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Optimal operational control for complex industrial processes

delete2014-01-01
delete104
PRE
AI
T
Tianyou Chai *
S
S. Joe Qin
王
王宏 (Hong Wang)
DOI:10.1016/j.arcontrol.2014.03.005delete
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摘要

摘要

En 中文
Process control should ensure not only controlled variables to follow their setpoint values, but also the whole process plant to meet operational requirements optimally (e.g., quality, efficiency and consumptions). Process control should also enable that operational indices for quality and efficiency be improved continuously, while keeping the indices related to consumptions at the lowest possible level. This paper starts with a survey on the existing operational optimization and control methodologies and then presents a data-driven hybrid intelligent optimal operational control for complex industrial processes where process operational models are difficult to obtain. Applications via a hybrid simulation system and an industrial roasting process for hematite ore mineral processing are presented to demonstrate the effectiveness of the proposed operational control method. Issues for future research on the optimal operational control for complex industrial processes are outlined before concluding the paper. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
MODEL-PREDICTIVE CONTROL
INTELLIGENT CONTROL
OPTIMIZING CONTROL
OPTIMIZATION
SYSTEM
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期刊

Annual Reviews in Control 封面图
Annual Reviews in Control
IF:
10.7
论文数:
830
被引数:
5.9K

机构

N
northeastern university - china
学者数:
3.1W
论文数: 2.7W
被引数: 37
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