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E. Process Control
E1 Multivariate statistical process control
- A MATLAB toolbox for data pre-processing and multivariate statistical process control
- Yi G, Herdsman C; Morris J
- Chemometrics and Intelligent Laboratory Systems 194 (2019) 103863
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DOI 10.1016/j.chemolab.2019.103863 |
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- Randomised Kernel Principal Component Analysis for Modelling and Monitoring of Nonlinear Industrial Processes with Massive Data
- Zhou Z, Du n, Xu j, Li Z, Wang P, Zhang J
- Industrial and Engineering Chemistry Research 2019, 58, 10410-10417
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- A Reliable Multi-Objective Control Strategy for Batch Processes based on Bootstrap Aggregated Neural Network Models
- Mukherjee A and Zhang J
Journal of Process Control, 2008, 18, 720-734
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DOI 10.1016/j.chemolab.2019.103863 |
- Batch-to-Batch Optimal Control of a Batch Polymerisation Process based on Stacked Neural Network Models
- Zhang J
Chemical Engineering Science, 2008, 63, 1273-1281
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DOI 10.1016/j.ces.2007.07.047 |
- Batch-to-Batch Optimal Control of Batch Processes Based on Recursively Updated Nonlinear Partial Least Squares Models
- Chunfu L, Zhang J and Wang G
Chemical Engineering Communications, 2007, 194, 261-297
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DOI 10.1080/00986440600829796 |
- Fault detection in dynamic processes using a simplified monitoring-specific CVA state space modelling approach
- Stubbs S, Zhang J, Morris J.
Computers & Chemical Engineering, 2012, Vol 41, 77-87
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DOI 10.1016/j.compchemeng.2012.02.009 |
- Fault localization in batch processes through progressive principal component analysis modeling
- Hong JJ, Zhang J, Morris J
Ind Eng Chem Res, 2011, Vol 50 (13), 8153-8162
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- Integrated tracking control strategy for batch processes using a batch-wise linear time-varying perturbation model
- Xiong Z, Zhang J, Xu Y and Wang X
IET Control Theory & Applications, 2007, 1, 179-188
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- Multiscale Multivariate Statistical Process Control
- Morris AJ,
Encyclopedia of Systems and Control (editors Tariq Samad and John Baillieul), 2014
- Multiway interval partial least squares for batch process performance
- Stubbs S, Zhang J, Morris J.
Ind Eng Chem Res, 2013, Vol 52 (35), 12399-12407
- On-line multivariate statistical monitoring of batch processes using Gaussian mixture model
- Chen T, Zhang J.
Computers & Chemical Engineering, 2010, Vol 34, 500-507
- Penalized reconstruction-based multivariate contribution analysis for fault isolation
- He B, Zhang J, Chen T and Yang X
Ind Eng Chem Res, 2013, Vol 52 (23), 7784-7794
- Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach
- He B, Ynag X, Chen T, Zhang J
Journal of Process Control, 2012, Vol 22, 1228-1236
E2 Process control
- Integrated predictive iterative learning control based on updating reference trajectory for point-to-point tracking
- Qiua W, Xiong Z, Zhang J, Honga Y, Li W
- Journal of Process Control 2020, 185, 41-51
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- A Reliable Multi-Objective Control Strategy for Batch Processes based on Bootstrap Aggregated Neural Network Models
- Mukherjee A and Zhang J
Journal of Process Control, 2008, 18, 720-734
- Adaptive Statistic Tracking Control Based on Two-Step Neural Networks With Time Delays
- Yi Y, Guo L and Wang H
IEEE T. Neural Netw., 2009, 20(3), 420-429
- An ILC-Based Adaptive Control for General Stochastic Systems With Strictly Decreasing Entropy
- Afshar P, Wang H and Chai TY
IEEE T. Neural Netw., 2009, 20(3), 471-482
- Artifical intelligence techniques applied as estimator in chemical process systems - A literature survey
- Ali J M, Hussain M A, Tade M O and Zhang J.
