A Learning Algorithm of Fuzzy Model Based on Improved Fuzzy Clustering and QR Decomposition

In this paper, we proposed a learning algorithm for fuzzy modeling based on the improved fuzzy clustering method and QR decomposition. The improved fuzzy clustering method is confirmed by using a new objective function, which includes the influence on the input variables and the output variables exerting the input space of fuzzy model. Fuzzy inference matrix acquired from improved fuzzy clustering method is analyzed on the basis of QR decomposition of matrix. According to analyzing the redundancy of the matrix, the structure of fuzzy system is confirmed in the paper. The structure and parameters of fuzzy model are estimated by means of the proposed algorithm. We demonstrate the performance of the proposed algorithm by using the simulating result of the nonlinear system