Cargando…

Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree

Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is...

Descripción completa

Detalles Bibliográficos
Autores principales: Leitold, Daniel, Vathy-Fogarassy, Agnes, Abonyi, Janos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164052/
https://www.ncbi.nlm.nih.gov/pubmed/30223464
http://dx.doi.org/10.3390/s18093096
_version_ 1783359508306722816
author Leitold, Daniel
Vathy-Fogarassy, Agnes
Abonyi, Janos
author_facet Leitold, Daniel
Vathy-Fogarassy, Agnes
Abonyi, Janos
author_sort Leitold, Daniel
collection PubMed
description Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is particularly small when compared to the size of the system, and, although structural observability is ensured, the system demands additional sensors to provide the small relative order needed for fast and robust process monitoring and control. In this paper, two clustering and simulated annealing-based methodologies are proposed to assign additional sensors to the dynamical systems. The proposed methodologies simplify the observation of the system and decrease its relative order. The usefulness of the proposed method is justified in a sensor-placement problem of a heat exchanger network. The results show that the relative order of the observability is decreased significantly by an increase in the number of additional sensors.
format Online
Article
Text
id pubmed-6164052
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-61640522018-10-10 Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree Leitold, Daniel Vathy-Fogarassy, Agnes Abonyi, Janos Sensors (Basel) Article Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is particularly small when compared to the size of the system, and, although structural observability is ensured, the system demands additional sensors to provide the small relative order needed for fast and robust process monitoring and control. In this paper, two clustering and simulated annealing-based methodologies are proposed to assign additional sensors to the dynamical systems. The proposed methodologies simplify the observation of the system and decrease its relative order. The usefulness of the proposed method is justified in a sensor-placement problem of a heat exchanger network. The results show that the relative order of the observability is decreased significantly by an increase in the number of additional sensors. MDPI 2018-09-14 /pmc/articles/PMC6164052/ /pubmed/30223464 http://dx.doi.org/10.3390/s18093096 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Leitold, Daniel
Vathy-Fogarassy, Agnes
Abonyi, Janos
Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title_full Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title_fullStr Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title_full_unstemmed Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title_short Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
title_sort network distance-based simulated annealing and fuzzy clustering for sensor placement ensuring observability and minimal relative degree
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164052/
https://www.ncbi.nlm.nih.gov/pubmed/30223464
http://dx.doi.org/10.3390/s18093096
work_keys_str_mv AT leitolddaniel networkdistancebasedsimulatedannealingandfuzzyclusteringforsensorplacementensuringobservabilityandminimalrelativedegree
AT vathyfogarassyagnes networkdistancebasedsimulatedannealingandfuzzyclusteringforsensorplacementensuringobservabilityandminimalrelativedegree
AT abonyijanos networkdistancebasedsimulatedannealingandfuzzyclusteringforsensorplacementensuringobservabilityandminimalrelativedegree