A Fuzzy Clustering Approach for TS Fuzzy Model Identification

摘要

In this paper, a fuzzy clustering approach for TS fuzzy model identification is presented. In the proposed method, the modified mountainx clustering algorithm is employed to determine the number of clusters. Secondly, the fuzzy c-regression model (FCRM) algorithm is used to obtain an optimal fuzzy partition matrix. As a result, the initial parameters can be determined by the optimal fuzzy partition. Finally, gradient descent algorithm is adopted to precisely adjust premise parameters and consequent parameters simultaneously. The simulation results reveal that the proposed algorithm can model an unknown system with a small number of fuzzy rules.