Application of pH control to a tubular flow reactor

doi:10.1016/j.cjche.2014.10.002

Chin.J.Chem.Eng. ›› 2015, Vol. 23 ›› