Fuzzy Identification of Systems and Its Applications to Fault Diagnosis Systems

Abstract This paper describes a method to build a fuzzy model of a Fault Diagnosis System using fuzzy implications and reasoning. The identification mechanism is a neurofuzzy adaptive model. We use this method to construct a Sugeno fuzzy model of a plant Finally we use this model for building a decision system for model-based fault diagnosis, using parity equations fault diagnosis method. A simple simulated case has been used to prove its performance.

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