An adaptive power system stabilizer using on-line self-learning fuzzy systems

An adaptive power system stabilizer consisting of an on-line identified planet model and self-learning fuzzy logic controller, for power system stabilizer (PSS) application is described in this paper. On-line model identification is used to obtain a dynamic equivalent model for the synchronous machine with respect to the rest of the system. A fuzzy controller with self-learning capability is then used to adapt the system performance. The self-learning ability of the fuzzy controller is based on the steepest descent algorithm. The effectiveness of the proposed technique is demonstrated on a power system by simulation studies. Results obtained show improvement in the overall system damping characteristics using the proposed adaptive fuzzy PSS (AFPSS).