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Robust Nonlinear Predictive Current Control Techniques for PMSM

Author

Listed:
  • Mingcheng Lyu

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Gongping Wu

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Derong Luo

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Fei Rong

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

  • Shoudao Huang

    (College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

Abstract

This paper proposes a robust nonlinear predictive current control (RNPCC) method for permanent magnet synchronous motor (PMSM) drives, which can optimize the current control loop performance of the PMSM system with model parameter perturbation. First, the disturbance caused by parameter perturbation was considered in the modeling of PMSM. Based on this model, the influence of parameter perturbation on the conventional predictive current control (PCC) was analyzed. The composite integral terminal sliding mode observer (SMO) was then designed to estimate the disturbance caused by the parameter perturbation in real time. Finally, a RNPCC method is developed without relying on the mathematical model of PMSM, which can effectively eliminate the influence of parameter perturbation by injecting the estimated disturbance value. Simulations and experiments verified that the proposed RNPCC method was able to remove the current error caused by the parameter perturbation during steady state operation.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:443-:d:202086
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    References listed on IDEAS

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    1. Maha Zoghlami & Ameni Kadri & Faouzi Bacha, 2018. "Analysis and Application of the Sliding Mode Control Approach in the Variable-Wind Speed Conversion System for the Utility of Grid Connection," Energies, MDPI, vol. 11(4), pages 1-17, March.
    2. Fang Hu & Derong Luo & Chengwei Luo & Zhuo Long & Gongping Wu, 2018. "Cascaded Robust Fault-Tolerant Predictive Control for PMSM Drives," Energies, MDPI, vol. 11(11), pages 1-17, November.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Sandra Eriksson, 2019. "Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 12(14), pages 1-5, July.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

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