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...
| Main Authors: | , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/7327 |
| _version_ | 1789406623104499712 |
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| author | Sánchez Molina, Jorge Antonio Rodríguez Díaz, Francisco Guzmán Sánchez, José Luis R. Arahal, Manuel |
| author_facet | Sánchez Molina, Jorge Antonio Rodríguez Díaz, Francisco Guzmán Sánchez, José Luis R. Arahal, Manuel |
| author_sort | Sánchez Molina, Jorge Antonio |
| collection | DSpace |
| 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. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-7327 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-73272023-04-12T19:26:11Z Virtual Sensors for Designing Irrigation Controllers in Greenhouses Sánchez Molina, Jorge Antonio Rodríguez Díaz, Francisco Guzmán Sánchez, José Luis R. Arahal, Manuel virtual sensor transpiration nonlinear model micro-lysimeter 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. 2020-01-16T08:22:43Z 2020-01-16T08:22:43Z 2012-11-08 info:eu-repo/semantics/article 1424-8220 http://hdl.handle.net/10835/7327 en https://www.mdpi.com/1424-8220/12/11/15244 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | virtual sensor transpiration nonlinear model micro-lysimeter Sánchez Molina, Jorge Antonio Rodríguez Díaz, Francisco Guzmán Sánchez, José Luis R. Arahal, Manuel 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 | virtual sensor transpiration nonlinear model micro-lysimeter |
| url | http://hdl.handle.net/10835/7327 |
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