Modeling pH neutralization processes using fuzzy satisfactory clustering

A fuzzy satisfactory clustering algorithm is presented in this paper. It starts with two cluster centers and increases a new center if necessary. During the clustering process, the former clustering information is fully used so that the convergence rate can be speed up. A system data set can be quickly divided into several satisfactory fuzzy clusters by this algorithm. A Takagi-Sugeno 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