Mostrar el registro sencillo del ítem
dc.contributor.author
Marchetti, Alejandro Gabriel
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.date.available
2023-09-08T14:30:47Z
dc.date.issued
2022-02
dc.identifier.citation
Marchetti, Alejandro Gabriel; Feasibility in Real-Time Optimization Under Model Uncertainty: The Use of Lipschitz Bounds; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 168; 2-2022; 1-13
dc.identifier.issn
0098-1354
dc.identifier.uri
http://hdl.handle.net/11336/210947
dc.description.abstract
In real-time optimization (RTO), feedback information from the plant is used to compensate for model uncertainty. Feasibility upon convergence can be guaranteed by simply adding bias correction terms to the constraints predicted by the model. However, the RTO solutions obtained prior to convergence may violate the plant constraints in the presence of model uncertainty. The use of constraint upper-bounding functions based on Lipschitz continuity assumptions has been proposed as a means to ensure the satisfaction of constraints. This paper presents a comparative study between three different types of Lipschitz bounds for providing theoretical feasibility guarantees in different RTO schemes. Based on a novel Lipschitz bound on the constraint modeling error, robust RTO algorithms are proposed for the two model adaptation strategies that are most commonly employed in industrial RTO practice, which are the constraint–adaptation and parameter-adaptation schemes. A robust modifier-adaptation algorithm is also studied.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
CONSTRAINT UPPER BOUNDS
dc.subject
FEASIBLE-SIDE CONVERGENCE
dc.subject
LIPSCHITZ BOUNDS
dc.subject
MODEL UNCERTAINTY
dc.subject
REAL-TIME OPTIMIZATION
dc.subject.classification
Ingeniería de Procesos Químicos
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
Ingeniería Química
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.title
Feasibility in Real-Time Optimization Under Model Uncertainty: The Use of Lipschitz Bounds
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-07-04T15:55:37Z
dc.journal.volume
168
dc.journal.pagination
1-13
dc.journal.pais
Estados Unidos
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.description.fil
Fil: Marchetti, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.journal.title
Computers and Chemical Engineering
![Se ha confirmado la validez de este valor de autoridad por un usuario](/themes/CONICETDigital/images/authority_control/invisible.gif)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135422003891
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.compchemeng.2022.108057
Archivos asociados