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	Identifiability of building thermal system models using on-line data
	Zhang Xiaotao ; Ni Weidou ; Li Zheng ; Zheng Song
	2010-05-11 ; 2010-05-11
关键词	Practical Theoretical or Mathematical/ closed loop systems heat systems identification modelling multivariable systems thermal engineering/ building thermal system models online data modelling principles conventional mechanistic method mechanical testing method input signal stimulation closed loop control system multivariable systems power load changing thermal system lag effects dynamic modelling system identification/ C3340B Control of heat systems C1340B Multivariable control systems C1220 Simulation, modelling and identification E2120 Heat and thermodynamic process (mechanical engineering) E2310 Power and plant engineering (mechanical engineering) E1550 Control technology and theory
中文摘要	Models of thermal systems were developed using basic modeling principles and on-line data to improve the conventional mechanistic method and testing method. The stimulation of the input signal, identifying closed loops of control system, and modeling of multi-variable systems were analyzed to meet the requirements of building thermal system model using on-line data. The stimulation of the input signal can be guaranteed by data obtained during power load changing in a large range; identifying closed loops of control systems benefit from the lag effects of thermal systems, and identifying of multi-variable systems can be guaranteed by the measured signals with noise. Dynamic models of thermal systems using on-line data can be obtained with the above conditions being met.
语种	中文 ; 中文
出版者	Tsinghua Univ. Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/25639]
专题	清华大学
推荐引用方式 GB/T 7714	Zhang Xiaotao,Ni Weidou,Li Zheng,et al. Identifiability of building thermal system models using on-line data[J],2010, 2010.
APA	Zhang Xiaotao,Ni Weidou,Li Zheng,&Zheng Song.(2010).Identifiability of building thermal system models using on-line data..
MLA	Zhang Xiaotao,et al."Identifiability of building thermal system models using on-line data".(2010).

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