IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6342-d649854.html
   My bibliography  Save this article

An Improved Finite-Control-Set Model Predictive Current Control for IPMSM under Model Parameter Mismatches

Author

Listed:
  • Zehao Lyu

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China)

  • Xiang Wu

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China)

  • Jie Gao

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China)

  • Guojun Tan

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China)

Abstract

The control performance of the finite control set model predictive current control (FCS-MPCC) for the interior permanent magnet synchronous machine (IPMSM) depends on the accuracy of the mathematical model. A novel robust model predictive current control method based on error compensation is proposed in order to reduce the parameter sensitivity and improve the current control robustness. In this method, the equivalent parameters are obtained from the known voltage and current information at the past time and the error between the predicted current and the actual current at the present time, which is utilized in the two-step prediction process to compensate the parameter mismatch error. Finally, the optimal voltage vector is selected by the cost function. The proposed method is compared with the traditional model predictive current control method through experiments. The experimental results show the effectiveness of the proposed method.

Suggested Citation

  • Zehao Lyu & Xiang Wu & Jie Gao & Guojun Tan, 2021. "An Improved Finite-Control-Set Model Predictive Current Control for IPMSM under Model Parameter Mismatches," Energies, MDPI, vol. 14(19), pages 1-13, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6342-:d:649854
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6342/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6342/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Farya Golesorkhie & Fuwen Yang & Ljubo Vlacic & Geoff Tansley, 2020. "Field Oriented Control-Based Reduction of the Vibration and Power Consumption of a Blood Pump," Energies, MDPI, vol. 13(15), pages 1-18, July.
    2. Ahmed Nasr & Chunyang Gu & Serhiy Bozhko & Chris Gerada, 2020. "Performance Enhancement of Direct Torque-Controlled Permanent Magnet Synchronous Motor with a Flexible Switching Table," Energies, MDPI, vol. 13(8), pages 1-15, April.
    3. Mingcheng Lyu & Gongping Wu & Derong Luo & Fei Rong & Shoudao Huang, 2019. "Robust Nonlinear Predictive Current Control Techniques for PMSM," Energies, MDPI, vol. 12(3), pages 1-19, January.
    4. Ting Yang & Takahiro Kawaguchi & Seiji Hashimoto & Wei Jiang, 2020. "Switching Sequence Model Predictive Direct Torque Control of IPMSMs for EVs in Switch Open-Circuit Fault-Tolerant Mode," Energies, MDPI, vol. 13(21), pages 1-15, October.
    5. Lihui Wang & Guojun Tan & Jie Meng, 2019. "Research on Model Predictive Control of IPMSM Based on Adaline Neural Network Parameter Identification," Energies, MDPI, vol. 12(24), pages 1-16, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuzhe Zhang & Xiaodong Liu & Haitao Li & Zhenbin Zhang, 2023. "A Model Independent Predictive Control of PMSG Wind Turbine Systems with a New Mechanism to Update Variables," Energies, MDPI, vol. 16(9), pages 1-15, April.
    2. Songklod Sriprang & Nitchamon Poonnoy & Babak Nahid-Mobarakeh & Noureddine Takorabet & Nicu Bizon & Pongsiri Mungporn & Phatiphat Thounthong, 2022. "Design, Modeling, and Model-Free Control of Permanent Magnet-Assisted Synchronous Reluctance Motor for e-Vehicle Applications," Sustainability, MDPI, vol. 14(9), pages 1-21, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Claudiu-Ionel Nicola & Marcel Nicola, 2023. "Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    3. Liqin Wu & Hao Chen & Tingyue Yu & Chengzhi Sun & Lin Wang & Xuerong Ye & Guofu Zhai, 2023. "Robust Design Optimization of the Cogging Torque for a PMSM Based on Manufacturing Uncertainties Analysis and Approximate Modeling," Energies, MDPI, vol. 16(2), pages 1-24, January.
    4. Hyungkwan Jang & Hyunwoo Kim & Huai-Cong Liu & Ho-Joon Lee & Ju Lee, 2021. "Investigation on the Torque Ripple Reduction Method of a Hybrid Electric Vehicle Motor," Energies, MDPI, vol. 14(5), pages 1-13, March.
    5. Chi Zhang & Binyue Xu & Jasronita Jasni & Mohd Amran Mohd Radzi & Norhafiz Azis & Qi Zhang, 2023. "Three Voltage Vector Duty Cycle Optimization Strategy of the Permanent Magnet Synchronous Motor Driving System for New Energy Electric Vehicles Based on Finite Set Model Predictive Control," Energies, MDPI, vol. 16(6), pages 1-18, March.
    6. Sandra Eriksson, 2019. "Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 12(14), pages 1-5, July.
    7. Fabiano C. Rosa & Edson Bim, 2020. "A Constrained Non-Linear Model Predictive Controller for the Rotor Flux-Oriented Control of an Induction Motor Drive," Energies, MDPI, vol. 13(15), pages 1-18, July.
    8. Wenjuan Zhang & Gongping Wu & Zhimeng Rao & Jian Zheng & Derong Luo, 2020. "Predictive Power Control of Novel N *3-phase PM Energy Storage Motor for Urban Rail Transit," Energies, MDPI, vol. 13(7), pages 1-17, April.
    9. 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.
    10. 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.
    11. Yongyang Zhou & Fei Yao & Shuguang Zhao, 2022. "Torque Superposition Compensation Fault-Tolerant Control for Dual Three-Phase PMSM with an Inverter Single-Leg Open-Circuit Fault," Energies, MDPI, vol. 15(16), pages 1-14, August.
    12. Wenjuan Zhang & Yu Li & Gongping Wu & Zhimeng Rao & Jian Gao & Derong Luo, 2021. "Robust Predictive Power Control of N *3-Phase PMSM for Flywheel Energy Storage Systems Application," Energies, MDPI, vol. 14(12), pages 1-17, June.
    13. Kai Zhou & Min Ai & Yancheng Sun & Xiaogang Wu & Ran Li, 2019. "PMSM Vector Control Strategy Based on Active Disturbance Rejection Controller," Energies, MDPI, vol. 12(20), pages 1-19, October.
    14. Haneen Ghanayem & Mohammad Alathamneh & R. M. Nelms, 2023. "Decoupled Speed and Flux Control of Three-Phase PMSM Based on the Proportional-Resonant Control Method," Energies, MDPI, vol. 16(3), pages 1-16, January.
    15. Yujiao Zhao & Haisheng Yu & Shixian Wang, 2021. "An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 14(19), pages 1-18, September.
    16. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.
    17. Yoon-Seong Lee & Kyoung-Min Choo & Won-Sang Jeong & Chang-Hee Lee & Junsin Yi & Chung-Yuen Won, 2023. "A Virtual Impedance-Based Flying Start Considering Transient Characteristics for Permanent Magnet Synchronous Machine Drive Systems," Energies, MDPI, vol. 16(3), pages 1-17, January.
    18. Yu-Chen Lin & Valentina Emilia Balas & Ji-Fan Yang & Yu-Heng Chang, 2020. "Adaptive Takagi–Sugeno Fuzzy Model Predictive Control for Permanent Magnet Synchronous Generator-Based Hydrokinetic Turbine Systems," Energies, MDPI, vol. 13(20), pages 1-18, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6342-:d:649854. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.