Neural Network Predictive Control in a Naturally Ventilated and Fog Cooled Greenhouse

被引:2
|
作者
Fitz-Rodriguez, E. [1 ]
Kacira, M. [1 ]
Villarreal-Guerrero, F. [1 ]
Giacomelli, G. A. [1 ]
Linker, R. [2 ]
Kubota, C. [3 ]
Arbel, A. [4 ]
机构
[1] Univ Arizona, Dept Agr & Biosyst Engn, Tucson, AZ 85719 USA
[2] Civil & Environm Engn Techn, Haifa, Israel
[3] Univ Arizona, Sch Plant Sci, Tucson, AZ 85721 USA
[4] Agr Res Org, Bet Dagan, Israel
关键词
greenhouse climate control; dynamic neural network model; evaporative fog cooling; AIR-TEMPERATURE; SYSTEM; MODEL; CLIMATE;
D O I
10.17660/ActaHortic.2012.952.2
中图分类号
S6 [园艺];
学科分类号
0902 ;
摘要
Passive ventilation in greenhouse production systems is predominant worldwide, limiting its usability and profitability to specific regions or for short production cycles. Evaporative fogging systems have increasingly been implemented in Arid and Semi-Arid regions to extend the production cycle during the warmest season, and also to achieve near-optimum environments for year-round production. However, appropriate control strategies for evaporative fogging systems are still lacking or limited despite its reported benefits in terms of environmental uniformity and potential savings in water and energy usage, when compared to fan and pad systems. The present research proposes a neural network predictive control approach for optimizing water and energy usage in a naturally ventilated and fog cooled greenhouse while providing a near-optimum and uniform environment for plant growth. As a first step the dynamic behavior of the greenhouse environment, defined by air temperature and relative humidity, was characterized by means of system identification using a recurrent dynamic network (NARMX). The multi-step ahead prediction capability of NARMX allows for the optimization of the control actions (vent configuration and fogging rate) for its implementation in the NN predictive control scheme. Greenhouse environmental data from a set of experiments consisting of several vent configurations (0/50, 0/100, 50/50, 50/100 and 100/100, percent opening of the side/roof vents) and three fogging rates (17.5, 22.3 and 27.0 g m(-2) min(-1)) during several days throughout the year were used in the system identification process. The resulting NN model accurately predicted the dynamic behavior of the greenhouse environment, having coefficients of determination (R-2) of 0.99 for each parameter (air temperature and relative humidity). These NN model will be incorporated into the NN predictive control scheme and its feasibility is in a naturally ventilated greenhouse equipped with a variable-rate fogging system is discussed, while achieving a greenhouse environment within defined permissible ranges of air temperature and relative humidity.
引用
收藏
页码:45 / 52
页数:8
相关论文
共 50 条
  • [1] Evaporation characteristics in a naturally ventilated, fog-cooled greenhouse
    Abdel-Ghany, Ahmed M.
    Goto, Eiji
    Kozai, Toyoki
    [J]. RENEWABLE ENERGY, 2006, 31 (14) : 2207 - 2226
  • [2] Dynamic modeling of the environment in a naturally ventilated, fog-cooled greenhouse
    Abdel-Ghany, Ahmed M.
    Kozai, Toyoki
    [J]. RENEWABLE ENERGY, 2006, 31 (10) : 1521 - 1539
  • [3] Research on Neural Network Model for Greenhouse Temperature Predictive Control
    Qi, Kai
    Chen, Yifei
    Liu, Baicheng
    Du, Shangfeng
    [J]. PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION, 2013, 254 : 551 - 557
  • [4] On the determination of the overall heat transmission coefficient and soil heat flux for a fog cooled, naturally ventilated greenhouse: Analysis of radiation and convection heat transfer
    Abdel-Ghany, Ahmed M.
    Kozai, Toyoki
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2006, 47 (15-16) : 2612 - 2628
  • [5] Air velocities in a naturally ventilated greenhouse
    Teitel, M.
    Liran, O.
    Barak, M.
    Tanny, J.
    [J]. PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON GREENHOUSE COOLING, 2006, (719): : 189 - +
  • [6] Microclimate Distribution in a Greenhouse Cooled by a Fog System
    Katsoulas, N.
    Kittas, C.
    Bartzanas, T.
    [J]. XXVIII INTERNATIONAL HORTICULTURAL CONGRESS ON SCIENCE AND HORTICULTURE FOR PEOPLE (IHC2010): INTERNATIONAL SYMPOSIUM ON GREENHOUSE 2010 AND SOILLESS CULTIVATION, 2012, 927 : 773 - 778
  • [7] Statistical modelling of the microclimate in a naturally ventilated greenhouse
    Litago, J
    Baptista, FJ
    Meneses, JF
    Navas, LM
    Bailey, BJ
    Sánchez-Girón, V
    [J]. BIOSYSTEMS ENGINEERING, 2005, 92 (03) : 365 - 381
  • [8] Naturally ventilated greenhouse designs for optimum cooling
    Short, TH
    Lee, I
    Stowell, RR
    [J]. PROCEEDINGS OF THE FIFTH INTERNATIONAL SYMPOSIUM ON PROTECTED CULTIVATION IN MILD WINTER CLIMATES: CURRENT TRENDS FOR SUSTAINABLE TECHNOLOGIES, VOLS I AND II, 2001, (559): : 177 - 182
  • [9] A naturally ventilated greenhouse for temperate vegetable production in the tropics
    Kamaruddin, R
    Bailey, BJ
    Montero, JI
    [J]. PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON DESIGN AND ENVIRONMENTAL CONTROL OF TROPICAL AND SUBTROPICAL GREENHOUSES, 2002, (578): : 97 - 103
  • [10] Modeling naturally ventilated greenhouse designs for Mediterranean climates
    Kacira, M
    Short, TH
    Stowell, R
    [J]. INTERNATIONAL SYMPOSIUM ON GREENHOUSE MANAGEMENT FOR BETTER YIELD AND QUALITY IN MILD WINTER CLIMATES, 1998, (491): : 113 - 118