Optimal operational control for complex industrial processes

Tianyou CHAI*, S. Joe QIN, Hong WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

110 Citations (Scopus)

Abstract

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. © 2014 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)81-92
Number of pages12
JournalAnnual Reviews in Control
Volume38
Issue number1
Early online date26 Apr 2014
DOIs
Publication statusPublished - 2014
Externally publishedYes

Bibliographical note

This work was partially supported by the National Natural Science Foundation of China under Grant 61020106003, 61290323, 61333007, Integrated Automation of Process Industry (IAPI) Fundamental Research Funds under Grant 2013ZCX04, and Project 111 of Ministry of Education of China under Grant B08015.

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