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dc.contributor.author
Luppi, Patricio Alfredo
dc.contributor.author
Braccia, Lautaro
dc.contributor.author
Zumoffen, David Alejandro Ramon
dc.date.available
2022-12-27T15:38:25Z
dc.date.issued
2021-01
dc.identifier.citation
Luppi, Patricio Alfredo; Braccia, Lautaro; Zumoffen, David Alejandro Ramon; Optimal Measurement Selection and Principal Component Analysis-Based Combination as Controlled Variables; American Chemical Society; Industrial & Engineering Chemical Research; 60; 1; 1-2021; 457-472
dc.identifier.issn
0888-5885
dc.identifier.uri
http://hdl.handle.net/11336/182554
dc.description.abstract
This work presents a methodology for defining the controlled variables based on two interrelated procedures. On the one hand, a linear combination of the selected measurements is performed through a combination matrix developed from the principal component analysis theory. On the other hand, the optimal sensor selection is formulated as a multiobjective optimization problem, which is efficiently solved via genetic algorithms. Three functional costs are considered, which provide a trade-off between controllability, interaction, and complexity of the resulting structures. The overall design procedure is based on steady-state information of the process. Moreover, the proposed formulation allows easily analyzing the control reconfiguration problem, particularly when potential modifications of the nominal sensor set are taken into account. For each considered scenario, a screening of the reconfiguration alternatives can be done from the obtained Pareto set. Then, the solutions of interest could be computationally simulated in order to choose the most convenient option. In this work, all the designs are implemented as conventional decentralized control structures based on multiple PI feedback loops, supplemented with the combination matrix. The latter enables the use of a number of sensors equal to or greater than the number of available actuators. These additional sensors can provide notable benefits to the dynamic performance of the system as well as flexibility to the design process, offering many more alternatives for an eventual reconfiguration action than the conventional square solutions. In addition, the reconfiguration process features reduced complexity because the controlled and manipulated variable structure remains unchanged when modifications in the sensor set occur. A rigorous nonlinear model of a bio-ethanol processor system coupled with a proton exchange membrane fuel cell is proposed as a case study.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
American Chemical Society
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
OPTIMAL MEASUREMENT SELECTION
dc.subject
PRINCIPAL COMPONENT ANALYSIS
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PLANT WIDE CONTROL
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FAULT TOLERANT CONTROL
dc.subject.classification
Sistemas de Automatización y Control
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Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Optimal Measurement Selection and Principal Component Analysis-Based Combination as 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
2022-08-31T14:59:23Z
dc.journal.volume
60
dc.journal.number
1
dc.journal.pagination
457-472
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Luppi, Patricio Alfredo. 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: Braccia, Lautaro. 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/url/https://pubs.acs.org/doi/10.1021/acs.iecr.0c04576
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1021/acs.iecr.0c04576
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