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<p>Heat exchangers (HEs) are mechanical devices primarily used in industry to exchange energy in the form of heat and temperature. This research focuses on controlling the temperature of cooling water by utilizing a plate heat exchanger (PHE), commonly used in the dairy, food and beverage, and chemical industries. A PHE operates on the principle of transferring heat between two fluids at different temperatures, making temperature control essential. To achieve effective temperature control, a 2-DOF-Fuzzy-PIDN controller is proposed. The parameters for the 2-DOF-PIDN controller are derived from a fuzzy inference system, with the input and output membership function ranges optimized using a modified human conception optimizer (MHCO). As a result, the PHE temperature is maintained more effectively. The uniqueness of this work lies in the optimization of both fuzzy input and output parameters through the meta-heuristic approach (MHCO). With the proposed controller, the developed model can maintain the cooling temperature with shorter settling time and reduced disturbances compared to other methods.</p>

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Optimal fuzzy logic controller design for a plate heat exchanger model

  • 期刊论文

  • 发表日期：

    2025年1月27日

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  • Subinaya Mohapatra,
  • Debasis Acharya,
  • Dushmanta Kumar Das

摘要

Heat exchangers (HEs) are mechanical devices primarily used in industry to exchange energy in the form of heat and temperature. This research focuses on controlling the temperature of cooling water by utilizing a plate heat exchanger (PHE), commonly used in the dairy, food and beverage, and chemical industries. A PHE operates on the principle of transferring heat between two fluids at different temperatures, making temperature control essential. To achieve effective temperature control, a 2-DOF-Fuzzy-PIDN controller is proposed. The parameters for the 2-DOF-PIDN controller are derived from a fuzzy inference system, with the input and output membership function ranges optimized using a modified human conception optimizer (MHCO). As a result, the PHE temperature is maintained more effectively. The uniqueness of this work lies in the optimization of both fuzzy input and output parameters through the meta-heuristic approach (MHCO). With the proposed controller, the developed model can maintain the cooling temperature with shorter settling time and reduced disturbances compared to other methods.