现代温室温度混杂系统的建模

Modelling of Temperature Hybrid System in a Modern Greenhouse

为了解决中国温室系统输入输出变量连续而环境控制设备动作离散的建模问题,通过将室外环境因子作为系统的连续输入量,天窗的开启和关闭状态作为离散变量,室内温度作为连续输出量,建立了温室混杂自动机的模型.首先采用有外源输入的自回归滑动平均模型描述每个子系统,其次,采用统计假设检验法与模型机理相结合的方法确定模型结构,然后,采用递推增广最小二乘法辨识模型参数,智能级监督模型参数的收敛性,最后,依据有限状态自动机的基本模型建立温度混杂自动机.采用实测数据进行仿真,该温度混杂自动机模型的拟合度可达90%以上,混杂系统控制的最大预测误差为2.8℃,能较好地预测温室温度系统的动态特性.

In order to establish the Chinese greenhouse system models with the characteristics of continuous input variables and discrete action climate control equipments, the authors proposed a model greenhouse temperature hybrid system with the control of ventilator. Outside environment factors were used as continuous input variables, while the switch of the ventilator was used as the states of hybrid automata and the inside temperature was used as continuous output variable. So the temperature system hybrid automaton model was established. Each sub model was developed by linear auto-regression moving average with extra input model for air temperature system. Statistic hypothesis test and model mechanism were applied together to select the model structure, and gradually extended least squares method was adopted to identify the model parameters on line. Moreover, an intelligent supervisory segment was devised to monitor and fix problems appearing during the on-line modeling process. Experiments were carried out in a greenhouse to validate the model. It is concluded that the temperature of the hybrid automaton model of fitting degree can reach more than 90% and the maximum error of hybrid control system is 2.5 ~C. The results show the algorithm is an effective measure to predict the temperature system