Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

Deyue MengThis email address is being protected from spambots. You need JavaScript enabled to view it., Zengqiang Ma, and Wei Liu

College of Mechanical and Electrical Engineering, Cangzhou Normal University, Cangzhou 061001, China


 

 

Received: February 4, 2024
Accepted: July 18, 2024
Publication Date: September 8, 2024

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202506_28(6).0008  


In PMSM motor drive systems, control accuracy and resistance have always been the most important challenges for researchers. This paper addresses these two challenges and presents a control structure that makes the system performance robust against model uncertainties of system disturbances as well as sudden load changes. In other words, in this paper, an improved MPC controller has been presented, in which model uncertainties and possible disturbances on the system are considered during design. In addition, in order to apply the physical limitations of the electric motor during the design of this improved controller, the input limitations of the system have also been considered. Therefore, the desired MPC controller is a resistant and constrained MPC, it is resistant to uncertainties and disturbances. In addition, in order to further strengthen the control loop against sudden load changes, a sliding estimator has also been designed to estimate the load torque. This estimator itself is also resistant to the uncertainties of the model, which makes the entire control structure have a very robust performance. The performance of the method presented in this article has been compared with a conventional sliding method during a series of practical tests. The results showed that the proposed method has a higher accuracy of 3 rpm and a shorter convergence time of 2 seconds.


Keywords: PMSM, Control, MPC, SMO, robust, constraint, drive, electrical machine.


