Learning issues in model reference based fuzzy control

Abstract

The question of learning in fuzzy model reference learning control (FMRLC) is investigated and it is proposed that the extent and importance of learning may potentially be less than has been claimed previously. An alternative view of FMRLC, incorporating proportional plus integral action in place of the updating mechanism of the fuzzy logic controller, and which has similarities with a form of linear high-gain robust control, is presented. The two approaches are applied to two nonlinear problems, discussed previously in the literature, and the results compared. It is concluded that although FMRLC, as applied to these two examples, is an effective form of control, it does not recall previously learned control behaviour as claimed.