Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
권호 표지
DOI QR코드

DOI QR Code

Model-Free Adaptive Integral Backstepping Control for PMSM Drive Systems

  • Li, Hongmei (Department of Electrical Engineering and Automation, Hefei University of Technology) ;
  • Li, Xinyu (Department of Electrical Engineering and Automation, Hefei University of Technology) ;
  • Chen, Zhiwei (Department of Electrical Engineering and Automation, Hefei University of Technology) ;
  • Mao, Jingkui (Department of Electrical Engineering and Automation, Hefei University of Technology) ;
  • Huang, Jiandong (Department of Electrical Engineering and Automation, Hefei University of Technology)
  • Received : 2018.06.26
  • Accepted : 2019.03.06
  • Published : 2019.09.20
Download PDF
⟨ Previous Next ⟩

Abstract

A SMPMSM drive system is a typical nonlinear system with time-varying parameters and unmodeled dynamics. The speed outer loop and current inner loop control structures are coupled and coexist with various disturbances, which makes the speed control of SMPMSM drive systems challenging. First, an ultra-local model of a PMSM driving system is established online based on the algebraic estimation method of model-free control. Second, based on the backstepping control framework, model-free adaptive integral backstepping (MF-AIB) control is proposed. This scheme is applied to the permanent magnet synchronous motor (PMSM) drive system of an electric vehicle for the first time. The validity of the proposed control scheme is verified by system simulations and experimental results obtained from a SMPMSM drive system bench test.

