Skip to main content
SpringerLink
Log in

Fuzzy Rule Reduction and Tuning of Fuzzy Logic Controllers for a HVAC System

  • Chapter
Fuzzy Applications in Industrial Engineering

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 201))

Abstract

Heating, Ventilating and Air Conditioning (HVAC) Systems are equipments usually implemented for maintaining satisfactory comfort conditions in buildings. The design of Fuzzy Logic Controllers (FLCs) for HVAC Systems is usually based on the operator’s experience. However, an initial rule set drawn from the expert’s experience sometimes fail to obtain satisfactory results, since inefficient or redundant rules are usually found in the final Rule Base. Moreover, in our case, the system being controlled is too complex and an optimal controller behavior is required.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. Alcalá, J. Casillas, J.L. Castro, A. González, F. Herrera, A multicriteria genetic tuning for fuzzy logic controllers, Mathware and Soft Computing 8:2 (2001) 179–201.

    MATH  Google Scholar 

  2. R. Alcalá, J.M. Benítez, J. Casillas, O. Cordón, R. Pérez, Fuzzy control of HVAC systems optimized by genetic algorithms, Applied Intelligence 18 (2003) 155–177.

    Article  MATH  Google Scholar 

  3. R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, F. Herrera, Hybrid Learning Models to Get the Interpretability-Accuracy Trade-Off in Fuzzy Modeling, International Journal of Soft Computing (2004) in press.

    Google Scholar 

  4. R. Alcalá, F. Herrera, Genetic tuning on fuzzy systems based on the linguistic 2-tuples representation, in Proc. of the 2004 IEEE International Conference on Fuzzy Systems 1 (Budapest, Hungary, 2004) 233–238.

    Google Scholar 

  5. M. Arima, E.H. Hara, J.D. Katzberg, A fuzzy logic and rough sets controller for HVAC systems, Proceedings of the IEEE WESCANEX’95 1 (NY, 1995) 133–138.

    Google Scholar 

  6. U. Bodenhofer and P. Bauer, A formal model of interpretability of linguistic variables, in Interpretability issues in fuzzy modeling, J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.), Springer-Verlag (2003) 524–545.

    Google Scholar 

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

    Article  Google Scholar 

  8. J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.), Accuracy improvements in linguistic fuzzy modeling, Studies in Fuzziness and Soft Computing 129 (Springer-Verlag, Heidelberg, Germany, 2002).

    Google Scholar 

  9. J. Casillas, O. Cordón, F. Herrera, L. Magdalena (Eds.), Interpretability issues in fuzzy modeling, Springer-Verlag (2003).

    Google Scholar 

  10. F. Cheong and R. Lai, Constraining the optimization of a fuzzy logic controller using an enhanced genetic algorithm, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 30:1 (2000) 31–46.

    Article  Google Scholar 

  11. T. C. Chin, X. M. Qi, Genetic algorithms for learning the rule base of fuzzy logic controller, Fuzzy Sets and Systems 97:1 (1998) 1–7.

    Article  Google Scholar 

  12. S. Chiu, Fuzzy model identification based on cluster estimation, Journal of Intelligent and Fuzzy Systems 2 (1994) 267–278.

    Article  Google Scholar 

  13. W. E. Combs, J. E. Andrews, Combinatorial rule explosion eliminated by a fuzzy rule configuration, IEEE Transactions on Fuzzy Systems 6:1 (1998) 1–11.

    Article  Google Scholar 

  14. O. Cordón, F. Herrera, A three-stage evolutionary process for learning descriptive and approximative fuzzy logic controller knowledge bases from examples, International Journal of Approximate Reasoning 17:4 (1997) 369–407.

    Article  MATH  Google Scholar 

  15. O. Cordón, M. J. del Jesús, F. Herrera, Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods, International Journal of Intelligent Systems 13:10–11 (1998) 1025–1053.

    Article  Google Scholar 

  16. O. Cordón, F. Herrera, A proposal for improving the accuracy of linguistic modeling, IEEE Transaction on Fuzzy Systems 8:3 (2000) 335–344.

    Article  Google Scholar 

  17. O. Cordón, F. Herrera, F. Hoffmann, and L. Magdalena, Genetic fuzzy systems–evolutionary tuning and learning of fuzzy knowledge bases, World Scientific (2001).

