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作 者:袁洪波[1,2] 李莉[1] 王俊衡[1] N.A.Sigrimis
机构地区:[1]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京100083 [2]河北农业大学机电工程学院,保定071001 [3]希腊雅典农业大学农业工程系,希腊雅典11855
出 处:《农业工程学报》2015年第11期221-227,共7页Transactions of the Chinese Society of Agricultural Engineering
基 金:国家自然科学基金(青年)项目(31301240);河北省自然科学基金项目(C2014204025);河北省高等学校科学研究计划青年基金项目(QN20131083);土壤植物机器系统技术国家重点实验室开放课题基金(2014-SKL-03)
摘 要:温室环境控制领域所研究的大多数智能控制算法复杂程度较高,不适宜实际生产应用,生产型温室大多采用设置静态工作点模式进行简单的环境控制,这种模式无法根据环境变化进行自动调整,浪费了大量的能量。针对这一问题,提出了基于温度积分算法的温室环境控制方法,根作物种类和生长阶段确定期望平均温度值,将全天24 h均分为长度更短的若干时间片,然后利用温度积分原理对每一时间片的温度调节点进行计算,根据得到的温度调节点结合当前实际温度进行环境控制。仿真试验表明,在保持温室内实际平均温度相同的情况下,利用温度积分算法对温室进行环境调节所消耗的能量为静态工作点的模式的64.43%。该方法计算量相对较小,适用于普通的温室环境控制器,能够简单有效地实现节能控制。In recent years, horticulture industry has been rapidly developed in China. The total area of cultivation is about 3.79 million hm2 by the end of 2012, but the climate control methods in actual greenhouse production are still relatively simple. Although many of the advanced intelligent control algorithms have been studied, however, there are two problems of these intelligent algorithms: the first one is the intelligent algorithms depend on the model of the greenhouse at the time of the operation. The control effect is better, only if the greenhouse model is accurate, but the greenhouse is a multivariable complex system with high coupling, so it is difficult to obtain accurate models. In addition, there are many different types of greenhouse in China, and each greenhouse structure may not be exactly the same, so it is inconsistent with the theoretical model. The second problem of intelligent algorithms is a large number of calculations are performed; the requirement is high for greenhouse controller’s processing capability and computing capability. The typical method for the climate control is to configure the static set point in actual greenhouse production, and the energy will be wasted because the static set point can not be automatically adjusted according to the external environment. In order to solve this problem, the greenhouse climate control method based on temperature integration was studied. When using this method, the first thing was to determine the expected average temperature, the maximum temperature and the minimum temperature in a certain period of time according to the type and growth stage of crop. Secondly, the actual average temperature of the current date would be calculated by the expected average temperature and the actual average temperature of previous day. Thirdly, the days were divided intoN equal time intervals, and the length of each interval wasint. The temperature set point of current time intervaln would be calculated according to the actual average temperature and actual avera
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