  1. [1] M. N. Uddin, M. A. Abido, and M. A. Rahman, (2005) “Real-time performance evaluation of a genetic-algorithmbased fuzzy logic controller for IPM motor drives" IEEE Transactions on Industry Applications 41: 246–252. DOI: 10.1109/TIA.2004.840995.
  2. [2] Z. Ibrahim and E. Levi, (2002) “A comparative analysis of fuzzy logic and PI speed control in high-performance AC drives using experimental approach" IEEE Transactions on Industry Applications 38: 1210–1218. DOI: 10.1109/TIA.2002.802993.
  3. [3] M. A. Rahman and M. A. Hoque, (1997) “Online selftuning ANN-based speed control of a PM DC motor" IEEE/ASME Transactions On Mechatronics 2: 169– 178. DOI: 10.1109/3516.622969.
  4. [4] S. Y. Yi and M. J. Chung, (1998) “Robustness of fuzzy logic control for an uncertain dynamic system" IEEE Transactions on Fuzzy Systems 6: 216–225. DOI: 10.1109/91.669018.
  5. [5] C.-K. Lin, L.-C. Fu, and T.-H. Liu. “Design and implementation of a nonlinear speed controller with adaptive backstepping sliding mode technique for an IPMSM drive system”. In: Proceedings of SICE Annual Conference 2010. IEEE. 2010, 110–115.
  6. [6] F. G. Areed, S. F. Saraya, and M. M. A. Elsalam, (2010) “Adaptive control of a synchronous motor via a sliding mode decomposition technique" Ain Shams Engineering Journal 1: 121–129. DOI: 10.1016/j.asej.2011.03.005.
  7. [7] M. Cernat, V. Comnac, M. Cotorogea, P. Korondi, S. Ryvkin, and R.-M. Cernat. “Sliding mode control of interior permanent magnet synchronous motors”. In: 7th IEEE International Power Electronics Congress. Technical Proceedings. CIEP 2000 (Cat. No. 00TH8529). IEEE. 2000, 48–53. DOI: 10.1109/CIEP.2000.891390.
  8. [8] C.-T. Pan and S.-M. Sue, (2005) “A linear maximum torque per ampere control for IPMSM drives over fullspeed range" IEEE Transactions on energy conversion 20: 359–366. DOI: 10.1109/TEC.2004.841517.
  9. [9] M. N. Uddin and J. Lau. “Adaptive backstepping based nonlinear control of an IPMSM drive”. In: 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No. 04CH37551). 5. IEEE. 2004, 3451–3457. DOI: 10.1109/PESC.2004.1355085.
  10. [10] M. Vilathgamuwa, M. Rahman, and K. Tseng. “Nonlinear control of interior permanent magnet synchronous motor”. In: Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No. 00CH37129). 2. IEEE. 2000, 1115–1120. DOI: 10.1109/IAS.2000.881971.
  11. [11] J. Zhou, Y. Wang, and R. Zhou. “Adaptive backstepping control of separately excited DC motor with uncertainties”. In: PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No. 00EX409). 1. IEEE. 2000, 91–96. DOI: 10.1109/ICPST.2000.900037.
  12. [12] M. N. Uddin, T. S. Radwan, and M. A. Rahman, (2002) “Performances of fuzzy-logic-based indirect vector control for induction motor drive" IEEE Transactions on Industry applications 38: 1219–1225. DOI: 10.1109/TIA.2002.802990.
  13. [13] H. Mathur and S. Ghosh. “A comprehensive analysis of intelligent controllers for load frequency control”. In: 2006 IEEE Power India Conference. IEEE. 2006, 5– pp. DOI: 10.1109/POWERI.2006.1632619.
  14. [14] M. N. Uddin and M. A. Rahman. “Fuzzy logic based speed control of an IPM synchronous motor drive”. In: Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No. 99TH8411). 3. IEEE. 1999, 1259– 1264. DOI: 10.1109/CCECE.1999.804872.
  15. [15] M. N. Uddin. “Comparative analysis of intelligent controllers for high performance interior permanent magnet synchronous motor drive systems”. In: Large Engineering Systems Conference on Power Engineering, 2003. IEEE. 2003, 50–54. DOI: 10.1109/LESCPE.2003.1204678.
  16. [16] M. Abido, M. N. Uddin, and M. Rahman. “A new fuzzy logic controller based IPM synchronous motor drive”. In: IEEE International Electric Machines and Drives Conference, 2003. IEMDC’03. 3. IEEE. 2003, 1795–1801. DOI: 10.1109/IEMDC.2003.1210696.
  17. [17] C. Butt and M. Rahman. “Limitations of simplified fuzzy logic controller for IPM motor drive”. In: Conference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting. 3. IEEE. 2004, 1891–1898. DOI: 10.1109/IAS.2004.1348727.
  18. [18] M. N. Uddin, (2010) “An adaptive-filter-based torqueripple minimization of a fuzzy-logic controller for speed control of IPM motor drives" IEEE transactions on industry applications 47: 350–358. DOI: 10.1109/TIA.2010.2090316.
  19. [19] Y. Zhetpissov, A. Kaibaldiyev, and T. D. Do. “Robust H-infinity speed control of permanent magnet synchronous motor without load torque observer”. In: 2019 IEEE Vehicle Power and Propulsion Conference (VPPC). IEEE. 2019, 1–4. DOI: 10.1109/VPPC46532.2019.8952432.
