Sensor Network Design based on the Observability and Precision degree
- Autores
- Rodriguez Aguilar, Leandro Pedro Faustino; Pantano, Maria Nadia; Scaglia, Gustavo Juan Eduardo; Sanchez, Mabel Cristina
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The Unscented Kalman Filter is a state estimation method used in nonlinear dynamic systems to estimate the mean and covariance of a random variable undergoing a nonlinear transformation, knowing the process model and the measurements. Therefore, an adequate choice of the measured variables improves the performance of the filter technique. In this context, the sensor network design problem allows selecting a set of variables that minimizes the global estimation error when the instrumentation budget is limited. This is solved using a level traversal tree search algorithm, whose computation time is reduced by evaluating the design criteria sequentially. In this work, it is proposed to address the effect of the circumstantial loss of measurements on the system observability and the estimates precision. The success of the sensor network design methodology is demonstrated for the copolymerization process of Methyl Methacrylate and Vinyl Acetate, widely studied in the literature.
Fil: Rodriguez Aguilar, Leandro Pedro Faustino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Pantano, Maria Nadia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina
Fil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina - Materia
-
COPOLYMERIZATION PROCESS
LEVEL TRAVERSAL SEARCH
OBSERVABILITY AND PRECISION DEGREE
SENSOR NETWORK DESIGN
UNSCENTED KALMAN FILTER - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/225050
Ver los metadatos del registro completo
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Sensor Network Design based on the Observability and Precision degreeRodriguez Aguilar, Leandro Pedro FaustinoPantano, Maria NadiaScaglia, Gustavo Juan EduardoSanchez, Mabel CristinaCOPOLYMERIZATION PROCESSLEVEL TRAVERSAL SEARCHOBSERVABILITY AND PRECISION DEGREESENSOR NETWORK DESIGNUNSCENTED KALMAN FILTERhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2The Unscented Kalman Filter is a state estimation method used in nonlinear dynamic systems to estimate the mean and covariance of a random variable undergoing a nonlinear transformation, knowing the process model and the measurements. Therefore, an adequate choice of the measured variables improves the performance of the filter technique. In this context, the sensor network design problem allows selecting a set of variables that minimizes the global estimation error when the instrumentation budget is limited. This is solved using a level traversal tree search algorithm, whose computation time is reduced by evaluating the design criteria sequentially. In this work, it is proposed to address the effect of the circumstantial loss of measurements on the system observability and the estimates precision. The success of the sensor network design methodology is demonstrated for the copolymerization process of Methyl Methacrylate and Vinyl Acetate, widely studied in the literature.Fil: Rodriguez Aguilar, Leandro Pedro Faustino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Pantano, Maria Nadia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; ArgentinaFil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; ArgentinaInstitute of Electrical and Electronics Engineers2023-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/225050Rodriguez Aguilar, Leandro Pedro Faustino; Pantano, Maria Nadia; Scaglia, Gustavo Juan Eduardo; Sanchez, Mabel Cristina; Sensor Network Design based on the Observability and Precision degree; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 21; 4; 4-2023; 588-5941548-0992CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://latamt.ieeer9.org/index.php/transactions/article/view/7137info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:05:39Zoai:ri.conicet.gov.ar:11336/225050instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:05:39.531CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Sensor Network Design based on the Observability and Precision degree |
title |
Sensor Network Design based on the Observability and Precision degree |
spellingShingle |
Sensor Network Design based on the Observability and Precision degree Rodriguez Aguilar, Leandro Pedro Faustino COPOLYMERIZATION PROCESS LEVEL TRAVERSAL SEARCH OBSERVABILITY AND PRECISION DEGREE SENSOR NETWORK DESIGN UNSCENTED KALMAN FILTER |
title_short |
Sensor Network Design based on the Observability and Precision degree |
