F. LI387

5. Conclusions

A dynamic neural network based online nonlinear identi-

fier for a binary distillation column is designed. The

learning algorithm of the network weights is established

in detail, which can guarantee the boundedness of the

identification error. To deal with the modeling error, a

nonlinear H∞ controller based on the identifier is given

by choosing the penalty variables for the column. The

effectiveness of the proposed strategy is demonstrated in

simulation results. The algorithm developed in this paper

can be applied to other chemical processes as well.

6. Acknowledgements

The author thanks the reviewers for very helpful com-

ments. Views expressed in this paper are the author’s

professional opinions and do not necessarily represent

the official position of the US Food and Drug Admini-

stration.

7. References

[1] T. J. McAvoy and Y. H. Wang, “Survey of Recent Dis-

tillation Control Results,” ISA Transactions, Vol. 25, No.

1, 1986, pp. 5-21.

[2] S. Skogestad and M. Morari, “Understanding the Dy-

namic Behavior of Distillation Columns,” Industrial &

Engineering Chemistry Research, Vol. 27, No. 10, 1988,

pp. 1848-1862. doi:10.1021/ie00082a018

[3] J. Lévine and P. Rouchon, “Quality Control of Binary

Distillation Columns via Nonlinear Aggregated Models,”

Automatica, Vol. 27, No. 3, 1991, pp. 463-480.

doi:10.1016/0005-1098(91)90104-A

[4] F. Viel, E. Busvelle and J. P. Gauthier. “A Stable Control

Structure for Binary Distillation Columns,” International

Journal of Control, Vol. 67, No. 4, 1997, pp. 475-505.

doi:10.1080/002071797224036

[5] N. F. Jerome and W. H. Ray, “High-Performance Multi-

variable Control Strategies for Systems Having Time

Delays,” AIChE, Vol. 32, No. 6, 1986, pp. 914-931.

doi:10.1002/aic.690320603

[6] S. Skogestad, M. Morari and J. C. Doyle, “Robust Con-

trol of Ill-Conditioned Plants: High Purity Distillation,”

IEEE Transactions on Automatic Control, Vol. 33, No.

12, 1988, pp. 1092-1105. doi:10.1109/9.14431

[7] J. Savkovic, “Neural Net Controller by Inverse Modeling

for a Distillation Plant,” Computers & Chemical Engi-

neering, Vol. 20, No. S2, 1996, pp. S925-S930.

doi:10.1016/0098-1354(96)00162-7

[8] W. Yu, S. Alexander and J. A. Poznykz, “Neuro Control

for Multicomponent Distillation Column,” 1999 IFAC

World Congress, Beijing, 5-9 July 1999, pp. 379-383.

[9] G. Cybenko, “Approximation by Superpositions of Sig-

moidal Function,” Mathematics of Control, Signals, and

Systems, Vol. 5, No. 4, 1989, pp. 303-314.

doi:10.1007/BF02551274

[10] K. Hunt, J. D. Sbarbaro, R. Zbikowshi and P. J. Gaw-

throp, “Neural Networks for Control Systems—A Sur-

vey,” Automatica, Vol. 28, No. 6, 1992, pp. 1083-1112.

doi:10.1016/0005-1098(92)90053-I

[11] M. J. Wills, G. A. Montague, C. Di Massimo, M. T.

Tham and A. J. Morris, “Artificial Neural Networks in

Process Esitmation and Control,” Automatica, Vol. 28,

No. 6, 1992, pp. 1181-1187.

doi:10.1016/0005-1098(92)90059-O

[12] P. Turner, G. Montagueand J. Morris, “Dynamic Neural

Networks in Nonlinear Predictive Control,” Computers &

Chemical Engineering, Vol. 20, No. S2, 1996, pp. S937-

S942. doi:10.1016/0098-1354(96)00164-0

[13] S. Li and F. Li, “Dynamic Neural Network Based Non-

linear Adaptive Control for a Distillation Column,” Pro-

ceedings of the 3rd World Congress on Intelligent Con-

trol and Automation, Hefei, June 28-July 2 2000, pp.

3087-3091.

[14] S. R. Li, H. T. Shi and F. Li. “RBFNN Based Direct

Adaptive Control of MIMO Nonlinear System and Its

Application to a Distillation Column,” Proceedings of

World Conference of Intelligent Control and Automation,

Shanghai, 10-14 June 2002, pp. 2896-2900.

[15] D. Muhammad, Z. Ahmad and N. Aziz, “Implementation

of Internal Model Control (IMC) in Continuous Distilla-

tion Column,” Proceedings of the 5th International Sym-

posium on Design, Operation and Control of Chemical

Processes, Singapore, 16 February 2010, pp. 812-821.

[16] H. E. Tonnang and A. Olatunbosun, “Neural Network

Controller for a Crude Oil Distillation Column,” Journal

of Engineering and Applied Sciences, Vol. 5, No. 6, 2010,

pp. 74-82.

[17] M. Ławryńczuk, “Explicit Nonlinear Predictive Control

of a Distillation Column Based on Neural Models,” Che-

mical Engineering & Technology, Vol. 32, No. 10, 2011,

pp. 1578-1587.

[18] S. R. Li, “Nonlinear H Controller Design for a Class of

Nonlinear Control Systems,” Proceedings of 23rd IEEE

Industrial Electronics, Control and Instrumentation, New

Orleans, 9-14 November 1997, pp. 291-294.

[19] A. Isidori, “Nonlinear Control Systems,” 2nd Edition,

Springer-Verlag, New York, 1989.

[20] A. Isidori and A. Astolfi, “Disturbance Attenuation and

H Control via Measurement Feedback in Nonlinear

Systems,” IEEE Transactions on Automatic Control, Vol.

37, No. 9, 1992, pp. 1283-1293. doi:10.1109/9.159566

[21] V. M. Popov, “Hyperstability of Control Systems,” 2nd

Edition, Springer-Verlag, New York, 1973.

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