CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Soft Sensor based on Adaptive Linear Network for Distillation Process

by Asha Rani, Vijander Singh, J. R. P Gupta
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 36 - Number 1
Year of Publication: 2011
Authors: Asha Rani, Vijander Singh, J. R. P Gupta
10.5120/4458-6244

Asha Rani, Vijander Singh, J. R. P Gupta . Soft Sensor based on Adaptive Linear Network for Distillation Process. International Journal of Computer Applications. 36, 1 ( December 2011), 39-45. DOI=10.5120/4458-6244

@article{ 10.5120/4458-6244,
author = { Asha Rani, Vijander Singh, J. R. P Gupta },
title = { Soft Sensor based on Adaptive Linear Network for Distillation Process },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 36 },
number = { 1 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 39-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume36/number1/4458-6244/ },
doi = { 10.5120/4458-6244 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:22:02.176629+05:30
%A Asha Rani
%A Vijander Singh
%A J. R. P Gupta
%T Soft Sensor based on Adaptive Linear Network for Distillation Process
%J International Journal of Computer Applications
%@ 0975-8887
%V 36
%N 1
%P 39-45
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main objective in refining units is to keep the product quality within specifications in the faces of disturbances. Online measurements of product composition using composition analyser are neither easy nor economically viable. In an effort to overcome these difficulties various soft sensors are designed in the recent years. In this research work, the authors have proposed the design of neural network based soft sensor for two types of chemical processes i.e. reactive distillation process and multicomponent distillation process. The designed soft sensor is based on adaptive linear network, Adaline and is used to infer the product composition from the temperature profile of the respective processes. For a comparative study Levenberg Marquardt based artificial neural network soft sensor is also designed. It is observed from the results that the Adaline based soft sensor is more efficient in comparison to LM based ANN soft sensor in terms of accuracy, time taken for training and memory usage.

References
  1. Vijander Singh, Indra Gupta and H.O. Gupta, 2005, ANN Based Estimator for Distillation-Inferential Control, Chemical Engineering and Processing, vol.44, Issue 7, pp. 785-795, July 2005.
  2. Vijander Singh, Indra Gupta and H.O. Gupta, 2007, ANN Based Estimator for Distillation using Levenberg-Marquardt Approach, special issue on Applications of Artificial Intelligence in Process Systems Engineering, Engineering Applications of Artificial Intelligence, Elsevier Science, vol.20, pp.249-259, 2007.
  3. Pierantonio Facco, Franco Doplicher, Fabrizio Bezzo, Massimiliano Barolo, 2009, Moving average PLS Soft Sensor for online Product Quality Estimation in an Industrial Batch Polymerization Process, Journal of Process Control, vol.19, pp.520-529, 2009.
  4. Almila Bahar, and Canan Ozgen, 2010, State Estimation and Inferential Control for a Reactive Batch Distillation Column, Engineering Applications of Artificial Intelligence, vol.23, pp.260-270, 2010.
  5. A. Rogina, I.Sisko, I. Mohler, Z. Uzevic, N. Bolf, 2011, Soft Sensor for Continuous Product quality estimation (in Crude Distillation Unit), Chemical Engineering Research and Design, vol.89, issue 10, Oct.2011, pp.2070-2077.
  6. Ming-Da Ma, Jing-Wei Ko, San-Jang Wang, Ming-Feng Wu, Shi-Shang Jang, Shyan-Shu Shieh, David Shan-Hill Wong, 2009, Development of Adaptive Soft Sensor based on Statistical Identification of Key Variables, Control Engineering Practice, vol.17, pp.1026-1034, 2009.
  7. S.R. Vijaya Raghavan, T.R. Radhakrishnan, K. Srinivasan, 2011, Soft Sensor Based Composition Estimation and Controller Design for an Ideal Reactive Distillation Column, ISA transactions, vol.50, pp.61-70, 2011.
  8. L. Fortuna, S. Graziani, M.G. Xibilia, 2005, Soft Sensor for Product Quality Monitoring in Debutanizer Distillation Columns, Control Engineering Practice, vol.13, 499-508, 2005.
  9. Fatima Barcelo Rico, Jose M. Gozalvez-Zefrilla, Jose Luis Diez, and Asuncion Santafe-Moros, 2011, Modeling and Control of a Continuous Distillation Tower through Fuzzy Techniques, Chemical Engineering Research and Design, vol.89, pp.107-115, 2011.
  10. S.N. Sivanandam, S. Sumathi, and S.N. Deepa, Introduction to Neural Networks using MATLAB 6.0, TATA McGraw-Hill Publishing Company Limited, New Delhi, Edition 2006.
  11. Simon Heykins, Neural Networks: A Comprehensive Foundation, Pearson Education, Second Edition 1999.
  12. Hagan M.T., Demuth H.B., Beale M., Neural Network Design, Vikas Publishing House, 7 International Student Edition 2003.
  13. William L. Luyben, Process Modelling, Simulation and Control for Chemical Engineers, McGraw-Hill Publishing Company, International Edition 1996.
  14. M. A. Al-Arfaj and W. L. Luyben, Comparison of alternative control structures for an ideal two-product reactive distillation column, Ind. Eng. Chem. Res., vol. 39, pp.3298-3307, 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Adaline soft sensor LM soft sensor Reactive distillation process Multicomponent distillation

Powered by PhDFocusTM