Quasinonlinear-Fuzzy-Model-Based Fuzzy Identification for Complex Systems
Zhang Pinga · Control theory & applications · 1998
In this paper,a new Quasinonlinear Fuzzy Model(QNFM) is presented to overcome the difficulty of the identification of complex systems using the first order Takagi-Sugeno model. The structure of thefuzzy model is based on the first order Takagi-Sugeno model,then a nonlinear map is carried out. The presented fuzzy model has the advantages of high identification accuracy and good generalization performance. Thestructure of the fuzzy model is identified by the modified FCM fuzzy clustering technique,compared with other existing methods,the procedure for finding the optimal structure of the fuzzy model is simplified. The simulation results show that this method is very efficient.