IDENTIFICATION OF DYNAMIC FUZZY MODELS

This paper discusses a new type of dynamic fuzzy model for the control of complex systems. The fuzzy model has two maps; one is a global rule map to describe the global approximation inference effects; the other is the local rule map to describe the properties of the inference rule on the local area. A simple example is given to show how the fuzzy model can be used to design a controller. An identification method is described to identify the dynamic fuzzy model. This includes the determination of the number of fuzzy rules, the structure and parameters of the local rule maps, and the estimation of the parameters in the membership functions.