Abstract
Language | English |
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Number of pages | 6 |
Publication status | Published - Nov 2006 |
Event | 2nd International Workshop on Networked Control Systems - Rende, Italy Duration: 23 Nov 2006 → 24 Nov 2006 |
Conference
Conference | 2nd International Workshop on Networked Control Systems |
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Country | Italy |
City | Rende |
Period | 23/11/06 → 24/11/06 |
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Keywords
- control
- operation
- heat exchanger networks
- model predictive control
Cite this
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Control and operation of heat exchanger networks using model predictive control. / Giovanini, L.; Balderud, J.
2006. Paper presented at 2nd International Workshop on Networked Control Systems, Rende, Italy.Research output: Contribution to conference › Paper
TY - CONF
T1 - Control and operation of heat exchanger networks using model predictive control
AU - Giovanini, L.
AU - Balderud, J.
PY - 2006/11
Y1 - 2006/11
N2 - While, during the past decades, many strategiesfor heat exchanger network synthesis and design have beendeveloped, much less effort have been dedicated to developingonline optimal control strategies to tackle their complex anddistributed dynamics. Since past optimal control design effortspredominately revolves around centralized control ideas theytypically suffer from high computational demands. By con-trast, this paper proposes an agent based decentralized predic-tive control approach, where the computational demand isdistributed between several agents. This paper also exploresthe computational demand associated with the proposed ap-proach and compares it against a traditional, centralized, pre-dictive control approach
AB - While, during the past decades, many strategiesfor heat exchanger network synthesis and design have beendeveloped, much less effort have been dedicated to developingonline optimal control strategies to tackle their complex anddistributed dynamics. Since past optimal control design effortspredominately revolves around centralized control ideas theytypically suffer from high computational demands. By con-trast, this paper proposes an agent based decentralized predic-tive control approach, where the computational demand isdistributed between several agents. This paper also exploresthe computational demand associated with the proposed ap-proach and compares it against a traditional, centralized, pre-dictive control approach
KW - control
KW - operation
KW - heat exchanger networks
KW - model predictive control
M3 - Paper
ER -