DocumentCode
2557259
Title
Dynamic data reconciliation for sequential modular simulators: application to a mixing process
Author
Becerra, V.M. ; Roberts, P.D. ; Griffiths, G.W.
Author_Institution
Dept. of Cybern., Reading Univ., UK
Volume
4
fYear
2000
fDate
2000
Firstpage
2740
Abstract
This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process
Keywords
Kalman filters; data handling; differential equations; mixing; nonlinear systems; process control; Kalman filters; data reconciliation; differential algebraic equations; mixing process; nonlinear systems; process control; sequential modular simulators; Control engineering; Cybernetics; Differential algebraic equations; Energy measurement; Noise measurement; Nonlinear equations; Nonlinear systems; State estimation; Steady-state; Weight control;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2000. Proceedings of the 2000
Conference_Location
Chicago, IL
ISSN
0743-1619
Print_ISBN
0-7803-5519-9
Type
conf
DOI
10.1109/ACC.2000.878707
Filename
878707
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