Hybrid Control of Greenhouse Temperature System Based on Crop Temperature Integration Theory

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• 英文论文题名：Hybrid Control of Greenhouse Temperature System Based on Crop Temperature Integration Theory
• 论文作者：MA Jiao ; DU Yuan Sen ; QIN Lin Lin ; WU Gang ; WANG Da Xin
• 英文论文作者：MA Jiao ; DU Yuan Sen ; QIN Lin Lin ; WU Gang ; WANG Da Xin ; Department of Automation ; University of Science & Technology of China
• 年：2017
• 作者机构：Department of Automation,University of Science & Technology of China;
• 英文论文关键词：Greenhouse ; Temperature Control ; Hybrid Automata ; Temperature Integration
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：S625
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：450k
• 原文格式：D
• 会议级别：全国

摘要

Greenhouse temperature system is a typical hybrid system, on account of the inputs of the system include discrete state variables, namely switching status of the environmental control equipment, as well as continuous state variables, namely the external environment factors. Therefor this paper presents a hybrid automata for greenhouse system based on crop temperature integration theory. Firstly, the model parameters of each discrete state is identified for transforming the value of outdoor environment factors into the predictive value of indoor temperature. Then taking the predictive value as the switching condition of the discrete states, and the hybrid control system based on predictive temperature is designed. At last, on the basis of the temperature accumulation of the previous period, the temperature plane can be divided into three different subareas, adjusting the setpoint curve dynamically. Experimental results show that the hybrid automata could switch the device status in a timely and reasonable manner, and there is a significant reduction to action frequency of equipment by applying temperature integration theory.
Greenhouse temperature system is a typical hybrid system, on account of the inputs of the system include discrete state variables, namely switching status of the environmental control equipment, as well as continuous state variables, namely the external environment factors. Therefor this paper presents a hybrid automata for greenhouse system based on crop temperature integration theory. Firstly, the model parameters of each discrete state is identified for transforming the value of outdoor environment factors into the predictive value of indoor temperature. Then taking the predictive value as the switching condition of the discrete states, and the hybrid control system based on predictive temperature is designed. At last, on the basis of the temperature accumulation of the previous period, the temperature plane can be divided into three different subareas, adjusting the setpoint curve dynamically. Experimental results show that the hybrid automata could switch the device status in a timely and reasonable manner, and there is a significant reduction to action frequency of equipment by applying temperature integration theory.

引文

[1]Luo Weihong Dai Jianfeng,Qiao Xiaojun,and Wang Cheng.Model-based decision support system for greenhouse heating temperature set point optimization.Transactions of the Chinese Society of Agricultural Engineering,11:041,2006.
    [2]Wang Ziyang,Qin Linlin,Wu Gang,and L¨u Xutao.Modeling of greenhouse temperature-humid system and model predictive control based on switching system control.Transactions of the Chinese Society of Agricultural Engineering,2008(7),2008.
    [3]Lili Ma,Jianwei Ji,and Chaoxing He.The study of greenhouse temperature modeling based on fuzzy neural network.In E-Product E-Service and E-Entertainment(ICEEE),2010International Conference on,pages 1-4.IEEE,2010.
    [4]IM Al-Helal,SA Waheeb,AA Ibrahim,MR Shady,and AM Abdel-Ghany.Modified thermal model to predict the natural ventilation of greenhouses.Energy and Buildings,99:1-8,2015.
    [5]Ying-Hao Yu,Chun-Hsien Yeh,Yuh-Kuang Chen,PingHsuan Lai,Pei-Yin Chen,and Chih-Yuan Lien.A practical survey of evaporative cooling system for orchids greenhouse.In Robot,Vision and Signal Processing(RVSP),2013 Second International Conference on,pages 303-306.IEEE,2013.
    [6]Abdelhafid Hasni,Rachid Taibi,Belkacem Draoui,and Thierry Boulard.Optimization of greenhouse climate model parameters using particle swarm optimization and genetic algorithms.Energy Procedia,6:371-380,2011.
    [7]Huihui Yu,Yingyi Chen,Shahbaz Gul Hassan,and Daoliang Li.Prediction of the temperature in a chinese solar greenhouse based on lssvm optimized by improved pso.Computers and Electronics in Agriculture,122:94-102,2016.
    [8]Linlin Qin,Chun Shi,Qing Ling,Gang Wu,Jun Wang,and Xiaojun Qiao.Predictive control of greenhouse temperature based on mixed logical dynamical systems.Intelligent Automation and Soft Computing,16(6):1207-1214,2010.
    [9]E Mirzaee-Ghaleh,M Omid,A Keyhani,and MJ Dalvand.Comparison of fuzzy and on/off controllers for winter season indoor climate management in a model poultry house.Computers and Electronics in Agriculture,110:187-195,2015.
    [10]Fathi Fourati.Multiple neural control of a greenhouse.Neurocomputing,139:138-144,2014.
    [11]Goran Martinovi and Janos Simon.Greenhouse microclimatic environment controlled by a mobile measuring station.NJAS-Wageningen Journal of Life Sciences,70:61-70,2014.
    [12]AP Montoya,JL Guzm′an,F Rodr′?guez,and JA S′anchezMolina.A hybrid-controlled approach for maintaining nocturnal greenhouse temperature:Simulation study.Computers and Electronics in Agriculture,123:116-124,2016.
    [13]Lala H Rajaoarisoa,Nacer K M’Sirdi,and Jean F Balmat.Acase study of a hybrid controller design of a class of hybrid system application to a greenhouse micro-climate control.In Communications,Computing and Control Applications(CC-CA),2012 2nd International Conference on,pages 1-6.IEEE,2012.
    [14]Chu Zhudong,Qin Linlin,Lu Linjian,Ma Guoqi,and Wu Gang.Hybrid controller design and analysis for experimental greenhouse temperature system.Journal of University of Science and Technology of China,45(4):268-274,2015.
    [15]Seyed Mohamed Buhari,Nor Jaidi Tuah,Kim Onn Chong,Sei Guan Lim,and Abd Ghani Naim.Fuzzy based room temperature control by integrating sensors and cameras with a grid.In Computational Intelligence for Communication Systems and Networks(CIComms),2013 IEEE Symposium on,pages 61-65.IEEE,2013.