar 

  5. Yu Y, Sun X, Zhang W (2017) Modeling and decoupling control for rotor system in magnetic levitation wind turbine. IEEE Access 27(5):15516–28

    Article  Google Scholar 

  6. Hemenway NR, Gjemdal H, Severson EL (2019) Magnetic bearing technology for industrial bearingless motor systems. In: 2019 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD), vol 1. IEEE, pp 51–58

  7. Chen C, Xu J, Ji W, Rong L, Lin G (2019) Sliding mode robust adaptive control of maglev vehicle’s nonlinear suspension system based on flexible track: Design and experiment. IEEE Access. 19(7):41874–84

    Article  Google Scholar 

  8. Sun N, Fang Y, Chen H (2017) Tracking control for magnetic-suspension systems with online unknown mass identification. Control Eng Pract 1(58):242–53

    Article  Google Scholar 

  9. Ginoya D, Gutte CM, Shendge PD, Phadke SB (2016) State-and-disturbance-observer-based sliding mode control of magnetic levitation systems. Trans Inst Meas Control 38(6):751–63

    Article  Google Scholar 

  10. Zhao D, Li S, Zhu Q, Gao F (2010) Robust finite-time control approach for robotic manipulators. IET Control Theory Appl 4(1):1–5

    Article  MathSciNet  Google Scholar 

  11. Malik AS, Ahmad I, Rahman AU, Islam Y (2019) Integral backstep** and synergetic control of magnetic levitation system. IEEE Access 8(7):173230–9

    Article  Google Scholar 

  12. Yaseen HM, Siffat SA, Ahmad I, Malik AS (2022) Nonlinear adaptive control of magnetic levitation system using terminal sliding mode and integral backstep** sliding mode controllers. ISA Trans 1(126):121–33

    Article  Google Scholar 

  13. Park Y (2014) Design and implementation of an electromagnetic levitation system for active magnetic bearing wheels. IET Control Theory Appl 8(2):139–48

    Article  MathSciNet  Google Scholar 

  14. Anantachaisilp P, Lin Z (2017) Fractional order PID control of rotor suspension by active magnetic bearings. In: Actuators, vol 6, No. 1. MDPI, p 4

  15. ElSinawi AH, Emam S (2011) Dual LQG-PID control of a highly nonlinear magnetic levitation system. In: 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization. IEEE, pp 1–4

  16. Ni F, Zheng Q, Xu J, Lin G (2019) Nonlinear control of a magnetic levitation system based on coordinate transformations. IEEE Access 11(7):164444–52

    Article  Google Scholar 

  17. Khan M, Siddiqui AS, Mahmoud AS (2018) Robust H-infinity control of magnetic levitation system based on parallel distributed compensator. Ain Shams Eng J 9(4):1119–29

    Article  Google Scholar 

  18. Santim M, Teixeira M, Souza WA, Cardim R, Assuncao E (2012) Design of a Takagi-Sugeno fuzzy regulator for a set of operation points. Math Probl Eng 1:2012

    MathSciNet  Google Scholar 

  19. Utkin VI (2013) Sliding modes in control and optimization. Springer, New York

    Google Scholar 

  20. Pérez-Ventura U, Fridman L (2020) Chattering comparison between continuous and discontinuous sliding-mode controllers. From Theory to Practice, Variable-Structure Systems and Sliding-Mode Control, pp 197–211

    Google Scholar 

  21. Chenarani H, Fateh MM (2023) Robust passivity-based sliding mode control of a large class of nonlinear systems subject to unmatched uncertainties: a robot manipulator case study. IETE J Res 69(7):4394–403

    Article  Google Scholar 

  22. Chenarani H, Binazadeh T (2017) Flexible structure control of unmatched uncertain nonlinear systems via passivity-based sliding mode technique. Iran J Sci Technol Trans Electr Eng 41:1–1

    Article  Google Scholar 

  23. Shieh HJ, Siao JH, Liu YC (2010) A robust optimal sliding-mode control approach for magnetic levitation systems. Asian J Control 12(4):480–7

    Article  MathSciNet  Google Scholar 

  24. Mourad A, Youcef Z (2022) Adaptive sliding mode control improved by fuzzy-PI controller: applied to magnetic levitation system. Eng Proc 14(1):14

    Google Scholar 

  25. Kumar EV, Jerome J (2013) LQR based optimal tuning of PID controller for trajectory tracking of magnetic levitation system. Procedia Eng 1(64):254–64

    Article  Google Scholar 

  26. Majewski P, Pawuś D, Szurpicki K, Hunek WP (2022) Toward optimal control of a multivariable magnetic levitation system. Appl Sci 12(2):674

    Article  CAS  Google Scholar 

  27. Benomair AM, Bashir FA, Tokhi MO (2015) Optimal control based LQR-feedback linearisation for magnetic levitation using improved spiral dynamic algorithm. In: 2015 20th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, pp 558–562

  28. Gandhi RV, Adhyaru DM (2018) Novel approximation-based dynamical modelling and nonlinear control of electromagnetic levitation system. Int J Comput Syst Eng 4(4):224–37

    Article  Google Scholar 

  29. Tran AT, Suzuki S, Sakamoto N (2017) Nonlinear optimal control design considering a class of system constraints with validation on a magnetic levitation system. IEEE Control Syst Lett 1(2):418–23

    Article  MathSciNet  Google Scholar 

  30. Pandey A, Adhyaru DM (2023) Control techniques for electromagnetic levitation system: A literature review. Int J Dynam Control 11(1):441–51

    Article  Google Scholar 

Download references

Acknowledgements

The manuscript discussed is a part of the full-time Ph.D. programme offered by the Institute of Technology, Nirma University, Ahmedabad, Gujarat, India.

Funding

No funding is provided.

Author information

Authors and Affiliations

Authors

Contributions

Both the authors have equally contributed

Corresponding author

Correspondence to Dipak M. Adhyaru.

Ethics declarations

Code availability

Not applicable.

Conflict of interest

The authors declare that there is no conflict of interest in the publication of this article.

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

Pandey, A., Adhyaru, D.M. Robust-optimal control design for current-controlled electromagnetic levitation system with unmatched input uncertainty. Int. J. Dynam. Control (2024). https://doi.org/10.1007/s40435-024-01412-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40435-024-01412-9

Keywords

Navigation