Publications
1. J. Zhang, P. D. Roberts, and J. E. Ellis, “An
Application of Expert System Techniques to the On-line Control and Fault
Diagnosis of a Mixing Process”, Journal
of Intelligent and Robotic Systems, Vol.1, No.3, 1988, PP209-223.
2. J. Zhang, P. D. Roberts, and J. E. Ellis, “Fault
Diagnosis of a Mixing Process Based on Qualitative Representation of Physical
Behaviours”, Journal of Intelligent and
Robotic Systems, Vol.3, No.2, 1990, PP103-115.
3. J. Zhang, P. D. Roberts, and J. E. Ellis, “A
Self-learning Fault Diagnosis System”, Transactions
of the Institute of Measurement and Control, Vol.13, No.1, 1991, PP29-35.
4. J. Zhang and P. D. Roberts, “Process Fault
Diagnosis with Diagnostic Rules based on Structural Decomposition”, Journal of Process Control, Vol.1,
November 1991, PP259-269.
5. J. Zhang and P. D. Roberts, “On-line Process Fault
Diagnosis Using Neural Network Techniques”, Transactions
of the Institute of Measurement and Control, Vol.14, No.4, 1992, PP179-188.
6. J. Zhang and P. D. Roberts, “Use of Genetic
Algorithms in Training Diagnostic Rules for Process Fault Diagnosis”, Knowledge-Based Systems, Vol.5, No.4,
1992, PP277-288.
7. F. G. Filip, P. D. Roberts, and J. Zhang, “Combined
Numeric/Knowledge based Hierarchical Control. Part I. A Survey of Reported
Results”, Studies in Informatics and
Control, Vol.1, No.2, 1992, PP87-97.
8. F. G. Filip, P. D. Roberts, and J. Zhang, “Combined
Numeric/Knowledge based Hierarchical Control. Part II. On-line Fault Diagnosis
with Deep Knowledge based Self-learning of Heuristic Rules”, Studies in Informatics and Control,
Vol.1, No.3, 1992, PP181-192.
9. F. G. Filip, P. D. Roberts, and J. Zhang, “Combined
Numeric/Knowledge based Hierarchical Control. Part III. Process Scheduling and
Co-operation”, Studies in Informatics and
Control, Vol.1, No.4, 1992, PP267-283.
10. J. Zhang, “Learning Diagnostic Knowledge through
Neural Networks and Genetic Algorithms”, Studies
in Informatics and Control, Vol.2, No.3, 1993, PP233-252.
11. J. Zhang and A. J. Morris, “On-line Process Fault
Diagnosis Using Fuzzy Neural Networks”, Intelligent
Systems Engineering, Vol.3, No.1, 1994, PP37-47.
12. J. Zhang and A. J. Morris, “Nonlinear Systems
Modelling Using Fuzzy Neural Networks”, Proceedings
of IEE - Control Theory And Applications, Vol.142, No.6, 1995, PP551-561.
13. J. Zhang, “A Data Based Approach to Process Fault
Diagnosis”, Studies in Informatics and
Control, Vol.4, No.2, 1995, PP93-105.
14. J. Zhang, “Modified Ratio Control Configurations
for Distillation Composition Control”, Studies
in Informatics and Control, Vol.4, No.4, 1995, PP331-342.
15. J. Zhang, E. B. Martin, and A. J. Morris, “Fault
Detection and Diagnosis Using Multivariate Statistical Techniques”, Chemical Engineering Research and Design,
Vol.74, No.1, 1996, PP89-96.
16. J. Zhang and A. J. Morris, “Process Modelling and
Fault Diagnosis Using Fuzzy Neural Networks”, Fuzzy Sets and Systems, Vol. 79, No.1, 1996, PP127-140.
17. E. B. Martin, A. J. Morris, and J. Zhang, “Process
Performance Monitoring through Multivariate Statistical Process Control”, Proceedings of IEE - Control Theory And
Applications, Vol.143, No.2, 1996, PP132-144.
18. J. Zhang, E. B. Martin, A. J. Morris, and C.
Kiparissides, “Inferential Estimation of Polymer Quality Using Stacked Neural
Networks”, Computers and Chemical
Engineering, Vol.21, 1997, PP s1025-s1030.
19. R. Shao, E. B. Martin, J. Zhang, and A. J. Morris,
“Confidence Bounds for Neural Network Representations”, Computers and Chemical Engineering, Vol.21, 1997, PP s1173-s1178.
20. J. Zhang, A. J. Morris, and E. B. Martin, “Process
Monitoring Using Non-linear Statistical Techniques”, Chemical Engineering Journal, Vol.67, No.3, 1997, PP181-189.
21. J. Zhang and A. J. Morris, “A Sequential Learning
Approach for Single Hidden Layer Neural Networks”, Neural Networks, Vol.11, No.1, 1998, PP65-80.
22. J. Zhang, A. J. Morris, and E. B. Martin, “Long
Term Prediction Models Based on Mixed Order Locally Recurrent Neural Networks”,
Computers and Chemical Engineering,
Vol.22, No.7-8, 1998, PP1051-1063.
23. J. Zhang, A. J. Morris, E. B. Martin, and C.
Kiparissides, “Prediction of Polymer Quality in Batch Polymerisation Reactors
Using Robust Neural Networks”, Chemical
Engineering Journal, Vol.69, No.2, 1998, PP135-143.
24. J. Zhang, A. J. Morris, E. B. Martin, and C.
Kiparissides, “Estimation of Impurity and Fouling in Batch Polymerisation
Reactors through the Application of Neural Networks”, Computers and Chemical Engineering, Vol.23, No.3, 1999, PP301-314.
25. J. Zhang, “Developing Robust Non-linear Models
through Bootstrap Aggregated Neural Networks”, Neurocomputing, Vol.25, 1999, PP93-113.
26. J. Zhang and A. J. Morris, “Recurrent Neuro-Fuzzy
Networks for Nonlinear Process Modelling”, IEEE
Transactions on Neural Networks, Vol.10, No.2, 1999, PP313-326.
27. J. Zhang, “Inferential Estimation of Polymer
Quality Using Bootstrap Aggregated Neural Networks”, Neural Networks, Vol.12, No.6, 1999, PP927-938.
28. J. Zhang and A. J. Morris, “Long Range Predictive
Control of Nonlinear Processes Based on Recurrent Neuro-Fuzzy Networks Models”,
Neural Computing & Applications,
Vol.9, No.1, 2000, PP50-59.
29. D. X. Huang, Y. H. Jin, J. Zhang, and J. Morris,
“Non-linear MIMO Predictive Control Based on Wavelet Networks”, Journal of Tsinghua University, Vol.40,
No.9, 2000, PP116-119.
30. J. Zhang, “Developing Robust Neural Network Models
by Using Both Dynamic and Static Process Operating Data”, Ind. Eng. Chem. Res., Vol.40. No.1, 2001, PP234-241.
31. J. Zhang, “A Nonlinear Gain Scheduling Control
Strategy Based on Neuro-fuzzy Networks”, Ind.
Eng. Chem. Res., Vol.40, No.14, 2001, PP3164-3170.
32. Y. Tian, J. Zhang, and A. J. Morris, “Modelling
and Optimal Control of a Batch Polymerisation Reactor Using a Hybrid Stacked
Recurrent Neural Network Model”, Ind.
Eng. Chem. Res., Vol.40, No.21, 2001, PP4525-4535.
33. Y. Tian, J. Zhang, and A. J. Morris, “Optimal
Control of a Fed-Batch Bioreactor based upon an Augmented Recurrent Neural
Network Models”, Neurocomputing,
2002, Vol.48, No.1-4, PP919-936.
34. Y. Tian, J. Zhang, and A. J. Morris, “Optimal
Control of a Batch Emulsion Copolymerisation Reactor based on Recurrent Neural
Network Models”, Chemical Engineering and
Processing, 2002, Vol.41, No.6, PP531-538.
35. D. X. Huang, Y. H. Jin, J. Zhang, and J. Morris,
“Non-linear chemical process modelling and application in epichlorhydrine
production plant using wavelet networks”, Chinese
Journal of Chemical Engineering, 2002, Vol.10, No.4, PP435-443.
36. J. Zhang and R. Agustriyanto, “Multivariable
Inferential Feed Forward Control”, Ind.
Eng. Chem. Res., Vol.42, No.18, 2003, PP4186-4197.
37. Z. Xiong and J. Zhang, “Product Quality Trajectory
Tracking in Batch Processes Using Iterative Learning Control Based on
Time-varying Perturbation Models”, Ind.
Eng. Chem. Res., Vol.42, No.26, 2003, PP6802-6814.
38. L. Chen, Y. Hontoir, D.
Huang, J. Zhang, and A. J. Morris, “Combining First Principles with Black-box
Techniques for Reaction Systems”, Control
Engineering Practice, Vol.12, No.7, 2004, PP819-826.
39. J. Zhang, “A Reliable Neural Network Model based
Optimal Control Strategy for a Batch Polymerisation Reactor”, Ind. Eng. Chem. Res., Vol.43, No.4,
2004, PP1030-1038.
40. Z. Xiong and J. Zhang, “Modelling and Optimal
Control of Fed-batch Processes Using a Novel Control Affine Feedforward Neural
Network”, Neurocomputing, Vol.61,
2004, PP317-337.
41. Z. Xiong and J. Zhang, “Batch-to-batch Optimal
Control of Non-linear Batch Processes based on Incrementally Updated Models”, IEE Proceedings - Control Theory and
Applications, Vol.151, No.2, 2004, PP158-165.
42. Y. Tian, J. Zhang, and A. J. Morris, “Dynamic
On-Line Re-Optimisation Control of A Batch MMA Polymerisation Reactor Using
Hybrid Neural Network Models”, Chemical
Engineering and Technology, Vol.27, No.9, 2004, PP1030-1038.
