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Design of a fuzzy system for living space thermal-comfort regulation

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  • Dounis, A. I.
  • Manolakis, D. E.

Abstract

The present paper describes the design of a living space comfort regulator using fuzzy logic. Comfort is a fuzzy concept, different for different people and depending on the work done in the space. The paper describes the structure of the system, the available measurements and the available actuators, the measurement fuzzification process and the defuzzification method. Particular attention is paid to the proper selection of the rules in the knowledge base and the design of the inference engine. Finally the system is tested, and shows satisfactory performance. General design guidelines are given, including the case of spaces having different actuators.

Suggested Citation

  • Dounis, A. I. & Manolakis, D. E., 2001. "Design of a fuzzy system for living space thermal-comfort regulation," Applied Energy, Elsevier, vol. 69(2), pages 119-144, June.
    • Handle: RePEc:eee:appene:v:69:y:2001:i:2:p:119-144
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    References listed on IDEAS

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    1. Dounis, A.I. & Santamouris, M.J. & Lefas, C.C. & Manolakis, D.E., 1994. "Thermal-comfort degradation by a visual comfort fuzzy-reasoning machine under natural ventilation," Applied Energy, Elsevier, vol. 48(2), pages 115-130.
    2. Dounis, A. I. & Lefas, C. C. & Argiriou, A., 1995. "Knowledge-based versus classical control for solar-building designs," Applied Energy, Elsevier, vol. 50(4), pages 281-292.
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    Cited by:

    1. Panagiotis Korkidis & Anastasios Dounis & Panagiotis Kofinas, 2021. "Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings," Energies, MDPI, vol. 14(16), pages 1-33, August.
    2. Sehar, Fakeha & Pipattanasomporn, Manisa & Rahman, Saifur, 2016. "A peak-load reduction computing tool sensitive to commercial building environmental preferences," Applied Energy, Elsevier, vol. 161(C), pages 279-289.
    3. Behl, Madhur & Smarra, Francesco & Mangharam, Rahul, 2016. "DR-Advisor: A data-driven demand response recommender system," Applied Energy, Elsevier, vol. 170(C), pages 30-46.
    4. Song, Dongran & Tu, Yanping & Wang, Lei & Jin, Fangjun & Li, Ziqun & Huang, Chaoneng & Xia, E & Rizk-Allah, Rizk M. & Yang, Jian & Su, Mei & Hoon Joo, Young, 2022. "Coordinated optimization on energy capture and torque fluctuation of wind turbines via variable weight NMPC with fuzzy regulator," Applied Energy, Elsevier, vol. 312(C).
    5. Ahn, Jonghoon & Cho, Soolyeon & Chung, Dae Hun, 2017. "Analysis of energy and control efficiencies of fuzzy logic and artificial neural network technologies in the heating energy supply system responding to the changes of user demands," Applied Energy, Elsevier, vol. 190(C), pages 222-231.
    6. Yan, Huaxia & Pan, Yan & Li, Zhao & Deng, Shiming, 2018. "Further development of a thermal comfort based fuzzy logic controller for a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 219(C), pages 312-324.
    7. Shahnawaz Ahmed, S. & Shah Majid, Md. & Novia, Hendri & Abd Rahman, Hasimah, 2007. "Fuzzy logic based energy saving technique for a central air conditioning system," Energy, Elsevier, vol. 32(7), pages 1222-1234.
    8. Ghahramani, Ali & Castro, Guillermo & Karvigh, Simin Ahmadi & Becerik-Gerber, Burcin, 2018. "Towards unsupervised learning of thermal comfort using infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 41-49.
    9. Whiffen, T.R. & Naylor, S. & Hill, J. & Smith, L. & Callan, P.A. & Gillott, M. & Wood, C.J. & Riffat, S.B., 2016. "A concept review of power line communication in building energy management systems for the small to medium sized non-domestic built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 618-633.
    10. Ghadi, Yazeed Yasin & Rasul, M.G. & Khan, M.M.K., 2016. "Design and development of advanced fuzzy logic controllers in smart buildings for institutional buildings in subtropical Queensland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 738-744.
    11. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    12. Tzivanidis, C. & Antonopoulos, K.A. & Gioti, F., 2011. "Numerical simulation of cooling energy consumption in connection with thermostat operation mode and comfort requirements for the Athens buildings," Applied Energy, Elsevier, vol. 88(8), pages 2871-2884, August.
    13. Shaikh, Pervez Hameed & Nor, Nursyarizal Bin Mohd & Nallagownden, Perumal & Elamvazuthi, Irraivan & Ibrahim, Taib, 2014. "A review on optimized control systems for building energy and comfort management of smart sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 409-429.
    14. Esmail Mahmoudi Saber & Issa Chaer & Aaron Gillich & Bukola Grace Ekpeti, 2021. "Review of Intelligent Control Systems for Natural Ventilation as Passive Cooling Strategy for UK Buildings and Similar Climatic Conditions," Energies, MDPI, vol. 14(15), pages 1-16, July.

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