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dc.contributor.authorAndersen, Joakim Rostrup
dc.contributor.authorSilva, Thiago Lima
dc.contributor.authorImsland, Lars Struen
dc.contributor.authorPavlov, Alexey
dc.date.accessioned2021-03-16T09:53:39Z
dc.date.available2021-03-16T09:53:39Z
dc.date.created2021-01-18T12:20:19Z
dc.date.issued2020
dc.identifier.isbn978-1-7281-7448-8
dc.identifier.urihttps://hdl.handle.net/11250/2733567
dc.description.abstractSystems with fast and slow dynamics give rise to objectives in different time scales which may not be aligned. The existing dynamic optimal control methods might become computationally infeasible due to the fine discretization required to capture the fast dynamics. On the other hand, a real time optimization (RTO) method based on steady-state models, which is computationally efficient, can greedily drive the plant towards optimal operation. The drawback of the RTO approach is that it may yield actions that only focus on near future goals and the objectives involving the slower dynamics are neglected. In this paper, we propose to extend RTO with a lookahead strategy by introducing a predictor to capture the effect of changing the current controls on the long-term objective. In this way, we introduce the long-term objectives in RTO while maintaining its computational efficiency and not losing focus of short-term objectives. The proposed approach is demonstrated in a simulation study from offshore petroleum production, that compares the proposed method with both an "industry-standard" RTO method, and a full fledged dynamic optimization method that takes both slow and fast dynamics into account. The proposed methodology performs almost as well as the dynamic optimization method while maintaining a low computational effort.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartof2020 59th IEEE Conference on Decision and Control (CDC)
dc.titleReal time optimization of systems with fast and slow dynamics using a lookahead strategyen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber2342-2349en_US
dc.identifier.doihttp://dx.doi.org/10.1109/CDC42340.2020.9304460
dc.identifier.cristin1873133
dc.description.localcode© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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