A physics-based modelling and control of greenhouse system air temperature aided by IoT technology

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dc.contributor.authorFaniyi, Beatrice
dc.contributor.authorLuo, Zhenhua
dc.date.accessioned2023-03-29T13:24:38Z
dc.date.available2023-03-29T13:24:38Z
dc.date.issued2023-03-14
dc.description.abstractThe need to reduce energy consumption in greenhouse production has grown. Thermal heating demand alone accounts for 80% of conventional greenhouse energy consumption; this significantly reduces production profit. Since microclimate affects crop metabolic processes and output, it is essential to monitor and control it to achieve both quantity and quality production with minimum energy consumption for maximum profit. The Internet of Things (IoT) is an evolving technology for monitoring and controlling environments that have recently been adopted to boost greenhouse efficiency in many applications by integrating hardware and software solutions; therefore, its adoption is thus critical in enabling greenhouse energy consumption minimisation. The first objective of this study is to improve and validate a greenhouse dynamic air temperature model required to simulate or predict indoor temperature. To achieve the first objective, therefore, an existing model was enhanced and a closed loop test experimental data from the IoT cloud-based control system platform deployed in the prototype greenhouse built in Cranfield University was used to validate the model using an optimisation-based model fitting approach. The second goal is to control the greenhouse air temperature in simulation using relatively simple PI and on-off control strategies to maintain the grower’s desired setpoint irrespective of the inevitable disturbances and to verify the potential of the controllers in minimising the total energy input to the greenhouse. For the second objective, the simulation results showed that the two controllers maintained the desired setpoint; however, the on-off strategy retained a sustainable oscillation, and the tuned PI effectively maintained the desired temperature, although the average energy used by the controllers is the same.en_UK
dc.identifier.citationFaniyi B, Luo Z. (2023) A physics-based modelling and control of greenhouse system air temperature aided by IoT technology. Energies, Volume 16, Issue 6, March 2023, Article number 2708en_UK
dc.identifier.issn1996-1073
dc.identifier.urihttps://doi.org/10.3390/en16062708
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19371
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectenergy modelen_UK
dc.subjectgreenhouse climateen_UK
dc.subjectenergy minimisationen_UK
dc.subjectcontrol algorithmen_UK
dc.subjectIoT control-based greenhouseen_UK
dc.titleA physics-based modelling and control of greenhouse system air temperature aided by IoT technologyen_UK
dc.typeArticleen_UK

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