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a new recurrent fuzzy neural network controller design for speed and exhaust temperature of a gas turbine power plant
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نویسنده
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Fakharian A. ,Mosaferin R. ,Menhaj M. B.
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منبع
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aut journal of modeling and simulation - 2015 - دوره : 47 - شماره : 1 - صفحه:33 -40
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چکیده
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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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کلیدواژه
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recurrent fuzzy-neural network (rfnn) ,gas turbine ,neural network ,direct control model
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آدرس
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Islamic Azad University, Qazvin Branch, Department of Electrical, Biomedical and Mechatronics Engineering, ایران, Islamic Azad University, South Branch, Department of Mechatronics Engineering, ایران, amirkabir university of technology, Department of Electrical Engineering, ایران
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پست الکترونیکی
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ahmad.fakharian@qiau.ac.ir
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Authors
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