Antecedent validity adaptation principle for fuzzy systems tuning

This paper proposes an antecedent validity adaptation (AVA) principle for fuzzy systems tuning. It is suggested that the fuzzy rules may be updated with respect to the validity of antecedents. This adaptation principle agrees with the human intuition and fuzzy logic reasoning. The principle is first applied to table look-up (TL) scheme to model recorded data; an on-line fuzzy identification algorithm is also proposed. Next, the principle is applied to fuzzy clustering algorithm. These methods are successfully applied to model nonlinear systems.