The Application of Adaptive Fuzzy Inference Model in the Nonlinear Dynamic System Identification

As the selection of the membership function affects the performance of fuzzy control system in the modeling of adaptive fuzzy inference, a kind of Gaussian-type membership function is proposed in this paper. It can change the shape of membership function adaptively with the changes of the system parameters, then the establishment of adaptive fuzzy inference model is completed. The structure of adaptive fuzzy inference system and the program of parameters adjustment have been designed, using gradient descent algorithm to learn the parameters of the model and applying adaptive fuzzy inference model to nonlinear dynamic system identification, the simulation shows the effective of the model.