Modeling pH neutralization processes using fuzzy satisfactory clustering

A fuzzy satisfactory clustering algorithm is presented in this paper. It starts with 2 duster centers and increases new center if necessary. During clustering process, former-clustering information is fully used so that convergence speed could be quickened. A system data set can be quickly divided into several satisfactory fuzzy clusters by this algorithm. A Takagi-Sugeno (T-S) type fuzzy model can then be identified. For three typical pH processes, satisfactory simulation results are obtained. The effective performance of the modified clustering algorithm is quantitatively evaluated.