Research Article
GMC DESIGN BASED ON SVM MODEL OF BATCH REACTOR
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 1 - Issue 20 |
| Published: February 2010 |
| Authors: S.Sujatha, N.Pappa |
10.5120/417-615
|
S.Sujatha, N.Pappa . GMC DESIGN BASED ON SVM MODEL OF BATCH REACTOR. International Journal of Computer Applications. 1, 20 (February 2010), 76-79. DOI=10.5120/417-615
@article{ 10.5120/417-615,
author = { S.Sujatha,N.Pappa },
title = { GMC DESIGN BASED ON SVM MODEL OF BATCH REACTOR },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 1 },
number = { 20 },
pages = { 76-79 },
doi = { 10.5120/417-615 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A S.Sujatha
%A N.Pappa
%T GMC DESIGN BASED ON SVM MODEL OF BATCH REACTOR%T
%J International Journal of Computer Applications
%V 1
%N 20
%P 76-79
%R 10.5120/417-615
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The use of support vector machine (SVM) in all aspects of process engineering activities, such as modeling, design, optimization and control has considerably increased in recent years. In this paper, a design procedure of support vector machine (SVM) based model identification and control strategy for a batch reactor process with input-output form is proposed. In order to implement the generic model control structure, straight model representation and identification methods are addressed in detail. The control of a simulated batch reactor mostly used in chemical and pharmaceutical industries illustrates the proposed design procedure and the properties of the SVM based model identification, for nonlinear systems. This non linear control is a generic model control (GMC). GMC is found to be well suited for a system when there is no significant rate of change of the set point.
References
- M.Mujtaba,N.Aziz,M.A.Hussain, Neural network based modeling and control in batch reactor Chemical Engg Research and Design, 84(A8);635-644
- G.T.Jemwa,C.Aldrich, Identification of Chaotic process Systems with Least Square Support Vector Machines pp.2066 – 2071, IEEE 2003.
- Hai- Bo Huo, Xin- Jian Zhu, Guang- Yi Cao, Nonlinear modeling of a SOFC stack based on a least square Support Vector Machine, Journal of Power Sources 162 (2006) 1220 – 1225
- Li-Na Li, Chao-Zhen Hou, The Identification of Industrial Processes based on SVM, in: proceeding of first International Conference on Machine Learning and Cybernetics, Beijing, 4-5 Nov 2002
- Suykens JAK, Vandewalle J. Least squares support vector machine classifiers.Neural Process Lett, 9(3):293–300, 1999.
- Liu B, Su H, Huang W, Chu J. Temperature predictive control based Least Squares Support Vector Machines.J Contr Theory 4;4:365–70, April 2000.
- Liling Ma, Junzheng Wang, zhigang Liu, A Fault Diagnosis method based on composite model and SVM for fermentation process ,IEEE International conference on Control and Automation 2007.
- Lee.P.L.,and Suvillivan,G.R.,Generic model control, Comput Chem Eng,12:573,1988
- Cott, B.J, Macchietto, S.Temperature Control of Exothermic Batch reactors using Generic Model Control, Industrial Engineering Chemical Research.28,1177-1184,1989.
Index Terms
Keywords