Intelligent dynamic thermal comfort control system with users' learning

被引：0

作者：

Li, Hui ^{[1
,2
,3
]}

Zhang, Qing-Fan ^{[1
]}

Duan, Pei-Yong ^{[2
]}

机构：

[1] School of Control Sci. and Eng., Shandong Univ., Ji'nan 250061, China

[2] Key Lab. of Building Energy Conservation of Shandong Province, Ji'nan 250101, China

[3] Key Lab. of Ministry of Education for Renewable Energy Utilization Technologies in Buildings, Ji'nan 250101, China

来源：

Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) | 2011年 / 43卷 / 02期

关键词：

Energy conservation - Health - Learning algorithms - Fuzzy inference - Control systems - Fuzzy neural networks - Energy utilization;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Considering the fact that the static thermal environment is unfavorable to the human's health since it can reduce the ability of human's heat adaptation, and the dynamic thermal environment is favorable to the human's health as it is similar to the natural environment. A dynamical thermal comfortable control system for the inhabited environment was proposed based on users' learning. The thermal comfort Predicted Mean Vote (PMV) index was the control aim of the system. The fuzzy learning algorithm of personal thermal comfort zone was proposed, which modified the personal thermal comfort zone on line to meet the needs of different humans. The dynamical thermal comfort control strategy was proposed based on computational experiments. The dynamical thermal comfort zone included comfort zone and energy saving zone, which changed periodically. The experiment results demonstrated that this method could meet the human's thermal comfort need and reduce the energy consumption, and is favorable to the human's health.

引用

页码：128 / 135