Keywords

References

  1. X. Zhang, Y. He, and B. Hou, "Double vector based model predictive torque control for SPMSM drives with improved steady-state performance," J. Power Electron., Vol. 18, No. 5, pp.1398-1408, Sep. 2018. https://doi.org/10.6113/JPE.2018.18.5.1398
  2. A. Gaeta, G. Scelba, and A. Consoli, “Modeling and control of three-phase PMSMs under open-phase fault,” IEEE Trans. Ind. Appl., Vol. 49, No. 1, pp. 74-83, Feb. 2013. https://doi.org/10.1109/TIA.2012.2228614
  3. L. Sepulchre, M. Fadel, and M. Pietrzak-David, "Improvement of the digital control of a high speed PMSM for vehicle application," 2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER), Monte Carlo, pp. 1-9, 2016.
  4. T. Kang, M.-S. Kim, and S. Y. Lee, “Modeling and a simple multiple model adaptive control of PMSM drive system ,” J. Power Electron., Vol. 17, No. 2, pp. 442-452, Mar. 2017. https://doi.org/10.6113/JPE.2017.17.2.442
  5. M. Ezzat, J. de Leon, and A. Glumineau, “Sensorless speed control of PMSM via adaptative interconnected observer,” Int. J. Contr., Vol. 84, No. 11, pp. 1926-1943, Nov. 2011. https://doi.org/10.1080/00207179.2011.629684
  6. S. Alahakoon and T. Fernando, “Unknown input sliding mode functional observers with application to sensorless control of permanent magnet synchronous machines,” J. Franklin Inst., Vol. 350, No. 1, pp. 107-128, Feb. 2013. https://doi.org/10.1016/j.jfranklin.2012.10.012
  7. F. S. Del, D. Bruttomesso, and P. F. Di, “First use of model predictive control in outpatient wearable artificial pancreas,” Diabetes Care, Vol. 37, No. 37, pp. 1212-1215, Jan. 2014. https://doi.org/10.2337/dc13-1631
  8. B. Z. Guo and Z. L. Zhao, “On the convergence of the nonlinear active disturbance rejection control for MIMO systems,” Contr. Optimization, Vol. 51, No. 2, pp. 1727-1757, May 2013. https://doi.org/10.1137/110856824
  9. J. Li, Y. Xia, and Z. Gao, “Study on the method of linear/nonlinear automatic disturb-restraint switching control,” Acta Automatica Sinica, Vol. 42, No. 2, pp. 202-212, Mar. 2016.
  10. M. Fliess and C. Join, "Model-free control and intelligent PID controllers: Towards a possible trivialization of nonlinear control," IFAC Proceedings Volumes, Vol. 42, No. 10, pp. 1531-1550, Oct. 2015.
  11. Y. Zhou, H. Li, and H. Zhang, “Model-free deadbeat predictive current control of a surface-mounted permanent magnet synchronous motor drive system,” J. Power Electron., Vol. 18, No. 1, pp. 103-115, Jan. 2018. https://doi.org/10.6113/JPE.2018.18.1.103
  12. Jesus R. Vazquez and A. D. Martin, “Backstepping control of a buck-boost converter in an experimental PVsystem,” J. Power Electron., Vol. 15, No. 6, pp. 1584-1592, Nov. 2015. https://doi.org/10.6113/JPE.2015.15.6.1584
  13. M. Karabacak and H. I. Eskikurt, “Design, modelling and simulation of a new nonlinear and full adaptive backstepping speed tracking controller for uncertain PMSM,” Applied Mathematical Modelling, Vol. 36, No. 1, pp. 5199-5213, Jan. 2012. https://doi.org/10.1016/j.apm.2011.12.048
  14. Y. Zhu, "Adaptive backstepping control for uncertain systems," Ph.D. Thesis, Zhejiang University, 2015.
  15. H. K. Khalil and P. V. Kokotovic, “On stability properties of nonlinear systems with slowly varying inputs,” IEEE Trans. Autom. Contr., Vol. 36, No. 2, pp. 229-241, Oct. 1991. https://doi.org/10.1109/9.67301
  16. H. P. Wang, Y. Tian, and N. Christov, “Piecewisecontinuous observers for linear systems with sampled and delayed output,” Int. J. Syst. Sci., Vol. 47, No. 8, pp. 1804-1815, Aug. 2016. https://doi.org/10.1080/00207721.2014.953798
  17. D. Tsubakino and M. Krstic, “Exact predictor feedbacks for multi-input LTI systems with distinct input delays,” Automatica, Vol. 71, No. 7, pp. 143-150, Oct. 2016. https://doi.org/10.1016/j.automatica.2016.04.047
  18. Y. O. Lee, Y. Han, and C. C. Chung, “Output tracking control with enhanced damping of internal dynamics and its output boundedness for static synchronous compensator system,” IET Contr. Theory & Appl., Vol. 6, No. 10, pp. 1445-1455, Aug. 2012. https://doi.org/10.1049/iet-cta.2011.0340
  19. S. Liu, X. Guo, and L. Zhang, “Robust adaptive backstepping sliding mode control for six-phase permanent magnet synchronous motor using recurrent wavelet Fuzzy Neural Network,” IEEE Trans. Autom. Contr., Vol. 1, No. 1, pp. 99-108, Jun. 2017.
  20. Y. H. Choi and S. J. Yoo, “Minimal-approximation based decentralized backstepping control of interconnected time-delay systems,” IEEE Trans. Cybernetics, Vol. 46, No. 12, pp. 3401-3413, Oct 2016. https://doi.org/10.1109/TCYB.2015.2507165
  21. X. Wang and C. Han, “A modified adaptive backstepping method for shaft deflection tracking control of magnetically suspended momentum wheel with nonlinear magnetic torque,” J. Franklin Inst., Vol. 99, No. 2, pp. 99-112, Mar. 2018.
  22. T. Ahmed-Ali and F. Giri, “Adaptive boundary observer for parabolic PDEs subject to domain and boundary parameter uncertainties,” Automatica, Vol. 72, No. 2, pp. 115-122, Oct. 2016. https://doi.org/10.1016/j.automatica.2016.06.006
  23. B. M. Dehkordi, A. F. Payam, M. N. Hashemnia, and S.-K. Sul, “Design of an adaptive backstepping controller for doubly-fed induction machine drives,” J. Power Electron., Vol. 9, No. 3, pp. 343-353, May 2009.
  24. M. Fliess and C. Join, “Model-free control,” Int. J. Contr., Vol. 86, No. 12, pp. 2228-2252, Jul. 2013. https://doi.org/10.1080/00207179.2013.810345
  25. M. Fliess and C. Join, "Stability margins and model-free control: A first look," in IEEE European Control Conference, pp. 454-459, 2014.
  26. H. J. Wang, M. Yang, L. Niu, and D. G. Xu, "Current-loop bandwidth expansion strategy for permanent magnet synchronous motor drives," Proc. the 5th IEEE Conference on Industrial Electronics and Applications, pp. 1340-1345, 2010.
  27. Y. C. Kwon, S. Kim, and S. K. Sul, “Voltage feedback current control scheme for improved transient performance of permanent magnet synchronous machine drives,” IEEE Trans. Ind. Electron., Vol. 59, No. 9, pp. 3373-3382, Sep. 2012. https://doi.org/10.1109/TIE.2011.2173097
  28. L. Harnefors, K. Pietilainen, and L. Gertmar, "Torquemaximizing field-weakening control: Design, analysis, and parameter selection," IEEE Trans. Ind. Electron., Vol. 48, No. 1, pp.161-168, Feb. 2001.
  29. Z. Gao, "Scaling and Bandwidth-Parameterization Based Controller Tuning," Proc. American Control Conference, 2003.
  30. M. Fliess and H. Sira-Ramirez, "Closed-loop parametric identification for continuous-time linear systems via new algebraic techniques," Advances in Industrial Control, pp. 363-391, 2008.