基于模糊控制的温室智能控制系统实现路径

Implementation Path of Greenhouse Intelligent Control System Based on Fuzzy Control

研究了温室智能控制系统的实现路径,提出的智能控制方案基于模糊神经网络,通过温室环境数学模型的构建实现对室内外环境因素的有效控制,并据此实现通风、喷雾和加热量的微分式的获取。在此基础上结合自适应模糊神经推理系统,并以温、湿度差作为输入,获取控制输出后,再用遗传算法优化控制器的输出比例因子,使控制响应速度和稳定性得到进一步提高。检测结果表明该系统能够对环境设置值进行快速且稳定地追踪,具有良好的控制效果。

This paper mainly studies the realization path of greenhouse intelligent control system. The proposed intelligent control scheme is based on fuzzy neural network. Based on the indoor and outdoor environmental factors, a mathematical model of greenhouse environment is completed, and ventilation and spraying are realized accordingly. And the differential equation of heating quantity, based on the combination of adaptive fuzzy neural inference system, is established. The equation is with the input of temperature and humidity difference. After the acquisition of control output, fuzzy reasoning is used to optimize the propotion factor of the controller through genetical algorithm. The algorithm can further improve the control response speed and stability. The test results show that the system can track the environmental settings and has good control effects.