پديد آورنده :
اسكندرلو، عليرضا
عنوان :
بكارگيري شبكه هاي عصبي مصنوعي﴿ANNS) در مدلسازي ، شبيه سازي و كنترل برج تقطير
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
پديده هاي انتقال
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مهندسي شيمي
صفحه شمار :
هفده، 150،[II] ص: مصور، جدول، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
ارجمند مهرباني
توصيفگر ها :
روشهاي ريلاكسيشن، حل همزمان , آلگوريتم لونبرگ ماركوارت , كنترل PID , دماي متانول
تاريخ نمايه سازي :
19/3/86
استاد داور :
خارجي: محمد رضا احمدزاده داخلي: شاپور رودپيما
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتال
چكيده انگليسي :
AbstractThe most important duty of a distillation column is separation and production of productswith certain purity In this project a model for a distillation tower including 7 equilibriumstages for separation of a methanol water mixture for study on production purity controlwas developed After modeling simulation of the distillation tower was carried out andthe results are compared with experimental data in order to evaluate the accuracy ofmodeling and simulation In various applications conventional controllers such asProportional Integral Derivative PID were used widely with reasonable operation Butin processes with long delay complex and non linear have not suitable performance Neural Networks with their high learning ability and estimation of non linear functionswith high accuracy are a new method in modeling simulation and control of process Thus neural network model are used for simulation and control of distillation column Also effects of various parameters such as number of neurons in hidden layer trainingalgorithms training speed parameter number of learning data in neural network and spanof input data were studied Matrix of relative gains for distillation column was developedand based on it couples of suitable input output variables were selected Temperature ofbottom product with reboiler thermal flux and temperature of top product with refluxratio were selected as two control loops In this project for identification and control of distillation column purity neural networkcontrollers were design Levenberg Marquardt algorithm was the best method in trainingof distillation column neural network The neural network controller in comparison withthe PID controller had lower offset overshoot and response time
استاد راهنما :
ارجمند مهرباني
استاد داور :
خارجي: محمد رضا احمدزاده داخلي: شاپور رودپيما
