LAPSE:2023.21522
Published Article
LAPSE:2023.21522
FPGA-Based Implementation of Finite Set-MPC for a VSI System Using XSG-Based Modeling
Vijay Kumar Singh, Ravi Nath Tripathi, Tsuyoshi Hanamoto
March 22, 2023
Abstract
Finite set-model predictive control (FS-MPC) is used for power converters and drives having unique advantages as compared to the conventional control strategies. However, the computational burden of the FS-MPC is a primary concern for real-time implementation. Field programmable gate array (FPGA) is an alternative and exciting solution for real-time implementation because of the parallel processing capability, as well as, discrete nature of the hardware platform. Nevertheless, FPGA is capable of handling the computational requirements for the FS-MPC implementation, however, the system development involves multiple steps that lead to the time-consuming debugging process. Moreover, specific hardware coding skill makes it more complex corresponding to an increase in system complexity that leads to a tedious task for system development. This paper presents an FPGA-based experimental implementation of FS-MPC using the system modeling approach. Furthermore, a comparative analysis of FS-MPC in stationary αβ and rotating dq frame is considered for simulation as well as experimental result. The FS-MPC for a three-phase voltage source inverter (VSI) system is developed in a realistic digital simulator integrated with MATLAB-Simulink. The simulated controller model is further used for experimental system implementation and validation using Xilinx FPGA: Zedboard Zynq Evaluation and Development Kit. The digital simulator termed as Xilinx system generator (XSG) provided by Xilinx is used for modeling-based FPGA design.
Keywords
field-programmable gate array, finite set-model predictive control, model-based design, voltage source inverter, Xilinx system generator
Subject
Suggested Citation
Singh VK, Tripathi RN, Hanamoto T. FPGA-Based Implementation of Finite Set-MPC for a VSI System Using XSG-Based Modeling. (2023). LAPSE:2023.21522
Author Affiliations
Singh VK: Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka 808-0196, Japan [ORCID]
Tripathi RN: Next Generation Power Electronics Research Center, Kyushu Institute of Technology, Fukuoka 808-0196, Japan
Hanamoto T: Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka 808-0196, Japan
Journal Name
Energies
Volume
13
Issue
1
Article Number
E260
Year
2020
Publication Date
2020-01-04
ISSN
1996-1073
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Original Submission
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PII: en13010260, Publication Type: Journal Article
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LAPSE:2023.21522
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https://doi.org/10.3390/en13010260
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