43. C. Li, J. Zhang, and G. Wang, “Adaptive quality
prediction for batch processes based on the PLS model”, Journal of Tsinghua University, 2004，Vol.44, No.10, PP1360-1363. (in Chinese)
44. L. Q. Di, J. Zhang, and X. H. Yang, “MWMPCA with
application to batch processes monitoring”, Journal of Jilin University:
Information Science, 2004, Vol.22, No.4, PP397-400. (in
Chinese)
45. S. J. Zhao, J. Zhang, and Y. M. Xu, “Monitoring of
Processes with Multiple Operating Modes through Multiple PCA Models”, Ind. Eng. Chem. Res., Vol.43, 2004,
PP7025-7035.
46. M. Shen, J. Zhang, and K. Scott, “Regulation of
power conversion in fuel cells”, Chemical Research in Chinese Universities,
Vol.20, No.4, 2004, PP466-469.
47. M. Shen, J. Zhang, and K. Scott, “The General Rule
of Power Converted from Chemical Energy to Electrical Energy”, Fuel Cells, 2004, Vol.4, No.3,
PP388-393.
48. Z. Xiong and J. Zhang, “Batch-to-Batch Iterative
Optimisation Control based on Recurrent Neural Network Models”, Journal of Process Control, Vol.15,
No.1, 2005, PP11-21.
49. Z. Xiong and J. Zhang, “Optimal Control of
Fed-Batch Processes Based on Multiple Neural Networks”, Applied Intelligence, 2005, Vol.22, No.2, PP149-161.
50. Z. Xiong and J. Zhang, “Neural Network Model Based
On-line Re-optimisation Control of Fed-batch Processes Using a Modified
Iterative Dynamic Programming Algorithm”, Chemical
Engineering and Processing, 2005, Vol.44, No.4, PP477-484.
51. Z. Ahmad and J. Zhang, “Bayesian Selective
Combination of Multiple Neural Networks for Improving Long Range Predictions in
Nonlinear Process Modelling”, Neural
Computing & Applications, 2005, Vol.14, No.1, PP78-87.
52. J. Zhang, “Batch Process Modelling and Optimal
Control based on Neural Network Models”, ACTA Automatica Sinica, 2005, Vol.31, No.1, PP19-31.
53. C. Li, H. Ye, G. Wang, and J. Zhang, “A Recursive
Nonlinear PLS Algorithm for Adaptive Nonlinear Process Modelling”, Chemical Engineering and Technology,
2005, Vol.28, No.2, PP141-152.
54. J. Zhang, “Modelling and Optimal Control of Batch
Processes Using Recurrent Neuro-Fuzzy Networks”, IEEE Transactions on Fuzzy Systems, 2005, Vol. 13, No.4, PP417-427.
55. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu,
“Tracking Control for Batch Processes through Integrating Batch-to-Batch
Iterative Learning Control and withing-Batch On-Line
Control”, Ind. Eng. Chem. Res.,
Vol.44, 2005, PP3983-3992.
56. J. Zhang, “A Neural Network Based Strategy for the
Integrated Batch-to-Batch Control and within Batch Control of Batch Processes”,
Transactions of the Institute of
Measurement and Control, 2005, Vol. 27, No. 5, PP391-410.
57. Z. Ahmad and J. Zhang, “Combination of Multiple
Neural Networks Using Data Fusion Techniques for Enhanced Nonlinear Process
Modelling”, Computers & Chemical
Engineering, Vol.30, No.2, 2006, PP295-308.
58. J. Zhang, “Modelling and Multi-Objective Optimal
Control of Batch Processes Using Recurrent Neuro-Fuzzy Networks”, International Journal of Automation and
Computing, 2006, Vol.3, No.1, PP1-7.
59. J. Zhang, “Improved On-line Process Fault
Diagnosis through Information Fusion in Multiple Neural Networks”, Computers & Chemical Engineering,
Vol.30, No.3, 2006, PP558-571.
60. J. Zhang, Q. Jin, and Y. M. Xu, “Inferential
Estimation of Polymer Melt Index Using Sequentially Trained Bootstrap
Aggregated Neural Networks”, Chemical
Engineering and Technology, Vol.29, No.4, 2006, PP442-448.
61. S. J. Zhao, J. Zhang, and Y. M. Xu, “Performance
Monitoring of Processes with Multiple Operating Modes through Multiple PLS
Models”, Journal of Process Control,
Vol.16, No.7, 2006, PP763-772.
62. J. Zhang, “Offset-Free Inferential Feedback
Control of Distillation Composition based on PCR and PLS Models”, Chemical Engineering and Technology,
Vol.29, No.5, 2006, PP560-566.
63. S. J. Zhao, J. Zhang, Y. M. Xu, and Z. H. Xiong,
“A Nonlinear Projection to Latent Structures Method and Its Applications”, Ind. Eng. Chem. Res., Vol. 45, No.11,
2006, PP3843-3852.
64. C. Li, J. Zhang, and G. Wang, “Adaptive quality
prediction for batch processes based on the PLS model”, Frontiers of Electrical and Electronic Engineering in China, 2006，Vol.1, No.2, PP211-215.
65. Z. Xiong J. Zhang, X. Wang, and Y. M. Xu, “An
Integrated Tracking Control Strategy for Batch Processes Using a Batch-wise
Linear Time-varying Perturbation Model”, IET
Control Theory and Applications, 2007, Vol.1, No.1, PP179-188.
66. C. Li, J. Zhang, and G. Wang, “Batch-to-Batch
Optimal Control of Batch Processes Based on Recursively Updated Nonlinear
Partial Least Squares Models”, Chemical
Engineering Communications, 2007, Vol.194, No.3, PP261-279.
67. Z. Xiong, Y. Xu, J. Zhang, and J. Dong, “Batch-to-batch Control of
Fed-Batch Processes Using Control-Affine Feedforward Neural Network”, Neural Computing & Applications,
2008, Vol.17, No.4, PP425-432.
68. J. Zhang, “Batch-to-Batch Optimal Control of a
Batch Polymerisation Process based on Stacked Neural Network Models”, Chemical Engineering Science, 2008,
Vol.63, No.5, PP1273-1281.
69. Z. Xiong, J. Zhang, and J. Dong, “Optimal
Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model”, Chinese Journal of Chemical Engineering, 2008, Vol. 16, No. 2,
PP235-240.
70. A. Mukherjee and J. Zhang, “A Reliable
Multi-Objective Control Strategy for Batch Processes based on Bootstrap
Aggregated Neural Network Models”, Journal
of Process Control, 2008, Vol.18, No.7-8, PP720-734.
71. Z. Ahmad and J. Zhang,
“Selective Combination of Multiple Neural Networks for Improving Model
Prediction in Nonlinear Systems Modelling through Forward Selection and
Backward Elimination”, Neurocomputing,
2009, Vol. 72, No. 4-6, PP1198-1204.
72. R. Agustriyanto and J.
Zhang, “Control Structure Selection for the ALSTOM Gasifier Benchmark Process
Using GRDG Analysis”, International
Journal of Modelling, Identification and Control, 2009, Vol. 6, No. 2,
PP126-135.
73. J. Zhang, J. Nguyen, and Z.
Xiong, “Iterative Learning Control of Batch Processes based on Time Varying
Perturbation Models”, Journal of Tsinghua
University, 2008, Vol.48, No. S2,
PP1771-1774 (in Chinese).
74.
H. Geng, Z. Xiong, Y. Xu, and J. Zhang, “Iterative
learning control with reference batch for linear time-variant system”, Control
and Decision, 2009, Vol. 24, No. 5, PP648-652
(in Chinese).
75. Z. Xiong, Y. Xu, J. Dong,
and J. Zhang, “Neural Network Based Iterative Learning Control for Product
Qualities in Batch Processes”, International
Journal of Modelling, Identification and Control, 2010, Vol.11, No.1-2,
PP107-114.
76. Z. Ahmad, R. A. M. Noor,
and J. Zhang, “Multiple Neural Networks Modeling
Techniques in Process Control: A Review”, Asia-Pacific
Journal of Chemical Engineering, 2009, Vol. 4, No. 4, PP403-419.
77. Z. Xiong, J. Dong,
and J. Zhang, “Optimal Iterative Learning Control for Endpoint Product
Qualities in Semi-batch Process based on Neural Network Model”, Science in China Series F:Information
Sciences, 2009,Vol.52 No.7, PP1136-1144.
78. S. Al-Mawali and J. Zhang,
“Compressor Surge Control Using a Variable Area Throttle and Fuzzy Logic
Control”, Transactions of the Institute
of Measurement and Control, 2010, Vol.32, No.4, PP347-375.
79. F. Herrera and J. Zhang,
“Optimal Control of Fed-Batch Processes Using Particle Swarm Optimisation with
Stacked Neural Network Models”, Computers
& Chemical Engineering, 2009, Vol. 33, No. 10, PP1593-1601.
80. T. Chen and J. Zhang,
“On-line multivariate statistical monitoring of batch processes using Gaussian
mixture model”, Computers & Chemical
Engineering, 2010, Vol.34, PP500-507.
81. J. J. Hong, J. Zhang, and
J. Morris, “Fault localization in batch processes through progressive principal
component analysis modeling”, Ind. Eng. Chem. Res., Vol.50(13), 2011, PP8153-8162 .
82. X. Liu, Y. Zhou, L. Cong,
and J. Zhang, “Nonlinear wave modeling and dynamic
analysis of internal thermally coupled distillation columns”, AIChE Journal, 2012, Vol.58, No.4,
PP1146-1156.
