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Defuzzification with Constraints

  • Ronald R. Yager
  • Dimitar P. Filev
Part of the Theory and Decision Library book series (TDLD, volume 16)

Abstract

We look at the problem of defuzzification in situations where in addition to the usual fuzzy output of the controller there exists some ancillary restriction on the allowable defuzzified values. We provide two basic approaches to address this problem. In the first approach we enforce the restriction by selecting the defuzzified value through a random experiment in which the only values which have nonzero probabilities are in the allowable region, this method makes use of a nonmonotonic conjunction operator. In the second approach we convert the problem to one of constraint optimization.

Keywords

Membership Function Fuzzy Logic Controller Fuzzy Subset Nonlinear Programming Problem Output Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1].
    Filev, D. and Yager, R. R., “A generalized defuzzification method under BAD distributions,” International Journal of Intelligent Systems 6, 687–697, 1991.CrossRefzbMATHGoogle Scholar
  2. [2].
    Yager, R. R. and Filev, D. P., “On the issue of defuzzification and selection based on a fuzzy set,” Fuzzy Sets and Systems 55, 255–272, 1993.CrossRefzbMATHMathSciNetGoogle Scholar
  3. [3].
    Yager, R. R., “On the use of combinability functions for intelligent defuzzification,” Proceedings Joint Fourth IEEE Conference on Fuzzy Systems and EFES, Yokohoma, (To Appear).Google Scholar
  4. [4].
    Pfluger, N., Yen, J. and Langari, R., “A defuzzification strategy for a fuzzy logic controller employing prohibitive information in command formulation,” Proceedings First IEEE Conference on Fuzzy Systems, 1991.Google Scholar
  5. [5].
    Yager, R. R., “Nonmonotonic set theoretic operations,” Fuzzy Sets and Systems 42, 173–190, 1991.CrossRefzbMATHMathSciNetGoogle Scholar
  6. [6].
    Alsina, C., Trillas, E. and Valverde, L., “On some logical connectives for fuzzy set theory,” J. Math Anal. & Appl. 93, 15–26, 1983.CrossRefzbMATHMathSciNetGoogle Scholar
  7. [7].
    Dubois, D. and Prade, H., “A review of fuzzy sets aggregation connectives,” Information Sciences 36, 85–121, 1985.CrossRefzbMATHMathSciNetGoogle Scholar

Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Ronald R. Yager
    • 1
  • Dimitar P. Filev
    • 1
  1. 1.Machine Intelligence InstituteIona CollegeNew RochelleUSA

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