Modeling and parameter identification of fresh air system based on ANFIS - 文章详情页

作者：

Yang, Jun (Yang, Jun.) | Wang, Li-Li (Wang, Li-Li.) | Chen, Chao (Chen, Chao.) (学者：陈超)

收录：

EI Scopus

摘要：

A　fresh　air　system　with　solar　collectors　and　Latent　Heat　Thermal　Storage　(LHTS)　tank　filled　with　Phase　Change　Material　was　firstly　introduced　in　this　paper.　For　the　mathematical　model　of　the　fresh　air　system　is　difficult　to　accurately　establish,　the　adaptive　neuro-fuzzy　inference　controller　was　proposed　to　realize　the　parameter　identifications　of　the　system　applying　for　the　back-propagation　algorithm　of　BP　neural　network.　The　results　shows　that　the　modeling　and　parameter　identification　method　of　the　algorithm　using　ANFIS　can　approximate　the　characteristics　of　the　fresh　air　system　to　a　great　extent,　and　the　error　is　almost　zero.　©　2010　IEEE.

关键词：

Adaptive control systems Backpropagation algorithms Fuzzy inference Fuzzy neural networks Heat storage Inference engines Parameter estimation Phase change materials

作者机构：

[ 1 ] [Yang, Jun]Automation School, Beijing University of Posts and Telecommunications, Beijing, China
[ 2 ] [Wang, Li-Li]Automation School, Beijing University of Posts and Telecommunications, Beijing, China
[ 3 ] [Chen, Chao]College of Architecture and Civil Engineering, Beijing University of Technology, Beijing, China

通讯作者信息：

电子邮件地址：

yjun@bupt.edu.cn

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