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: | Article |
| Language: | English |
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MDPI AG
2012-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/11/15244 |
| _version_ | 1798005754753449984 |
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| author | Manuel R. Arahal José Luis Guzmán Francisco Rodríguez Jorge Antonio Sánchez |
| author_facet | Manuel R. Arahal José Luis Guzmán Francisco Rodríguez Jorge Antonio Sánchez |
| author_sort | Manuel R. Arahal |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T12:44:07Z |
| format | Article |
| id | doaj.art-4de748e9ca044c4f8bd14854fae91ac5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:44:07Z |
| publishDate | 2012-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4de748e9ca044c4f8bd14854fae91ac52022-12-22T04:23:24ZengMDPI AGSensors1424-82202012-11-011211152441526610.3390/s121115244Virtual Sensors for Designing Irrigation Controllers in GreenhousesManuel R. ArahalJosé Luis GuzmánFrancisco RodríguezJorge Antonio SánchezMonitoring 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.http://www.mdpi.com/1424-8220/12/11/15244virtual sensortranspirationnonlinear modelmicro-lysimeter |
| spellingShingle | Manuel R. Arahal José Luis Guzmán Francisco Rodríguez Jorge Antonio Sánchez Virtual Sensors for Designing Irrigation Controllers in Greenhouses Sensors virtual sensor transpiration nonlinear model micro-lysimeter |
| 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://www.mdpi.com/1424-8220/12/11/15244 |
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