Fuzzy neuro-computational technique and its application to modelling and control

Abstract

The authors present a model building technique which combines the strength of the fuzzy set theory and the neural network based structures. This technique can simultaneously deal with two types of knowledge, a nonfuzzy one and a fuzzy one, which usually describe the behavior of complex processes. The proposed method can also be directly applied to the construction of a new type of intelligent fuzzy controller. Some aspects of the adequacy of this fuzzy neuro-computational model are also discussed. A numerical example is provided.<>