<title>Design of a robust and adaptive fuzzy-logic-based power system stabilizer (RAFLPSS) for damping low frequency electromechanical oscillations</title>

Abstract

This paper presents a design procedure for a Robust and Adaptive Fuzzy Logic based Power System Stabilizer (RAFLPSS) to improve the small signal stability of Power System. The parameters of RAFLPSS are tuned by adaptive neural network. This RAFLPSS uses ANFIS network (Adaptive Network based Fuzzy Inference System) which provides a natural framework of multi-layered feed forward adaptive network using fuzzy logic inference system. In this approach, the hybrid-learning algorithm tunes the fuzzy rules and the membership functions of the RAFLPSS. The dynamic performance of SMIB system with the proposed RAFLPSS under different operating conditions and change in system parameters has been investigated. The simulation results obtained from the conventional PSS (CPSS) and Fuzzy logic based PSS (FPSS) are compared with the proposed RAFLPSS. The simulation results demonstrate that the proposed RAFLPSS performs well in damping and quicker response when compared with the other two PSSs.