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Identification and Iterative Learning Control for Building Systems: A Data-driven Approach
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Identification and Iterative Learning Control for Building Systems: A Data-driven Approach. |
| 개인저자 | Minakais, Matthew. |
| 단체저자명 | Rensselaer Polytechnic Institute. Electrical Engineering. |
| 발행사항 | [S.l.]: Rensselaer Polytechnic Institute., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 137 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438206540 |
| 학위논문주기 | Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Advisers: John Wen |
| 요약 | Commercial 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 |
| 요약 | For 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 |
| 요약 | For 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 |
| 일반주제명 | Electrical engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
