FCM clustering algorithm for T-S fuzzy model identification

An approach for building T-S fuzzy model is proposed based on fuzzy c-mean clustering algorithm on the basis of nonlinear modeling experience. An alternative T-S fuzzy model is adapted, which has the uniformed premise structure, the premise parameter is decided by fuzzy c-mean clustering algorithm and the consequence parameters is calculated by least square algorithm, and the identification precision is enhanced. Finally the effectiveness and practicability of this method is demonstrated by the simulation result of Box-Jenkins gas furnace data and Mackey-Glass chaos time series.