Deep Learning Model Predictive Control Frameworks: Application to a Fluid Catalytic Cracker–Fractionator Process-Reference-Cited by-同舟云学术

Deep Learning Model Predictive Control Frameworks: Application to a Fluid Catalytic Cracker–Fractionator Process

Published:2023-06-29 Issue:27 Volume:62 Page:10587-10600
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Santander Omar¹,Kuppuraj Vidyashankar²,Harrison Christopher A.²,Baldea Michael¹³^ORCID

Affiliation:

1. McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 East Dean Keeton Street, Austin, Texas 78712-1589, United States

2. Marathon Petroleum Corporation, Garyville, Louisiana 70051, United States

3. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th Street, Austin, Texas 78712-1229, United States

Funder

Marathon Petroleum Corporation

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.3c01110

Reference49 articles.

1. Integrated production scheduling and process control: A systematic review

2. On the interaction and integration of production planning and (advanced) process control

3. Control-aware batch process scheduling