Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 141-143.doi: 10.11896/j.issn.1002-137X.2017.11A.029

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Interval Type 2 Fuzzy System Identification Using NT Type Reduction Algorithm

WANG Zhe   

  • Online:2018-12-01 Published:2018-12-01

Abstract: KM is a commonly used algorithm for interval type 2 fuzzy sets type reduction,which has the weakness of low efficiency,thus it is difficult to be used for online identification and control.A simplified interval type 2 fuzzy system identification method was proposed in this article.The method uses type 2 T-S fuzzy model,the premise fuzzy set of which is interval type 2 fuzzy sets and the consequent parameter is the same as type 1 T-S fuzzy model.A simplified type reduction algorithm was used in this article instead of KM algorithm.The simulation shows that the simplified method can improve identification efficiency without reducing identification accuracy and can be used for real time identification and control.

Key words: Interval type 2 fuzzy sets,KM type reduction,T-S fuzzy system,Fuzzy identification

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