Temperature and Humidity Deficit Model for Greenhouses Based on System Identification Method with Two-Variable Input: Quick Setup and Model Evaluation during Spring and Fall
Temperature and Humidity Deficit Model for Greenhouses Based on System Identification Method with Two-Variable Input: Quick Setup and Model Evaluation during Spring and Fall
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DOI：
10.3173/air.30.1
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发表时间：
2021-04
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通讯作者：
Shin Nakayama;Taku Takada;Ryushi Kimura;K. Oka
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作者：
Shin Nakayama;Taku Takada;Ryushi Kimura;K. Oka
建立温湿度模型对于温室的预测控制具有重要意义。在这项研究中，我们开发了温度和HD模型，通过使用系统识别方法与少量的参数，用于在约100平方米的小型温室中快速设置控制环境。温度和HD模型由线性自回归外生（ARX）和输出误差（OE）模型创建。建模数据是在2018年秋季和2019年春季不加热生长绿色辣椒的温室中测量的。温室空气温度由室外空气温度和室内太阳辐射输出。温室HD是从外部HD和内部太阳辐射输出的。5天的数据对于建立模型是足够的。将输出温度（和HD）与测量的瓦尔-ues进行比较，我们发现拟合优度非常准确，在秋季可以保持70%（80%）1周，在春季可以保持70%（75%）2周。由于该设备需要的传感器很少，并且模型可以在安装后一周内使用，因此温度和HD模型可以用于没有广泛传感器网络的小型温室。
Building a model of temperature and humidity deficit (HD) is important for the predictive control of greenhouses. In this study, we developed temperature and HD models by using the system identification method with a small number of parameters for the quick setup of a control environment in a small greenhouse of about 100 m 2 . The temperature and HD models were created from linear auto-regressive exogenous (ARX) and output error (OE) models. The modeling data were measured in a greenhouse where green peppers were grown unheated in the fall of 2018 and the spring of 2019. The greenhouse air temperature is output from the outside air temperature and the interior solar radiation. The greenhouse HD is output from the outside HD and the interior solar radiation. Data of 5 days are sufficient for building the model. Comparing the output temperature (and HD) with the measured val -ues, we found that the goodness of fit was highly accurate and could be maintained at 70% (80%) for 1 week in the fall and 70% (75%) for up to 2 weeks in the spring. Because the device needs few sensors and the model can be used within a week of installa-tion, the temperature and HD models can be used in small greenhouses without an extensive sensor network.