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Digital
Library of the European Council for Modelling and Simulation |
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Title: |
Greenhouse
Modeling And Simulation Framework For Extracting Optimal Control Parameters |
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Authors: |
Byeong
Soo Kim, Bong Gu Kang,
Tag Gon Kim, Hae Sang
Song |
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Published in:
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(2016).ECMS 2016 Proceedings edited
by: Thorsen Claus, Frank Herrmann, Michael Manitz, Oliver Rose, European Council for Modeling and
Simulation. doi:10.7148/2016 ISBN:
978-0-9932440-2-5 30th
European Conference on Modelling and Simulation, Regensburg Germany, May 31st
– June 3rd, 2016 |
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Citation
format: |
Byeong
Soo Kim, Bong Gu Kang,
Tag Gon Kim, Hae Sang
Song (2016). Greenhouse Modeling And Simulation Framework For Extracting
Optimal Control Parameters, ECMS 2016 Proceedings edited by: Thorsten Claus,
Frank Herrmann, Michael Manitz, Oliver Rose European
Council for Modeling and Simulation. doi:10.7148/2016-0368 |
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DOI: |
http://dx.doi.org/10.7148/2016-0368 |
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Abstract: |
In a greenhouse system a control is
important to allow optimal growth conditions fir crops. However, because
testing the greenhouse for real conditions requires much time and money, the
modeling-and-simulation approach is necessary to predict and improve the
greenhouse environment. There is much research related to greenhouse control,
there is alack of research on applicable framework to extract optimal control
parameters. The proposed work is composed of three parts: system
identification, controller design, and optimization. The plant model is built
through system identification, and the model is controlled by the controller which is affected by disturbances. This
simulation is repeated through design of experiments to optimize the control
parameters. This paper presents an experiment with real greenhouse data from Jinju, Korea to show the usefulness of the proposed
framework. It gives insight into the decision of choosing control parameters
and helps to raise agricultural productivity. |
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