dc.contributor.author | Matias, José O.A. | |
dc.contributor.author | Oliveira, Julio P.C. | |
dc.contributor.author | Le Roux, Galo A. C. | |
dc.contributor.author | Jäschke, Johannes | |
dc.date.accessioned | 2023-02-10T09:29:46Z | |
dc.date.available | 2023-02-10T09:29:46Z | |
dc.date.created | 2022-11-30T10:56:19Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Journal of Process Control. 2022, 115 181-196. | en_US |
dc.identifier.issn | 0959-1524 | |
dc.identifier.uri | https://hdl.handle.net/11250/3049931 | |
dc.description.abstract | Real-time optimization with persistent parameter adaptation (ropa) is an rto approach, where the steady-state model parameters are updated dynamically using transient measurements. Consequently, we avoid waiting for a steady-state before triggering the optimization cycle, and the steady-state economic optimization can be scheduled at any desired rate. The steady-state wait has been recognized as a fundamental limitation of the traditional rto approach. In this paper, we implement ropa on an experimental rig that emulates a subsea oil well network. For comparison, we also implement traditional and dynamic rto. The experimental results confirm the in-silico findings that ropa’s performance is similar to dynamic rto’s performance with a much lower computational cost. Additionally, we present some guidelines for ropa’s practical implementation and a theoretical analysis of ropa’s convergence properties. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Steady-state real-time optimization using transient measurements on an experimental rig | en_US |
dc.title.alternative | Steady-state real-time optimization using transient measurements on an experimental rig | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.pagenumber | 181-196 | en_US |
dc.source.volume | 115 | en_US |
dc.source.journal | Journal of Process Control | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.jprocont.2022.04.015 | |
dc.identifier.cristin | 2085280 | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 2 | |