TY - JOUR ID - 574 TI - A New Recurrent Fuzzy Neural Network Controller Design for Speed and Exhaust Temperature of a Gas Turbine Power Plant JO - AUT Journal of Modeling and Simulation JA - MISCJ LA - en SN - 2588-2953 AU - Fakharian, A. AU - Mosaferin, R. AU - Menhaj, M. B. AD - Assistant Professor, Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran AD - Department of Mechatronics Engineering, South Branch, Islamic Azad University, Tehran, Iran AD - Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran Y1 - 2014 PY - 2014 VL - 46 IS - 2 SP - 23 EP - 30 KW - Recurrent fuzzy-neural network (RFNN) KW - Gas turbine KW - Neural Network KW - Direct Control Model DO - 10.22060/miscj.2014.574 N2 - In this paper, a recurrent fuzzy-neural network (RFNN) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. Since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command signal and inlet guide vane position. Also practical limitations are applied to system inputs. In addition, demand power and ambient temperature are considered as disturbance. Simulation results show the effectiveness of proposed controller in comparison with other conventional methods such as Model Predictive Control (MPC) and H∞ control in a same operating condition UR - https://miscj.aut.ac.ir/article_574.html L1 - https://miscj.aut.ac.ir/article_574_174b6b34c74ab629ea1a2a32c85f4086.pdf ER -