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Model Predictive Control of DC–DC Boost Converter Based on Generalized Proportional Integral Observer

Author

Listed:
  • Rongchao Niu

    (Xi’an Institute of Applied Optics, Xi’an 710065, China)

  • Hongyu Zhang

    (School of Automation, Northwestern Polytechnical University, Xi’an 710129, China)

  • Jian Song

    (School of Automation, Northwestern Polytechnical University, Xi’an 710129, China)

Abstract

Due to the nonminimum phase characteristics and nonlinearity of boost converters, the control design is always a challenging issue. A novel model predictive control strategy is proposed for the boost converter in this work. First, the Super-Twisting algorithm is applied to current control, and the input–output plant for voltage control is derived based on the linearization technique. All the model uncertainties are defined as lumped disturbances, and a generalized proportional integral observer is designed to estimate the lumped disturbance. Second, a composite predictive approach is developed on the basis of the predictive model and disturbance estimations. By solving the cost function directly, the optimal control law is derived explicitly. Lastly, the effectiveness of the proposed control strategy is verified by both simulation and experimental results.

Suggested Citation

  • Rongchao Niu & Hongyu Zhang & Jian Song, 2023. "Model Predictive Control of DC–DC Boost Converter Based on Generalized Proportional Integral Observer," Energies, MDPI, vol. 16(3), pages 1-16, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1245-:d:1045168
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    References listed on IDEAS

    as
    1. Gerardo Humberto Valencia-Rivera & Ivan Amaya & Jorge M. Cruz-Duarte & José Carlos Ortíz-Bayliss & Juan Gabriel Avina-Cervantes, 2021. "Hybrid Controller Based on LQR Applied to Interleaved Boost Converter and Microgrids under Power Quality Events," Energies, MDPI, vol. 14(21), pages 1-31, October.
    2. Ke Guo & Qiang Liu & Xinze Xi & Mingxuan Mao & Yihao Wan & Hao Wu, 2020. "Coordinated Control Strategy of a Combined Converter in a Photovoltaic DC Boost Collection System under Partial Shading Conditions," Energies, MDPI, vol. 13(2), pages 1-18, January.
    3. Julio Alves Mesquita da Silva & Grace Silva Deaecto & Tarcio Andre dos Santos Barros, 2022. "Analysis and Design Aspects of Min-Type Switching Control Strategies for Synchronous Buck–Boost Converter," Energies, MDPI, vol. 15(7), pages 1-15, March.
    4. Jiang You & Weiyan Fan & Lijun Yu & Bin Fu & Mengyan Liao, 2019. "Disturbance Rejection Control Method of Double-Switch Buck-Boost Converter Using Combined Control Strategy," Energies, MDPI, vol. 12(2), pages 1-15, January.
    5. Tao Yang & Yong Liao, 2019. "Discrete Sliding Mode Control Strategy for Start-Up and Steady-State of Boost Converter," Energies, MDPI, vol. 12(15), pages 1-13, August.
    6. El Manaa Barhoumi & Ikram Ben Belgacem & Abla Khiareddine & Manaf Zghaibeh & Iskander Tlili, 2018. "A Neural Network-Based Four Phases Interleaved Boost Converter for Fuel Cell System Applications," Energies, MDPI, vol. 11(12), pages 1-18, December.
    7. Xiaocong Li & Xin Chen, 2021. "A Multi-Index Feedback Linearization Control for a Buck-Boost Converter," Energies, MDPI, vol. 14(5), pages 1-14, March.
    Full references (including those not matched with items on IDEAS)

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