Identification method of fuzzy inference system based on improved fuzzy clustering arithmetic

An improved clustering method is presented by combining subtractive clustering and fuzzy C-means clustering(FCM) It was hoped that through a series of steps to optimize the Takagi-Sugeno(T-S) model structure and realized the identification of nonlinear systems. The first to use subtraction initial cluster of input space, get few rules and the initial cluster centers, with improved FCM clustering algorithm further optimize the centers; Then using the least square method draw conclusions model parameters to achieve the identification of nonlinear systems. The simulation results of the famous Box-Jenkins gas furnace show the effectiveness of the improved method.