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Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency

Author

Listed:
  • Jaime A. Rohten

    (Department of Electrical and Electronic Engineering, Universidad Del Bío-Bío, Avenida Collao 1202, 4051381 Concepción, Chile
    These authors contributed equally to this work.)

  • David N. Dewar

    (Department of Electrical and Electronic Engineering, University Park, University of Nottingham, Nottingham NG7 2RD, UK
    These authors contributed equally to this work.)

  • Pericle Zanchetta

    (Department of Electrical and Electronic Engineering, University Park, University of Nottingham, Nottingham NG7 2RD, UK
    Department of Electrical Computer and Biomedical Engineering, University of Pavia, Via A. Ferrata 5, 27100 Pavia, Italy
    These authors contributed equally to this work.)

  • Andrea Formentini

    (Department of Electrical and Electronic Engineering, University Park, University of Nottingham, Nottingham NG7 2RD, UK
    These authors contributed equally to this work.)

  • Javier A. Muñoz

    (Department of Electrical Engineering, Universidad de Talca, Camino Los Niches Km. 1, 3340000 Curicó, Chile
    These authors contributed equally to this work.)

  • Carlos R. Baier

    (Department of Electrical Engineering, Universidad de Talca, Camino Los Niches Km. 1, 3340000 Curicó, Chile
    These authors contributed equally to this work.)

  • José J. Silva

    (Department of Electrical Engineering, Universidad de Concepción, Victor Lamas 1290, 4070386 Concepción, Chile
    These authors contributed equally to this work.)

Abstract

Power converters have turned into a critical and every-day solution for electric power systems. In fact, the incorporation of renewable energies has led towards the constant improvement of power converter topologies and their controls. In this context, over the last 10 years, model predictive control (MPC) is positioned as one the most studied and promising alternatives for power converter control. In voltage source inverters (VSI), MPC has only been applied in the inner current control loop, accelerating and improving its dynamic response, but as mentioned, has been limited only to the current control loop. The fastest of the MPC techniques is the Deadbeat (DB) control, and in this paper, it is proposed to employ DB control on the entire system, therefore accelerating the time response not only for the current loops, but also for voltage loops. At the same time, this avoids overshoots and overpower in order to protect the power converter, leading to the fastest dynamic response according to VSI capabilities. For renewable energies, fast-dynamics entails fast maximum power tracking and therefore, maximizes energy harvesting, or in other words, reduces the losses due to the control dynamics. Thus, this paper gives a clear procedure and key points for designing a DB control for all the variables based on a mathematical model, which is corroborated by simulations and the experimental results.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:2:p:313-:d:476894
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    References listed on IDEAS

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    1. Pedro Gonçalves & Sérgio Cruz & André Mendes, 2019. "Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview," Energies, MDPI, vol. 12(24), pages 1-42, December.
    2. Miaomiao Ma & Xiangjie Liu & Kwang Y. Lee, 2020. "Maximum Power Point Tracking and Voltage Regulation of Two-Stage Grid-Tied PV System Based on Model Predictive Control," Energies, MDPI, vol. 13(6), pages 1-16, March.
    3. Ramon Guzmán & Luís García de Vicuña & Miguel Castilla & Jaume Miret & Antonio Camacho, 2017. "Finite Control Set Model Predictive Control for a Three-Phase Shunt Active Power Filter with a Kalman Filter-Based Estimation," Energies, MDPI, vol. 10(10), pages 1-14, October.
    4. Tien Hai Nguyen & Kyeong-Hwa Kim, 2017. "Finite Control Set–Model Predictive Control with Modulation to Mitigate Harmonic Component in Output Current for a Grid-Connected Inverter under Distorted Grid Conditions," Energies, MDPI, vol. 10(7), pages 1-25, July.
    5. Zih-Cing You & Cheng-Hong Huang & Sheng-Ming Yang, 2019. "Online Current Loop Tuning for Permanent Magnet Synchronous Servo Motor Drives with Deadbeat Current Control," Energies, MDPI, vol. 12(18), pages 1-19, September.
    6. Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.
    7. Radek Martinek & Jaroslav Rzidky & Rene Jaros & Petr Bilik & Martina Ladrova, 2019. "Least Mean Squares and Recursive Least Squares Algorithms for Total Harmonic Distortion Reduction Using Shunt Active Power Filter Control," Energies, MDPI, vol. 12(8), pages 1-26, April.
    8. Vijay Kumar Singh & Ravi Nath Tripathi & Tsuyoshi Hanamoto, 2020. "FPGA-Based Implementation of Finite Set-MPC for a VSI System Using XSG-Based Modeling," Energies, MDPI, vol. 13(1), pages 1-18, January.
    9. Sergio Toledo & Edgar Maqueda & Marco Rivera & Raúl Gregor & Pat Wheeler & Carlos Romero, 2020. "Improved Predictive Control in Multi-Modular Matrix Converter for Six-Phase Generation Systems," Energies, MDPI, vol. 13(10), pages 1-13, May.
    10. Jaehong Kim & Jitae Hong & Hongju Kim, 2016. "Improved Direct Deadbeat Voltage Control with an Actively Damped Inductor-Capacitor Plant Model in an Islanded AC Microgrid," Energies, MDPI, vol. 9(11), pages 1-15, November.
    11. Yuhan Zhang & Guiping Du & Jiajian Li & Yanxiong Lei, 2020. "Hybrid Control Strategy of MPC and DBC to Achieve a Fixed Frequency and Superior Robustness," Energies, MDPI, vol. 13(5), pages 1-14, March.
    12. 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.
    13. 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.
    14. Mohamed Abdelrahem & Christoph M. Hackl & José Rodríguez & Ralph Kennel, 2020. "Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems," Energies, MDPI, vol. 13(18), pages 1-15, September.
    15. 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.
    16. Yahya Danayiyen & Kyungsuk Lee & Minho Choi & Young Il Lee, 2019. "Model Predictive Control of Uninterruptible Power Supply with Robust Disturbance Observer," Energies, MDPI, vol. 12(15), pages 1-22, July.
    17. Wei Wang & Gaoshuai Shen & Run Min & Qiaoling Tong & Qiao Zhang & Zhenglin Liu, 2020. "State Switched Discrete-Time Model and Digital Predictive Voltage Programmed Control for Buck Converters," Energies, MDPI, vol. 13(13), pages 1-21, July.
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