Multiobjective hierarchical control architecture for greenhouse crop growth |
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| Authors: | A Ramírez-Arias F Rodríguez JL Guzmán M Berenguel |
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| Affiliation: | 1. Área de Agronomía, Universidad Autónoma de Chapingo, km 38.5 carr. Mexico-Texcoco, 56200, Chapingo, Mexico;2. Department of Lenguajes y Computación, University of Almería, Ctra. Sacramento s/n, 04120 Almería, Spain;1. Aix Marseille Université, CNRS, ENSAM, LSIS UMR 7296, 13397 Marseille, France;2. Université de Toulon, CNRS, LSIS UMR 7296, 83957 La Garde, France;3. LIX (UMR CNRS 7161), École polytechnique, 91128 Palaiseau, France;4. AL.I.E.N. (Algèbre pour Identification & Estimation Numériques), 24-30 rue Lionnois, BP 60120, 54003 Nancy, France;1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, PR China;2. Mathematical and Statistical Methods Group (Biometris), Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands;1. Department of Energy Engineering, Sharif University of Technology, Tehran, Iran;2. School of Forestry & Environment, Center for Industrial Ecology, Yale University, USA;3. Institute of Environmental Engineering, Chair of Ecological System Design, ETH Zurich, Zurich, Switzerland;1. Farm Technology Group, Wageningen University, P.O. Box 16, NL-6700AH Wageningen, the Netherlands;2. Bontsema Consultancy, Johan Kievietstraat 10, NL-6708SP Wageningen, the Netherlands;3. Biobased Chemistry & Technology, Wageningen University, P.O. Box 17, NL-6700AA Wageningen, the Netherlands;1. State Key Lab Fluid Power Transmiss & Control, Zhejiang University, Hangzhou 310027, PR China;2. Key Laboratory of E & M, Ministry of Education Zhejiang Province, Zhejiang University of Technology, Hangzhou 310014, PR China;3. Institute of Modern Agricultural Science & Engineering, Tongji University, Shanghai 200092, PR China |
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| Abstract: | The problem of determining the trajectories to control greenhouse crop growth has traditionally been solved by using constrained optimization or applying artificial intelligence techniques. The economic profit has been used as the main criterion in most research on optimization to obtain adequate climatic control setpoints for the crop growth. This paper addresses the problem of greenhouse crop growth through a hierarchical control architecture governed by a high-level multiobjective optimization approach, where the solution to this problem is to find reference trajectories for diurnal and nocturnal temperatures (climate-related setpoints) and electrical conductivity (fertirrigation-related setpoints). The objectives are to maximize profit, fruit quality, and water-use efficiency, these being currently fostered by international rules. Illustrative results selected from those obtained in an industrial greenhouse during the last eight years are shown and described. |
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