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dc.contributor.author
Marchetti, Alejandro Gabriel
dc.contributor.author
Zumoffen, David Alejandro Ramon
dc.date.available
2017-12-05T16:00:48Z
dc.date.issued
2014-04
dc.identifier.citation
Marchetti, Alejandro Gabriel; Zumoffen, David Alejandro Ramon; Self-Optimizing Control Structures with Minimum Number of Process-Dependent Controlled Variables; American Chemical Society; Industrial & Engineering Chemical Research; 153; 4-2014; 10177-10193
dc.identifier.issn
0888-5885
dc.identifier.uri
http://hdl.handle.net/11336/29714
dc.description.abstract
In order to operate continuous processes near the economically optimal steady-state operating point, selfoptimizing control schemes reformulate the optimization problem as a process control problem. The objective is to find controlled variables and constant set points such that the controller leads to optimal adjustments of the inputs in the presence of stable disturbances. In particular, the null space approach consists in selecting the self-optimizing controlled variables as linear combinations of the inactive output variables, based on the first-order variation of the necessary conditions of optimality. In the self-optimizing control structures proposed in the literature, the number of controlled variables required is typically equal to the number of degrees of freedom (inputs) that are available after all the equality and active inequality constrained variables are controlled. In this paper, we propose new self-optimizing control structures based on the null space approach, where depending on the number of disturbances, the number of active constraints, and the number of inputs, it is possible to decrease the number of process-dependent controlled variables by fixing linear combinations of the inputs. The effectiveness of the proposed selfoptimizing control structures with minimum number of process-dependent controlled variables is demonstrated in simulation by means of a continuous stirred tank reactor and an evaporator
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Chemical Society
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Self-Optimizing Control
dc.subject
Null-Space Method
dc.subject
Minimum Number of Control Loops
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones
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Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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INGENIERÍAS Y TECNOLOGÍAS
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Otras Ingeniería Química
dc.subject.classification
Ingeniería Química
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Self-Optimizing Control Structures with Minimum Number of Process-Dependent Controlled Variables
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2017-12-05T15:18:38Z
dc.journal.volume
153
dc.journal.pagination
10177-10193
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Washington
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.description.fil
Fil: Zumoffen, David Alejandro Ramon. 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
Industrial & Engineering Chemical Research
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/ie5010509
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/doi/10.1021/ie5010509
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