A FLN artificial neural network based fuzzy controller for generator excitation control

A new methodology based on a functional link net (FLN) artificial neural network is introduced for excitation control of a synchronous generator based on a fuzzy power system stabilizer (FPSS). This method combines the advantages of the fuzzy controller along with the independence from model identification and fast processing of artificial neural network (ANN) and proposes new form of excitation controller for a synchronous generator. The delta-rule was used for training of the ANN. The ANN was trained for different load patterns which were produced by FPSS, and was continued until the total error was smaller that certain value. The analysis of a three-phase short circuit fault condition under various loading conditions of a single machine infinite bus system is presented to illustrate the application of the developed methodology. The obtained results show that the proposed FLN artificial neural network based on fuzzy controller for power system stabilizer (PSS) can provide very good damping characteristic through a wide range of operating conditions for power system and it has smoother control for system variables. Hence it improves dynamic operating of the system considerably.