Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation

Greenhouse climate is crucial for crop growth. Traditional climate control techniques are carried out through on–off actuators based on growers’ experience. Advanced control algorithms usually track setpoints through continuous control inputs. These setpoints cannot guarantee maximum profit, which c...

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Main Authors: Dan Xu, Yanfeng Li, Anguo Dai, Shumei Zhao, Weitang Song
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Information Processing in Agriculture
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Online Access:http://www.sciencedirect.com/science/article/pii/S2214317323000586
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author Dan Xu
Yanfeng Li
Anguo Dai
Shumei Zhao
Weitang Song
author_facet Dan Xu
Yanfeng Li
Anguo Dai
Shumei Zhao
Weitang Song
author_sort Dan Xu
collection DOAJ
description Greenhouse climate is crucial for crop growth. Traditional climate control techniques are carried out through on–off actuators based on growers’ experience. Advanced control algorithms usually track setpoints through continuous control inputs. These setpoints cannot guarantee maximum profit, which can be treated as the control objective of the optimal control algorithm. This paper investigated on–off optimal control algorithms based on two-time-scale decomposition. Mixed-integer nonlinear dynamic programming is used in the fast subproblem to quantify the influence of restricting different control inputs to be integers on the control objective and the CPU time. Results show that compared with continuous control inputs, a decrease of 2.21 ¥·m−2 in the control objective and an increase of 7.84·103 s in the CPU time can be found when defining all control inputs to be integers with 12 collocation points in one day. The methods of sorting and pulse width modulation are used to simulate the receding horizon optimal control in the whole growing period. Results show that compared with continuous control inputs, decreases of 83.54 ¥·m−2 and 4.45 ¥·m−2 can be found with the methods of sorting and pulse width modulation. Moreover, the method of pulse width modulation cannot guarantee state constraint satisfaction. This paper suggests modifying actuators to supply continuous control inputs before implementing optimal control algorithms for maximum profit.
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spelling doaj-art-f6cfd462dda247c8af736fcf7259bce12024-12-11T05:56:34ZengElsevierInformation Processing in Agriculture2214-31732024-12-01114488498Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivationDan Xu0Yanfeng Li1Anguo Dai2Shumei Zhao3Weitang Song4College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs, Beijing 100083, ChinaVegetable Research Institute, Tibet Academy of Agriculture and Animal Husbandry Sciences, Tibet 850000, ChinaVegetable Research Institute, Tibet Academy of Agriculture and Animal Husbandry Sciences, Tibet 850000, ChinaCollege of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs, Beijing 100083, ChinaCollege of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs, Beijing 100083, China; Corresponding author at: College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China.Greenhouse climate is crucial for crop growth. Traditional climate control techniques are carried out through on–off actuators based on growers’ experience. Advanced control algorithms usually track setpoints through continuous control inputs. These setpoints cannot guarantee maximum profit, which can be treated as the control objective of the optimal control algorithm. This paper investigated on–off optimal control algorithms based on two-time-scale decomposition. Mixed-integer nonlinear dynamic programming is used in the fast subproblem to quantify the influence of restricting different control inputs to be integers on the control objective and the CPU time. Results show that compared with continuous control inputs, a decrease of 2.21 ¥·m−2 in the control objective and an increase of 7.84·103 s in the CPU time can be found when defining all control inputs to be integers with 12 collocation points in one day. The methods of sorting and pulse width modulation are used to simulate the receding horizon optimal control in the whole growing period. Results show that compared with continuous control inputs, decreases of 83.54 ¥·m−2 and 4.45 ¥·m−2 can be found with the methods of sorting and pulse width modulation. Moreover, the method of pulse width modulation cannot guarantee state constraint satisfaction. This paper suggests modifying actuators to supply continuous control inputs before implementing optimal control algorithms for maximum profit.http://www.sciencedirect.com/science/article/pii/S2214317323000586Greenhouse climateOptimal controlOn–offMixed-integerPulse width modulationProfit
spellingShingle Dan Xu
Yanfeng Li
Anguo Dai
Shumei Zhao
Weitang Song
Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
Information Processing in Agriculture
Greenhouse climate
Optimal control
On–off
Mixed-integer
Pulse width modulation
Profit
title Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
title_full Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
title_fullStr Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
title_full_unstemmed Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
title_short Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation
title_sort model based quantitative analysis in two time scale decomposed on off optimal control of greenhouse cultivation
topic Greenhouse climate
Optimal control
On–off
Mixed-integer
Pulse width modulation
Profit
url http://www.sciencedirect.com/science/article/pii/S2214317323000586
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AT anguodai modelbasedquantitativeanalysisintwotimescaledecomposedonoffoptimalcontrolofgreenhousecultivation
AT shumeizhao modelbasedquantitativeanalysisintwotimescaledecomposedonoffoptimalcontrolofgreenhousecultivation
AT weitangsong modelbasedquantitativeanalysisintwotimescaledecomposedonoffoptimalcontrolofgreenhousecultivation