Mathematics in Computer Science

, Volume 7, Issue 3, pp 367–378 | Cite as

Intuitionistic Fuzzy Logic Control for Heater Fans

  • Muhammad Akram
  • Saadia Shahzad
  • Arif Butt
  • Abdul Khaliq


The concept of intuitionistic fuzzy systems, including intuitionistic fuzzy sets and intuitionistic fuzzy logic, was introduced by Atanassov as a generalization of fuzzy systems. Intuitionistic fuzzy systems provide a mechanism for communication between computing systems and humans. In this paper, we describe the development of an intuitionistic fuzzy logic controller for heater fans, developed on the basis of intuitionistic fuzzy systems. Intuitionistic fuzzy inference systems and defuzzification techniques are used to obtain crisp output (i.e., speed of the heater fan) from an intuitionistic fuzzy input (i.e., ambient temperature). The speed of the heater fan is calculated using intuitionistic fuzzy rules applied in an inference engine using defuzzification methods.


Intuitionistic fuzzy sets Intuitionistic fuzzy logic Intuitionistic fuzzy logic controller Defuzzification 

Mathematics Subject Classification



Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agarwal, M., Biswas, K.K., Hanmandlu, M.: Probabilistic intuitionistic fuzzy rule based controller. ICARA, 214–219 (2011)Google Scholar
  2. 2.
    Akram M., Dudek W.A.: Intuitionistic fuzzy hypergraphs with applications. Inf. Sci. 218, 182–193 (2013)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Alcalá R., Casillas J., Cordón O., González A., Herrera F.: A genetic rule weighting and selection process for fuzzy control of heating, ventilating andair conditioning systems. Eng. Appl. Artif. Intell. 18, 279–296 (2005)CrossRefGoogle Scholar
  4. 4.
    Angelov P.: Crispification: defuzzification over intuitionistic fuzzy sets. Bull. Stud. Exch. Fuzziness Appl. (BUSEFAL) 64, 51–55 (1995)Google Scholar
  5. 5.
    Atanassov, K.T.: Intuitionistic fuzzy sets, VII ITKR’s session, Sofia. Deposed in Central Science—Technology Library of Bulgaria Academy of Science, 1697/84 (in Bulgarian) (1983)Google Scholar
  6. 6.
    Atanassov K.T., Gargov G.: Elements of intuitionistic fuzzy logic. Part I. Fuzzy Sets Syst. 95(1), 39–52 (1998)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Atanassov, K.T.: Intuitionistic Fuzzy Sets: Theory and Applications, Studies in Fuzziness and Soft Computing. Physica-Verlag Heidelberg/New York (2012)Google Scholar
  8. 8.
    Ban, A.I.: Nearest interval approximation of an intuitionistic fuzzy number. In: Reusch, B. (eds.) Computational Intelligence, Theory and Applications, pp. 229–240. Springer, New York (2006)Google Scholar
  9. 9.
    Chen S.J., Hwang C.L.: Fuzzy Multiple Attribute Decision Making. Springer Verlag, Berlin/Heildelberg/New York (1992)CrossRefzbMATHGoogle Scholar
  10. 10.
    Ganesh M.: Introduction to Fuzzy Sets and Fuzzy Logic. Prentice Hall of India, New Delhi (2006)Google Scholar
  11. 11.
    Isizoh A.N., Okide S.O., Anazia A.E., Ogu C.D.: Temperature control system using fuzzy logic technique. Int. J. Adv. Res. Artif. Intell. 1(3), 27–31 (2012)Google Scholar
  12. 12.
    Lin, Y., Zhou, X., Gu, S., Wang, S.: The Takagi-Sugeno intuitionistic fuzzy systems are universal approximators. In: 2nd international conference on consumer electronics, communications and networks (2012)Google Scholar
  13. 13.
    Parvathi R., Malathi C., Akram M., Atanassov K.T.: Intuitionistic fuzzy linear regression analysis. Fuzzy Optim. Decis. Mak. 12, 215–229 (2013)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Pedrycz W.: Fuzzy control and fuzzy systems. Research studies. Press/John Wiley, New York (1993)Google Scholar
  15. 15.
    Su, X., Shi, P., Wu, L., Song, Y.-D.: A novel control design on discrete-time Takagi-Sugeno fuzzy systems with time-varying delays. IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2012.2226941
  16. 16.
    Su X., Shi P., Wu L., Song Y.-D.: A novel approach to filter design for T–S fuzzy discrete-time systems with time-varying delay. IEEE Trans. Fuzzy Syst. 20(6), 1114–1129 (2012)CrossRefGoogle Scholar
  17. 17.
    Zadeh L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Zadeh L.A.: The concept of linguistic variable and its application to approximate reasoning I. Inf. Sci. 8, 199–249 (1975)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Zadeh L.A.: The concept of linguistic variable and its application to approximate reasoning II. Inf. Sci. 8, 310–357 (1976)Google Scholar
  20. 20.
    Zimmermann H.-J.: Fuzzy set theory and its applications. Springer, New York (2012)Google Scholar
  21. 21.
    Zou L., Liu X., Ruan D., Xu Y.: Linguistic truth-valued intuitionistic fuzzy algebra. Multiple Val. Logic Soft Comput. 18(5–6), 445–456 (2012)MathSciNetGoogle Scholar
  22. 22.
    Zou L., Li W., Xu Y.: Six-element linguistic truth-valued intuitionistic reasoning in decision making. ISNN 1, 266–274 (2008)Google Scholar

Copyright information

© Springer Basel 2013

Authors and Affiliations

  • Muhammad Akram
    • 1
  • Saadia Shahzad
    • 1
  • Arif Butt
    • 1
  • Abdul Khaliq
    • 1
  1. 1.Punjab University College of Information TechnologyUniversity of the PunjabLahorePakistan

Personalised recommendations