a new recurrent fuzzy neural network controller design for speed and exhaust temperature of a gas turbine power plant

نویسندگان

a. fakharian

r. mosaferin

m. b. menhaj

چکیده

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

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عنوان ژورنال:
amirkabir international journal of modeling, identification, simulation & control

ناشر: amirkabir university of technology

ISSN 2008-6067

دوره 46

شماره 2 2014

میزبانی شده توسط پلتفرم ابری doprax.com

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