TRADE‐OFF BETWEEN APPROXIMATION ACCURACY AND COMPLEXITY FOR TS FUZZY MODELS
Péter Bárányi, Péter Köröndi, Ron J. Patton, Hideki Hashimoto · Asian Journal of Control · 2004
ABSTRACT This paper proposes a transformation method that serves the trade‐off between the modelling complexity and accuracy of multi‐variable Takagi‐Sugeno fuzzy inference operator‐based modelling (TS fuzzy modelling). The relation between the number of fuzzy rules and the modelling accuracy is defined in the paper. The proposed transformation method is capable of finding the minimal number of fuzzy rules for a given accuracy of a given TS fuzzy model. A case study, focusing on a benchmark problem of fault diagnosis, developed in the framework of EC‐founded Research Training Network DAMADICS, of an actuator in a sugar factory, is presented to provide feasibility of the proposed method.