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Identification and Iterative Learning Control for Building Systems: A Data-driven Approach
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Identification and Iterative Learning Control for Building Systems: A Data-driven Approach
자료유형  
 학위논문
Control Number  
0014997378
International Standard Book Number  
9780438206540
Dewey Decimal Classification Number  
621.3
Main Entry-Personal Name  
Minakais, Matthew.
Publication, Distribution, etc. (Imprint  
[Sl] : Rensselaer Polytechnic Institute, 2018
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2018
Physical Description  
137 p
General Note  
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
General Note  
Advisers: John Wen
Dissertation Note  
Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018.
Summary, Etc.  
요약Commercial heating, ventilation, and air conditioning (HVAC) systems have been the focus of sustainability research due to their large energy footprint and relatively rudimentary control strategies. This thesis presents a novel approach to build
Summary, Etc.  
요약For simulation and system analysis, we model a multi-zone building as a lumped-parameter thermal resistance-capacitance network. This model is used to perform simulations and to study the inherent passivity in multi-zone building systems. We sho
Summary, Etc.  
요약For experimental valuation, we have designed, built, and instrumented a unique test facility. This intelligent building testbed was created to serve as a standardized platform for building modeling and control evaluation. Key features include wi
Subject Added Entry-Topical Term  
Electrical engineering
Added Entry-Corporate Name  
Rensselaer Polytechnic Institute Electrical Engineering
Host Item Entry  
Dissertation Abstracts International. 79-12B(E).
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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Control Number  
joongbu:555653
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