The System of Environment Control of Botanic Garden Greenhouses

被引:0
作者
Dik, D. [1 ]
Polyakova, E. [1 ]
Chelovechkova, A. [1 ]
Moskvin, V. [1 ]
Nikiforova, T. [1 ]
机构
[1] Kurgan State Univ, Kurgan, Russia
来源
2018 INTERNATIONAL SCIENTIFIC MULTI-CONFERENCE ON INDUSTRIAL ENGINEERING AND MODERN TECHNOLOGIES (FAREASTCON) | 2018年
关键词
greenhouse environment control; remote monitoring; neural-network; adaptive control; Genetic Algorithm; PREDICTIVE CONTROL; OPTIMIZATION; MODEL;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Monitoring and control of environment has a key role for garden greenhouses. To ensure proper plant growth and development, parameters of environment, in the first place, temperature and humidity must be within certain optimal range. Each plant culture, grown in a greenhouse, has its own special requirements for environment conditions, providing it with suitable environment for growth. What is more, for one and the same culture optimal regimes of temperature and humidity change, depending on the stage of plant growth and development. Also, optimal parameters of environment for a plant depend on the time of the day, especially from the point of view of light. Control of optimal environment in a greenhouse ensures necessary level of transpiration, plant nutrition and prophylactic of plant damage because of the deficit of some nutrients (for example, calcium). Moreover, temperature control and relative humidity ensures prophylactic of plant diseases, especially different types of rot, developing in the conditions of high humidity. So, environment monitoring and control in greenhouses is one of the highest priorities while cultivating plants. In the article the architecture of the system of environment monitoring and control in the greenhouses of a botanic garden is presented. This system of monitoring and control is built with the use of program products with an open source software opeHAB and Zabbix. The use of popular open program platforms allows getting reliable and economical solution for the construction of the system of greenhouse monitoring and control, at the same time giving an opportunity of remote monitoring and sending emergency messages to the service personnel through the system of instant message exchange. To control greenhouse environment adaptive algorithm of control is offered. Adaptability of control is based on neural-network climatic model of a greenhouse. On the basis of a climatic model with the help of Genetic Algorithm the search for optimal control actions is carried out. Whereas as a criterion of control quality minimization of error with the necessary paths of climate change in the greenhouse is chosen.
引用
收藏
页数:7
相关论文
共 30 条
  • [1] Environmental control for plants on Earth and in space
    Albright, LD
    Gates, RS
    Arvanitis, KG
    Drysdale, AE
    [J]. IEEE CONTROL SYSTEMS MAGAZINE, 2001, 21 (05): : 28 - +
  • [2] [Anonymous], 2004, International Journal of Computational Cognition
  • [3] [Anonymous], 2008, IFAC P VOL, DOI DOI 10.3182/20080706-5-KR-1001.01616
  • [4] [Anonymous], 2011, Int. J. Adv. Comput. Technol, DOI [10.4156/ijact.vol3.issue9.43, DOI 10.4156/IJACT.VOL3.ISSUE9.43]
  • [5] Greenhouse climate modelling and robust control
    Bennis, N.
    Duplaix, J.
    Enea, G.
    Haloua, M.
    Youlal, H.
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2008, 61 (02) : 96 - 107
  • [6] Bettini L., 2016, IMPLEMENTING DOMAIN, P426
  • [7] Model-based predictive control of greenhouse climate for reducing energy and water consumption
    Blasco, X.
    Martinez, M.
    Herrero, J. M.
    Ramos, C.
    Sanchis, J.
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2007, 55 (01) : 49 - 70
  • [8] Fuzzy greenhouse climate control system based on a field programmable gate array
    Castaneda-Miranda, Rodrigo
    Ventura-Ramos, Eusebio, Jr.
    del Rocio Peniche-Vera, Rebeca
    Herrera-Ruiz, Gilberto
    [J]. BIOSYSTEMS ENGINEERING, 2006, 94 (02) : 165 - 177
  • [9] Cavaness C., 2006, QUARTZ JOB SCHEDULIN, P304
  • [10] Greenhouse air temperature predictive control using the particle swarm optimisation algorithm
    Coelho, JP
    Oliveira, PBD
    Cunha, JB
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2005, 49 (03) : 330 - 344