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2006 | 16 | 1 | 37-49
Tytuł artykułu

What is not clear in fuzzy control systems

Autorzy
Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a number of unclear, unsolved or partly solved problems of fuzzy logic, which hinder precise transformation of expert knowledge about proper control of a plant in a fuzzy controller. These vague problems comprise the realization of logical and arithmetic operations and another basic problem, i.e., the construction of membership functions. The paper also indicates how some of the above problems can be solved.
Rocznik
Tom
16
Numer
1
Strony
37-49
Opis fizyczny
Daty
wydano
2006
otrzymano
2005-09-19
poprawiono
2006-02-04
Twórcy
  • Faculty of Computer Science and Information Technology, Szczecin University of Technology, ul. Żołnierska 49, 71-210 Szczecin, Poland
Bibliografia
  • Borgelt Ch. and Kruse R. (2003): Learning possibilistic graphical models from data. - IEEE Trans. Fuzzy Syst., Vol. 11, No. 2, pp. 159-172.
  • Civanlar M.R. and Trussel H.J. (1986): Constructing membership functions using statistical data. - Fuzzy Sets Syst., Vol. 18,No. 1, pp. 1-13.
  • Devi B.B. and Sarma V.V.S. (1985): Estimation of fuzzy memberships from histograms. - Inf. Sci., Vol. 35, No. 1, pp. 43-59.
  • Driankov D., Hellendoorn H. and Reinfrank M. (1993): An introductionto fuzzy control. - Berlin, Heidelberg, Springer-Verlag.
  • Dubois D. and Prade H. (1983): Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms. - Fuzzy Sets Syst., Vol. 10, No. 1, pp. 15-20.
  • Dubois D. and Prade H. (1986): Possibility Theory. - New York, London: Plenum Press.
  • Dubois D., Foulloy L. and Mauris G. (2004): Probability - Possibility transformations, triangular fuzzy sets, and probabilistic inequalities. - Reliable Computing, Vol. 10, No. 4, pp. 273-297.
  • Kaufmann A. and Gupta M.M. (1991): Introduction to Fuzzy Arithmetic. - New York: Van Nostrand Reinhold.
  • Kosiński W., Prokopowicz P. and Ślązak D. (2003): On algebraic operations on fuzzy reals, In: Neural Networks and Soft Computing (Rutkowski L., Siekmann J.,Tadeusiewicz R., Zadeh L.A., Eds.).- Heidelberg: Physica Verlag, pp. 54-61.
  • Piegat A. (2001): Fuzzy Modeling and Control. - Heidelberg: Physica Verlag.
  • Piegat A. (2005): A new definition of the fuzzy set. - Appl.Math. Comput. Sci., Vol. 15, No. 1, pp. 125-140.
  • Rakus-Anderson E. (2003): The Newton interpolation method with fuzzy numbers as the entries, In: Neural Networks and Soft Computing (Rutkowski L., Siekmann J.,Tadeusiewicz R., Zadeh L.A., Eds.) - Heidelberg: Physica Verlag, pp. 310-315.
  • Yager R.R. and Filev D. (1994): Essentials of Fuzzy Modeling and Control. - New York: Wiley.
  • Von Altrock C. (1995): Fuzzy Logic. - Muenchen: R. Oldenburg Verlag.
  • Zadeh L.A. (1978): Fuzzy sets as a basis for a theory of possibility. - Fuzzy Sets Syst., Vol. 1, No. 1, pp. 3-28.
  • Zhou C. (2002): Fuzzy-arithmetic-based Lyapunov synthesis to the design of stable fuzzy controllers: Computing with Words approach. - Appl. Math.Comput. Sci., Vol. 12, No. 3, pp. 411-422.
  • Zimmermann H.J. and Zysno P. (1980): Latent connectives in human decision making. - Fuzzy Sets Syst., Vol. 4, No. 1, pp. 37-51.
  • Zimmermann H.J. (1991): Fuzzy Set Theory and Its Applications. - Boston: Kluwer.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv16i1p37bwm
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