Quasinonlinear-fuzzy-model-based fuzzy identification for complex systems

In this paper, a new Quasinonlinear Fuzzy Model(QNFM) is presented to overcome the diffi-culty of the identification of complex systems using the first order Takagi-Sugeno model. The structure of the fuzzy model is based on the first order Takagi-Sugeno model, then a nonlinear map is carried out. The present-ed fuzzy model has the advantages of high identification accuracy and good generalization performance. The structure of the fuzzy model is identified by the modified FCM fuzzy clustering technique, compared with oth-er existing methods, the procedure for finding the optimal structure of the fuzzy model is simplified. The sim-ulation results show that this method is very efficient.