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Dynamic data reconciliation for sequential modular simulators: application to a mixing process

Becerra, V. M., Roberts, P. D. and Griffiths, G. W. (2000) Dynamic data reconciliation for sequential modular simulators: application to a mixing process. In: American Control Conference, 2000, 28-30 Jun 2000, Chicago, IL, USA, pp. 2740-2744.

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To link to this item DOI: 10.1109/ACC.2000.878707

Abstract/Summary

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.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science
ID Code:19226
Uncontrolled Keywords:Kalman filters, data reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators
Additional Information:Proceedings ISBN: 0780355199

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