Advertisement

Clustering Methods in Fuzzy Control

  • F. Klawonn
  • R. Kruse
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Summary

Fuzzy controllers can be interpreted as an interpolation technique on the basis of fuzzy clusters of input/output pairs. It is therefore obvious that fuzzy clustering algorithms are a promising tool for supporting the design of a fuzzy controller when data of the process to be controlled are available.

This paper discusses the possibilities and limitations of fuzzy clustering for fuzzy control

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. BEZDEK, J.C. (1973): Fuzzy Mathematics in Pattern Classification. Ph.D. Dissertation, Appl. Math., Cornell Univ., Ithaca, NY.Google Scholar
  2. BEZDEK, J.C., and PAL, S.K. (1992): Fuzzy Models for Pattern Recognition. IEEE Press, New York.Google Scholar
  3. DUBOIS, D., and PRADE, H. (1988): Possibility Theory. Plenum Press, New York.Google Scholar
  4. DUBOIS, D., and PRADE, H. (1993): Possibility Theory, Belief Revision and Non-Monotonic Logic. Proc. EUFIT’93, Aachen, 714–719.Google Scholar
  5. DUNN, J.C. (1974): A Fuzzy Relative of the ISODATA Process and its Use in Detecting Compact Well-Separated Clusters. Journal of Cybernetics, 3, 32–57. CrossRefGoogle Scholar
  6. HÖHLE, U., and KLAWONN, F. (1992): Fuzzy Control und Ununterscheidbarkeit. Proc. VDE-Fachtagung Technische Anwendungen von Fuzzy-Systemen, Dortmund, 3–9.Google Scholar
  7. KLAWONN, F. (1994): Fuzzy Sets and Vague Environments. Fuzzy Sets and Systems (to appear).Google Scholar
  8. KLAWONN, F., and KRUSE, R. (1993): Equality Relations as a Basis for Fuzzy Control. Fuzzy Sets and Systemsj 54, 147–156 CrossRefGoogle Scholar
  9. KLAWONN, F., and KRUSE, R. (1993): Fuzzy Control as Interpolation on the Basis of Equality Relations. Proc. 2nd IEEE International Conference on Fuzzy Systems 1993, IEEE, San Francisco, 1125–1130.Google Scholar
  10. KRISHNAPURAM, R., and KELLER, J.M. (1993): A Possibilistic Approach to Clustering.IEEE Transactions on Fuzzy Systems, 1, 98–110. CrossRefGoogle Scholar
  11. KRUSE, R., GEBHARDT, J., and KLAWONN, F. (1993): Fuzzy-Systeme. Teub- ner Stuttgart. (English translation: Foundations of Fuzzy Systems. Wiley, Chichester, 1994).Google Scholar
  12. NAUCK, D., KLAWONN, F., and KRUSE, R. (1994): Neuronale Netze und Fuzzy Systeme: Grundlagen des Konnektionismus, Neuronaler Netze und der Kopplung mit wissensbasierten Methoden. Vieweg, Braunschweig.Google Scholar
  13. TRILLAS, E., and VALVERDE, L. (1984): An Inquiry into Indistinguishability Operators. In: H.J. Skala, S. Termini, E. Trillas (eds.): Aspects of Vagueness. Reidel, Dordrecht, 231–256CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1996

Authors and Affiliations

  • F. Klawonn
    • 1
  • R. Kruse
    • 1
  1. 1.Department of Computer ScienceUniversity of BraunschweigBraunschweigGermany

Personalised recommendations