1 Henson, M.A., “Nonlinear model predictive control: Current status and future
directions”, Computers and Chemical Engineering, 23(2), 187—202(1998).
2 Cutler, C.R., Ramaker B.L., “Dynamic matrix control - A computer control algorithm
”, In: Proc. of the American Control Conf., IEEE Press, Piscataway, NJ (1980).
3 Clarke, D.W., Mohtadi, C., Tuffs, P.S., “Generalized pre-dictive control (Ⅰ) & (
Ⅱ)”, Automatica, 23(2), 137—160(1987).
4 Chen, Z.Q., Mao, Z.X., Du, S.Z., Sun, Q.L., Yuan, Z.Z., “Analysis of robustness of
PID-GPC based on IMC structure”, Chin. J. Chem. Eng., 11(1), 55—61(2003).
5 Su, B.L, Chen, Z.Q., Yuan, Z.Z., “Multivariable decoup-ling predictive control
with input constraints and its ap-plication on chemical process”, Chin. J. Chem. Eng., 14
(2), 216—222(2006).
6 Zhong, W.M., He, G.L., Pi, D.Y., Sun, Y.X., “SVM with quadratic polynomial kernel
function based nonlinear model one-step-ahead predictive control,” Chin. J. Chem. Eng.,
13(3), 373—379(2005).
7 Wang, Y.H., Huang, D.X., Jin, Y.H., “A hybrid model predictive control for
handling infeasibility and con-straint prioritization”, Chin. J. Chem. Eng., 13(2), 211—
217(2005).
8 Hornik, K., Stinchcombe, M., White, H., “Multilayer feedforward network are
universal approximators”, Neural Networks, 2(5), 359—366(1989).
9 Chen, T.P., Chen, H., “Approximations of continuous functionals by neural network
with application to dy-namics systems”, IEEE Trans. Neural Networks, 4(6), 910—918(1993).
10 Hussian, M.A., “Review of the applications of neural networks in chemical process
control — Simulation and online implementation”, Artificial Intelligence in Engi-neering,
13(1), 55—68(1999).
11 Saint, D.J., Bhat, N., McAvoy, T.J., “Neural net based model predictive control”,
Int. J. Control, 54(6), 1453—1468(1991).
12 Tan, Y., Cauwenberghe, A., “Nonlinear one-step- ahead control using neural
networks: Control strategy and sta-bility design”, Automatica, 32(12), 1701—1706(1996).
13 Ahmed, M.S., Anjum, M.F., “Neural-net-based direct self-turning control of
nonlinear plants”, Int. J. Control, 66(1), 85—104(1997).
14 Li, X., Chen, Z.Q., Yuan, Z.Z., “Simple recurrent neural network-based adaptive
predictive control for nonlinear systems”, Asian J. Control, 4(2), 231—239(2002).
15 Zhang, Y., Chen, Z.Q, Yang, P., Yuan, Z.Z., “Multi- vari-able nonlinear
proportional- integral-derivative decoup-ling control based on recurrent neural net-works”
, Chin. J. Chem. Eng., 12(5), 677—681(2004).
16 Soloway, D., Haley, P.J., “Neural generalized predictive control: A Newton-Raphson
implementation”, In: Proc. IEEE Int. Symposium on Intelligent Control, IEEE Press,
Piscataway, NJ, 277—282(1996).
17 Noriega, J.R., Wang, H., “A direct adaptive neural net-work control for unknown
nonlinear systems and its ap-plication”, IEEE Trans. Neural Networks, 9(1), 27-34(1998).
18 Shin, S.C., Park, S.B., “GA-based predictive control for nonlinear processes”,
Electronics Letters, 34(20), 1980—1981(1998).
19 Wang, X., Xiao, J., “PSO-based model predictive control for nonlinear processes”,
In: Lecture Notes in Computer Science 3611, Springer-Verlag, Berlin, Germany, 196—203
(2005).
20 Li, B., Jiang, W.S., “Optimizing complex functions by chaos search”, Cybernetics
and Systems, 29(4), 409—419(1998).
21 Yu, C.C., Liu, B.D., “A backpropagation algorithm with adaptive learning rate and
momentum coefficient”, In: Proc. 2002 Int. Joint Conf. Neural Networks, IEEE Press,
Piscataway, NJ, 1218—1223(2002).
22 Steeb, W.H., The Nonlinear Workbook: Chaos, Fractals, Cellular Automata, Neural
Networks, Genetic Algo-rithms, Gene Expression Programming, Support Vector Machine,
Wavelets, Hidden Markov Models, Fuzzy Logic with C++, Java and SymbolicC++ Programs, 3rd
Ed. World Science Publisher, Kackensack, NJ (2005).
23 Yan, X.F., Chen, D.Z., Hu, S.X., “Chaos-genetic algo-rithms for optimizing the
operating conditions based RBF-PLS model”, Computers and Chemical Engineering, 27(10),
1393—1404(2003).
24 Liu, B., Wang, L., Jin, Y.H., “Improved particle swarm optimization combined with
chaos”, Chaos, Solitons and Fractals, 25(5), 1261—1271(2005).
25 Lu, Z., Shieh, L.S, Chen, G.R., Coleman, N.P., “Simplex sliding mode control for
nonlinear uncertain systems via chaos optimization”, Chaos, Solitons and Fractals, 23(3),
747—755(2005).
26 Rumelhart, D.E., Hinton, G.E., Williams R.J., “Learning representations by back-
propagating errors”, Nature, 323, 533—536(1986).
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