基于分级模糊模型的温室环境控制方法

doi:10.11707/j.1001-7488.20060519

林业科学 ›› 2006, Vol. 42 ›› Issue (5): 104-109.doi: 10.11707/j.1001-7488.20060519

基于分级模糊模型的温室环境控制方法

陈健¹ 姜宇^1,2 杨国辉³

1.东北林业大学机电工程学院,哈尔滨150040；2.哈尔滨工程大学信息与通信工程学院哈尔滨150001；3.哈尔滨工业大学电气工程学院,哈尔滨150001

收稿日期:2005-11-02 修回日期:1900-01-01 出版日期:2006-05-25 发布日期:2006-05-25

Technique for Controlling Greenhouse Environment on Hierarchical Collaborative Structure

Chen Jian¹,Jiang Yu^1,2,Yang Guohui³

1.College of Mechanical and Electrical Engineering, Northeast Forestry University Harbin150040;2.College of Information and Communication Engineering, Harbin Engineering University Harbin 150001;3.College of Electrical Engineering, Harbin Institute of Technology Harbin150001

Received:2005-11-02 Revised:1900-01-01 Online:2006-05-25 Published:2006-05-25

摘要/Abstract

摘要：

提出一种基于分级协同结构的温室环境模糊模型,在建立环境变量物理模型及其子模型的基础上,构建温室环境的分级模糊子模型。试验表明:在保持传统平式结构模糊算法预测精度的同时,基于分级协同结构的温室环境模糊算法减少了规则数目,提高了模糊系统规则的可读牲且降低了子模型规则改变的系统成本。

关键词: 分级协同结构, 模糊控制, 温室环境

Abstract:

Greenhouse environment is a complex and nonlinear system. Flat fuzzy rules adopted settle the problems of input and output for system, however, great number of rules result poor readability. Greenhouse environment model based on hierarchical collaborative structure(HCS) is presented. Hierarchical sub-fuzzy model of greenhouse environment was built on physical sub-model on environment variables. Experiments showed that the fuzzy algorithm of greenhouse environment on hierarchical collaborative structure had merits in reducing the number of rules, advancing readability for rules, lowing system cost and keeping pretty prediction accuracy.

Key words: hierarchical collaborative structure(HCS), fuzzy control, greenhouse environment

陈健姜宇;杨国辉. 基于分级模糊模型的温室环境控制方法[J]. 林业科学, 2006, 42(5): 104-109.

Chen Jian;Jiang Yu;Yang Guohui. Technique for Controlling Greenhouse Environment on Hierarchical Collaborative Structure[J]. Scientia Silvae Sinicae, 2006, 42(5): 104-109.

基于分级模糊模型的温室环境控制方法

Technique for Controlling Greenhouse Environment on Hierarchical Collaborative Structure

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