83. J. Zhang and N. G.
Pantelelis, “Modelling and Control of Reactive Polymer Composite Moulding Using
Bootstrap Aggregated Neural Network Models”, Chemical Product and Process Modeling, Vol.6(2), 2011, Article 5 (DOI: 10.2202/1934-2659.1603).
84. S. Stubbs, J. Zhang, and J.
Morris, “Fault detection in dynamic processes using a simplified
monitoring-specific CVA state space modelling approach”, Computers & Chemical Engineering, 2012, Vol. 41, PP77-87.
85. C. Zhou, Q. Liu, D. X.
Huang, and J. Zhang, “Inferential estimation of kerosene dry point in
refineries with varying crudes”, Journal
of Process Control, 2012, Vol.22, No.6, PP1122-1126.
86. B. He, X. Yang, T. Chen,
and J. Zhang, “Reconstruction-based multivariate contribution analysis for
fault isolation: A branch and bound approach”, Journal of Process Control, 2012, Vol.22, PP1228-1236.
87. K. R. Mohammed and J.
Zhang, “Reliable Optimisation Control of a Reactive Polymer Composite Moulding
Process Using Ant Colony Optimisation and Bootstrap Aggregated Neural
Networks”, Neural Computing &
Applications, 2013, Vol.23, PP1891–1898.
88. B. He, J. Zhang, T. Chen, and
X. Yang, “Penalized reconstruction-based multivariate contribution analysis for
fault isolation”, Ind. Eng. Chem. Res.,
Vol.52(23), 2013, PP7784-7794.
89. S. Stubbs, J. Zhang, and J.
Morris, “Multiway Interval Partial Least Squares for Batch Process Performance
Monitoring”, Ind. Eng. Chem. Res., Vol.52(35), 2013, PP12399−12407.
90. J. J. Hong, J. Zhang, and
J. Morris, “Progressive Multi-block Modelling for Enhanced Fault Isolation in
Batch Processes”, Journal of Process
Control, 2014, Vol.24, PP13−26.
91. A. Alawi, J. Zhang, and J.
Morris, “Multiscale Multiblock Batch Monitoring:
Sensor and Process Drift and Degradation”, Organic
Process Research & Development, 2015, Vol.19, PP145−157.
92. F. Li, J. Zhang, E. Oko,
and M. Wang, “Modelling of a Post-combustion CO2 Capture Process Using Neural
Networks”, Fuel, 2015, Vol.151,
PP156-163.
93. E. Oko, M. Wang, and J.
Zhang, “Neural Network Approach for Predicting Drum Pressure and Level in
Coal-fired Subcritical Power Plant”, Fuel,
2015, Vol.151, PP139-145.
94. S. Hao, T. Liu, J. Zhang, X. Sun, and C. Zhong, “Robust output feedback stabilization for discrete-time
systems with time-varying input delay”, Systems Science & Control Engineering: An Open Access
Journal, 2015, Vol. 3, PP300–306,
http://dx.doi.org/10.1080/21642583.2015.1018556.
95. F. Osuolale, and J. Zhang,
“Distillation control structure selection for energy efficient operations”, Chemical Engineering & Technology,
2015, Vol.38, No.5, PP907-916.
96. J. M. Ali, M. A. Hussain,
M. O. Tade, and J. Zhang, “Artificial Intelligence
techniques applied as estimator in chemical process systems -A literature
survey”, Expert Systems With Applications, 2015, Vol.42, No.14, PP5915-5931.
97. Z. Ahmad, J. Zhang, T. Kashiwao, A. Bahadori, “Prediction of absorption and stripping
factors in natural gas processing industries using feed forward artificial
neural network”, Petroleum Science and
Technology, 2016, Vol. 34, No. 2, PP105-113.
98. F. Osuolale, and J. Zhang,
“Energy Efficiency Optimisation for Distillation Column Using Artificial Neural
Network Models”, Energy, 2016,
Vol.106, PP562-578.
99. S. A. Lawal and J. Zhang, “Actuator Fault Monitoring and
Fault Tolerant Control in Distillation Columns”, International Journal of Automation and Computing, 2016, in press.
II. Refereed Book Chapters
1. J. Zhang and A. J. Morris, “Neuro-Fuzzy Networks
for Process Modelling and Fault Diagnosis”, Chapter 19 for the book Neural
Networks, (Ed.) J. G. Taylor, Unicom Press, 1995, PP333-352.
2. J. Zhang and A. J. Morris, “Fuzzy Modelling Using
Two Connectionist Architectures”, Chapter 22 for the book Computer-Aided
Chemical Engineering, Volume 6: Neural networks for Chemical Engineers, (Ed.) A. B. Bulsari,
Elsevier Science, 1995, PP547-572.
3. E. B. Martin, A. J. Morris, and J. Zhang,
“Artificial Neural Networks and Multivariate Statistics”, Chapter 26 for the
book Computer-Aided Chemical Engineering, Volume 6: Neural networks for
Chemical Engineers, (Ed.) A. B. Bulsari, Elsevier Science, 1995, PP627-658.
4. J. Zhang and A. J. Morris, “A Sequential Training
Strategy for Locally Recurrent Neural Networks”, Chapter 10 for the book
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic
Algorithms, (ed) D. Ruan, Kluwer Academic Publishers, 1997, PP125-135.
5. J. Zhang and P. D. Roberts, “A Hierarchical
Structure for On-line Process Fault Diagnosis Based on Deep Qualitative
Modelling”, Chapter 16 for the book Issues of Fault Diagnosis for Dynamic
Systems, (eds.) R. J. Patton, P. M. Frank, and R. N. Clark, Springer-Verlag, 2000, PP461-483.
6. J. Zhang and A. J. Morris, “Inferential Estimation
and Optimal Control of a Batch Polymerisation Reactor Using Stacked Neural
Networks”, Chapter 11 for the book Application of Neural Network and Other
Learning Technologies in Process Engineering, (ed) I.
M. Mujtaba and M. A. Hussain, Imperial College Press, 2001, PP243-266.
7. J. Morris and J. Zhang, “Performance Monitoring and
Batch to Batch Control of Biotechnological Processes”, Chapter 10 for the book
Computational Intelligent Techniques for Bioprocesses Modelling Supervision and
Control, (eds.) M. C. Nicoletti and L. C. Jain, Springer-Verlag,
2009, PP281-310.
8. J. Zhang, “Nonlinear Process Modelling and Control
Using Neurofuzzy Networks”, Chapter 12 for the book
Handbook of Natural Computing, (eds.) G. Rozenberg,
T. Back, and J. Kok, Springer-Verlag,
2012, Vol. 1, PP401-434.
9. J. Zhang, Y. Feng, M. H. Al-Mahrouqi,
“Reliable Optimal Control of a Fed-Batch Fermentation Process Using Ant Colony
Optimisation and Bootstrap Aggregated Neural Network Models”, Chapter 7 for the
book Applications of Metaheuristics in
Process Engineering, (eds.) J. Valadi
and P. Siarry, Springer-Verlag,
2014, PP183-200.
1. J. Zhang, P. D. Roberts, and J. E. Ellis, “A Fault
Diagnosis System with Self-Reasoning Facilities Based on Qualitative
Modelling”, presented at IMACS/IFAC International Symposium on Mathematical and
Intelligent Models in System Simulation, Brussels, September 3-7, 1990,
published in Mathematical and Intelligent Models in System Simulation, (eds) R. Hanus, P. Kool, and S. Tzafestas, Scientific Publishing Co., 1991, PP431-444.
2. J. Zhang, M. T. Tham, A. J. Morris, and P. D.
Roberts, “Knowledge based Process Supervisory Control”, Proceedings of
IFAC/IFORS/IMACS International Symposium on Large Scale Systems: Theory and
Applications, 23-25 August 1992, Beijing, China, PP269-274. (Invited paper)
3. J. Zhang and M. T. Tham, “A Systematic Approach for
the Comparison and Selection of Distillation Control Configurations”,
Proceedings of I. Chem. E. conference “Advances in Process Control III”, York,
U.K., 23-24 September 1992, PP247-250.
4. J. Zhang, A. J. Morris, G. A. Montague, and M. T.
Tham, “Dynamic System Modelling Using Mixed Node Neural Networks”, Proceedings
of IFAC Symposium ADCHEM'94, Kyoto, Japan, May 25-27, 1994, PP114-119.
5. M. Bravi, A. Chianese, C.
Mustacchi, M. Sed, and J.
Zhang, “A Neural Network Inferential Model for Crystallizer Dynamics”,
presented at the First National Conference on Chaos and Fractals in Chemical
Engineering, Rome, Italy, May 25-27, 1994.
6. J. Zhang and A. J. Morris, “Fuzzy Neural Networks
in Process Modelling and Fault Diagnosis”, Proceedings of Advanced Summer Institute
(ASI'94) in Cooperative Intelligent Manufacturing Systems, Patras,
Greece, June 26 - July 1, 1994, Vol.1, PP166-173.
7. J. Zhang and A. J. Morris, “Process Fault Diagnosis
Using Fuzzy Neural Networks”, Proceedings of American Control Conference 1994,
Baltimore, Maryland, USA, June 29 - July 1, 1994, Vol.1, PP971-975.
8. J. Zhang, A. J. Morris, and G. A. Montague, “Fault
Diagnosis of a CSTR Using Fuzzy Neural Networks”, Proceedings of IFAC Symposium
AIRTC'94, Valencia, Spain, October 3-5, 1994, PP153-158.
9. J. Zhang, M. T. Tham, and A. J. Morris, “High
Performance Distillation Column Control through Novel Control Configurations”,
Proceedings of IFAC Symposium DYCORD+95, Helsingor,
Denmark, 7-9 June, 1995, PP93-98.
