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Fuzzy Adaptive Controller Design for Control of Air in Conditioned Room

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Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9226))

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Abstract

In the paper we describe an adaptive controller for control of air in conditioned room. We know, that exist more procedures for management of change of climate air in room (for setup and maintain of optimal temperature) - classical control by using the button on/of, management by bimetallic sensors, temperature management through control elements and the like. The human body perceives the minimum temperature difference (+3/−3) in your area. Where it is necessary to maintain a constant temperature for a very long time (e.g. in offices, server rooms), we need to consider the controlled system. Control system is part of the control circuit and may be considered as transfer element with certain characteristics. In the choice of the controller and its configuration is important to know the dynamic properties of the system. The simplest is to determine the dynamic characteristics of the system obtained from the its step response. We may also use the frequency response, which is much more difficult to obtain. Dynamic properties of the control system can we mathematically to express as the relationship between the change in input (Action) and a change the output value of controlled variable. On the basis of the current research, as the most appropriate way to set up and maintain a constant temperature in room at minimum operating costs may be solution by using fuzzy adaptive controller.

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References

  1. Guillemin, A., Morel, n: An innovative lighting controller integrated in a self adaptive building control system. Energy Build. 33, 477–487 (2001)

    Article  Google Scholar 

  2. Dounis, A.I., Santamouris, M., Lefas, C.C., Argiriou, A.: Design of a fuzzy set environment comfort system. Energy Build. 22, 81–87 (1994)

    Article  Google Scholar 

  3. Dounis, A.I., Santamouris, M.J., Lefas, C.C.: Building Visual comfort control with fuzzy reasoning. Energy Convers. Manag. 34, 17–28 (1993)

    Article  Google Scholar 

  4. Amrich, M., Hrubý, D.: Možnosti simulácie a návrhu Fuzzy Riadiacich Algoritmov. In: International Professional Seminar Topical Questions of Instruction of Electricaal Engineering Subjects at Faculties with Non-electrical Orientation “SEKEL2006. 12–14 Sept 2006, Vrátna, Slovakia. pp. 29–33. ISBN 80-8070-584-4 (2006)

    Google Scholar 

  5. Altrock, C.V., Arend, H.O., Krause, B., Steffens, C., Behrens-Rommler, E.: Adaptive fuzzy control applied to home heating system. Fuzzy Sets Syst. 61, 29–35 (1994)

    Article  Google Scholar 

  6. Chen, T.: Real-time predictive supervisory operation of building thermal systems with thermal mass. Energy Build. 33(2), 141–150 (2001)

    Article  Google Scholar 

  7. Chiang, M.L., Fu, L.C.: Hybrid Systém based adaptive control for the nonlinear hvac system. In: Proceeding of the Conference on American Control Minneapolis, 14–16 June 2006 Minnesota, USA pp. 5324–5329 (2006)

    Google Scholar 

  8. Collewet, C., Rault, G., Quellec, S., Marchai, P.: fuzzy adaptive controller design for the joint space control of an agricultural robot. Fuzzy Sets Syst. 99(1), 1–25 (1998)

    Article  Google Scholar 

  9. Curtis, P.S., Shavit, G., Kreider, K.: neural networks applied to buildings—a tutorial and case studies in prediction and adaptive control. ASHRAE Trans. 102(1), 24 (1996)

    Google Scholar 

  10. Kolokotsa, D., Tsiavos, D., Stavrakakis, G.S., Kalaitzakis, K., Antonidakis, E.: Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal visual comfort and indoor air quality satisfaction. Energy Build. 33, 531–543 (2001)

    Article  Google Scholar 

  11. Dounis, A.I., Caraiscos, C.: Advanced control systems engineering for energy and comfort management in a building environment-a review. Renew. Sustain. Energy Rev. 13(6–7), 1246–1261 (2009)

    Article  Google Scholar 

  12. Calvino, F., Gennusca, M.L., Rizzo, G., Scaccianoce, G.: The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller. Energy Build. 36, 97–102 (2004)

    Article  Google Scholar 

  13. Huaguang, Z., Cai, L.: Decentralized nonlinear adaptive control of an HVAC system. Trans. Syst. Part C. 32, 493–498 (2002)