    Google Scholar 

  18. D. Driankov, H. Hellendoorn, M. Reinfrank, An introduction to fuzzy control (Springer-Verlag, 1993).

    Google Scholar 

  19. L.J. Eshelman, The CHC adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination, in: G.J.E. Rawlins (Ed.), Foundations of Genetic Algorithms (Morgan Kauffman, San Mateo, CA, 1991) 265–283.

    Google Scholar 

  20. L.J. Eshelman, J.D. Schaffer, Real-coded genetic algorithms and intervalschemata, in: Foundations of Genetic Algorithms 2 (Morgan Kauffman, San Mateo, CA, 1993) 187–202.

    Google Scholar 

  21. J. Espinosa and J. Vandewalle, Constructing fuzzy models with linguistic integrity from numerical data-afreli algorithm, IEEE Transactions on Fuzzy Systems—Part B: Cybernetics 8:5 (2000) 591–600.

    Google Scholar 

  22. P.Y. Glorennec, Application of fuzzy control for building energy management, in: Building Simulation: International Building Performance Simulation Association 1 (Sophia Antipolis, France, 1991) 197–201.

    Google Scholar 

  23. A. F. Gómez-Skarmeta, F. Jiménez, Fuzzy modeling with hybrid systems, Fuzzy Sets and Systems 104 (1999) 199–208.

    Article  Google Scholar 

  24. H. B. Gürocak, A genetic-algorithm-based method for tuning fuzzy logic controllers, Fuzzy Sets and Systems, 108:1 (1999) 39–47.

    Article  MATH  Google Scholar 

  25. S. Halgamuge, M. Glesner, Neural networks in designing fuzzy systems for real world applications, Fuzzy Sets and Systems 65:1 (1994) 1–12.

    Article  Google Scholar 

  26. F. Herrera, M. Lozano, J.L. Verdegay, Fuzzy connectives based crossover operators to model genetic algorithms population diversity, Fuzzy Sets and Systems 92:1 (1997) 21–30.

    Article  Google Scholar 

  27. F. Herrera, M. Lozano, J.L. Verdegay, A learning process for fuzzy control rules using genetic algorithms, Fuzzy Sets and Systems 100 (1998) 143–158.

    Article  Google Scholar 

  28. F. Herrera, M. Lozano, and J. L. Verdegay, Tuning fuzzy controllers by genetic algorithms, Int. J. of Approximate Reasoning 12 (1995) 299–315.

    Article  MATH  MathSciNet  Google Scholar 

  29. F. Herrera and L. Martínez, A 2-tuple fuzzy linguistic representation model for computing with words, IEEE Transactions on Fuzzy Systems 8 (2000) 746–752.

    Article  Google Scholar 

  30. K. Hirota (Ed.), Industrial applications of fuzzy technology (Springer-Verlag, 1993).

    Google Scholar 

  31. S. Huang, 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 100:1 (1994) 841–850, 851–856.

    Google Scholar 

  32. H. Ishibuchi, T. Murata, I. B. Türksen, Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems, Fuzzy Sets and Systems 89 (1997) 135–150.

    Article  Google Scholar 

  33. H. Ishibuchi, K. Nozaki, N. Yamamoto, H. Tanaka, Selecting fuzzy if-then rules for classification problems using genetic algorithms, IEEE Transactions on Fuzzy Systems 9:3 (1995) 260–270.

    Article  Google Scholar 

  34. Y. Jin, W. von Seelen, and B. Sendhoff, On generating FLC 3 fuzzy rule systems from data using evolution strategies, IEEE Transactions on Systems, Man, and Cybernetics 29:4 (1999) 829–845.

    Google Scholar 

  35. C.L. Karr, Genetic algorithms for fuzzy controllers, AI Expert 6:2 (1991) 26–33.

    Google Scholar 

  36. A. Krone, H. Krause, T. Slawinski, A new rule reduction method for finding interpretable and small rule bases in high dimensional search spaces, Proceedings of the 9th IEEE International Conference on Fuzzy Systems, San Antonio, TX, USA, 2000, 693–699.

    Google Scholar 

  37. L. Lu, W. Cai, L. Xie, S. Li, Y.C. Soh, HVAC system optimization in building section, Energy and Buildings 37 (2005) 11–22.

    Article  Google Scholar 

  38. E.H. Mamdani, Applications of fuzzy algorithms for control a simple dynamic plant, Proceedings of the IEEE 121:12 (1974) 1585–1588.

