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Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor
Research Areas
  • Engineering
Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.
International Conference of Agricultural Engineering CIGR-AgEng 2012
Valencia- España
Start Date
End Date
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Book of Abstracts
  • Autor: Abdulkhalik Abakarov . (UPM)
  • Autor: Heidi Tatiana Jimenez Ariza (UPM)
  • Autor: Eva Cristina Correa Hernando (UPM)
  • Autor: Belen Diezma Iglesias (UPM)
  • Autor: Francisco Javier Arranz Saiz (UPM)
  • Autor: Javier García Hierro (CENIM-CSIC)
  • Autor: José ignacio Robla (CNIM-CSIC)
  • Autor: Pilar Barreiro Elorza (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación
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