  20. [20] F. Oudjama, A. Boumediene, K. Saidi, and D. Boubekeur, (2023) “Robust speed control in nonlinear electric vehicles using H-infinity control and the LMI approach" J. Intell Syst. Control 2: 170–182. DOI: 10.56578/jisc020305.
  21. [21] N. V. Ramana and V. L. N. Sastry, (2015) “A Novel speed control strategy for five phases permanent magnet synchronous motor with linear quadratic regulator" International Journal of Computer and Electrical Engineering 7: 408. DOI: 10.17706/ijcee.2015.7.6.408-416.
  22. [22] M. Huang, Y. Deng, H. Li, and J. Wang, (2022) “Torque ripple attenuation of PMSM using improved robust twodegree-of-freedom controller via extended sliding mode parameter observer" ISA transactions 129: 558–571. DOI: 10.1016/j.isatra.2022.01.033.
  23. [23] M. Abu-Ali, F. Berkel, M. Manderla, S. Reimann, R. Kennel, and M. Abdelrahem, (2022) “Deep learningbased long-horizon MPC: robust, high performing, and computationally efficient control for PMSM drives" IEEE transactions on power electronics 37(10): 12486–12501. DOI: 10.1109/TPEL.2022.3172681.
  24. [24] V. Ghaffari, S. V. Naghavi, A. A. Safavi, and M. Shafiee. “An LMI framework to design robust MPC for a class of nonlinear uncertain systems”. In: 2013 9th Asian control Conference (ASCC). IEEE. 2013, 1–5. DOI: 10.1109/ASCC.2013.6606169.
  25. [25] S. Niu, Y. Luo, W. Fu, and X. Zhang, (2020) “Robust model predictive control for a three-phase PMSM motor with improved control precision" IEEE Transactions on Industrial Electronics 68: 838–849. DOI: 10.1109/TIE.2020.3013753.
  26. [26] D. Li and P. Kakosimos. “Encoderless predictive control of pmsm drives combining sliding-mode and luenberger observers”. In: 2023 IEEE Applied Power Electronics Conference and Exposition (APEC). IEEE. 2023, 2405–2412. DOI: 10.1109/APEC43580.2023.10131478.
  27. [27] D. Mohanraj, J. Gopalakrishnan, B. Chokkalingam, and L. Mihet-Popa, (2022) “Critical aspects of electric motor drive controllers and mitigation of torque ripple" IEEE Access 10: 73635–73674. DOI: 10.1109/ACCESS.2022.3187515.
  28. [28] D. Mohanraj, R. Aruldavid, R. Verma, K. Sathiyasekar, A. B. Barnawi, B. Chokkalingam, and L. Mihet-Popa, (2022) “A review of BLDC motor: state of art, advanced control techniques, and applications" Ieee Access 10: 54833–54869. DOI: 10.1109/ACCESS.2022.3175011.
  29. [29] M. Deepak, G. Janaki, C. Bharatiraja, and J. O. Ojo, (2023) “An enhanced model predictive direct torque control of SRM drive based on a novel modified switching strategy for low torque ripple" IEEE Journal of Emerging and Selected Topics in Power Electronics: DOI: 10.1109/JESTPE.2023.3343732.
  30. [30] W. Xu, Y. Jiang, and C. Mu, (2016) “Novel composite sliding mode control for PMSM drive system based on disturbance observer" IEEE Transactions on Applied Superconductivity 26: 1–5. DOI: 10.1109/TASC.2016. 2611623.
  31. [31] Y. Wei, D. Ke, X. Yu, F. Wang, and J. Rodríguez, (2024) “Adaptive Inertia Observer-based Model-Free Predictive Current Control for PMSM Driving System of Electric Vehicles" IEEE Transactions on Industry Applications: DOI: 10.1109/TIA.2024.3396123.
  32. [32] Y. Wei, D. Ke, X. Yu, F. Wang, and J. Rodríguez, (2024) “Adaptive Inertia Observer-based Model-Free Predictive Current Control for PMSM Driving System of Electric Vehicles" IEEE Transactions on Industry Applications: DOI: 10.1109/TIA.2024.3396123.
  33. [33] H. Ahn, S. Kim, J. Park, Y. Chung, M. Hu, and K. You. “Adaptive Quick Sliding Mode Reaching Law and Disturbance Observer for Robust PMSM Control Systems”. In: Actuators. 13. 4. MDPI. 2024, 136. DOI: 10.3390/act13040136.
  34. [34] Z. Zhang, X. Yang, W. Wang, K. Chen, N. C. Cheung, and J. Pan, (2024) “Enhanced Sliding Mode Control for PMSM Speed Drive Systems Using a Novel Adaptive Sliding Mode Reaching Law Based on Exponential Function" IEEE Transactions on Industrial Electronics: DOI: 10.1109/TIE.2023.3347845.
  35. [35] Y. Liu, B. Zi, X. Zhang, and D. Xu. “Electromechanical Coupling Dynamic Model and Speed Response Characteristics of the Flexible Robotic Manipulator”. In: Intelligent Robotics and Applications: 10th International Conference, ICIRA 2017, Wuhan, China, August 16–18, 2017, Proceedings, Part II 10. Springer. 2017, 91–100. DOI: 10.1007/978-3-319-65292-4_9.
  36. [36] J. Hu, L. Liu, D.-w. Ma, and N. Ullah, (2015) “Adaptive nonlinear feedback control of chaos in permanentmagnet synchronous motor system with parametric uncertainty" Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229: 2314–2323. DOI: 10.1177/0954406214557344.


    



 

2.1
2023CiteScore
 
 
69th percentile
Powered by  Scopus

SCImago Journal & Country Rank

Enter your name and email below to receive latest published articles in Journal of Applied Science and Engineering.