No abstract

A fuzzy logic based Power System Stabilizer (PSS) with learning ability is proposed in this paper. The proposed PSS employs a multilayer adaptive network. The network is trained directly from the input and the output of the generating unit. The algorithm combines the advantages of the Artificial Neural Networks (ANNs) and Fuzzy Logic Control (FLC) schemes. Studies show that the proposed Adaptive-Network-Based Fuzzy Logic PSS (ANF PSS) can provide good damping of the power system over a wide range of operating conditions and improve the dynamic performance of the system.

No abstract

No 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.