Identification of fuzzy relational model and its application to control

Soo Yeong Yi, Myung Jin Chung

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

In the case of control systems where physical mechanisms are not well known due to high complexity and nonlinearity, a fuzzy relational model may be useful. In this paper, we propose a recursive parameter tuning algorithm for the identification of fuzzy relational model for an unknown dynamic system. Furthermore, using the fact that a dynamic system is represented by the relational strength between a few reference input and output fuzzy sets in the fuzzy relational model, we construct a control input fuzzy set inducing a desired output fuzzy set by calculating the possibility between the model output and the desired output fuzzy set for the control purpose. Simulation results show the usefulness of the proposed identification and control algorithms.

Original languageEnglish
Pages (from-to)25-33
Number of pages9
JournalFuzzy Sets and Systems
Volume59
Issue number1
DOIs
StatePublished - 11 Oct 1993

Keywords

  • Fuzzy relational model
  • max-product operation
  • possibility
  • recursive least square method
  • unknown dynamic system

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