    Article  Google Scholar 

  14. Inoue, T., Kawase, T., Ibamoto, T., Takakusa, S., Matsuo, Y.: The development of an optimal control system for window shading devices based on investigations in office buildings. ASHRAE Trans. 104, 1034–1049 (1998)

    Google Scholar 

  15. Ang, K.H., Chong, G.C.Y., Li, Y.: PID Control system analysis, design, and technology. IEEE Trans. Control Syst. Technol. 13(4), 559–576 (2005)

    Article  Google Scholar 

  16. Kummert, M., Andre, P., Nicolas, J.: Optimal heating control in a passive solar commercial building. Solar Energy 69(1–6), 103–116 (2001)

    Article  Google Scholar 

  17. Lam, H.N.: Stochastic modeling and genetic algorithm based optimal control of air conditioning systems. In: Proceedings of the 3rd International Conference of the International Building Performance Simulation Association, Adelaide, Australia, pp. 435–441 (1993)

    Google Scholar 

  18. Li, S., Zhang, X., Xu, J., Cai, W.: An improved fuzzy RBF based on cluster and its application in HVAC system. In: Proceedings of the 6th World Congress on Intelligent Control and Automation, 21–23 June 2006 Dalian, China, pp. 6455–6459 (2006)

    Google Scholar 

  19. Liang, J., Du, R.: Thermal comfort control based on neural network for HVAC application. In: Proceeding of the IEEE Conference on Control Applications, 28–31 Aug 2005, Toronto, Canada, pp. 819–824 (2005)

    Google Scholar 

  20. Eftekhari, M., Marjanovic, L., Angelov, P.P.: Design and performance of a rulebased controller in a naturally ventilated room. Comput. Ind. 51, 299–326 (2003)

    Article  Google Scholar 

  21. Gouda, M., Danaher, S., Underwood, C.: Thermal comfort based fuzzy logic controller. Build. Serv. Eng. Res. Technol. 22(4), 237–253 (2001)

    Article  Google Scholar 

  22. Lah, M.T., Borut, Z., Krainer, A.: Fuzzy control for the illumination and temperature comfort in a test chamber. Build. Environ. 40, 1626–1637 (2005)

    Article  Google Scholar 

  23. Mirinejad, H., Sadati, S.H., Ghasemian, M., Torab, H.: Control techniques in heating, ventilating and air conditioning systems. J. Comput. Sci. 4, 777–783 (2008)

    Article  Google Scholar 

  24. Morel, N., Bauer, M., Khoury, M., El-Krauss, J.: Neurobat a predictive and adaptive heating control system using artificial neural networks. Int. J. Solar Energy 21, 161–201 (2000)

    Article  Google Scholar 

  25. Paris, B., Eynard, J., Grieu, S., Polit, M.: Hybrid PID-fuzzy control Scheme for managing energy resources in buildings. Appl. Soft Comput. J. 11(8), 5068–5080 (2001)

    Article  Google Scholar 

  26. Winn, C.B.: Controls in solar energy systems. Adv. Solar Energy (Am. Solar Energy Soc.) 1, 209–220 (1982)

    Google Scholar 

  27. Li, Y., Ang, K.H., Chong, G.C.Y.: PID control system analysis and design – problems, remedies, and future directions. IEEE Control Syst. Mag. 26(1), 32–41 (2006)

    Article  Google Scholar 

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Acknowledgment

This publication is supported thanks to the project KEGA 015UKF-4/2013 Modern computer science – New methods and forms for effective education.

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Natural Sciences, Constantine the Philosopher University in Nitra, Tr. A. Hlinku 1, 949 74, Nitra, Slovakia

    Štefan Koprda & Martin Magdin

Authors
  1. Štefan Koprda
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  2. Martin Magdin
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Correspondence to Martin Magdin .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Liverpool John Moores University, Liverpool, United Kingdom

    Abir Hussain

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Koprda, Š., Magdin, M. (2015). Fuzzy Adaptive Controller Design for Control of Air in Conditioned Room. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_31

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  • DOI: https://doi.org/10.1007/978-3-319-22186-1_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22185-4

  • Online ISBN: 978-3-319-22186-1

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