A self-tuning fuzzy controller via fuzzy inference network

The goal of this paper is to present a method of designing self-tuning fuzzy logic controller (STFLC). The basic ideas of our proposed approach include: (1) the connectionist implementation of fuzzy logic controller uses a simplified fuzzy inference network (SFIN); (2) the initialization of the STFLC uses supervised learning control; and (3) online adaptation of the STFLC uses GPC performance index. A nonlinear plant with nonminimum phase characteristics and uncertainty is employed in our simulations. The observed results demonstrate the effectiveness of the STFLC presented