中文摘要：

温室温度系统由于受到室外气象条件、温室的覆盖材料、温室的结构、温室作物栽培方式、品种和生长等因素影响,具有大时延、非线性、强干扰、时变的特点,基于参数的模型难以在线描述模型结构.为此提出了一种用有限脉冲响应（finite impulse response,FIR）描述温度系统、通过脉冲响应序列的稀疏性辨识系统时延的方法.首先分析时滞系统FIR序列的稀疏性;然后根据压缩感知理论,利用较少的测量数据恢复出系统输入量对应的FIR序列,得到系统的时滞特性;最后依据模型的结构辨识模型的参数.通过实验数据辨识得到室外温度、太阳辐射强度、湿帘对应的时间延迟分别为6分钟、1分钟和1分钟,与温室温度系统的机理分析一致.由于温室温度控制设备无法实现连续控制,因此在建模时将设备状态纳入模型中,建立了湿帘-风机作用下的温室温度系统模型.仿真表明,在湿帘-风机关闭的和开启的情况下,模型拟合度分别达到94.68%和94.14%,说明该模型具有较高的可信度.

英文摘要：

Due to the effect of outside meteorological conditions, greenhouse covering materials, greenhouse structure and the growth and variety of greenhouse crops and their cultivation methods, a greenhouse temperature system has the characteristics of large time delay, nonlinearity, strong external noise disturbances, time variance. Parameter modeling can hardly describe model structures online. A method was thus proposed, which uses the finite impulse response（FIR） model to describe the temperature system and identi{y the time delay through the sparsity of FIR sequences. First, the sparsity of FIR sequences were analyzed. Then, according to the compressed sensing theory, a relatively small amount of data to recover the FIR sequences by solving the sparse optimization problems, hereby obtaining the timedelay property of the system. Finally, the parameters of FIR model were identified. The time delay of the outside temperature, outside solar radiation, cooling pad, is 6 minutes, 1 minute and 1 minute, respectively. These results are consistent with the mechanism model of the greenhouse temperature system. As the control equipment is incapable of continuous control, the ＂on＂ and ＂off＂ status of the equipment was brought into the model which was built under the effect of the Wet Curtain-Fan. The fitting of the model was 94.68%, 94.14% when the Wet Curtain-Fan was on or off, suggesting that the model has higher credibility.