Higher order fuzzy system identification using subtractive clustering

摘要: This paper proposes a higher order fuzzy system identification method using subtractive clustering, which is an extended application of clustering. Minimum error models are obtained through enumerative search clustering parameters. The results the study presented in this explain mechanism behind and introduce modification penalizing process applying modeling to both linear non-linear systems given paper. comparison with other shows improvement performance by technique. resulted fewer rules compared lower models. Results case studies on different complexities also presented.