A new cluster validity criterion for fuzzy c-regression model and its application to T-S fuzzy model identification

This paper proposes a new cluster validity criterion designed for the fuzzy c-regression model (FCRM) clustering algorithm. The proposed cluster validity criterion is utilized to determine the appropriate number of clusters in the FCRM. A systematic procedure for the T-S fuzzy model identification is proposed based on the FCRM accompanied with the new cluster validity criterion. Simulation results show that for a given nonlinear system, the proposed algorithm can effectively and accurately obtain a T-S fuzzy model for it.