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Direct Torque Control of PMSM with Modified Finite Set Model Predictive Control

Author

Listed:
  • GuangQing Bao

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
    Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China
    National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China)

  • WuGang Qi

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
    Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou 730050, China
    National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China)

  • Ting He

    (Gansu Natural Energy Research Institute, Lanzhou 730046, China)

Abstract

A direct torque control (DTC) with a modified finite set model predictive strategy is proposed in this paper. The eight voltage space vectors of two-level inverters are taken as the finite control set and applied to the model predictive direct torque control of a permanent magnet synchronous motor (PMSM). The duty cycle of each voltage vector in the finite set can be estimated by a cost function, which is designed based on factors including the torque error, maximum torque per ampere (MTPA), and stator current constraints. Lyapunov control theory is introduced in the determination of the weight coefficients of the cost function to guarantee stability, and thus the optimal voltage vector reference value of the inverter is obtained. Compared with the conventional finite control set model predictive control (FCS-MPC) method, the torque ripple is reduced and the robustness of the system is clearly improved. Finally, the simulation and experimental results verify the effectiveness of the proposed control scheme.

Suggested Citation

  • GuangQing Bao & WuGang Qi & Ting He, 2020. "Direct Torque Control of PMSM with Modified Finite Set Model Predictive Control," Energies, MDPI, vol. 13(1), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:1:p:234-:d:304750
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    Citations

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    Cited by:

    1. Jie Chen & Jiajun Wang & Bo Yan, 2022. "Simulation Research on Deadbeat Direct Torque and Flux Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 15(9), pages 1-15, April.
    2. Habib Benbouhenni & Nicu Bizon, 2021. "Improved Rotor Flux and Torque Control Based on the Third-Order Sliding Mode Scheme Applied to the Asynchronous Generator for the Single-Rotor Wind Turbine," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    3. Karol Wróbel & Piotr Serkies & Krzysztof Szabat, 2020. "Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches," Energies, MDPI, vol. 13(5), pages 1-15, March.
    4. Pankaj Kumar & Yashwant Kashyap & Roystan Vijay Castelino & Anabalagan Karthikeyan & Manjunatha Sharma K. & Debabrata Karmakar & Panagiotis Kosmopoulos, 2023. "Laboratory-Scale Airborne Wind Energy Conversion Emulator Using OPAL-RT Real-Time Simulator," Energies, MDPI, vol. 16(19), pages 1-30, September.
    5. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of PMSM Sensorless Control Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(6), pages 1-30, March.
    6. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    7. Bowei Zou & Yougui Guo & Xi Xiao & Bowen Yang & Xiao Wang & Mingzhang Shi & Yulin Tu, 2020. "Performance Improvement of Matrix Converter Direct Torque Control System," Energies, MDPI, vol. 13(12), pages 1-17, June.
    8. Jaime A. Rohten & David N. Dewar & Pericle Zanchetta & Andrea Formentini & Javier A. Muñoz & Carlos R. Baier & José J. Silva, 2021. "Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency," Energies, MDPI, vol. 14(2), pages 1-16, January.
    9. Omar Sandre Hernandez & Jorge S. Cervantes-Rojas & Jesus P. Ordaz Oliver & Carlos Cuvas Castillo, 2021. "Stator Fixed Deadbeat Predictive Torque and Flux Control of a PMSM Drive with Modulated Duty Cycle," Energies, MDPI, vol. 14(10), pages 1-15, May.
    10. Hao Yu & Jiajun Wang & Zhuangzhuang Xin, 2022. "Model Predictive Control for PMSM Based on Discrete Space Vector Modulation with RLS Parameter Identification," Energies, MDPI, vol. 15(11), pages 1-16, May.
    11. Chunyan Li & Fei Guo & Baoquan Kou & Tao Meng, 2021. "Research on the Non-Magnetic Conductor of a PMSM Based on the Principle of Variable Exciting Magnetic Reluctance," Energies, MDPI, vol. 14(2), pages 1-29, January.

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