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Adaptive Hierarchical Fuzzy controller for HVAC Systems in Low Energy Buildings

Year 2015, Volume: 3 Issue: 2, 1 - 7, 14.11.2015
https://doi.org/10.5505/apjes.2015.46220

Abstract

Proper control for low energy buildings is more difficult than conventional buildings due to their complexity and sensitivity to operating conditions. In this paper, Adaptive Hierarchical Fuzzy control is used to control Heating, Ventilating and Air Conditioning (HVAC) System which is time varying nonlinear system. The proposed Controller is capable of maintaining comfort conditions under time varying thermal loads. Adaptive Hierarchical Fuzzy is consist of two levels; first fuzzy level is to control (Air temperature and Air quality); the second fuzzy level is to control the Error and Change of Error that comes from first level. A hierarchical structure is used to reduce the number of rules, trim redundant information and reduce the computing time required for the optimization. The controller is developed using a computer simulation of a virtual building contains most parameters of a real building. Fuzzy rules are learned from experts and system performance observations. Matlab program is used to simulate HVAC system and to see the results of the new controller.

References

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Adaptive Hierarchical Fuzzy controller for HVAC Systems in Low Energy Buildings

Year 2015, Volume: 3 Issue: 2, 1 - 7, 14.11.2015
https://doi.org/10.5505/apjes.2015.46220

Abstract

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References

  • T0 - T1 T2 - T3 (T2 - T3) T2 (T0 - T1) T2 T3 System (Room) -K- Ratio adjustment1 Fuzzy Logic Controller Level 1 Parameters Limits 5 Parameters Limits 4 Limits 3 Parameters Limits 2 Parameters Limits 1 Infinity loop Prevention Clas A. Jacobson, “Energy Efficient Buildings A Systems Approach Market Status”, Regulatory Pressure, Technology Gaps Stanford Energy Seminar May 9, 2011
  • Farinaz Behrooz1, Abdul Rahman Ramli and Khairulmizam Samsudin ”A survey on applying different control methods approach in building automation efficiency”, International Journal of the Physical Sciences Vol. 6(9), pp. 2308-2314, 4 May, 2011
  • John Lataire, Frequency Domain Measurement and Identification of Linear, Time-Varying Systems. Sadik Kakaç and Hongtan Liu (2002). Heat
  • Exchangers: Selection, Rating and Thermal Design (2nd ed.). CRC Press. ISBN 0-8493-0902-6
  • Hassan K. Khalil, Nonlinear Systems Third Edition, ISBN 0-13-067389-7, Prentice Hall 2002
  • M. Arima, E.H. Hara, and J.D. Katzberg, “A fuzzy logic and rough sets controller for HVAC systems,” in Proc. of the IEEE WESCANEX’95, vol. 1, NY, 1995, pp. 133–138. obtain more energy
  • P.Y. Glorennec, “Application of fuzzy control for building Simulation: International Building Performance Simulation Association 1, Sophia Antipolis: France, 1991, pp. 197–201.
  • S. Huang, and R.M. Nelson, “Rule development and adjustment strategies of a fuzzy logic controller for an HVAC system— Parts I and II (analysis and experiment),” ASHRAE Transactions, vol. 100, no. 1, pp. 841–850, 851–856, 1994.
  • Astrom, Karl Adaptive Control. Dover,2008
  • E. H. Mamdani and S. Assilian, “An experiment with in linguistic synthesis with a fuzzy logic controller,” International journal of Man-Machine studies, vol. 7, pp. 1-13, 1975.
  • M. Arima, E.H. Hara, and J.D. Katzberg, “A fuzzy logic and rough sets controller for HVAC systems,” in Proc. of the IEEE WESCANEX’95, vol. 1, NY, 1995, pp. 133–138. in Building Zak,Temperature https://controls.engin.umich.edu/wiki/index.php/Tem peratureSensors
  • Timothy J. Ross, Fuzzy Logic with Engineering Applications, Third Edition © 2010 John Wiley & Sons, Ltd. ISBN: 978-0-470-74376-8
  • Mohammed S. EL-Moghany, Sun and Maximum Power Point Tracking in Solar Array Systems Using Fuzzy University,2011
  • Riza,B. Sheldon,T., Fuzzy Systems Design Principles Building Fuzzy IF-THEN Rule Bases, IEEE PRESS(1997). 2006 Online: Controllers Via FPGA, Islamic
There are 14 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Basil Hamed This is me

Fadi Alami This is me

Publication Date November 14, 2015
Submission Date November 14, 2015
Published in Issue Year 2015 Volume: 3 Issue: 2

Cite

IEEE B. Hamed and F. Alami, “Adaptive Hierarchical Fuzzy controller for HVAC Systems in Low Energy Buildings”, APJES, vol. 3, no. 2, pp. 1–7, 2015, doi: 10.5505/apjes.2015.46220.