Identification of fuzzy models
Easter Tan, Gilles Mourot, Didier Maquin, José Ragot · 1994
The objective of this work is to describe a numerical technique to identify parameters of a fuzzy model. When this model and the membership functions of the input variables are continuously differentiable, we show that the estimation of parameters can be performed with a two-levels hierarchical algorithm, comprising the estimation of the model parameters and the estimation of the membership functions parameters. The proposed algorithm is then applied to an example describing a non-linear system. KEYWORDS Fuzzy model, identification, parameter estimation. 1. INTRODUCTION Building of fuzzy models can be applied to fuzzy control and to modeling of complex systems. Moreover, the implementation of a fuzzy logic controller involves the design of linguistic rules to compute the command to be applied on a process according to the measurement of the position error. In simple situations, these rules can be derived from those of a conventional PID controller ; on the other hand, for non-linear ...