LDR | | 02048nmm uu200397 4500 |
001 | | 000000332471 |
005 | | 20240805170842 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438206540 |
035 | |
▼a (MiAaPQ)AAI10787057 |
035 | |
▼a (MiAaPQ)rpi:11267 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 621.3 |
100 | 1 |
▼a Minakais, Matthew. |
245 | 10 |
▼a Identification and Iterative Learning Control for Building Systems: A Data-driven Approach. |
260 | |
▼a [S.l.] :
▼b Rensselaer Polytechnic Institute.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 137 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Advisers: John Wen |
502 | 1 |
▼a Thesis (Ph.D.)--Rensselaer Polytechnic Institute, 2018. |
520 | |
▼a 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 |
520 | |
▼a 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 |
520 | |
▼a 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 |
590 | |
▼a School code: 0185. |
650 | 4 |
▼a Electrical engineering. |
690 | |
▼a 0544 |
710 | 20 |
▼a Rensselaer Polytechnic Institute.
▼b Electrical Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0185 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997378
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |