Virtual Sensors for Designing Irrigation Controllers in Greenhouses

Monitoring the greenhouse transpiration for control purposes is currently a difficult task. The absence of affordable sensors that provide continuous transpiration measurements motivates the use of estimators. In the case of tomato crops, the availability of estimators allows the design of automatic...

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Autores principales: Sánchez, Jorge Antonio, Rodríguez, Francisco, Guzmán, José Luis, Arahal, Manuel R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3522961/
https://www.ncbi.nlm.nih.gov/pubmed/23202208
http://dx.doi.org/10.3390/s121115244
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author Sánchez, Jorge Antonio
Rodríguez, Francisco
Guzmán, José Luis
Arahal, Manuel R
author_facet Sánchez, Jorge Antonio
Rodríguez, Francisco
Guzmán, José Luis
Arahal, Manuel R
author_sort Sánchez, Jorge Antonio
collection PubMed
description Monitoring the greenhouse transpiration for control purposes is currently a difficult task. The absence of affordable sensors that provide continuous transpiration measurements motivates the use of estimators. In the case of tomato crops, the availability of estimators allows the design of automatic fertirrigation (irrigation + fertilization) schemes in greenhouses, minimizing the dispensed water while fulfilling crop needs. This paper shows how system identification techniques can be applied to obtain nonlinear virtual sensors for estimating transpiration. The greenhouse used for this study is equipped with a microlysimeter, which allows one to continuously sample the transpiration values. While the microlysimeter is an advantageous piece of equipment for research, it is also expensive and requires maintenance. This paper presents the design and development of a virtual sensor to model the crop transpiration, hence avoiding the use of this kind of expensive sensor. The resulting virtual sensor is obtained by dynamical system identification techniques based on regressors taken from variables typically found in a greenhouse, such as global radiation and vapor pressure deficit. The virtual sensor is thus based on empirical data. In this paper, some effort has been made to eliminate some problems associated with grey-box models: advance phenomenon and overestimation. The results are tested with real data and compared with other approaches. Better results are obtained with the use of nonlinear Black-box virtual sensors. This sensor is based on global radiation and vapor pressure deficit (VPD) measurements. Predictive results for the three models are developed for comparative purposes.
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spelling pubmed-35229612013-01-09 Virtual Sensors for Designing Irrigation Controllers in Greenhouses Sánchez, Jorge Antonio Rodríguez, Francisco Guzmán, José Luis Arahal, Manuel R Sensors (Basel) Article Monitoring the greenhouse transpiration for control purposes is currently a difficult task. The absence of affordable sensors that provide continuous transpiration measurements motivates the use of estimators. In the case of tomato crops, the availability of estimators allows the design of automatic fertirrigation (irrigation + fertilization) schemes in greenhouses, minimizing the dispensed water while fulfilling crop needs. This paper shows how system identification techniques can be applied to obtain nonlinear virtual sensors for estimating transpiration. The greenhouse used for this study is equipped with a microlysimeter, which allows one to continuously sample the transpiration values. While the microlysimeter is an advantageous piece of equipment for research, it is also expensive and requires maintenance. This paper presents the design and development of a virtual sensor to model the crop transpiration, hence avoiding the use of this kind of expensive sensor. The resulting virtual sensor is obtained by dynamical system identification techniques based on regressors taken from variables typically found in a greenhouse, such as global radiation and vapor pressure deficit. The virtual sensor is thus based on empirical data. In this paper, some effort has been made to eliminate some problems associated with grey-box models: advance phenomenon and overestimation. The results are tested with real data and compared with other approaches. Better results are obtained with the use of nonlinear Black-box virtual sensors. This sensor is based on global radiation and vapor pressure deficit (VPD) measurements. Predictive results for the three models are developed for comparative purposes. Molecular Diversity Preservation International (MDPI) 2012-11-08 /pmc/articles/PMC3522961/ /pubmed/23202208 http://dx.doi.org/10.3390/s121115244 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Sánchez, Jorge Antonio
Rodríguez, Francisco
Guzmán, José Luis
Arahal, Manuel R
Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title_full Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title_fullStr Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title_full_unstemmed Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title_short Virtual Sensors for Designing Irrigation Controllers in Greenhouses
title_sort virtual sensors for designing irrigation controllers in greenhouses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3522961/
https://www.ncbi.nlm.nih.gov/pubmed/23202208
http://dx.doi.org/10.3390/s121115244
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