Implementation of neural control for neutralization process

مقدم أطروحة جامعية

Abd al-Karim, Dirar Isam

مشرف أطروحة جامعية

Butrus, Karimah M.

الجامعة

الجامعة التكنولوجية

الكلية

-

القسم الأكاديمي

قسم الهندسة الكيمياوية

دولة الجامعة

العراق

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2009

الملخص الإنجليزي

The dynamic behavior of neutralization process in (CSTR) was studied theoretical and experimental and the process control was implemented using different control strategies, conventional feedback control, and neural network (NARMA-L2, NN Predictive) control.

For acetic acid / caustic soda.

The system transient responses to one type of perturbation in feed flow rate: step.

Step testing approximation is used for predicting a transfer function of the neutralization process, a good agreement is obtained between the simulated and experimental responses of the dynamic model for the pH neutralization system in open loop.

The optimum tuning of Control Parameters were found by two different methods ; Frequency curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method.

PI and PID controls were implemented as control strategies in this work.

Artificial neural network is the best method to control on neutralization process and it better than the conventional method because the mean square error is lower.

And we use two different control strategies in neural network (NARMA-L2, NN Predictive) control.

For all cases, the NARMA-L2 controller can be a preferable method for control purposes because it has smaller value of mean square error (MSE).

MATLAB program is used as a tool of solution for all cases used in this work.

التخصصات الرئيسية

الكيمياء

الموضوعات

• الشبكات العصبية(الحاسبات الإلكترونية)

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-305299