摘要
针对传统控制方法无法综合考虑温室环境参数相互关联和影响的不足,提出用RBF网络进行温室建模,用FALCON进行温度、湿度、光照等参数控制的方法。仿真结果表明,该方法对温室标准环境参数拟合效果好,控制过程响应快、无震荡、超调量小、稳态误差小。利用该方法能提高温室控制系统的精确性、适应性和鲁棒性。
In view of the fact that controlling methods can't consider colligatedly the problems of the environment parameters of greenhouse associating with and influencing others, the method was established by using RBF net to model the environment of greenhouse and FALCON so as to realize the controlling of temperature,humidity,and illumination. Experimentation results show that the standard environment parameters have been well approached, and the controlling process has good velocity response, with characteristics of no shaking, little overshoot and steady state error. This method can be used to improve accuracy and robustness of the greenhouse control system.
出处
《西北农林科技大学学报(自然科学版)》
CSCD
北大核心
2007年第8期189-192,共4页
Journal of Northwest A&F University(Natural Science Edition)
基金
陕西省自然科学基金项目(2004D12)
关键词
RBF网络
FALCON
温室环境参数控制
RBF neural network
FALCON network
environment data controlling for greenhouse