10. J. Zhang, X. Yang, A. J. Morris, and C.
Kiparissides, “Neural Network Based Estimators for a Batch Polymerization
Reactor”, Proceedings of IFAC Symposium DYCORD+95, Helsingor,
Denmark, 7-9 June, 1995, PP129-133.
11. J. Zhang and A. J. Morris, “A Comparison of
Several on-line Fault Diagnosis Systems for a CSTR”, Proceedings of IFAC
Workshop on Fault Detection and Supervision in the Chemical Process Industries,
Newcastle, U.K., 12-13 June, 1995, PP89-94.
12. J. Zhang and A. J. Morris, “Dynamic Process
Modelling Using Locally Recurrent Neural Networks”, Proceedings of American
Control Conference 1995, Seattle, USA, 21-23 June, 1995, Vol.4, PP2767-2771.
13. A. K. Conlin, J. Zhang,
E. B. Martin, and A. J. Morris, “Nonlinear Statistical Projection Methods and
Artificial Neural Networks”, Proceedings of American Control Conference 1995,
Seattle, USA, 21-23 June, 1995, Vol.3, PP1852-1856.
14. J. Zhang, E. B. Martin, and A. J. Morris, “Fault
Detection and Classification through Multivariate Statistical Techniques”,
Proceedings of American Control Conference 1995, Seattle, USA, 21-23 June,
1995, Vol.1, PP751-755.
15. J. Zhang and A. J. Morris, “Inferential Estimators
for a Batch Polymerisation Reactor based on Mixed Node Neural Networks”,
Proceedings of IFAC Conference on Youth Automation, Beijing, China, 22-24
August, 1995, Vol.2, PP689-693.
16. J. Zhang, M. T. Tham, and A. J. Morris,
“Distillation Control Structure Selections through Robust Performance
Analysis”, Proceedings of IFAC Conference on Youth Automation, Beijing, China,
22-24 August, 1995, Vol.2, PP824-828.
17. J. Zhang and A. J. Morris, “Long Range Prediction
Models based on Locally Recurrent Neural Networks”, Proceedings of IFAC
Conference on Youth Automation, Beijing, China, 22-24 August, 1995, Vol.2,
PP708-712.
18. J. Zhang, M. T. Tham, and A. J. Morris, “Improved
Distillation Operation through New Control Configurations”, Proceedings of the
3rd European Control Conference, Rome, Italy, 5-8 September, 1995, PP3105-3110.
19. L. Chen, J. Zhang, A. J. Morris, G. A. Montague,
C. A. Kent, and J. P. Norton, “Combining Neural Networks with Physical
Knowledge in Modelling and State Estimation of Bioprocesses”, Proceedings of
the 3rd European Control Conference, Rome, Italy, 5-8 September, 1995,
PP2426-2431.
20. M. Bravi, A. Chianese,
and J. Zhang, “Dynamic Process Modelling of a Cooling Crystallizer Using
Locally Recurrent Neural Networks”, Proceedings of the 3rd European Control
Conference, Rome, Italy, 5-8 September, 1995, PP2432-2437.
21. X. Yang, J. Zhang, and A. J. Morris, “Target Space
Decomposition and Simplification in Modelling via Artificial Neural Networks”,
presented at IFAC Symposium on Information Control Problems in Manufacturing,
Beijing, China, 11-13 October, 1995.
22. J. Zhang and A. J. Morris, Proceedings of
EUFIT'95, “Sequential Orthogonal Training of Mixed Order Polynomial Neural
Networks”, Aachen, Germany, 28 - 30 August, 1995, Vol.1, PP340-344.
23. J. Zhang and A. J. Morris, “Fuzzy Neural Networks
for the Modelling of Nonlinear Dynamic Systems”, Proceedings of EUFIT'95,
Aachen, Germany, 28 -30 August 1995, Vol.3, PP1581-1585.
24. X. Yang, J. Zhang, and A. J. Morris, “An
Artificial Neural Network Approach for Inferential Measurement”, Proceedings of
International Conference on Neural Information Processing, Beijing, China, 30
October - 3 November, 1995, Vol.1, PP485-488.
25. J. Zhang, E. B. Martin, and A. J. Morris,
“Non-linear Statistical Process Monitoring”, presented at Advances in Fault
Diagnosis in Process Control III, York, U.K., 22 April
1996.
26. J. Zhang, A. J. Morris, and E. B. Martin, “Robust
Process Fault Detection Using Neuro-Fuzzy Networks”, Proceedings of The 13th
IFAC World Congress, San Francisco, USA, June 30 - July 5, 1996, Vol.N, PP169-174.
27. J. Zhang, E. B. Martin, and A. J. Morris, “Process
Monitoring Using Non-linear Principal Component Analysis”, Proceedings of The
13th IFAC World Congress, San Francisco, USA, June 30 - July 5, 1996, Vol.N, PP265-270.
28. X. Yang, J. Zhang, and A. J. Morris, “Neural
Network Model and System Used for Nonlinear Control”, Proceedings of The 13th
IFAC World Congress, San Francisco, USA, June 30 - July 5, 1996, Vol.F, PP145-150.
29. J. Zhang, E. B. Martin, and A. J. Morris,
“Non-linear Performance Monitoring”, Proceedings of UKACC International
Conference on Control'96, Exeter, U.K., 2 - 5 September, 1996, Vol.2,
PP924-929.
30. J. Zhang and A. J. Morris, “Neuro-Fuzzy Networks:
Contributions to Process Modelling and Fault Diagnosis”, semi-plenary
presentation at EUFIT'96, Aachen, Germany, 2 - 5 September, 1996.
31. T. Hong, J. Zhang, A. J. Morris, E. B. Martin, and
M. N. Karim, “Neural Based Predictive Control of a Multivariable Microalgae
Fermentation”, Proceedings of IEEE International Conference on Systems, Man and
Cybernetics, Beijing, China, 14-17 October, 1996, Vol.1, PP345-350.
32. T. Hong, M. N. Karim, A. J. Morris, J. Zhang, and
W. Luo, “Nonlinear Control of a Wastewater pH Neutralisation Process Using
Adaptive NARX Models”, Proceedings of IEEE International Conference on Systems,
Man and Cybernetics, Beijing, China, 14-17 October, 1996, Vol.2, PP911-916.
33. J. Zhang, E. B. Martin, and A. J. Morris, “Robust
Non-linear Models through Bootstrap Aggregated Neural Networks”, in Neural
Networks - Producing Dependable Systems, ERA Technology, Surrey, U. K., 17
April, 1997, PP15-26, ISBN 0 7008 0636 9.
34. J. Morris, E. Martin, J. Zhang, R. Shao, “Building
Robust Neural Networks for Industrial Process Applications”, IEE Colloquium on
Neural Networks for Industrial Applications, 1997, PP7/1-7/3.
35. J. Zhang and A. J. Morris, “Neuro-Fuzzy Networks
for Process Modelling and Model-based Control”, IEE Colloquium on Neural and
Fuzzy Systems: Design, Hardware and Applications, Savoy Place, London, 9 May,
1997, PP6/1-6/4.
36. J. Zhang, A. J. Morris, E. B. Martin, and C.
Kiparissides, “Estimation of Impurity and Fouling in Batch Polymerisation
Reactors Using Stacked Neural Networks”, Proceedings of American Control
Conference 1997, Albuquerque, U.S.A., 4 - 6 June, 1997, Vol.1, PP247-251.
37. J. Zhang, E. B. Martin, A. J. Morris, and C.
Kiparissides, “Prediction of Polymer Quality in Batch Polymerisation Reactors”,
Proceedings of American Control Conference 1997, Albuquerque, U.S.A., 4 - 6
June, 1997, Vol.3, PP1370-1374.
38. J. Zhang and A. J. Morris, “Nonlinear Process
Modelling Using Dynamic Neuro-Fuzzy Networks”, Proceedings of IFAC Symposium
ADCHEM'97, Banff, Canada, 9-11 June, 1997, PP339-344.
39. J. Zhang, E. B. Martin, and A. J. Morris,
“Building Robust Nonlinear Models through Multiple Neural Networks”,
Proceedings of The Second Chinese World Congress on Intelligent Control and
Intelligent Automation, Xian, China, 23 - 27 June, 1997, Vol.3, PP1724-1729.
40. R. Shao, J. Zhang, E. B. Martin, and A. J. Morris,
“Novel Approaches to Confidence Bound Generation for Neural Network
Representations”, Proceedings of The 5th International Conference on Artificial
Neural Networks, Cambridge, England, 7 - 9 July, 1997, PP76-81.
41. J. Zhang and A. J. Morris, “Neuro-Fuzzy Network
Model Based Predictive Control”, Proceedings of EUFIT'97, Aachen, Germany, 8 -
11 September, 1997, Vol.2, PP1009-1013.
42. J. Zhang and A. J. Morris, “Long Range Predictive
Control of Nonlinear Processes Based on Recurrent Neuro-Fuzzy Network Models”,
Proceedings of 5th UK Workshop on Fuzzy Systems, Sheffield, U.K., 26 -27 May,
1998, Vol.1, PP11-18.
43. Y. Tian, J. Zhang and A. J. Morris, “Neural
Network Based Optimal Control of a Fed-Batch Reactor”, Proceedings of EUFIT'98,
Aachen, Germany, 7 - 10 September, 1998, Vol.1, PP308-312.
44. Y. Tian, J. Zhang and A. J. Morris, “Optimal Control
of a Batch Copolymerisation Reactor Based on Recurrent Neural Networks”,
Proceedings of EUFIT'99, Aachen, Germany, 13 - 16 September, 1999, CD-ROM.
