Application of Feed Forward and Recurrent Neural Network Topologies for the Modeling and Identification of Binary Distillation Column

Abstract

This paper presents identification of artificial neural network model of a Binary Distillation Column (BDC). In this paper, the two most common topologies of artificial neural networks in the area of control are introduced: Feed forward neural network and recurrent neural networks. The training of neural network has been performed by the data set acquired from real 9-tray continuous BDC setup available in laboratory. The network model is composed of two layers. A hyperbolic tangent sigmoid function and a pure linear function have been utilized as activation functions in the first and the second layers, respectively. The developed neural network model has been validated by an extensive data set of practical data received from real BDC setup.

Keywords:

• Binary distillation column
• Feed forward neural network
• Identification
• Modelling
• Recurrent neural network

Additional information

Notes on contributors

Amit Kumar Singh

Amit Kumar Singh is currently working toward his Ph.D. degree in Department of Electrical Engineering at Indian Institute of Technology, Roorkee (India). His research interests include control system, process control and application of evolutionary techniques to chemical processes. E-mail: [email protected]

Barjeev Tyagi

Barjeev Tyagi received B. Tech. degree in Electrical Engineering from University of Roorkee (India) in 1987 and Ph. D. degree from IIT Kanpur in 2006. Presently, he is an Associate professor faculty member in Electrical Engineering Department at Indian Institute of Technology, Roorkee (India). His research interests include control system, power system deregulation, power system optimization and control. E-mail: [email protected]

Vishal Kumar

Vishal Kumar received the Ph.D. degree in power system engineering from the Indian Institute of Technology, Roorkee, India, in 2007. Currently, he is an Assistant professor in the Department of Electrical Engineering, Indian Institute of Technology, Roorkee, India. His research interests include power distribution system operation and protection, and digital design and verification. E-mail: [email protected]