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Sequential Model Predictive Control of Three-Phase Direct Matrix Converter

Author

Listed:
  • Jianwei Zhang

    (Faculty of Engineering and IT, University of Technology Sydney, Broadway NSW 2007, Sydney, Australia
    College of Electric Power, Inner Mongolia University of Technology, Hohhot 010000, China)

  • Margarita Norambuena

    (Departamento de Ing. Electrica, Universidad Tecnica Federico Santa Maria, Valparaiso 2390123, Chile)

  • Li Li

    (Faculty of Engineering and IT, University of Technology Sydney, Broadway NSW 2007, Sydney, Australia)

  • David Dorrell

    (Department of Electrical Engineering, University of KwaZulu-Natal, Durban 4001, South Africa)

  • Jose Rodriguez

    (Facultad de Ingenieria, Universidad Andres Bello, Santiago 7500791, Chile)

Abstract

The matrix converter (MC) is a promising converter that performs the direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful tool for power electronic converters, including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the generalized sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required. Compared with the standard MPC, the computation burden is reduced because only the pre-selected switch states are evaluated in the second and subsequent sequential cost functions. In addition, the prediction model computation for the following cost functions is also reduced. Specifying the priority for control objectives can be achieved. A comparative study with traditional MPC is carried out both in simulation and an experiment. Comparable control performance to the traditional MPC is achieved. This controller is suitable for the MC because of the reduced computational burden. Simulation and experimental results verify the effectiveness of the proposed strategy.

Suggested Citation

  • Jianwei Zhang & Margarita Norambuena & Li Li & David Dorrell & Jose Rodriguez, 2019. "Sequential Model Predictive Control of Three-Phase Direct Matrix Converter," Energies, MDPI, vol. 12(2), pages 1-14, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:214-:d:196592
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    References listed on IDEAS

    as
    1. Joaquim Monteiro & Sónia Pinto & Aranzazu Delgado Martin & José Fernando Silva, 2017. "A New Real Time Lyapunov Based Controller for Power Quality Improvement in Unified Power Flow Controllers Using Direct Matrix Converters," Energies, MDPI, vol. 10(6), pages 1-13, June.
    2. Shiyang Hu & Guorong Liu & Nan Jin & Leilei Guo, 2018. "Constant-Frequency Model Predictive Direct Power Control for Fault-Tolerant Bidirectional Voltage-Source Converter with Balanced Capacitor Voltage," Energies, MDPI, vol. 11(10), pages 1-20, October.
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    Citations

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    Cited by:

    1. Tomasz Sieńko & Jerzy Szczepanik & Claudia Martis, 2020. "Reactive Power Transfer via Matrix Converter Controlled by the “One Periodical” Algorithm," Energies, MDPI, vol. 13(3), pages 1-14, February.
    2. Pawel Szczesniak, 2019. "Challenges and Design Requirements for Industrial Applications of AC/AC Power Converters without DC-Link," Energies, MDPI, vol. 12(8), pages 1-18, April.
    3. Sergio Toledo & David Caballero & Edgar Maqueda & Juan J. Cáceres & Marco Rivera & Raúl Gregor & Patrick Wheeler, 2022. "Predictive Control Applied to Matrix Converters: A Systematic Literature Review," Energies, MDPI, vol. 15(20), pages 1-30, October.
    4. Shuang Feng & Chaofan Wei & Jiaxing Lei, 2019. "Reduction of Prediction Errors for the Matrix Converter with an Improved Model Predictive Control," Energies, MDPI, vol. 12(15), pages 1-20, August.
    5. Duberney Murillo-Yarce & Baldomero Araya & Carlos Restrepo & Marco Rivera & Patrick Wheeler, 2023. "Impact of Sequential Model Predictive Control on Induction Motor Performance: Comparison of Converter Topologies," Mathematics, MDPI, vol. 11(4), pages 1-21, February.

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