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RBF Neural Network Fractional-Order Sliding Mode Control with an Application to Direct a Three Matrix Converter under an Unbalanced Grid

Author

Listed:
  • Xuhong Yang

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Haoxu Fang

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Yaxiong Wu

    (College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Wei Jia

    (Shanghai Solar Energy Engineering Technology Research Center Co., Ltd., Shanghai 200241, China)

Abstract

This paper presents a fractional-order sliding mode control scheme based on an RBF neural network (RBFFOSMC) for a direct three matrix converter (DTMC) operating under unbalanced grid voltages. The RBF neural network (RBF NN) is designed to approximate a nonlinear fractional-order sliding mode controller. The proposed method aims to achieve constant active power whilst maintaining a near unity input power factor. First, an opportune reference current is accurately generated according to the reference power and the RBFFOSMC is designed in a dq reference frame to achieve a perfect tracking of the input current reference. An almost constant active power, free of low-frequency ripples, is then supplied from the grid after compensating for the output voltage. Simulation and experimental studies prove the feasibility and effectiveness of the proposed control method.

Suggested Citation

  • Xuhong Yang & Haoxu Fang & Yaxiong Wu & Wei Jia, 2022. "RBF Neural Network Fractional-Order Sliding Mode Control with an Application to Direct a Three Matrix Converter under an Unbalanced Grid," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3193-:d:766935
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    References listed on IDEAS

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    1. Mohammad Mehdi Roshani & Seyed Hamidreza Kargar & Visar Farhangi & Moses Karakouzian, 2021. "Predicting the Effect of Fly Ash on Concrete’s Mechanical Properties by ANN," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
    2. Zahra Malekjamshidi & Mohammad Jafari & Jianguo Zhu & Marco Rivera & Wen Soong, 2021. "Model Predictive Control of the Input Current and Output Voltage of a Matrix Converter as a Ground Power Unit for Airplane Servicing," Sustainability, MDPI, vol. 13(17), pages 1-17, August.
    3. Marco Rivera & Sebastián Rojas & Carlos Restrepo & Javier Muñoz & Carlos Baier & Patrick Wheeler, 2020. "Control Techniques for a Single-Phase Matrix Converter," Energies, MDPI, vol. 13(23), pages 1-15, December.
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