A C-means clustering based fuzzy modeling method

Proposes a neuro-fuzzy method to model the dynamic behavior of complex systems based on real experimental data. First, we investigate the firing strength of rules by a fuzzy C-means clustering method. Then, we retrieve the membership functions of input variables by a neuro-fuzzy network. Finally, we identify the parameters of linear local models by recursive least squares. In particular, we applied this method to construct the dynamics of a boiler combustion process.