【摘要】 为实现通过控制温室通风口开度来调节室内温湿环境的目的,首先根据热量平衡和水汽质量平衡原理构建了温室气温和湿度的动态变化数学模型,然后基于自适应神经模糊控制系统(ANFIS),分别选择梯形和高斯型隶属度函数完成了2类通风控制器的设计,其中包括控制变量的选取、论域的量化、模糊集的定义、隶属函数的选择及控制器的训练等过程.最后将控制器与温室模型相结合,利用Matlab构建了以通风为输入、以室内温湿度为输出的Simulink仿真框图,并利用2类典型天气下的实测资料对控制系统进行了仿真检验.仿真结果表明:无论晴天还是阴雨天,采用梯形隶属度函数的温室模糊控制器比高斯型控制器更敏感,对室内温湿环境的变化具有更好的控制效果,有效减小了温湿度变化率的波动幅度,起到了优化调控作用.更多还原

【Abstract】 To regulate the temperature and humidity environment in greenhouse by controlling vent ope-ning intellectively,on the principle of thermal balance and water vapor quality balance,two non-linear differential models for air temperature and humidity inside greenhouse respectively were constructed.Based on ANFIS,with trapezoid and Gaussian membership functions respectively,two fuzzy controllers for greenhouse ventilation control were set up,including choosing variables,quantifying the domain,defining fuzzy sets,choosing membership functions and controller training.By combining the controllers and the controlled object,with ventilation as input and greenhouse temperature as output,using Matlab,Simulink simulations were established.By applying observed data of two kinds of typical weather,the performance of two control systems was simulated and tested.The results show that,compared with the Gaussian controller,the greenhouse fuzzy controller with a trapezoid membership function is more sensitive,and has a better control effect on the indoor environment,which effectively reduces the fluctuation extent of temperature and humidity in greenhouse and optimizes control function.The research has certain reference value for the development in intelligent control of the greenhouse microclimate.更多还原