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Developing of Fuzzy Logic Controller for Air Condition System

by Sameh Mohamed Sobhy, Wael Mohamed Khedr
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 15
Year of Publication: 2015
Authors: Sameh Mohamed Sobhy, Wael Mohamed Khedr
10.5120/ijca2015906083

Sameh Mohamed Sobhy, Wael Mohamed Khedr . Developing of Fuzzy Logic Controller for Air Condition System. International Journal of Computer Applications. 126, 15 ( September 2015), 1-8. DOI=10.5120/ijca2015906083

@article{ 10.5120/ijca2015906083,
author = { Sameh Mohamed Sobhy, Wael Mohamed Khedr },
title = { Developing of Fuzzy Logic Controller for Air Condition System },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 15 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number15/22625-2015906083/ },
doi = { 10.5120/ijca2015906083 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:17:29.868780+05:30
%A Sameh Mohamed Sobhy
%A Wael Mohamed Khedr
%T Developing of Fuzzy Logic Controller for Air Condition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 15
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fuzzy logic control was developed to control the compressor motor speed , fan speed , fin direction and operation mode to maintain the room temperature at or closed to the set point temperature and save energy and keep devices from damage. This paper describes the development of Fuzzy logic algorithm for Air Condition control system. This system consists of four sensors for feedback control: first for input electric volt which used to save devices from damage due to alternated voltages, second for temperature and third for humidity and fourth for dew point. Simulation of the Fuzzy logic algorithm for Air Condition controlling system is carried out based on MATLAB.

References
  1. Karray FO, de Silva C (2004) Soft computing and intelligent system design. Addison Wesley Longman, Boston.
  2. Zadeh LA (1965) Fuzzy sets. Info Control 8(3):338–353.
  3. Guanrong C, Trung P (2000) Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems CRC, Boca Raton, FL.
  4. Timothy RJ (1995) Fuzzy logic with engineering applications. McGraw-Hill, Boston.
  5. J. Mendel. Fuzzy logic systems for engineering: a tutorial. Proceedings of the IEEE, 83(3):345{377, Mar 1995.
  6. Buckley , J ; Tucker , D. (1995) - Second generation fuzzy expert system- Fuzzy Sets and Systems.
  7. Forgy. C.L. (2002). On the efficient implementation of production systems,PhD thesis- Department of computer science CMU.
  8. Graham. I . (2000) - Fuzzy logic in commercial expert systems results and prospects Fuzzy Sets and Systems).
  9. Jan Jantzen (1998),”Tutorial on fuzzy logic”.
  10. Lotfi A (2001), Zadeh. “Fuzzy logic Toolbox”,.
  11. Lotfi A.Zadeh (1999),”Fuzzy systems”, Handbook, Second Edition.
  12. Mamdani E. H. (2000) - Application of fuzzy logic to approximate reasoning using guistic synthesis. IEEE Transaction on Computers .
  13. Rebecca Shalfield (2001),”Fuzzy logic toolkit “, http://www.Ipa.co.uk/.
  14. Zadeh L. A (1998) -The role of fuzzy logic in the management of uncertainty in expert system- Fuzzy Sets and Systems - North Holland.
  15. Allahverdi N, “Expert Systems, An Application of Artificial Intelligent”, Atlas Press, Istanbul, 2002.
  16. Tsoukalas L. H, Uhrig R. E, “Fuzzy and Neural Approaches in Engineering”, John Wiley & Sons, Inc. New York, USA, 1997.
  17. Wakami N, Araki S, Nomura H, “Recent Applications of Fuzzy Logic to Home Appliances”, Proceedings of the IECON '93. International Conference on, 15-19 Nov. 1993, vol.1, pp. 155-160, 1993.
  18. Caponetto, R, Fortuna, L, Nunnari, G, Occhipinti, L, “A fuzzy approach to greenhouse climate control” American Control Conference, Proceedings of the 1998, vol.3, pp.1866- 1870, 1998.
  19. Pan Lanfang, Wang Wanliang, Wu Qidi, “Application of adaptive fuzzy logic system to model for greenhouse climate” Intelligent Control and Automation, Proceedings of the 3rd World Congress on vol. 3, pp.1687-1691, 2000.
  20. Orchard, B., “Fuzzy Sets”, http://www.iit.nrc.ca/IR public/fuzzy/fuzzyJDocs/ FuzzySet.html, Accessed April 2006.
  21. Agarwal, S., Joshi, A., Finin, T. and Yesha, Y., “A Pervasive Computing System for the Operating Room of the Future”, http://ebiquity.umbc.edu/get/a/ publication/328.pdf, Accessed April 2006.
  22. Casas, F., A. Orozcob, W.A. Smitha, J.A. De Abreu-Garcı´ab, J. Durkin, “A fuzzy system cardio pulmonary bypass rotary blood pump controller”, Expert Systems with Applications 26, pp. 357-361, 2004.
  23. Fuzzy control programming. Technical report, International Electrotechnical Commission, 1997.
  24. US Patent – 5,921,099; Air conditioner temperature control apparatus; Inventor: Seon Woo Lee; Assignee: Samsung Electronics Co., Ltd. Issue date: Jul 13, 1999.
  25. US Patent – 5,148,977; control system for air conditioner; Inventors: Yozo Hibino, Susumu Nakayama, Hiromu Yasuda, Kensaku Oguni, Kenji Tokusa; Assignee: Hitachi, Ltd. Issue date: Sep 22, 1992.
  26. Technical case studies and articles on fuzzy logic and fuzzy logic based control systems www.sciencedirect.com, http://en.wikipedia.org and http://www.aptronix.com/.
  27. X.M. Song, “Research on LQR-fuzzy control algorithm of inverted pendulum system”, Xi'an University of Electronic Science and Technology Master’s thesis, January 2006.
  28. Amiya Patanaik, " Fuzzy Logic Control of Air Conditioners", Indian Institute of Technology, Kharagpur, - 721302, India.
  29. Sanjit Kumar Dash, Gouravmoy Mohanty, Abhishek Mohanty," Intelligent Air Conditioning System using Fuzzy Logic", International Journal of Scientific & Engineering Research Volume 3, Issue 12, December-2012
  30. K. Lavanya1, M.A. Saleem Durai2, N.Ch. Sriman Narayana Iyengar3," Fuzzy Rule Based Inference System for Detection and Diagnosis of Lung Cancer", International Journal of Latest Trends in Computing (E-ISSN: 2045-5364) 165 Volume 2, Issue 1, March 2011
  31. M. GLORIA SANCHEZ-TORRUBIA, CARMEN TORRES-BLANC, SANJAY KRISHNANKUTTY," Mamdani's Fuzzy Inference eMathTeacher: a Tutorial for Active Learning",
  32. Kuntze, H.-B, Bernard, Th, “A new fuzzy-based supervisory control concept for the demand-responsive optimization of HVAC control systems” Decision and Control, Proceedings of the 37th IEEE Conference on, vol. 4, pp. 4258-4263, 1998.
  33. http://www.dpcalc.org/index.php. available at:dew point calculator.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Logic Controller (FLC) Fuzzy Inference Systems(FIS) and Air Conditioning System.

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