    Google Scholar 

  39. E.H. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies 7 (1975) 1–13.

    Article  MATH  Google Scholar 

  40. D. Nauck and R. Kruse, Neuro-fuzzy systems for function approximaton, Fuzzy Sets and Systems 101:2 (1999) 261–271.

    Article  MATH  MathSciNet  Google Scholar 

  41. J. V. de Oliveira, Semantic constraints for membership function optimization, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans 29:1 (1999) 128–138.

    Article  Google Scholar 

  42. J. V. de Oliveira, Towards neuro-linguistic modeling: constraints for optimization of membership functions, Fuzzy Sets and Systems 106:3 (1999) 357–380.

    Article  MATH  MathSciNet  Google Scholar 

  43. J. Pargfrieder, H. J ÖRGL, An integrated control system for optimizing the energy consumption and user comfort in buildings, Proceedings of the 12th IEEE International Symposium on Computer Aided Control System Design (Glasgow, Scotland, 2002) 127–132.

    Google Scholar 

  44. A. Rahmati, F. Rashidi, M. Rashidi, A hybrid fuzzy logic and PID controller for control of nonlinear HVAC systems, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 3 (Washington, D.C., USA, 2003) 2249–2254.

    Google Scholar 

  45. H. Roubos, M. Setnes, Compact fuzzy models through complexity reduction and evolutionary optimization, Proceedings of the 9th IEEE International Conference on Fuzzy Systems 2 (San Antonio, Texas, USA, 2000) 762–767.

    Google Scholar 

  46. H. Roubos and M. Setnes, Compact and transparent fuzzy models through iterative complexity reduction, IEEE Transactions on Fuzzy Systems 9:4 (2001) 515–524.

    Article  Google Scholar 

  47. R. Rovatti, R. Guerrieri, G. Baccarani, Fuzzy rules optimization and logic synthesis, Proceedings of the 2nd IEEE International Conference on Fuzzy Systems 2 (San Francisco, USA, 1993) 1247–1252.

    Google Scholar 

  48. M. Setnes, R. Babuska, U. Kaymak, H. R. van Nauta-Lemke, Similarity measures in fuzzy rule base simplification, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 28 (1998) 376–386.

    Article  Google Scholar 

  49. M. Setnes, H. Hellendoorn, Orthogonal transforms of ordering and reduction of fuzzy rules, Proceedings of the 9th IEEE International Conference on Fuzzy Systems 2 (San Antonio, Texas, USA, 2000) 700–705.

    Google Scholar 

  50. D. Whitley, J. Kauth, GENITOR: A different genetic algorithm, Proceedings of the Rocky Mountain Conference on Artificial Intelligence, Denver (1988) 118–130.

    Google Scholar 

  51. J. Wu, W. Cai, Development of an adaptive neuro-fuzzy method for supply air pressure control in HVAC system, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 5 (Nashville, Tennessee, USA, 2000) 3806–3809.

    Google Scholar 

  52. I.H. Yang, M.S. Yeo, K.W. Kim, Application of artificial neural network to predict the optimal start time for heating system in building, Energy Conversion and Management 44 (2003) 2791–2809.

    Article  Google Scholar 

  53. J. Yen, L. Wang, Simplifying fuzzy rule-based models using orthogonal transformation methods, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 29 (1999) 13–24.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Computer Science and Artificial Intelligence, University of Granada, Granada, E-18071, Spain

    R. Alcalá, J. Alcalá-Fdez, M.J. Gacto & F. Herrera

Authors
  1. R. Alcalá
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Alcalá-Fdez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M.J. Gacto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. F. Herrera
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Industrial Department of Engineering Faculty Management, Istanbul Technical University, Campus Macka, Istanbul, 80680, Turkey

    Cengiz Kahraman Dr.

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this chapter

Cite this chapter

Alcalá, R., Alcalá-Fdez, J., Gacto, M., Herrera, F. (2006). Fuzzy Rule Reduction and Tuning of Fuzzy Logic Controllers for a HVAC System. In: Kahraman, C. (eds) Fuzzy Applications in Industrial Engineering. Studies in Fuzziness and Soft Computing, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33517-X_3

Download citation

  • DOI: https://doi.org/10.1007/3-540-33517-X_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33516-0

  • Online ISBN: 978-3-540-33517-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation