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Environmental Health Oriented Optimal Temperature Control for Refrigeration Systems Based on a Fruit Fly Intelligent Algorithm

Author

Listed:
  • Yuxiao Qin

    (Jiangsu Province Key Lab of Aerospace Power System, Chien-Shiung Wu College, Southeast University, Nanjing 210096, China)

  • Li Sun

    (Key Lab of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China)

  • Qingsong Hua

    (School of Mechanical and Electrical Engineering, Qingdao University, Ningxia Road 308, Qingdao 266071, China)

Abstract

The recent decades have witnessed refrigeration systems playing an important role in the life of human beings, with wide applications in various fields, including building comfort, food storage, food transportation and the medical special care units. However, if the temperature is not controlled well, it will lead to many harmful public health effects, such as the human being catching colds, food spoilage and harm to the recovering patients. Besides, refrigeration systems consume a significant portion of the whole society’s electricity usage, which consequently contributes a considerable amount of carbon emissions into the public environment. In order to protect human health and improve the energy efficiency, an optimal control strategy is designed in this paper with the following steps: (1) identifying the refrigeration system model based on a least squares method; (2) tuning an initial group of parameters of the proportional-integral-derivative (PID) controller via the pidTuner Toolbox of Matlab; (3) using an intelligent algorithm, namely fruit fly optimization (FOA), to further optimize the parameters of the PID controller. By comparing the optimal PID controller and the controller provided in the reference, the simulation results demonstrate that the proposed optimal PID controller can produce a more controllable temperature, with less tacking overshoot, less settling time, and more stable performance under a constant set-point.

Suggested Citation

  • Yuxiao Qin & Li Sun & Qingsong Hua, 2018. "Environmental Health Oriented Optimal Temperature Control for Refrigeration Systems Based on a Fruit Fly Intelligent Algorithm," IJERPH, MDPI, vol. 15(12), pages 1-15, December.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:12:p:2865-:d:190620
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    References listed on IDEAS

    as
    1. Yuxiao Qin & Li Sun & Qingsong Hua & Ping Liu, 2018. "A Fuzzy Adaptive PID Controller Design for Fuel Cell Power Plant," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    2. Yuhui Jin & Li Sun & Qingsong Hua & Shunjia Chen, 2018. "Experimental Research on Heat Exchanger Control Based on Hybrid Time and Frequency Domain Identification," Sustainability, MDPI, vol. 10(8), pages 1-17, July.
    3. Sun, Li & Shen, Jiong & Hua, Qingsong & Lee, Kwang Y., 2018. "Data-driven oxygen excess ratio control for proton exchange membrane fuel cell," Applied Energy, Elsevier, vol. 231(C), pages 866-875.
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