现代温室温度系统在线建模  

On-line Modeling of Modern Greenhouse Temperature System

作　　者：李晋[1] 秦琳琳[1] 吴刚[1] 苑媛[1] 吕旭涛[1] 

机构地区：[1]中国科学技术大学自动化系,安徽合肥230027

出　　处：《信息与控制》2008年第4期500-508,共9页Information and Control

基　　金：国家863计划资助项目(2006AA10Z253);新世纪优秀人才支持计划资助项目(NCET-04-0564);安徽省优秀青年科技基金资助项目

摘　　要：在分析温室温度系统机理模型的基础上,分别采用ARMAX模型和ARIMAX模型描述温度系统.选择温室外温度、相对湿度、太阳辐射强度和风速作为系统扰动输入变量,选择温室内温度作为系统输出变量.采用统计假设检验和模型拟合度分析相结合的方法确定模型结构,采用渐消记忆递推增广最小二乘法在线辨识模型参数,并构造智能监督级监控在线建模过程.最后对4输入或3输入(忽略风速)的ARMAX模型或ARIMAX模型相互组合,总计4种模型的在线建模及仿真结果进行了对比分析.仿真试验结果表明,带智能监督级的渐消记忆递推增广最小二乘在线建模能够较好地描述现代温室温度系统的动力学特性.The mechanism models of the greenhouse temperature system are analyzed, and then the temperature system is described respectively with auto regressive moving average models with external input （ARMAX） and auto regressive integrated moving average models with external input （ARIMAX）. The outside air temperature, relative humidity, global solar radiation and wind speed are used as the input variables of the system, and the inside air temperature is used as the output variable of the system. Statistical hypothesis test and model fitness analysis are used together to select the model structure, gradually oblivious recursive extended least squares method is adopted to identify the model parameters on line, and an intelligent supervisory segment is devised to monitor the on-line modeling process. Finally it is investigated to what extent ARMAX and ARIMAX with 4 input variables or 3 input variables （wind speed is omitted） can be used to describe the greenhouse inside air temperature system. The results of the modeling and simulation experiments indicate that the gradually oblivious recursive extended least squares with intelligent supervisory segment can satisfactorily characterize the dynamic features of the greenhouse temperature system.

关 键 词：温室 小气候 在线建模 系统辨识 ARMAX ARIMAX 智能监督级 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] S625.5[自动化与计算机技术—计算机科学与技术]