摘要
针对传统温室控制系统中存在的控制方案达不到最优化、反应滞后以及控制器调节不同步等问题,提出了基于全局变量的优化预测方法。该方法将温室内部温湿度与光照等数据、作物的生长状况、控制器当前状态、温室外部环境的相应数据及当地天气情况进行融合,利用各全局变量,通过数学模型得出温室未来环境状况的短期预测值,采用神经网络实现控制,解决了温室控制中的大滞后和大惯性等问题。仿真结果证明了该模型的有效性及合理性,对温室内气候智能控制的发展具有一定的参考价值。
The paper deals with the problem of modeling and control of greenhouses inside climate based on the global variable optimization method for prediction.A mathematical model of greenhouse climate was established.Confronted with problem of greenhouse climate control existed in conventional controller such as control system is reactive,the adjustment of the actuators is not synchronized,control scheme is not optimal.In the method,inside the greenhouse temperature,humidity,radiation values,crop growth status,current state of actuators,external environment and the local weather conditions by data fusion as the-global variables.Then,the greenhouse of the future state of the environment short-term predictive value are obtained by mathematical model of neural network control.The simulation results testify the validity and reasonability of the global optimization prediction control strategy for the climate control in the greenhouse,and the achievement has certain reference value for the development in intelligent control of the greenhouse microclimate.
出处
《农机化研究》
北大核心
2013年第10期26-29,共4页
Journal of Agricultural Mechanization Research
基金
河北省科技支撑计划项目(11227179)
河北省高等学校科学技术研究青年基金项目(z2011271)
关键词
温室
智能控制
全局变量
优化预测
神经网络
greenhouse
intelligent control
global variable
optimization prediction
neural network
