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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/3893

Title: Identification of bilinear models for chemical processes using canonical variate analysis
Authors: LAKSHMINARAYANAN, S
MHATRE, P
GUDI, R
Keywords: nonlinear-systems
hammerstein models
Issue Date: 2001
Publisher: AMER CHEMICAL SOC
Citation: INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 40(20), 4415-4427
Abstract: The identification of nonlinear models for chemical processes solely from experimental data is described in this paper. The canonical variate analysis (CVA) technique that has served well in the identification of empirical linear process models is extended to construct data-based bilinear models in an iterative fashion. Numerous examples involving engineering systems are included to illustrate the practicality of the suggested approach for bilinear model identification. Finally, the use of the identified nonlinear models for control is demonstrated using the example of a simulated paper machine headbox system.
URI: http://dx.doi.org/10.1021/ie000685b
http://dspace.library.iitb.ac.in/xmlui/handle/10054/3893
http://hdl.handle.net/10054/3893
ISSN: 0888-5885
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