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Model-Free Predictive Control and Its Applications

Author

Listed:
  • Muhammad Nauman

    (Departemnt of Electrical and Computer Engineering, The University of Houston, Houston, TX 77204, USA)

  • Wajiha Shireen

    (Department of Electrical Technology, The University of Houston, Houston, TX 77204, USA)

  • Amir Hussain

    (Texas Instruments, Sugar Land, TX 77479, USA)

Abstract

Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper.

Suggested Citation

  • Muhammad Nauman & Wajiha Shireen & Amir Hussain, 2022. "Model-Free Predictive Control and Its Applications," Energies, MDPI, vol. 15(14), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5131-:d:863055
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    References listed on IDEAS

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    1. Sanaz Sabzevari & Rasool Heydari & Maryam Mohiti & Mehdi Savaghebi & Jose Rodriguez, 2021. "Model-Free Neural Network-Based Predictive Control for Robust Operation of Power Converters," Energies, MDPI, vol. 14(8), pages 1-12, April.
    2. Felix Garcia-Torres & Ascension Zafra-Cabeza & Carlos Silva & Stephane Grieu & Tejaswinee Darure & Ana Estanqueiro, 2021. "Model Predictive Control for Microgrid Functionalities: Review and Future Challenges," Energies, MDPI, vol. 14(5), pages 1-26, February.
    3. Mohamed Abdelrahem & José Rodríguez & Ralph Kennel, 2020. "Improved Direct Model Predictive Control for Grid-Connected Power Converters," Energies, MDPI, vol. 13(10), pages 1-14, May.
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