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008181129s2018 ||| | | | eng d
020 ▼a 9780438359949
035 ▼a (MiAaPQ)AAI10843166
035 ▼a (MiAaPQ)purdue:23091
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 620
1001 ▼a Jaramillo, Rita.
24512 ▼a A Multi-Agent Control Approach for Optimization of Central Cooling Plants.
260 ▼a [S.l.] : ▼b Purdue University., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 167 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Advisers: James E. Braun
5021 ▼a Thesis (Ph.D.)--Purdue University, 2018.
520 ▼a This research focuses on the application of a multi-agent control approach to optimal supervisory control of central cooling systems. Most of the research related to supervisory control of central cooling systems has focused on centralized contr
520 ▼a The work starts from a multi-agent control simulation framework developed by Cai (2015) for optimization of distributed air-conditioning systems. In this setting, the multi-agent structure and optimization-based control algorithm can be automati
520 ▼a The Purdue Northwest Chiller Plant, a system with a significant degree of complexity, was utilized as the test facility to conduct an extensive computational simulation of the approach for different operating conditions, including chilled water
590 ▼a School code: 0183.
650 4 ▼a Engineering.
650 4 ▼a Mechanical engineering.
650 4 ▼a Ecology.
690 ▼a 0537
690 ▼a 0548
690 ▼a 0329
71020 ▼a Purdue University. ▼b Mechanical Engineering.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0183
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999902 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자