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Optimal Sliding-Mode Control of Semi-Bridgeless Boost Converters Considering Power Factor Corrections

Author

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  • José R. Ortiz-Castrillón

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia
    Department of Electronics and Telecommunications Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia
    Facultad de Ingeniería, Departamento de Eléctrica, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050036, Colombia)

  • Sergio D. Saldarriaga-Zuluaga

    (Facultad de Ingeniería, Departamento de Eléctrica, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050036, Colombia)

  • Nicolás Muñoz-Galeano

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia)

  • Jesús M. López-Lezama

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia)

  • Santiago Benavides-Córdoba

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia)

  • Juan B. Cano-Quintero

    (Research Group on Efficient Energy Management (GIMEL), Department of Electrical Engineering, Universidad de Antioquia (UdeA), Medellín 050010, Colombia)

Abstract

Sliding-mode control (SMC) is a robust technique used in power electronics (PE) for controlling the behavior of power converters. This paper presents simulations and experimental results of an optimal SMC strategy applied to Semi-Bridgeless Boost Converters (SBBC), which includes Power Factor Correction (PFC). As the main contribution, the optimal coefficients of the SMC strategy are obtained using two metaheuristic approaches, namely the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The main objective is to obtain the sliding coefficients that ensure the best converter response in terms of the input current and output voltage, both during start-up and under disturbances (including changes in load, source, and references). The fitness function to be minimized includes two coefficients, namely the Integrative Absolute Error (IAE) and the Integral Time Absolute Error (ITAE), for both the input current and output voltage. These coefficients measure the converter’s effort to follow the control references. The IAE penalizes errors during start-up, whereas the ITAE penalizes errors in the steady state. The tests carried out demonstrated the effectiveness of the GA and PSO techniques in the optimization process; nonetheless, the GA outperformed the PSO approach, providing sliding coefficients that allowed for a reduction in the input current overshoot during start-up of up to 24.15% and a reduction in the setting time of the output voltage of up to 99%. The experimental results were very similar when tuning with the GA and PSO techniques; nevertheless, tuning with the GA technique produced a better response in the face of disturbances compared to the PSO technique.

Suggested Citation

  • José R. Ortiz-Castrillón & Sergio D. Saldarriaga-Zuluaga & Nicolás Muñoz-Galeano & Jesús M. López-Lezama & Santiago Benavides-Córdoba & Juan B. Cano-Quintero, 2023. "Optimal Sliding-Mode Control of Semi-Bridgeless Boost Converters Considering Power Factor Corrections," Energies, MDPI, vol. 16(17), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6282-:d:1228108
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    References listed on IDEAS

    as
    1. Muhammad Bachtiar Nappu & Ardiaty Arief & Willy Akbar Ajami, 2023. "Energy Efficiency in Modern Power Systems Utilizing Advanced Incremental Particle Swarm Optimization–Based OPF," Energies, MDPI, vol. 16(4), pages 1-13, February.
    2. Musawenkosi Lethumcebo Thanduxolo Zulu & Rudiren Pillay Carpanen & Remy Tiako, 2023. "A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks," Energies, MDPI, vol. 16(4), pages 1-32, February.
    3. Muhammad Awais & Abdul Rehman Yasin & Mudassar Riaz & Bilal Saqib & Saba Zia & Amina Yasin, 2021. "Robust Sliding Mode Control of a Unipolar Power Inverter," Energies, MDPI, vol. 14(17), pages 1-15, August.
    4. Andrés Felipe Pérez Posada & Juan G. Villegas & Jesús M. López-Lezama, 2017. "A Scatter Search Heuristic for the Optimal Location, Sizing and Contract Pricing of Distributed Generation in Electric Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-16, September.
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