Expert Systems with Applications, 2015, Vol 42 No 14, 5915-5913
- Batch to batch iterative learning control using updated models based on a moving window of historical data
- Jewaratnam J, Zhang J, Hussain A and Morris J
Procedia Engineering, 2012, Vol 42, 232-240
- Batch-to-batch control of fed-batch processes using control-affine feedforward neural network
- Xiong Z, Xu Y, Zhang J and Dong J
Neural Computing & Applications, 2008, 17, 425-432
- Batch-to-Batch Optimal Control of a Batch Polymerisation Process based on Stacked Neural Network Models
- Zhang J
Chemical Engineering Science, 2008, 63, 1273-1281
- Batch-to-Batch Optimal Control of Batch Processes Based on Recursively Updated Nonlinear Partial Least Squares Models
- Chunfu L, Zhang J and Wang G
Chemical Engineering Communications, 2007, 194, 261-297
- Compressor Surge Control Using a Variable Area Throttle and Fuzzy Logic Control
- Al-Mawali s, Zhang J.
Transactions of the Institute of Measurement and Control, 2010, Vol 32 No 4, 347-375
- Constrained PI tracking control for output probability distributions based on two-step neural networks
- Yi Y, Guo L and Wang H
IEEE T. Circuits Syst., 2009, 56, 1416-1426
- Distillation control structure selection for energy efficient operations
- Osuolale F, Zhang J.
Chemical Engineering and Technology, 2015, Vol 38, No 5, 907-916
- Distribution function tracking filter design using hybrid characteristic functions
- Zhou J, Zhou D, Wang H, Guo L and Chai TY
Automatica, 2010, 46(1), 101-109
- Energy efficiency optimisation for distillation column using artificial neural network models
- Osuolale F, Zhang J.
Energy, 2016, Vol 106, 562-578
- ILC-based fixed-structure controller design for output PDF shaping in stochastic systems using LMI techniques
- Wang H and Afshar P
IEEE T. Automat. Cont., 2009, 54, 760-773
- Inferential estimation of kerosene dry point in refineries with varying crudes
- Zhou C, Liu Q, Huang D X, Zhang J.
Journal of Process Control, 2012, Vol 22 No 6, 1122-1126
- Integrated tracking control strategy for batch processes using a batch-wise linear time-varying perturbation model
- Xiong Z, Zhang J, Xu Y and Wang X
IET Control Theory & Applications, 2007, 1, 179-188
- Intelligent optimal-setting control for grinding circuits of mineral processing process
- Zhou P, Chai T and Wang H
IEEE T. Automat. Sci. Eng., 2009, 6, 730-743
- Iterative learning control of a crystallisation process using batch wise updated linearised models identified using PLS
- Zhang J, Nguyan J and Morris AJ
Computer Aided Chemical Engineering 26, Proceedings of the 19th European Symposium on Computer Aided Process Engineering, 2009, 387-392
- Modelling and control of reactive polymer composite moulding using bootstrap aggregated neural network models
- Zhang J, Pantelelis N G.
Chemical Product and Process Modeling, 2011, Vol 6 (2), Article 5
- Modelling of a post combustion CO2 capture process using neural networks
- Li F, Zhang J, Oko E and Wang M
Fuel, 2015, 151, 156-163
- Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant
- Oko E, Wang M and Zhang J.
Fuel, 2015, 151, 139-145
- Noniterative N-infinity Based Model Order Reduction of LTI Systems Using LMIs
- Nobakhti A and Wang H
IEEE T. Cont. Syst. Tec., 2009, 17, 494-501
- Nonlinear wave modeling and dynamic analysis of internal thermally coupled distillation columns
- Liu X, Zhou Y, Cong L, Zhang J.
AIChE Journal, 2012, Vol 58 No 4, 1146-1156
- Optimal control of fed-batch processess using particle swarm optimisation with staked neural network models
- Herrara F, Zhang J
Computers & Chemical Engineering, 2009, Vol 33, No 10, 1593-1601
- Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model
- Xiong Z, Zhang J and Dong J
Chinese Journal of Chemical Engineering, 2008, 16, 235-240
- Process analytical technology and compensating for nonlinear effects in process spectroscopic data for improved process monitoring and control
- Chen Z and Morris J
Biotechnology J., 2009, 4(5), 610-619
- Reliable optimal control of a fed-batch fermentation process using ant colony optimisation and bootstrap aggregated neural network models
- Zhang J, Feng M
Appl. Metaheuristics Process. Eng., 2014, 183-200
- Reliable optimisation control of a reactive polymer composite moulding process using ant colony optimisation and bootstrap aggregated neural networks
- Mohammed K R, Zhang J.
Neural computing & Applications, 2013, Vol 23, 1891-1898
- Robust output feedback stabilization for discrete-time systems with time-varying input delay
- Hao S, Liu T, Zhang J, Sun X and Zhong C
Syst. Sci. Cont. Eng. An Open Access J., 2015, 3, 300-306