Power system stabilizer based on a self-learning adaptive network fuzzy inference system

Abstract

Application of a self-learning adaptive network-based fuzzy inference system as a power system stabilizer (PSS) is described in this paper. A multilayer adaptive network is employed to design the fuzzy logic controller with self-learning capability that does not require another controller to tune the fuzzy inference rules and membership functions. Details of the design process are given. Behaviour of the proposed PSS, investigated under different operating conditions and disturbances in both simulation and real-time tests, illustrates its effectiveness in providing enhanced damping of the power system oscillations.