MPC Based Trajectory Planning for Permanent Magnet Synchronous Motor
Published online: 10/11/2025
Corressponding author's email:
vinhhao@hcmut.edu.vnDOI:
https://doi.org/10.54644/jte.2025.1795Keywords:
PMSM, Model Predictive Control, Load Torque Observer, Trajectory Planning, Space-Vector Pulse Width ModulationAbstract
Permanent Magnet Synchronous Motor (PMSM) is increasingly used in applications requiring precise control, particularly in robotic joint control systems. This study aims to assess the feasibility of applying Model Predictive Control (MPC) for position and velocity control of PMSM. The research methodology involves using simulations to verify the effectiveness of MPC, along with the integration of an Kalman Filter (KF) to estimate external loads, thereby improving response time and control over motor parameters. Simulation results demonstrate that MPC achieves high precision in controlling PMSM under basic trajectory planning modes, while the KF enhances load estimation accuracy, allowing the system to stabilize quickly. Additionally, the algorithm has been tested to operate stably at low frequencies, confirming the applicability of MPC in real-time systems. The study concludes that the combination of MPC and KF is a feasible and effective solution for precise PMSM control, with broad potential applications in modern control systems.
Downloads: 0
References
Z. Zedong, M. Fadel, and Y. Li, “A high-performance control system of PMSM based on load torque observer,” in Proc. IEEE Power Electron. Spec. Conf. (PESC), Orlando, FL, USA, 2007, pp. 587–592, doi: 10.1109/PESC.2007.4342053. DOI: https://doi.org/10.1109/PESC.2007.4342053
R. Cai, Current Control with Self-Learning Ability for PMSM Drives, Aalborg Univ., 2022.
E. Yesilbag and L. T. Ergene, “Field oriented control of permanent magnet synchronous motors used in washers,” in Proc. Int. Power Electron. Motion Control Conf. (PEMC), Antalya, Turkey, 2014, pp. 1259–1264, doi: 10.1109/EPEPEMC.2014.6980685. DOI: https://doi.org/10.1109/EPEPEMC.2014.6980685
H. Wang, S. Xu, and H. Hu, “PID controller for PMSM speed control based on improved quantum genetic algorithm optimization,” IEEE Access, vol. 11, pp. 61091–61102, 2023, doi: 10.1109/ACCESS.2023.3284971. DOI: https://doi.org/10.1109/ACCESS.2023.3284971
J. W. Jung, V. Q. Leu, T. D. Do, E. K. Kim, and H. H. Choi, “Adaptive PID speed control design for permanent magnet synchronous motor drives,” IEEE Trans. Power Electron., vol. 30, no. 2, pp. 900–908, Feb. 2015, doi: 10.1109/TPEL.2014.2311462. DOI: https://doi.org/10.1109/TPEL.2014.2311462
R. C. García, W. I. Suemitsu, and J. O. P. Pinto, “Precise position control of a PMSM based on new adaptive PID controllers,” in Proc. IEEE Annu. Conf. Ind. Electron. Soc. (IECON), Melbourne, VIC, Australia, 2011, pp. 1983–1988, doi: 10.1109/IECON.2011.6119443. DOI: https://doi.org/10.1109/IECON.2011.6119443
K. Li, J. Ding, X. Sun, and X. Tian, “Overview of sliding mode control technology for permanent magnet synchronous motor system,” IEEE Access, vol. 12, pp. 71685–71704, 2024, doi: 10.1109/ACCESS.2024.3402983. DOI: https://doi.org/10.1109/ACCESS.2024.3402983
L. Weijie, L. Dongliang, W. Qiuxuan, and Z. Xiaodan, “On sliding mode control of permanent magnet synchronous motor,” in Proc. Chinese Control Decis. Conf. (CCDC), Changsha, China, 2014, pp. 4555–4559, doi: 10.1109/CCDC.2014.6852985. DOI: https://doi.org/10.1109/CCDC.2014.6852985
A. Kiselev, A. Kuznietsov, and R. Leidhold, “Position control of a permanent magnet synchronous motor using generalized predictive control algorithm,” in Proc. Int. Symp. Power Electron., Electr. Drives, Autom. Motion (SPEEDAM), Capri, Italy, 2016, pp. 110–115, doi: 10.1109/SPEEDAM.2016.7525840. DOI: https://doi.org/10.1109/SPEEDAM.2016.7525840
X. Huang, H. Pan, and K. Yuan, “Speed and current control of PMSM based on double MPC,” in Proc. Int. Forum Electr. Eng. Autom. (IFEEA), Hefei, China, 2020, pp. 300–304, doi: 10.1109/IFEEA51475.2020.00070. DOI: https://doi.org/10.1109/IFEEA51475.2020.00070
S. Bolognani, L. Peretti, and M. Zigliotto, “Combined speed and current model predictive control with inherent field-weakening features for PMSM drives,” in Proc. IEEE Mediterranean Electrotech. Conf. (MELECON), Ajaccio, France, 2008, pp. 472–478, doi: 10.1109/MELCON.2008.4618480. DOI: https://doi.org/10.1109/MELCON.2008.4618480
Č. Lukáš, Algorithms for Advanced Motion Control Using Permanent Magnet Synchronous Motors and Brushless DC Motors, 2020, ch. 3, sec. 3.5, pp. 35–36.
S. Chai, L. Wang, and E. Rogers, “Model predictive control of a permanent magnet synchronous motor,” in Proc. IEEE Annu. Conf. Ind. Electron. Soc. (IECON), Melbourne, VIC, Australia, 2011. DOI: https://doi.org/10.1109/IECON.2011.6119601
S. V. Zadeh, “Machine modeling,” in Control of Permanent Magnet Synchronous Motors, Oxford, U.K.: Oxford Univ. Press, 2018, ch. 2, sec. 2.3, pp. 43–75.
Z. Zheng, Y. Li, X. Xiao, and M. Fadel, “Load torque observer of permanent magnet synchronous motor,” Trans. China Electrotech. Soc., vol. 25, no. 2, pp. 30–36, 2010. ⟨hal-03549440⟩
L. Wang, Model Predictive Control System Design and Implementation Using MATLAB, Springer, RMIT Univ., Australia, 2009, ch. 2, sec. 2.4, pp. 43–67.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 Journal of Technical Education Science
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright © JTE.
