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HIL Co-Simulation of Finite Set-Model Predictive Control Using FPGA for a Three-Phase VSI System

Author

Listed:
  • Vijay Kumar Singh

    (Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu 808-0196, Fukuoka, Japan)

  • Ravi Nath Tripathi

    (Next Generation Power Electronics Research Center, Kyushu Institute of Technology, Kitakyushu 808-0196, Fukuoka, Japan)

  • Tsuyoshi Hanamoto

    (Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu 808-0196, Fukuoka, Japan)

Abstract

The conversion and control for the utilization of power generated from energy sources can be performed using a power electronic converter system. The voltage source inverter (VSI) is one of the commonly used converter topologies, being controlled by a switching control algorithm for power conversion. Finite set-model predictive control (FS-MPC) is a modern switching control algorithm and has received significant attention due to its predictive nature. In this paper, the implementation of FS-MPC is presented for the load-side current control of a three-phase VSI system using an integrated platform of MATLAB/Simulink and Xilinx system generator (XSG). The XSG provides the functionality of digital design and intuitive implementation of field-programmable gate array (FPGA) controlled systems. The additional functionality of hardware-in-the-loop (HIL) co-simulation using FPGA is used for the testing and validation of controller performance. The controller performance is validated through three platforms: MATLAB/Simulink, XSG and HIL co-simulation using ZedBoard Zynq evaluation and development FPGA kit.

Suggested Citation

  • Vijay Kumar Singh & Ravi Nath Tripathi & Tsuyoshi Hanamoto, 2018. "HIL Co-Simulation of Finite Set-Model Predictive Control Using FPGA for a Three-Phase VSI System," Energies, MDPI, vol. 11(4), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:909-:d:140808
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    References listed on IDEAS

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    1. Issam A. Smadi & Saher Albatran & Hamzeh J. Ahmad, 2018. "On the Performance Optimization of Two-Level Three-Phase Grid-Feeding Voltage-Source Inverters," Energies, MDPI, vol. 11(2), pages 1-17, February.
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    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. Deepa Sankar & Lakshmi Syamala & Babu Chembathu Ayyappan & Mathew Kallarackal, 2021. "FPGA-Based Cost-Effective and Resource Optimized Solution of Predictive Direct Current Control for Power Converters," Energies, MDPI, vol. 14(22), pages 1-26, November.
    3. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    4. Jian Li & Xiaoyan Huang & Feng Niu & Chaojie You & Lijian Wu & Youtong Fang, 2018. "Prediction Error Analysis of Finite-Control-Set Model Predictive Current Control for IPMSMs," Energies, MDPI, vol. 11(8), pages 1-16, August.
    5. Van-Quang-Binh Ngo & Minh-Khai Nguyen & Tan-Tai Tran & Young-Cheol Lim & Joon-Ho Choi, 2018. "A Simplified Model Predictive Control for T-Type Inverter with Output LC Filter," Energies, MDPI, vol. 12(1), pages 1-18, December.
    6. 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.

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