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Erschienen in: Optimization and Engineering 1/2017

04.11.2015

Overview of estimation methods for industrial dynamic systems

verfasst von: John D. Hedengren, Ammon N. Eaton

Erschienen in: Optimization and Engineering | Ausgabe 1/2017

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Abstract

Measurement technology is advancing in the oil and gas industry. Factors such as wireless transmitters, reduced cost of measurement technology, and increased regulations that require active monitoring tend to increase the number of available measurements. There is a clear opportunity to distill the recent flood of measurements into relevant and actionable information. Common methods to do this include a filtered bias update, implicit dynamic feedback, Kalman filtering, and moving horizon estimation. The purpose of these techniques is to validate measurements and align imperfect mathematical models to the actual process. Additionally, they can determine a best-estimate of the current state of the process and any potential disturbances. These methods allow potential improvements in earlier detection of disturbances, process equipment faults, and improved state estimates for optimization and control.

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Metadaten
Titel
Overview of estimation methods for industrial dynamic systems
verfasst von
John D. Hedengren
Ammon N. Eaton
Publikationsdatum
04.11.2015
Verlag
Springer US
Erschienen in
Optimization and Engineering / Ausgabe 1/2017
Print ISSN: 1389-4420
Elektronische ISSN: 1573-2924
DOI
https://doi.org/10.1007/s11081-015-9295-9

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