引用本文:
【打印本页】   【下载PDF全文】   查看/发表评论  下载PDF阅读器  关闭
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 885次   下载 835 本文二维码信息
码上扫一扫!
分享到: 微信 更多
基于FALCON的温室自动控制方法研究
张 静, 何东健, 李书琴
西北农林科技大学 信息工程学院
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。
关键词:  RBF网络  温室环境参数控制
DOI:
分类号:
基金项目:陕西省自然科学基金项目(2004D12)
Study on greenhouse automatic control system based on FALCON
Abstract:
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.
Key words:  RBF neural network  FALCON network  environment data controlling for greenhouse