بر اساس كنترل كننده فازي براي كنترل تحريك ژنراتور FLN كنترل كننده تحريك شبكه عصبي مصنوعي

Generator Excitation Control Using FLN Artificial Neural Network Controller

A new methodology based on a functional link net (FLN) artificial neural network (ANN) is introduced for excitation control of a synchronous generator based on fuzzy power system stabilizer (FPSS). This method combines the advantages of the fuzzy controller along with the independence from model identification and fast processing ANN and proposes a new form of excitation controller for a synchronous generator. Delta-rule is used for training of ANN. ANN is trained for different load patterns which are produced by FPSS, and is continued until the total error was smaller than 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 wide rang of operating conditions for power system and it has smoother control for system variables; hence it improves dynamic operating of the system considerably.