Engell S. Feedback control for optimal process operation. Journal of Process Control, 2007, 17(3): 203-219
[2]
Scattolini R. Architectures for distributed and hierarchical model predictive control——a review. Journal of Process Control, 2009, 19(5): 723-731
[3]
Hasikos J, Sarimveis H, Zervas P L, Markatos N C. Operational optimization and real-time control of fuel-cell systems. Journal of Power Sources, 2009, 193(1): 258-268
[4]
Tatjewski P. Advanced control and on-line process optimization in multilayer structures. Annual Reviews in Control, 2008, 32(1): 71-85
[5]
Alvarez L A, Odloak D. Robust integration of real time optimization with linear model predictive control. Computers and Chemical Engineering, 2010, 34(12): 1937-1944
[6]
Bischoff K B, Denn M M, Seinfeld J H, Stephanopoulos G, Chakraborty A, Peppas N, Ying J, Wei J. Advances in Chemical Engineering. vol.26. San Diego: Academic Press, 2001
[7]
Findeisen W, Bailey F N, Bryds M, Malinawski K, Tatjewski P, Wozniak A. Control and Coordination in Hierarchical Systems. New York: John Wiley, 1980
[8]
Nath R, Alzein Z. On-line dynamic optimization of olefins plants. Computers & Chemical Engineering, 2000, 24(2-7): 533-538
[9]
Bartusiak R D. NLMPC: a platform for optimal control of feed-or product-flexible manufacturing. Assessment and Future Directions of Nonlinear Model Predictive Control Lecture Notes in Control and Information Sciences. Berlin, Heidelberg: Springer, 2007, 358: 367-381
[10]
Li H X, Guan S P. Hybrid intelligent control strategy. Supervising a DCS-controlled batch process. IEEE Control Systems Magazine, 2001, 21(3): 36-48
[11]
Yang C H, Gui W H, Kong L S, Wang Y L. A two-stage intelligent optimization system for the raw slurry preparing process of alumina sintering production. Engineering Applications of Artificial Intelligence, 2009, 22(4-5): 786-795
[12]
Zhou P, Chai T Y, Sun J. Intelligence-based supervisory control for optimizing the operation of a DCS-controlled grinding system. IEEE Transactions on Control Systems Technology, 2013, 21(1): 162-175
[13]
Chai T Y, Liu J X, Ding J L, Su C Y. Hybrid intelligent optimising control for high-intensity magnetic separating process of hematite ore. Measurement and Control, 2007, 40(6): 171-175
[14]
Yan A J, Chai T Y, Yue H. Multivariable intelligent optimizing control approach for shaft furnace roasting process. Acta Automatica Sinica, 2006, 32(4): 636-640
[15]
Zhou P, Chai T Y, Wang H. Intelligent optimal-setting control for grinding circuits of mineral processing process. IEEE Transactions on Automation Science and Engineering, 2009, 6(4): 730-743
[16]
Ding J L, Chai T Y, Wang H, Chen X K. Knowledge-based global operation of mineral processing under uncertainty. IEEE Transactions on Industry Informatics, 2012, 8(4): 849-859
[17]
Liu Q, Chai T Y, Wang H, Qin S Z J. Data-based hybrid tension estimation and fault diagnosis of cold rolling continuous annealing processes. IEEE Transactions on Neural Networks, 2011, 22(12): 2284-2295
[18]
Chai T Y, Zhao L, Qiu J B, Liu F Z, Fan J L. Integrated network-based model predictive control for setpoints compensation in industrial processes. IEEE Transactions on Industrial Informatics, 2013, 9(1): 417-426
[19]
Darby M L, Nikolaou M, Jones J, Nicholson D. RTO: an overview and assessment of current practice. Journal of Process Control, 2011, 21(6): 874-884
[20]
Mercang?z M, Doyle F J III. Real-time optimization of the pulp mill benchmark problem. Computers and Chemical Engineering, 2008, 32(4-5): 789-804
[21]
J?schke J, Skogestad S. NCO tracking and self-optimizing control in the context of real-time optimization. Journal of Process Control, 2011, 21(10): 1407-1416
[22]
Adetola V, Guay M. Integration of real-time optimization and model predictive control. Journal of Process Control, 2010, 20(2): 125-133
[23]
Wu M, Cao W H, He C Y, She J H. Integrated intelligent control of gas mixing-and-pressurization process. IEEE Transactions on Control Systems Technology, 2009, 17(1): 68-77
[24]
Skogestad S. Plantwide control: the search for the self-optimizing control structure. Journal of Process Control, 2000, 10(5): 487-507
[25]
Marlin T E, Hrymak A N. Real-time operations optimization of continuous processes. In: Proceedings of the 5th International Conference on Chemical Process Control. New York: American Institute of Chemical Engineers, 1997. 156-164
[26]
Hartmann J C M. Distinguish between scheduling and planning models. Hydrocarbon Processing, 1998, 77: 93-100
[27]
Qin S J, Badgewell T A. A survey of industrial model predictive control technology. Control Engineering Practice, 2003, 11(7): 733-764
[28]
Wang Z J, Wu Q D, Chai T Y. Optimal-setting control for complicated industrial processes and its application study. Control Engineering Practice, 2004, 12(1): 65-74
[29]
Wu M, Xu C H, She J H, Yokoyama R. Intelligent integrated optimization and control system for lead-zinc sintering process. Control Engineering Practice, 2009, 17(2): 280-290
[30]
Chai Tian-You, Ding Jin-Liang, Wang Hong, Su Chun-Yi. Hybrid intelligent optimal control method for operation of complex industrial processes. Acta Automatica Sinica, 2008, 34(5): 505-515 (柴天佑, 丁进良, 王宏, 苏春翌. 复杂工业过程运行的混合智能优化控制方法. 自动化学报, 2008, 34(5): 505-515)
[31]
Chai T Y, Ding J L, Wu F H. Hybrid intelligent control for optimal operation of shaft furnace roasting process. Control Engineering Practice, 2011, 19(3): 264-275
[32]
Wu F H, Chai T Y. Soft sensing method for magnetic tube recovery ratio via fuzzy systems and neural networks. Neurocomputing, 2010, 73(13-15): 2489-2497
[33]
Chai T Y, Wu F H, Ding J L, Su C Y. Intelligent work-situation fault diagnosis and fault-tolerant system for the shaft-furnace roasting process. Proceedings of the Institution of Mechanical Engineers Part I: Journal of Systems and Control Engineering, 2007, 221(16): 843-855
[34]
Ding J L, Chai T Y, Wang H. Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization. IEEE Transactions on Neural Networks, 2011, 22(3): 408-419
[35]
Chai T Y, Zhang Y J, Wang H, Su C Y, Sun J. Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control. IEEE Transactions on Neural Networks, 2011, 22(12): 2154-2172
[36]
Yu G, Chai T Y, Luo X C. Multiobjective production planning optimization using hybrid evolutionary algorithms for mineral processing. IEEE Transactions on Evolutionary Computation, 2011, 15(4): 487-514