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Artificial Neural Network Control of Chemical Processes
السیطرة على العملیات الكیمیاویة بطریقة الشبكة العصبیة الاصطناعیة

Author: Duraid Fadhil Ahmed
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2014 Volume: 32 Issue: 1 Part (A) Engineering Pages: 176-196
Publisher: University of Technology الجامعة التكنولوجية


This paper presents an artificial neural network based control scheme for studying the control of continuous stirred tank reactor, distillation column and neutralization process and this method is compared with conventional proportional- /integral-derivative controller. A multi-layer back-propagation neural network isemployed to model the nonlinear relationships between the inputs variables and controlled variables of processes in order to regulate the manipulating variables to a variety of operating conditions and acquire a more flexible learning ability. The robustness of this control structure is studied in the case of setpoint changes andload disturbances. The experimental results suggest that such neural controllers can provide excellent setpoint-tracking and disturbance rejection. The neural network based control has higher speed of response and the offset has a smaller average value than that of the conventional controller. The control action based on the neural network controller shows less oscillation and an improvement in the controlled variables stabilization time with respect to the conventional controllerand gives a better control performance.

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