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Indirect Model Predictive Control of Matrix Converter Based on EKF Parameter Identification
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Jianwei ZHANG1, 2, Zaixin YANG3, Yunhui WANG1, 2, Guangchen LIU1, 2
Electric Drive | 2025, 55(1) : 18 - 24
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Electric Drive | 2025, 55(1): 18-24
Indirect Model Predictive Control of Matrix Converter Based on EKF Parameter Identification
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Jianwei ZHANG1, 2, Zaixin YANG3, Yunhui WANG1, 2, Guangchen LIU1, 2
Affiliations
  • 1 College of Electric Power,Inner Mongolia University of Technology,Hohhot 010080,Nei Mongol,China
  • 2 Engineering Research Center of Large Energy Storage Technology of Ministry of Education,Inner Mongolia University of Technology,Hohhot 010080,Nei Mongol,China
  • 3 Inner Mongolia Key Laboratory of Smart Grid of New-type Power System,Inner Mongolia Electric Power Research Institute,Hohhot 010020,Nei Mongol,China
Published: 2025-01-20 doi: 10.19457/j.1001-2095.dqcd25455
Outline
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In order to alleviate the intensive computational burden in the model predictive control(MPC)of the matrix converter,the MPC of the matrix converter was divided into the predictive control of the virtual rectifier and virtual inverter based on the equivalent indirect modulation of the matrix converter. Compared with the traditional direct MPC,the computational burden and execution time of the proposed strategy were reduced. Considering the issue of the high dependence of MPC on model parameters,the extended Kalman filter(EKF)was used to identify system model parameters online,thereby improving the robustness and anti-interference ability of MPC. The experimental results show that the proposed indirect MPC based on the extended Kalman filter parameter identification algorithm offers a good control performance on the load current and the grid side power factor control,and the dependence on the model parameters is reduced.

matrix converter  /  model predictive control(MPC)  /  computational burden  /  extended Kalman filter(EKF)  /  parameter identification
Jianwei ZHANG, Zaixin YANG, Yunhui WANG, Guangchen LIU. Indirect Model Predictive Control of Matrix Converter Based on EKF Parameter Identification[J]. Electric Drive, 2025 , 55 (1) : 18 -24 . DOI: 10.19457/j.1001-2095.dqcd25455
Year 2025 volume 55 Issue 1
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Article Info
doi: 10.19457/j.1001-2095.dqcd25455
  • Receive Date:2023-10-24
  • Online Date:2025-10-29
  • Published:2025-01-20
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  • Received:2023-10-24
  • Revised:2023-12-22
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Affiliations
    1 College of Electric Power,Inner Mongolia University of Technology,Hohhot 010080,Nei Mongol,China
    2 Engineering Research Center of Large Energy Storage Technology of Ministry of Education,Inner Mongolia University of Technology,Hohhot 010080,Nei Mongol,China
    3 Inner Mongolia Key Laboratory of Smart Grid of New-type Power System,Inner Mongolia Electric Power Research Institute,Hohhot 010020,Nei Mongol,China
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表12种不同金属材料的力学参数

Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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