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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/6890
Title: Application of neural network based control strategies to binary distillation column
Authors: Singh A.K.
Tyagi B.
Kumar V.
Published in: Control Engineering and Applied Informatics
Abstract: This paper presents three different neural network based control schemes to the control of the Distillate composition of binary distillation column. The main goal is to control a single output variable, the Distillate composition, by changing two manipulated input variables, reflux flow rate and steam flow rate. A first-principle equation based model of binary distillation column is developed in SIMULINK┬« and validated by the experimental results. This model is used here as a reference model on which the developed neural control schemes have been applied. Three approaches Neural Network based Direct Inverse control (NN-DIC), Neural network based model reference adaptive control (NN-MRAC) and Neural network based internal model control (NN-IMC), are simulated and their performances are assessed. Comparison was also made with conventional PID cascade control. The results demonstrate that NN-IMC strategy provides a better performance than PID, NN-DIC and NN-MRAC for the cases analyzed.
Citation: Control Engineering and Applied Informatics (2013), 15(4): 47-57
URI: http://repository.iitr.ac.in/handle/123456789/6890
Issue Date: 2013
Keywords: Direct inverse control (DIC)
Distillation column
Feed forward networks (FFN)
Internal model control (IMC)
Model reference adaptive control (MRAC)
ISSN: 14548658
Author Scopus IDs: 56330906800
7005609418
57202530521
Author Affiliations: Singh, A.K., Electrical Engineering Department, Indian Institute of Technology, Roorkee, India
Tyagi, B., Electrical Engineering Department, Indian Institute of Technology, Roorkee, India
Kumar, V., Electrical Engineering Department, Indian Institute of Technology, Roorkee, India
Corresponding Author: Singh, A.K.; Electrical Engineering Department, Indian Institute of Technology, Roorkee, India; email: akschauhan.amit@gmail.com
Appears in Collections:Journal Publications [EE]

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