Takip et
S. Joe Qin
S. Joe Qin
Lingnan University, Hong Kong, President, Member of EASA, Fellow of HKAES, NAI, IEEE, IFAC, AIChE
ln.edu.hk üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
A survey of industrial model predictive control technology
SJ Qin, TA Badgwell
Control engineering practice 11 (7), 733-764, 2003
63922003
Statistical process monitoring: basics and beyond
S Joe Qin
Journal of Chemometrics: A Journal of the Chemometrics Society 17 (8‐9), 480-502, 2003
17792003
An overview of industrial model predictive control technology
SJ Qin, TA Badgwell
AIche symposium series 93 (316), 232-256, 1997
15321997
Survey on data-driven industrial process monitoring and diagnosis
SJ Qin
Annual reviews in control 36 (2), 220-234, 2012
14422012
Recursive PCA for adaptive process monitoring
W Li, HH Yue, S Valle-Cervantes, SJ Qin
Journal of process control 10 (5), 471-486, 2000
10302000
Nonlinear Model Predictive Control, chap. An overview of nonlinear model predictive control applications
S Qin, T Badgwell
Birkhäuser Verlag, Boston, MA, 2000
784*2000
An overview of nonlinear model predictive control applications
SJ Qin, TA Badgwell
Nonlinear model predictive control, 369-392, 2000
7742000
Identification of faulty sensors using principal component analysis
R Dunia, SJ Qin, TF Edgar, TJ McAvoy
AIChE Journal 42 (10), 2797-2812, 1996
7711996
Recursive PLS algorithms for adaptive data modeling
SJ Qin
Computers & Chemical Engineering 22 (4-5), 503-514, 1998
7701998
An overview of subspace identification
SJ Qin
Computers & chemical engineering 30 (10-12), 1502-1513, 2006
7642006
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
7241999
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
6831999
Nonlinear PLS modeling using neural networks
SJ Qin, TJ McAvoy
Computers & Chemical Engineering 16 (4), 379-391, 1992
6621992
Reconstruction-based fault identification using a combined index
HH Yue, SJ Qin
Industrial & engineering chemistry research 40 (20), 4403-4414, 2001
5992001
Reconstruction-based contribution for process monitoring
CF Alcala, SJ Qin
Automatica 45 (7), 1593-1600, 2009
5702009
Subspace approach to multidimensional fault identification and reconstruction
R Dunia, SJ Qin
AIChE Journal 44 (8), 1813-1831, 1998
5491998
Multimode process monitoring with Bayesian inference‐based finite Gaussian mixture models
J Yu, SJ Qin
AIChE Journal 54 (7), 1811-1829, 2008
5482008
Control performance monitoring—a review and assessment
SJ Qin
Computers & Chemical Engineering 23 (2), 173-186, 1998
5041998
Total projection to latent structures for process monitoring
D Zhou, G Li, SJ Qin
AIChE Journal 56 (1), 168-178, 2010
5012010
Fault detection and diagnosis based on modified independent component analysis
JM Lee, SJ Qin, IB Lee
AIChE journal 52 (10), 3501-3514, 2006
4842006
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Makaleler 1–20