S. Joe Qin
S. Joe Qin
IFAC Fellow, AIChE Fellow, IEEE Fellow, Chair Professor of Data Science
Verifierad e-postadress på cityu.edu.hk
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A survey of industrial model predictive control technology
SJ Qin, TA Badgwell
Control engineering practice 11 (7), 733-764, 2003
51042003
Statistical process monitoring: basics and beyond
S Joe Qin
Journal of Chemometrics: A Journal of the Chemometrics Society 17 (8‐9), 480-502, 2003
14032003
An overview of industrial model predictive control technology
SJ Qin, TA Badgwell
AIche symposium series 93 (316), 232-256, 1997
13381997
Survey on data-driven industrial process monitoring and diagnosis
SJ Qin
Annual reviews in control 36 (2), 220-234, 2012
9012012
Recursive PCA for adaptive process monitoring
W Li, HH Yue, S Valle-Cervantes, SJ Qin
Journal of process control 10 (5), 471-486, 2000
8572000
Recursive PLS algorithms for adaptive data modeling
SJ Qin
Computers & Chemical Engineering 22 (4-5), 503-514, 1998
6601998
Identification of faulty sensors using principal component analysis
R Dunia, SJ Qin, TF Edgar, TJ McAvoy
AIChE Journal 42 (10), 2797-2812, 1996
6541996
Nonlinear predictive control and moving horizon estimation—an introductory overview
F Allgöwer, TA Badgwell, JS Qin, JB Rawlings, SJ Wright
Advances in control, 391-449, 1999
6041999
Advances in Control–Highlights of ECC’99, chapter Nonlinear Predictive Control and Moving Horizon Estimation–An Introductory Overview
F Allgöwer, TA Badgwell, JS Qin, JB Rawlings, SJ Wright
Springer, 1999
604*1999
Nonlinear PLS modeling using neural networks
SJ Qin, TJ McAvoy
Computers & Chemical Engineering 16 (4), 379-391, 1992
5841992
An overview of nonlinear model predictive control applications
SJ Qin, TA Badgwell
Nonlinear model predictive control, 369-392, 2000
5612000
An overview of subspace identification
SJ Qin
Computers & chemical engineering 30 (10-12), 1502-1513, 2006
5552006
Selection of the number of principal components: the variance of the reconstruction error criterion with a comparison to other methods
S Valle, W Li, SJ Qin
Industrial & Engineering Chemistry Research 38 (11), 4389-4401, 1999
5411999
Subspace approach to multidimensional fault identification and reconstruction
R Dunia, SJ Qin
AIChE Journal 44 (8), 1813-1831, 1998
4981998
Control performance monitoring—a review and assessment
SJ Qin
Computers & Chemical Engineering 23 (2), 173-186, 1998
4621998
Reconstruction-based fault identification using a combined index
HH Yue, SJ Qin
Industrial & engineering chemistry research 40 (20), 4403-4414, 2001
4592001
Multimode process monitoring with Bayesian inference‐based finite Gaussian mixture models
J Yu, SJ Qin
AIChE Journal 54 (7), 1811-1829, 2008
4332008
Reconstruction-based contribution for process monitoring
CF Alcala, SJ Qin
Automatica 45 (7), 1593-1600, 2009
4052009
Fault detection and diagnosis based on modified independent component analysis
JM Lee, SJ Qin, IB Lee
AIChE journal 52 (10), 3501-3514, 2006
3902006
On unifying multiblock analysis with application to decentralized process monitoring
SJ Qin, S Valle, MJ Piovoso
Journal of Chemometrics: A Journal of the Chemometrics Society 15 (9), 715-742, 2001
3612001
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