45. L. Chen, Y. Hontoir, J.
Zhang, and G. Bastin, “Model Based Control of A
Reactive Distillation Column”, Proceedings of IFAC ADCHEM2000, Pisa, Italy, 14
- 16 June, 2000, PP99-104.
46. L. Chen, Y. Hontoir, D.
Huang, J. Zhang, and J. Morris, “Combining First Principles with Black-Box
Techniques for Reaction Systems”, Proceedings of IFAC SYSID2000, Santa Barbara,
California, USA, 21 - 23 June, 2000, PP427-432.
47. J. Zhang, “Inferential Feedback Control of
Distillation Composition based on PCR and PLS Models”, Proceedings of American
Control Conference 2001, Arlington, Virginia, U.S.A., 25 - 27 June, 2001,
PP1196-1201.
48. J. Zhang and R. Agustriyanto, “Inferential
Feedforward Control of a Distillation Column”, Proceedings of American Control
Conference 2001, Arlington, Virginia, U.S.A., 25 - 27 June, 2001, PP2555-2560.
49. J. Zhang and A. J. Morris, “Nonlinear Model
Predictive Control based on Multiple Local Linear Models”, Proceedings of
American Control Conference 2001, Arlington, Virginia, U.S.A., 25 - 27 June,
2001, PP3503-3508. (Invited paper)
50. Y. Tian, J. Zhang, and A. J. Morris, “On-line
Re-optimisation Control of a Batch Polymerisation Reactor based on a Hybrid
Recurrent Neural Network Model”, Proceedings of American Control Conference
2001, Arlington, Virginia, U.S.A., 25 - 27 June, 2001, PP350-355. (Invited
paper)
51. J. Zhang, “Recurrent Neuro-Fuzzy Networks for the
Modelling and Optimal Control of Batch Processes”, Proceedings of the Joint 9th
IFSA World Congress and the 20th NAFIPS International Conference, Vancouver,
Canada, 25-28 July, 2001, Vol.1, PP523-528. (Invited paper)
52. R. J. Patton, C. J. Lopez, S. Simani,
J. Morris, E. Martin, and J. Zhang, “Actuator Fault Diagnosis in a Continuous
Stirred Tank Reactor Using Identification Techniques”, Proceedings of European
Control Conference 2001, Porto, Portugal, 4 - 7 September, 2001, PP2729-2734.
53. Z. Xiong and J. Zhang, “Neural Network Based
On-Line Re-Optimisation Control of Fed-Batch Processes Using Iterative Dynamic
Programming for Discret-Time Systems”, Proceedings of
the 15th IFAC World Congress, Barcelona, Spain, July 21-26, 2002, PP967-972.
54. J. Zhang, “Sequential Training of Bootstrap
Aggregated Neural Networks for Nonlinear Systems Modelling”, Proceedings of
American Control Conference 2002, Anchorage, Alaska, U.S.A., 8 - 10 May, 2002,
Vol.1, PP531-536.
55. X. G. Liu, Y. M. Xu, J. Zhang, and J. X. Qian,
“Optimal energy cost in ideal internal thermally coupled distillation columns”,
Proceedings of American Control Conference 2002, Anchorage, Alaska, U.S.A., 8 -
10 May, 2002, Vol.2, PP1502-1507.
56. J. Wei, S. Fan, Y. M. Xu, and J. Zhang, “Dynamic
Modelling of an Industrial Polypropylene Reactor and Its Application in Melt
Index Prediction During Grade Transitions”, Proceedings of American Control
Conference 2002, Anchorage, Alaska, U.S.A., 8 - 10 May, 2002, Vol.4,
PP2725-2730.
57. Z. Xiong and J. Zhang, “Modelling and Optimal
Control of Fed-Batch Processes Using Affine-Feedforward Neural Networks”,
Proceedings of American Control Conference 2002, Anchorage, Alaska, U.S.A., 8 -
10 May, 2002, Vol.6, PP5025-5030.
58. Z. Ahmad and J. Zhang, “A Comparison of Different
Methods for Combining Multiple Neural Networks Models”, Proceedings of The 2002
International Joint Conference on Neural Networks, Honolulu, Hawaii, U.S.A., 12
- 17 May, 2002, Vol.1, PP828-833.
59. J. Zhang, “A Training Method for Enhancing Neural
Network Model Generalisation”, Proceedings of The 2002 International Joint
Conference on Neural Networks, Honolulu, Hawaii, U.S.A., 12 - 17 May, 2002,
Vol.1, PP800-805.
60. J. Wei, Y. M. Xu, and J. Zhang, “Neural Networks
based Model Predictive Control of an Industrial Polypropylene Process”,
Proceedings of IEEE Conference on Control Applications, Glasgow, Scotland, 18 -
20 September, 2002, Vol.1, PP397-402.
61. M. Zhang, Y. M. Xu, X. G. Liu, and J. Zhang,
“Industrial Application of Non-equilibrium Model: Simulation and Analysis of
Ethylene Fractionator”, Proceedings of IEEE Conference on Control Applications,
Glasgow, Scotland, 18 - 20 September, 2002, Vol.1, PP415-420.
62. “A Steady State Model for Propylene Polymerization
in an Industrial Loop Reactor and Its Application in Melt Index Predication”,
J. Jiang, Y. M. Xu, and J. Zhang, Proceedings of IEEE Conference on Control
Applications, Glasgow, Scotland, 18 - 20 September, 2002, Vol.1, PP409-414.
63. Z. Xiong and J. Zhang, “Optimal Control of Batch
Processes Incorporating Model Prediction Confidence Bounds based on Multiple
Neural Networks”, Proceedings of IEEE Conference on Control Applications,
Glasgow, Scotland, 18 - 20 September, 2002, Vol.1, PP48-53. (Invited paper)
64. Z. Ahmad and J. Zhang, “Improving Long Range
Prediction for Nonlinear Process Modelling through Combining Multiple Neural
Networks”, Proceedings of IEEE Conference on Control Applications, Glasgow,
Scotland, 18 - 20 September, 2002, Vol.2, PP966-971.
65. J. Zhang, “Improved On-line Process Fault
Diagnosis Using Stacked Neural Networks”, Proceedings of IEEE Conference on
Control Applications, Glasgow, Scotland, 18 - 20 September, 2002, Vol.2,
PP689-694.
66. Z. Ahmad and J. Zhang, “Selective Combination of
Multiple Neural Networks for Improving Long Range Prediction in Nonlinear
Process Modelling through Correlation Coefficient Analysis”, Proceedings of
International Conference on Robotics, Vision, Information and Signal Processing
(ROVISP) 2003, Penang Malaysia, 22-24 January 2003, PP472-479.
67. J. Zhang and Y. M. Xu, “Inferential Estimation of
Polymer Melt Index Using Bootstrap Aggregated Neural Networks with Sequential
Training”, Proceedings of the IFAC International Conference on Intelligent
Control and Signal Processing, Faro, Portugal, 8 - 11 April, 2003, PP389-394.
68. M. Ahmed and J. Zhang, “Multivariable Inferential
Feedback Control of Distillation Compositions Using Dynamic Principal Component
Regression Models”, Proceedings of American Control Conference 2003, Denver,
Colorado, U.S.A., 4 - 6 June, 2003, Vol.3, PP1974-1979.
69. Z. Xiong and J. Zhang, “Batch-to-Batch Model-based
Iterative Optimisation Control for a Batch Polymerisation Reactor”, Proceedings
of American Control Conference 2003, Denver, Colorado, U.S.A., 4 - 6 June,
2003, Vol.3, PP1962-1967.
70. Z. Xiong and J. Zhang, “Improved Operation of a
Batch Polymerisation Reactor through Batch-to-Batch Iterative Optimisation”,
Proceedings of the IFAC Symposium on Advanced Control of Chemical Processes,
Hong Kong, 18 - 20 June, 2003, PP1068-1073.
71. J. Zhang, “Reliable Optimal Control of a Batch
Polymerisation Reactor Based on Neural Network Model with Model Prediction
Confidence Bounds”, Proceedings of the 8th International Symposium on Process
Systems Engineering, Kunming, China, 22 - 27 June 2003, PP1129-1134.
72. J. Zhang, “Multi-Objective Optimal Control of
Batch Processes Using Neuro-Fuzzy Networks”, Proceedings of The 2003
International Joint Conference on Neural Networks, Portland, Oregon, U.S.A., 20
- 24 July, 2003, PP304-309.
73. Z. Ahmad and J. Zhang, “Improving Data based
Nonlinear Process Modelling through Bayesian Combination of Multiple Neural
Networks”, Proceedings of The 2003 International Joint Conference on Neural
Networks, Portland, Oregon, U.S.A., 20 - 24 July, 2003, PP2472-2477.
74. Z. Ahmad, J. Zhang and F. S. Taip,
“Selective Combination of Multiple Neural Networks for Improving Long Range
Prediction in Nonlinear Process Modelling based on Correlation Analysis”,
Proceedings of International Conference on Chemical and Bioprocess Engineering,
Kota Kinabalu, Sabah, Malaysia, August 2003, Vol.1,
PP326-333.
75. J. Zhang, “Neural Network Model based
Batch-to-Batch Optimal Control”, Proceedings of The 2003 IEEE International
Symposium on Intelligent Control, Houston, Texas, U.S.A., 5 - 8 October, 2003,
PP352-357.
76. M. Ahmed and J. Zhang, “Improved Inferential
Feedback Control through Combining Multiple PCR Models”, Proceedings of The
2003 IEEE International Symposium on Intelligent Control, Houston, Texas,
U.S.A., 5 - 8 October, 2003, PP878-883.
77. Z. Xiong and J. Zhang, “Recurrent Neural Network
Model based Batch-To-Batch Iterative Optimising Control”, Proceedings of IASTED
International Conference on Neural Network and Computational Intelligence, Grindelwald, Switzerland, 22 - 25 February, 2004, PP1-6.
78. Z. Xiong and J. Zhang, “Trajectory Tracking of
Batch Processes with Varying Control Interval and Incrementally Updated
Models”, in (Eds) A. Barbosa-Povoa
and H. Matos, Computer-Aided Chemical Engineering 18, European Symposium on
Computer-Aided Process Engineering - 14, Lisbon, Portugal, 16 – 19 May, 2004,
PP853-858, Elsevier Science BV, Amsterdam.
79. Z. Ahmad and J. Zhang,, “Improving Long Range
Prediction in Nonlinear Process Modelling through Bayesian Combination of
Multiple Neural Networks”, Proceedings of ESCAPE14, Lisbon, Portugal, 16 – 19
May, 2004, CD.
80. S. J. Zhao, Y. M. Xu, and
J. Zhang, “A Multiple PCA Model based Technique for the Monitoring of Processes
with Multiple Operating Modes”, in (Eds) A. Barbosa-Povoa and H. Matos, Computer-Aided Chemical Engineering 18,
European Symposium on Computer-Aided Process Engineering - 14, Lisbon,
Portugal, 16 – 19 May, 2004, PP865-870, Elsevier Science BV, Amsterdam.
81. K. Bezas, D. Farrugia, A. Richardson, T. Musicka,
J. Zhang, and E. B. Martin, “Modelling the Distortion of Long Product Sections
after Hot Rolling Using Finite Elements and Neural Networks”, 5th International
Conference on Quality, Reliability and Maintenance, Oxford, England, 1 – 2
April, 2004, PP201-204.
82. J. Zhang, “Integrated Batch-to-Batch Control and
within Batch Control of Batch Processes Using Neural Network Models”,
Proceedings of The 2004 IEEE International Symposium on Intelligent Control,
Taipei, Taiwan, China, 2 - 4 September, 2004, PP114-119. (Invited paper)
83. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu,
“Run-to-Run Iterative Optimization Control of Batch Processes Based on
Recurrent Neural Networks”, Proceedings of International Symposium on Neural
Networks, Dalian, China, 19 - 21 August, 2004, in Yin, F., Wang, J., Guo, C.
(Eds.), Advances in Neural Networks - ISNN2004, Lecture Notes in Computer
Science (LNCS), Springer-Verlag Heidelberg, Vol.
3174, 2004, PP97-103.
84. Y. Liu, X. Yang, and J. Zhang, “A Neural Network Modeling Method for Batch Process”, Proceedings of
International Symposium on Neural Networks, Dalian, China, 19 - 21 August,
2004, in Yin, F., Wang, J., Guo, C. (Eds.), Advances in Neural Networks -
ISNN2004, Lecture Notes in Computer Science (LNCS), Springer-Verlag Heidelberg, Vol. 3174, 2004, PP874-879.
85. S. J. Zhao, Y. M. Xu, and J. Zhang, “A Novel
Nonlinear Projection to Latent Structures Algorithm”, Proceedings of
International Symposium on Neural Networks, Dalian, China, 19 - 21 August,
2004, in Yin, F., Wang, J., Guo, C. (Eds.), Advances in Neural Networks -
ISNN2004, Lecture Notes in Computer Science (LNCS), Springer-Verlag Heidelberg, Vol. 3174, 2004, PP773-778.
86. Q. Zhou, J. Zhang, and Y. M. Xu, “Predicting the
Product Yield Profile and Cracking Degrees in an Industrial Ethylene Pyrolysis
Furnace”, Proceedings of the 8th International Conference on Control,
Automation, Robotics and Vision (ICARCV2004), 6 - 9 December, 2004, Kunming,
China, Vol.3, 2129-2133.
87. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu,
“Integrated Batch-to-Batch Iterative Learning Control and within Batch Control
of Product Quality for Batch Processes”, Proceedings of the 16th IFAC World
Congress, Prague, Czech Republic, 4 - 8 July, 2005.
88. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu, “An
Integrated Batch-to-batch Iterative Learning Control and within Batch Control
Strategy for Batch Processes”, Proceedings of the 2005 American Control
Conference (ACC 2005), 8 – 10 June, 2005, Portland, Oregon, USA, PP1935-1940.
89. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu, “Neural
Network Based on-line Shrinking Horizon Re-optimization of Fed-batch
Processes”, Proceedings of the Second International Symposium on Neural
Networks (ISNN2005), 30 May – 1 June, 2005, Chongqing, China, in Wang, J.,
Liao, X., Zhang, Y. (Eds.), Advances in Neural Networks – ISNN 2005, Lecture
Notes in Computer Science (LNCS), Springer-Verlag
GmbH, Vol. 3498, 2005, PP839-844.
90. Y. Liu, X. Yang, Z. Xiong, and J. Zhang,
“Batch-to-Batch Optimal Control Based on Support Vector Regression Model”,
Proceedings of the Second International Symposium on Neural Networks
(ISNN2005), 30 May – 1 June, 2005, Chongqing, China, in Wang, J., Liao, X.,
Zhang, Y. (Eds.), Advances in Neural Networks – ISNN 2005, Lecture Notes in
Computer Science (LNCS), Springer-Verlag GmbH, Vol.
3498, 2005, PP125-130.
91. Q. Zhou, Z. Xiong, J. Zhang, and Y. M. Xu,
“Hierarchical Neural Network Based Product Quality Prediction of Industrial
Ethylene Pyrolysis Process”, Proceedings of the Third International Symposium
on Neural Networks (ISNN2006), 28 May – 1 June, 2006, Chengdu, China, Advances
in Neural Networks – ISNN 2006, Lecture Notes in Computer Science (LNCS),
Springer-Verlag GmbH, Vol. 3973, 2006, PP1132-1137.
92. Z. Ahmad and J. Zhang, “A Nonlinear Model
Predictive Control Strategy Using Multiple Neural Network Models”, Proceedings
of the Third International Symposium on Neural Networks (ISNN2006), 28 May – 1
June, 2006, Chengdu, China, Advances in Neural Networks – ISNN 2006, Lecture
Notes in Computer Science (LNCS), Springer-Verlag
GmbH, Vol. 3972, 2006, PP943-948.
93. A. Mukherjee and J. Zhang, “Reliable
Multi-Objective Optimal Control of Batch Processes based on Stacked Neural
Network Models”, in (Eds) W. Marquardt and C. Pantelides, Computer-Aided Chemical Engineering 21, 16th
European Symposium on Computer Aided Process Engineering and 9th International
Symposium on Process Systems Engineering, July 9 - 13, 2006,
Garmisch-Partenkirchen, Germany, PP1407-1412.
94. R. Agustriyanto and J. Zhang, “Control Structure
Selection for the Alstom Gasifier Benchmark Process Using GRDG Analysis”,
Proceedings of the International Conference Control 2006, 30 August – 1
September, 2006, Glasgow, Scotland, CD.
95. R. Agustriyanto and J. Zhang, “Self Optimizing
Control of an Evaporation Process Under Noisy
Measurements”, Proceedings of the International Conference Control 2006, 30
August – 1 September, 2006, Glasgow, Scotland, CD.
96. S. Al-Mawali and J. Zhang, “A Fuzzy Approach to
Active Surge Control of Centrifugal Compressors”, Proceedings of the
International Conference Control 2006, 30 August – 1 September, 2006, Glasgow,
Scotland, CD.
97. Z. Xiong, J. Zhang, X. Wang, and Y. M. Xu,
“Integrated Control of Product Quality for Batch Processes with Model
Uncertainties”, Proceedings of the International Conference Control 2006, 30
August – 1 September, 2006, Glasgow, Scotland, CD.
98. F. Herrera and J. Zhang, “Optimal Control of a
Fed-Batch Process Using Particle Swarm Optimisation and Neural Networks”,
Proceedings of the 2006 UK Workshop on Computational Intelligence, Leeds, 4 – 6
September 2006, Leeds, UK, PP149-156.
99. S. Al-Mawali and J. Zhang, “Fuzzy Active Surge
Control for Centrifugal Compressors”, Proceedings of the 2006 UK Workshop on Computational
Intelligence, Leeds, 4 – 6 September 2006, Leeds, UK, PP173-180.
100. J. Zhang, “Multi-Objective Optimal Control of a
Fed-Batch Process Using Recurrent Neuro-Fuzzy Networks”, Proceedings of the
2006 UK Workshop on Computational Intelligence, Leeds, 4 – 6 September 2006,
Leeds, UK, PP191-197.
101. R. Agustriyanto and J. Zhang, “Obtaining the
Worst Case RGA and RDGA for Uncertain Systems via Optimization”, Proceeding of
the 2007 American Control Conference (ACC 2007), 11 – 13 July, 2007, New York,
USA, PP5360-5365.
102. Z. Xiong and J. Zhang, “Integrated Tracking
Control for Batch Processes in the Presence of Model Uncertainties”,
Proceedings of The Sixth IEEE International Conference
on Control and Automation (IEEE ICCA 2007), 30 May – 1 June, 2007, Guangzhou,
China, PP2417-2422.
104. S. Al-Mawali
and J. Zhang, “A Novel Fuzzy Logic Control Strategy for Compressor Surge
Control Using a Variable Area Throttle”, Proceedings of the
22nd IEEE International Symposium on Intelligent Control, 1 – 3 October
2007, Singapore, PP682-687.
105. R. Agustriyanto and J. Zhang, “GRDG Analysis of
the ALSTOM Gasiifier Benchmark Process under Model
Plant Mismatch”, Proceeding of International Conference on Control, Automation
and Systems 2007, 17 – 20 October, 2007, Seoul, Korea, PP883-888.
106. Z. Xiong and J. Zhang, “Optimal Iterative
Learning Control for Endpoint Product Qualities in Semi-batch Process based on
Neural Network Model”, Proceedings of
the 2008 International Conference on Modelling, Identification and
Control (ICMIC’2008), June 29- July 2,
2008 Shanghai, China, CD, paper No. A6-52.
107. A. Mukherjee and J. Zhang, “Reliable
Multi-Objective On-line Re-Optimisation Control of Batch Processes Based on
Bootstrap Aggregated Neural Networks”,
Proceedings of the 17th IFAC World Congress, 6 – 11 July, 2008, Seoul,
Korea, PP10927-10932.
108. M. Al-Mahrouqi and J.
Zhang, “Reliable Optimal Control of a Fed-Batch Bio-Reactor Using Ant Colony
Optimization and Bootstrap Aggregated Neural Networks”, Proceedings of the 17th
IFAC World Congress, 6 – 11 July, 2008, Seoul, Korea, PP8407-8412.
109. F. Herrera and J. Zhang, “Optimal Control of
Fed-Batch Processes Using Particle Swarm Optimisation with Stacked Neural
Network Models”, in (Eds) B. Braunschweig
and X. Joulia, Computer-Aided Chemical Engineering
25, Proceedings of the 18th European Symposium on Computer Aided Process
Engineering, 1 – 4 June 2008, Lyon, France, PP375-380.
110. J. Zhang, J. Nguyan, J.
Morris, and Z. Xiong, “Batch to Batch Iterative Learning Control of A Fed-batch
Fermentation Process Using Linearised Models”,
Proceedings of the Tenth International Conference on Control, Automation,
Robotics and Vision (ICARCV 2008), 17 – 20 December, 2008, Hanoi, Vietnam,
PP745-750.
111. H. Geng, Z. Xiong, Y.
Xu, and J. Zhang, “Iterative Learning Control with Reference Batch for Linear
Time-Variant Systems”, Proceedings of the Tenth International Conference on
Control, Automation, Robotics and Vision (ICARCV 2008), 17 – 20 December, 2008,
Hanoi, Vietnam, PP739-744.
112. J. Zhang, J. Nguyan,
and J. Morris, “Iterative learning control of a crystallisation process using
batch wise updated linearised models identified using
PLS”, in (Eds) J. Jeżowski
and J. Thullie, Computer-Aided Chemical Engineering
26, Proceedings of the 19th European Symposium on Computer Aided Process
Engineering, 14 – 17 June 2009, Cracow, Poland, PP387-392.
113. C. Zhou, Q. Liu, D. X. Huang, and J. Zhang,
“Inferential estimation of kerosene dry point in refineries with varying
crudes”, in (Eds) J. Jeżowski
and J. Thullie, Computer-Aided Chemical
Engineering 26, Proceedings of the 19th European Symposium on
Computer Aided Process Engineering, 14 – 17 June 2009, Cracow, Poland,
PP273-278.
114. J. J. Hong, J. Zhang, and J. Morris, “Enhanced
Predictive Modeling Using Multi Block Methods”, in (Eds) J. Jeżowski and J. Thullie, Computer-Aided Chemical Engineering 26,
Proceedings of the 19th European Symposium on Computer Aided Process
Engineering, 14 – 17 June 2009, Cracow, Poland, PP327-332.
115. S. Stubbs, J. Zhang, and J. Morris, “Fault
detection of dynamic processes using a simplified monitoring-specific CVA state
space approach”, in (Eds) J. Jeżowski
and J. Thullie, Computer-Aided Chemical Engineering
26, Proceedings of the 19th European Symposium on Computer Aided Process
Engineering, 14 – 17 June 2009, Cracow, Poland, PP339-344.
116. H. Geng, Z. Xiong, Y.
Xu, and J. Zhang, “Iterative Learning Control with Fixed Reference Batch and
Exponential Learning Gain for Linear Systems”, Proceedings of the 21st Chinese
Control and Decision Conference, Guilin, China, 17 - 19 June, 2009,
PP1740-1745.
117. J. Zhang, J. Nguyan, Z.
Xiong, and J. Morris, “Iterative Learning Control of a Crystallisation Process
Using Batch Wise Updated Linearised Models”,
Proceedings of the 21st Chinese Control and Decision Conference, Guilin, China,
17 - 19 June, 2009, PP1734-1739.
118. T. Chen and J. Zhang, “On-line statistical monitoring
of batch processes using Gaussian mixture model”, Proceedings of the IFAC
Symposium on Advanced Control of Chemical Processes, Istanbul, Turkey, 12 - 15
July, 2009.
119. F. L. F. Barbosa, M. Tham, and J. Zhang, “Human
Operator Based Fuzzy Intuitive Controllers Tuned with Genetic Algorithms”,
Proceedings of the IFAC Symposium on Advanced Control of Chemical Processes,
Istanbul, Turkey, 12 - 15 July, 2009.
120. J. J. Hong and J. Zhang, “Quality Prediction for
a Fed-Batch Fermentation Process Using Multi-Block PLS”, in (Eds) J. H. Lee, H. Lee, J. S. Kim, EKC 2009 Proceedings of
EU-Korea Conference on Science and Technology, Springer Proceedings in Physics,
Vol. 135, Reading, UK, 5-7 August 2009, PP155-162.
121. M.Y.M. Yunus and J. Zhang, “A Multidimensional
Scaling based Process Monitoring Technique ”, in (Eds)
S. Pierucci and G. Buzzi
Ferraris, Computer-Aided Chemical Engineering, Proceedings of the 20th European
Symposium on Computer Aided Process Engineering, 6 – 9 June 2010, Naples,
Italy.
122. M.Y.M. Yunus and J. Zhang, “Multivariate Process
Monitoring Using Classical Multidimensional Scaling and Procrustes Analysis”,
Proceedings of the IFAC Symposium on Dynamics and Control of Process Systems
(DYCOPS 2010), Leuven, Belgium, 5 - 7 July, 2010, PP151-156.
123. S. Stubbs, J. Zhang, and J. Morris, “A Novel
State Space Stochastic Estimation Algorithm and Improved Fault Detection using
Combined Index Monitoring for Dynamic Processes”, Proceedings of the IFAC
Symposium on Dynamics and Control of Process Systems (DYCOPS 2010), Leuven,
Belgium, 5 - 7 July, 2010, PP797-802.
124. J. Lingeson, J. Zhang, A. Hussain and J. Morris,
“Batch-to-Batch Iterative Learning Control of a Fed-batch Fermentation Process
Using Incrementally Updated Models”, Proceedings of the IFAC Symposium on
Computer Applications in Biotechnology (CAB 2010), Leuven, Belgium, 7 - 9 July,
2010, PP78-83.
125. M.Y.M. Yunus and J. Zhang, “Multivariate Process
Monitoring Using Multidimensional Scaling and Procrustes Analysis”, Proceedings
of the 7th European Congress of Chemical Engineering and 19th International
Congress of Chemical and Process Engineering, Prague, Czech Republic, 28 August
– 1 September, 2010, paper F8.1.
126. W. McLeod and J. Zhang, “Iterative Learning
Control of a Fed-batch Bioreactor with Incrementally Updated Models”,
Proceedings of the 7th European Congress of Chemical Engineering and 19th
International Congress of Chemical and Process Engineering, Prague, Czech
Republic, 28 August – 1 September, 2010, paper F8.4.
127. J. J. Hong and J. Zhang, “Progressive PCA modeling for enhanced fault diagnosis in a batch process”,
Proceedings of International Conference on Control, Automation and Systems
(ICCAS 2010), Gyeonggi-do, Korea, 27-30 October 2010,
PP713-718.
128. J. Zhang and N G. Pantelelis, “Modelling and
Optimisation Control of Polymer Composite Moulding Processes Using Bootstrap
Aggregated Neural Network Models”, Proceedings of the International Conference
on Electric Information and Control Engineering (ICEICE 2011), 15 – 17 April
2011, Wuhan, China, Vol.3, PP2363-2366.
129. J. Zhang and N G. Pantelelis, “Iterative learning
control of a reactive polymer composite moulding process using batch wise
updated linearised models”, in (Eds)
E. N. Pistikopoulos,
M. C. Georgiadis, and A. C. Kokossis, Computer-Aided Chemical Engineering, Proceedings
of the 21st European Symposium on Computer Aided Process Engineering, 29 May –
1 June 2011, Chalkidiki, Greece, PP1613-1617.
130. J. Zhang, Y. Feng, and M. H. Al-Mahrouqi, “Reliable optimal control of a fed-batch
fermentation process using ant colony optimisation and bootstrap aggregated
neural network models”, in (Eds) E. N. Pistikopoulos, M. C. Georgiadis,
and A. C. Kokossis, Computer-Aided Chemical
Engineering, Proceedings of the 21st European Symposium on Computer Aided
Process Engineering, 29 May – 1 June 2011, Chalkidiki,
Greece, PP664-667.
131. Z. Xiong, J. Zhang, C. Ren, and M. Chen,
“Integrated Tracking Control of Batch Processes with Model Uncertainties by
Updating a Linear Perturbation Model”, Proceedings of the 18th IFAC World
Congress, August 28 - September 2, 2011, Milano, Italy, PP4868-4873.
132. K. Ferguson, J. Zhang, C. Steele, C. Clarke, and
J. Morris, “Modelling Vitrified Glass Viscosity in a Nuclear Fuel Reprocessing
Plant Using Neural Networks”, Proceedings of the International Conference on
Neural Computation Theory and Applications (NTCA2011), 24 – 26 October, 2011,
Paris, France, PP322-325.
133. J. Zhang, and N. G. Pantelelis, “Reliable
Modelling and Optimisation Control of Reactive Polymer Composite Moulding
Processes Using Bootstrap Aggregated Neural Network Models”, Proceedings of the
International Conference on Neural Computation Theory and Applications
(NTCA2011), 24 – 26 October, 2011, Paris, France, PP236-241.
134. J. Zhang, Z. Xiong, D. Guillaume, and A. Lamande, “Batch to Batch Iterative Learning Control of a
Fed-batch Fermentation Process”, Proceeding of the 2011
International Conference on Mechanical Engineering and Technology (ICMET
2011), London, UK, Nov. 24-25, 2011, Advances in Intelligent and Soft
Computing, Vol. 125, T.B. Zhang (Ed.), Springer, Mechanical Engineering and
Technology, 2011, pp 253-260.
135. J. Zhang, and N. G. Pantelelis, “Modeling of Reactive Polymer Composite Moulding Processes
Using Neural Networks”, Proceedings of 33rd SAMPLE EUROPE International
Conference, 26 – 27 March, 2012, Paris, France, PP248-253.
136. J. Jewaratnam, J. Zhang, A. Hussain, and J.
Morris, “Reliable Batch-to-Batch Iterative Learning Control of a Fed-batch
Fermentation Process”, in (Eds) I. D. L. Bogle, and
M. Fairweather, Computer-Aided Chemical Engineering,
Proceedings of the 22nd European Symposium on Computer Aided Process
Engineering, 17 – 20 June 2012, London, UK, PP802-806.
137. J. Jewaratnam, J. Zhang, A. Hussain, and J.
Morris, “Batch-to-Batch Iterative Learning Control Using updated Models based
on a Moving Window of Historical Data”, Procedia Engineering, Vol. 42, 2012,
PP232 – 240.
138. J. Zhang, S. Yemashov, and N. G. Pantelelis,
“Iterative Learning Control of a Reactive Polymer Composite Moulding Process”,
Procedia Engineering, Vol. 42, 2012, PP1205 – 1210.
139. F. Antelo and J. Zhang, “Plantwide
control of a benchmark bleach plant ”, Proceedings of the 2012 UKACC
International Conference on Control, CONTROL 2012, 3 – 5 September 2012,
Cardiff, UK, PP154-159.
140. J. Jewaratnam, J. Zhang, J. Morris, and A.
Hussain, “Batch-to-batch iterative learning control using linearised
models with adaptive model updating”, Proceedings of the 2012 UKACC
International Conference on Control, CONTROL 2012, 3 – 5 September 2012,
Cardiff, UK, PP271-276.
141. A. Ganjian, J. Zhang, J. M.L. Dias, R. Oliveira,
“Modelling of a Sequencing Batch Reactor for Producing Polyhydroxybutyrate
with Mixed Microbial Culture Cultivation Process Using Neural Networks and
Operation Regime Classification”, Chemical Engineering Transactions, Vol.32,
2013, PP1261−1266.
142. D. L. Kaunga, J. Zhang,
K. Ferguson, C. Steele, “Reliable Modeling of
Chemical Duarability of High Level Waste Glass Using
Bootstrap Aggregated Neural Networks”, Proceedings of the 9th International
Conference on Natural Computation (ICNC 2013), 23 – 25 July, 2013, Shenyang,
China, PP178-183.
143. A. Ganjin, J. Zhang,
and R. Oliveira, “Optimisation of a Sequencing Batch Reactor for Production of Polyhydroxybutyrate Using Process Characterisation Method
and Neural Network Modelling”, in (Eds) J. J. Klemes, P. S. Varbanov, and P. Y. Liew,
Computer-Aided Chemical Engineering, Proceedings of the 24th European Symposium
on Computer Aided Process Engineering, 15 – 18 June 2014, Budapest, Hungary,
PP733-738.
144. A. Brown, and J. Zhang, “Active Disturbance
Rejection Control of a Neutralisation Process”, in (Eds)
J. J. Klemes, P. S. Varbanov, and P. Y. Liew, Computer-Aided Chemical Engineering, Proceedings of
the 24th European Symposium on Computer Aided Process Engineering, 15 – 18 June
2014, Budapest, Hungary, PP739-744.
145. F. N. Osuolate, and J.
Zhang, “Energy efficient control and optimisation of distillation column using
artificial neural network”, Chemical Engineering Transactions, Vol. 39, Special
Issue, 2014, Pages 37-42, 17th Conference on Process Integration, Modelling and
Optimisation for Energy Saving and Pollution Reduction, PRES 2014; Prague;
Czech Republic; 23-27 August 2014.
146. F. Al-Kalbani, S. M. Al Hosni, and J. Zhang, “Active Disturbance
Rejection Control of a Methanol-Water Separation Distillation Column”, Proceedings
of the 8th IEEE GCC Conference and Exhibition, Muscat, Oman, 1-4 February,
2015, PP. (best paper award, third prize).
147. F. N. Osuolate, and J. Zhang, “Exergetic
Optimisation of Atmospheric and Vacuum Distillation System Based on Bootstrap
Aggregated Neural Network Models”, in Proceedings of the 7th International Exergy, Energy and Environment
Symposium (IEEES'7-2015), Valenciennes,
France, April 27-30, 2015, PP.
148. F. N. Osuolate, and J. Zhang, “Multi-objective Optimisation of
Crude Distillation System Operations Based on Bootstrap Aggregated Neural
Network Models”, in (Eds) Rafiqul Gani, Stefano Cignitti,
and Seyed Soheil Mansouri, Computer-Aided
Chemical Engineering, Proceedings of
the 12th International Symposium on Process Systems Engineering and the 25th
European Symposium on Computer Aided Process Engineering, 31 May – 4 June
2015, Copenhagen, Denmark, PP671-676.
149. F. Al-Kalbani, and J. Zhang, “Inferential Active Disturbance Rejection Control of a
Distillation Column”, Proceedings
of the 9th IFAC International Symposium on Advanced Control of Chemical
Processes (ADCHEM2015), Whistler, British Columbia, Canada, 7-10 June,
2015, PP.
150. F. Al-Kalbani,
and J. Zhang, “Inferential Active
Disturbance Rejection Control of a Distillation Column Using Dynamic Principal
Component Regression Models”, Proceedings
of the 12th International Conference on Informatics in Control, Automation and
Robotics (ICINCO2015), Colmar,
Alsace, France, 21-23 July, 2015, PP.
151. S. Jung,
J. Zhang, and R. Oliveira, “Iterative
Learning Control of Polyhydroxybutyrate Production in
a Sequencing Batch Reactor”, Proceedings
of the 20th International Conference on Methods and Models in Automation and
Robotics (MMAR2015), Miedzyzdroje, Poland, 24-27 August, 2015, PP459-464.
152. S. A. Lawal and J. Zhang, “Actuator Fault Monitoring and Fault Tolerant Control in
Distillation Columns”, Proceedings
of the 21st International Conference on Automation and Computing
(ICAC’15), University of
Strathclyde, Glasgow, UK, 11-12
September, 2015, PP.
153. Weiwei Qiu, Zhihua Xiong, Wanzhou Li,
Jie Zhang, “Point-to-Point Tracking of Integrated Predictive Iterative Learning
Control By using Updating-Reference and CARIMA Model”, accepted for
presentation at the 5th Data-Driven Control and Learning Systems (2016 DDCLS),
May 29-31, 2016, Yinchuan, China, PP.
154. S. A. Lawal and J. Zhang, “Sensor Fault Detection and Fault Tolerant Control
of a Crude Distillation Unit”, in Zdravko Kravanja (Ed), Computer-Aided
Chemical Engineering, Proceedings of the 26th European Symposium on Computer
Aided Process Engineering – ESCAPE 26, 12 -15 June 2016, Portorož, Slovenia, PP2091-2096.
155. Z. Bai, F. Li, J. Zhang, E. Oko, M. Wang, Z. Xiong, D. Huang, “Modelling of a Post-combustion CO2 Capture
Process Using Bootstrap Aggregated Extreme Learning Machines”, in Zdravko Kravanja (Ed), Computer-Aided Chemical Engineering,
Proceedings of the 26th European Symposium on Computer Aided Process
Engineering – ESCAPE 26, 12 -15 June 2016, Portorož,
Slovenia, PP2007-2012.
156. Jingxian Liu, Tao Liu,
Jie Zhang, “Phase Partition for Nonlinear Batch Process Monitoring”, Proceedings of 11th IFAC Symposium on
Dynamics and Control
of Process Systems, including Biosystems (DYCOPS-CAB 2016), 6-8 June 2016,
Trondheim, Norway, PP.
157. Zhihua Xiong, Chen Chen,
Jie Zhang, “Convergence analysis of integrated predictive iterative learning
control based on two-dimensional theory”, Proceedings
of 2016 American Control Conference, 6-8 July 2016, Boston, USA, PP.
158. F. Li, J.
Zhang, E. Oko, M. Wang, “Modelling of a Post-Combustion CO2 Capture
Process Using Extreme Learning Machine”,
Proceedings of the 21st International
Conference on Methods and Models in Automation and Robotics (MMAR2016), Miedzyzdroje,
Poland, 29 August – 1 September, 2016, PP.
159. S. A. Lawal and J. Zhang, “Fault Monitoring and Fault Tolerant Control in
Distillation Columns”, Proceedings of the 21st International
Conference on Methods and Models in Automation and Robotics (MMAR2016), Miedzyzdroje,
Poland, 29 August – 1 September, 2016, PP.
160. F. Al-Kalbani, J. Zhang, T. Bisgaard, J. K. Huusom, “Active Disturbance Rejection
Control of a Heat Integrated Distillation Column”, Proceedings of the 21st
International Conference on Methods and Models in Automation and Robotics
(MMAR2016), Miedzyzdroje,
Poland, 29 August – 1 September, 2016, PP.