Intuitionistic, 2-way adaptive fuzzy control

We develop a 2-way adaptive fuzzy control system that makes use of the intuitionistic fuzzy sets for modeling expert knowledge bearing uncertainty. Adaptive fuzzy control systems are fuzzy logic systems whose rule parameters are automatically adjusted through training. In our system, all supports to propositions have interval valued distributions with necessity at the lower bound and possibility at the upper. Uncertainty in expert knowledge determines the width of the interval. Our first level training tunes rule parameters with necessity function values, while the second level training re-adjusts these parameters so as to minimize uncertainty based on possibility function values. The intuitionistic 2-way adaptive fuzzy controller is found to have a better performance due to the richness of information in interval valued supports with nonantagonistic bounds opposed to antagonistic ones in ordinary fuzzy sets