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

V. M. Becerra; P. D. Roberts; G. W. Griffiths

doi:10.1109/ACC.2000.878707

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

V. M. Becerra, P. D. Roberts, G. W. Griffiths

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 2000 American Control Conference, 2000
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2740-2744
Volume	4
ISBN (Print)	0780355199
DOIs	https://doi.org/10.1109/ACC.2000.878707
Publication status	Published - 2000

Keywords

Kalman filters, data reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators

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10.1109/ACC.2000.878707

Cite this

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title = "Dynamic data reconciliation for sequential modular simulators: application to a mixing process",

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 reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators",

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volume = "4",

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Dynamic data reconciliation for sequential modular simulators: application to a mixing process. / Becerra, V. M.; Roberts, P. D.; Griffiths, G. W.
Proceedings of the 2000 American Control Conference, 2000. Vol. 4 Piscataway: Institute of Electrical and Electronics Engineers Inc., 2000. p. 2740-2744.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Roberts, P. D.

AU - Griffiths, G. W.

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AB - 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.

KW - Kalman filters, data reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators

U2 - 10.1109/ACC.2000.878707

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M3 - Conference contribution

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BT - Proceedings of the 2000 American Control Conference, 2000

PB - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway

ER -

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

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Keywords

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