LAPSE:2020.0272
Published Article
LAPSE:2020.0272
Integration of Prognostics and Control of an Oil/CO2 Subsea Separation System
March 11, 2020
The exploitation of reserves with a high CO2 content is challenging because of the need for its separation and the environmental impact associated with its generation. In this context, a suitable use for the generated CO2 is its reinjection into the reservoir, and subsea CO2 separation improves the efficiency of this process. The main objective of this work is to investigate the health-aware control of a subsea CO2 separation system. Previously identified linear models were used in a predictive controller with Kalman filter-based state estimation and online model update, and simulations were performed to evaluate the controller tuning. Regarding prognostics, a stochastic model of pump degradation, sensitive to its operating conditions, was proposed, and a particle filter was implemented to perform online degradation state estimation and remaining useful lifetime prediction. Finally, a health-aware controller was designed, which could extend the life of the process by four months when compared to operation with a conventional model predictive controller. Some difficulties in combining reference tracking and lifetime extension objectives were also investigated. The obtained results indicate that dealing with the control problem through the multiobjective optimization theory or addressing the lifetime extension in an optimization layer may improve its performance.
Keywords
equipment reliability, predictive control, remaining useful lifetime, statistic inference, subsea processing
Suggested Citation
Bernardino LF, Souza AFFD, Secchi AR, de Souza Jr. MB, Barros A. Integration of Prognostics and Control of an Oil/CO2 Subsea Separation System. (2020). LAPSE:2020.0272
Author Affiliations
Bernardino LF: Programa de Engenharia Química, UFRJ, Rio de Janeiro 21941-450, Brazil [ORCID]
Souza AFFD: Programa de Engenharia Química, UFRJ, Rio de Janeiro 21941-450, Brazil
Secchi AR: Programa de Engenharia Química, UFRJ, Rio de Janeiro 21941-450, Brazil [ORCID]
de Souza Jr. MB: Programa de Engenharia Química, UFRJ, Rio de Janeiro 21941-450, Brazil; Escola de Química, UFRJ, Rio de Janeiro 21941-909, Brazil [ORCID]
Barros A: Department of Mechanical and Industrial Engineering, NTNU, 7491 Trondheim, Norway
Journal Name
Processes
Volume
8
Issue
2
Article Number
E148
Year
2020
Publication Date
2020-01-23
Published Version
ISSN
2227-9717
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Original Submission
Other Meta
PII: pr8020148, Publication Type: Journal Article
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LAPSE:2020.0272
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doi:10.3390/pr8020148
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Mar 11, 2020
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CC BY 4.0
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Mar 11, 2020
 
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Original Submitter
Calvin Tsay
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