Robust adaptive integral sliding mode control of a half-bridge bidirectional DC-DC converter

A novel approach to improving the dynamic response of a half-bridge bidirectional DC-DC converter is presented in this paper, particularly in the face of disturbances from internal or external sources. These converters, which are integral to the operation of DC microgrids, are responsible for stepping up or stepping down voltage as required. To optimize the converter's performance under varying conditions, we propose an adaptive integral sliding mode controller (AISMC) enhanced by particle swarm optimization (PSO). The proposed controller leverages the strengths of both super-twisting sliding mode control (STSMC) and adaptive control, providing a robust and responsive solution to the challenges posed by the converter's nonlinear dynamics. The system's stability is rigorously ensured through the application of Lyapunov stability criteria, which underpin the enhanced performance of the controller. Simulations conducted in the MATLAB/Simulink environment demonstrate that the AISMC-PSO outperforms conventional control strategies, offering superior stability, robustness, and precision. The results clearly indicate that the proposed approach minimizes errors and enhances the overall efficiency and reliability of the bidirectional half-bridge DC-DC converter, making it a highly effective solution for DC microgrid applications.

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Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2024-11-18
DOI
https://doi.org/10.11591/ijece.v15i1.pp114-128
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Robust adaptive integral sliding mode control of a half-bridge bidirectional DC-DC converter

Ambe Harrison, Alexandre Teplaira Boum, Julius Derghe Cham, Francis Lénine Djanna Koffi
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Microgrid Control and Optimization
article

Robust adaptive integral sliding mode control of a half-bridge bidirectional DC-DC converter

Ambe Harrison, Alexandre Teplaira Boum, Julius Derghe Cham, Francis Lénine Djanna Koffi
article en

Abstract

A novel approach to improving the dynamic response of a half-bridge bidirectional DC-DC converter is presented in this paper, particularly in the face of disturbances from internal or external sources. These converters, which are integral to the operation of DC microgrids, are responsible for stepping up or stepping down voltage as required. To optimize the converter's performance under varying conditions, we propose an adaptive integral sliding mode controller (AISMC) enhanced by particle swarm optimization (PSO). The proposed controller leverages the strengths of both super-twisting sliding mode control (STSMC) and adaptive control, providing a robust and responsive solution to the challenges posed by the converter's nonlinear dynamics. The system's stability is rigorously ensured through the application of Lyapunov stability criteria, which underpin the enhanced performance of the controller. Simulations conducted in the MATLAB/Simulink environment demonstrate that the AISMC-PSO outperforms conventional control strategies, offering superior stability, robustness, and precision. The results clearly indicate that the proposed approach minimizes errors and enhances the overall efficiency and reliability of the bidirectional half-bridge DC-DC converter, making it a highly effective solution for DC microgrid applications.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 15(1)
University of Buea (CM), University of Douala (CM)
Affordable and clean energy
Openalex Percentile: Top 76%
Microgrid Control and Optimization
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Robust adaptive integral sliding mode control of a half-bridge bidirectional DC-DC converter — Ambe Harrison, Alexandre Teplaira Boum, et al. · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) | TGRS Research Map | TGRS