title_full |
Sensor Network Design based on the Observability and Precision degree |
title_fullStr |
Sensor Network Design based on the Observability and Precision degree |
title_full_unstemmed |
Sensor Network Design based on the Observability and Precision degree |
title_sort |
Sensor Network Design based on the Observability and Precision degree |
dc.creator.none.fl_str_mv |
Rodriguez Aguilar, Leandro Pedro Faustino Pantano, Maria Nadia Scaglia, Gustavo Juan Eduardo Sanchez, Mabel Cristina |
author |
Rodriguez Aguilar, Leandro Pedro Faustino |
author_facet |
Rodriguez Aguilar, Leandro Pedro Faustino Pantano, Maria Nadia Scaglia, Gustavo Juan Eduardo Sanchez, Mabel Cristina |
author_role |
author |
author2 |
Pantano, Maria Nadia Scaglia, Gustavo Juan Eduardo Sanchez, Mabel Cristina |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
COPOLYMERIZATION PROCESS LEVEL TRAVERSAL SEARCH OBSERVABILITY AND PRECISION DEGREE SENSOR NETWORK DESIGN UNSCENTED KALMAN FILTER |
topic |
COPOLYMERIZATION PROCESS LEVEL TRAVERSAL SEARCH OBSERVABILITY AND PRECISION DEGREE SENSOR NETWORK DESIGN UNSCENTED KALMAN FILTER |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
dc.description.none.fl_txt_mv |
The Unscented Kalman Filter is a state estimation method used in nonlinear dynamic systems to estimate the mean and covariance of a random variable undergoing a nonlinear transformation, knowing the process model and the measurements. Therefore, an adequate choice of the measured variables improves the performance of the filter technique. In this context, the sensor network design problem allows selecting a set of variables that minimizes the global estimation error when the instrumentation budget is limited. This is solved using a level traversal tree search algorithm, whose computation time is reduced by evaluating the design criteria sequentially. In this work, it is proposed to address the effect of the circumstantial loss of measurements on the system observability and the estimates precision. The success of the sensor network design methodology is demonstrated for the copolymerization process of Methyl Methacrylate and Vinyl Acetate, widely studied in the literature. Fil: Rodriguez Aguilar, Leandro Pedro Faustino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina Fil: Pantano, Maria Nadia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina Fil: Scaglia, Gustavo Juan Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Ingeniería Química; Argentina Fil: Sanchez, Mabel Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (I). Grupo Vinculado al Plapiqui - Investigación y Desarrollo en Tecnología Química; Argentina |
description |
The Unscented Kalman Filter is a state estimation method used in nonlinear dynamic systems to estimate the mean and covariance of a random variable undergoing a nonlinear transformation, knowing the process model and the measurements. Therefore, an adequate choice of the measured variables improves the performance of the filter technique. In this context, the sensor network design problem allows selecting a set of variables that minimizes the global estimation error when the instrumentation budget is limited. This is solved using a level traversal tree search algorithm, whose computation time is reduced by evaluating the design criteria sequentially. In this work, it is proposed to address the effect of the circumstantial loss of measurements on the system observability and the estimates precision. The success of the sensor network design methodology is demonstrated for the copolymerization process of Methyl Methacrylate and Vinyl Acetate, widely studied in the literature. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/225050 Rodriguez Aguilar, Leandro Pedro Faustino; Pantano, Maria Nadia; Scaglia, Gustavo Juan Eduardo; Sanchez, Mabel Cristina; Sensor Network Design based on the Observability and Precision degree; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 21; 4; 4-2023; 588-594 1548-0992 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/225050 |
identifier_str_mv |
Rodriguez Aguilar, Leandro Pedro Faustino; Pantano, Maria Nadia; Scaglia, Gustavo Juan Eduardo; Sanchez, Mabel Cristina; Sensor Network Design based on the Observability and Precision degree; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 21; 4; 4-2023; 588-594 1548-0992 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://latamt.ieeer9.org/index.php/transactions/article/view/7137 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers |
publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.13397 |