An Optimized Control Method of Multifactor for Greenhouse Microclimate Based on Crop Photosynthesis Rate

被引:0
|
作者
Huang, Xianzhou [1 ]
Xu, Lihong [1 ]
Wei, Ruihua [1 ]
机构
[1] Tongji Univ, Coll Elect & Informat Engn, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
photosynthesis rate; multifactor; greenhouse model; resource cost; RESPONSE CURVES; MODEL; LIGHT; CLIMATE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
According to the recent situation that there is less feasible greenhouse controlling strategy been presented, an optimized energy-saving control method of multifactor for greenhouse is proposed in this paper considering of photosynthetic rate of crops. The data of crops photosynthesis rates in greenhouse are acquired by field tests. Using the data of solar radiation and CO2 concentration inside greenhouse in Jiading, Shanghai, the light-photosynthesis and CO2-photosynthesis response curves are fitted respectively. Thus, via these fitting photosynthesis models and the collected climate data, we could get the real-time crops photosynthetic rate, which is modified in the respect of other greenhouse environment factors, such as temperature and CO2 concentration. Finally, take the environmental multifactorial control algorithm, already in use, as the basic control strategy, a feasible control output is computed and given, so as to promote crop photosynthesis yield and reduce greenhouse control cost. This control strategy integrates with three simplified models, crops growth model, greenhouse control model and energy consumption model.
引用
收藏
页码:482 / 487
页数:6
相关论文
共 50 条
  • [31] An IoT-based Hierarchical Control Method for Greenhouse Seedling Production
    Feng, Jingyuan
    Hu, Xiangpei
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021), 2021, 192 : 1954 - 1963
  • [32] Environment control method in greenhouse based on global variable prediction model
    Cheng, Man
    Yuan, Hongbo
    Cai, Zhenjiang
    Wang, Nan
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2013, 29 (SUPPL1): : 177 - 183
  • [33] The Research of Control Method of Greenhouse Based on Global Variable Prediction Model
    Cheng Mao
    Yuan HongBo
    Zhang Meng
    Cheng Man
    3RD INTERNATIONAL CONFERENCE ON APPLIED ENGINEERING, 2016, 51 : 277 - 282
  • [34] Slip rate control method based on model predictive control
    Li, Shou-Tao
    Yang, Lu
    Qu, Ru-Yi
    Sun, Peng-Peng
    Yu, Ding-Li
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2024, 54 (09): : 2687 - 2696
  • [35] An Optimal Control Method for Greenhouse Climate Management Considering Crop Growth's Spatial Distribution and Energy Consumption
    Li, Kangji
    Mi, Yanhui
    Zheng, Wen
    ENERGIES, 2023, 16 (09)
  • [36] Monitoring method of crop growth environment in greenhouse based on embedded 5G communication technology
    Wang, Qiong-Pei
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL TECHNOLOGY AND MANAGEMENT, 2024, 27 (03) : 186 - 199
  • [37] Robust control of a space robot based on an optimized adaptive variable structure control method
    Shi, Lingling
    Yao, He
    Shan, Minghe
    Gao, Qingbin
    Jin, Xin
    AEROSPACE SCIENCE AND TECHNOLOGY, 2022, 120
  • [38] Network data acquisition method based on crop pest control knowledge
    Han Chunyu
    Fang Jiandong
    Li Bajin
    Zhao Yudong
    PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21), 2021,
  • [39] Predictive control method for greenhouse measurement and control system based on switch devices optimization combination
    Shen, Min
    Zhang, Rongbiao
    Sheng, Biqi
    Song, Yongxian
    Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural Machinery, 2011, 42 (02): : 186 - 189
  • [40] Crop Photosynthetic Performance Monitoring Based on a Combined System of Measured and Modelled Chloroplast Electron Transport Rate in Greenhouse Tomato
    Yu, Wenjuan
    Koerner, Oliver
    Schmidt, Uwe
    FRONTIERS IN PLANT SCIENCE, 2020, 11