An integrated modeling algorithm of fuzzy model using objective function
基于目标函数的模糊模型一体化建模

For dynamic systems with complex, ill-conditioned or nonlinear characteristics, the fuzzy modeling method based on fuzzy sets is very effective to describe the properties of the systems. By using objective function, we propose a new algorithm to confirm the structure and parameters of fuzzy model for nonlinear systems. First, the structure of fuzzy model is confirmed by using Gustafson-Kessel(GK) fuzzy clustering; and then, the objective function and parameter estimation are simultaneously employed in recursive calculations to simply the model structure and delete redundant rules. The UD matrix decomposition is used to reduce the amount of computation in the determination process of fuzzy model. The simulation results demonstrate the effectiveness of the proposed method.