Our objective in this paper is to 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. The training of such system was applied until now, to supports of rule propositions with single distribution such that they can be termed 1-way adaptive. 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 readjusts these parameters so as to minimize uncertainty based on possibility function values.