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Accurate and optimal control of a bidirectional DC-DC converter: A robust adaptive approach enhanced by particle swarm optimization

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Abstract

• A brief Literature Review • Problem statement • Modeling and description of the converter • Design of non-linear controllers • Simulations in MATLAB-Simulink environment The efficient operation of DC-microgrids is highly depend on DC-DC converters. The Half-bridge Bidirectional DC-DC converter, a special class of power electronic converters has received significant attention in DC-microgrids due to its high flexibility. However, arriving at an optimal operating performance of this converter requires robust, accurate control and regulation of its output. To address the control requirements of this system, this paper proposes a robust adaptive nonlinear control strategy based on adaptive sliding mode controller. Unlike contemporary controllers, the proposed control strategy alleviates the chattering limitations of the classical sliding mode controller through the integration of a smooth hyperbolic tangent function. Additionally, the control structure is enhanced by an optimal adjustment of its gains through particle swarm optimization. A series of numerical investigations are conducted under diverse operating conditions such as variations in reference voltage, load resistance, and input voltages. The acquired results revealed a satisfactory response of the proposed control structure. Furthermore, by thoroughly comparing its performance against existing controllers such as conventional sliding mode controller, super-twisting sliding mode controller, adaptive sliding mode controller, this paper aims to emphasize the superiority of the proposed controller in achieving accurate and robust performance of the Half-bridge bidirectional DC-DC. Finally, experimental results were provided to validate the proposed controller in real time.

Research topics

  • Advanced DC-DC Converters
  • Photovoltaic System Optimization Techniques
  • Microgrid Control and Optimization

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DOI: 10.1016/j.prime.2025.100899

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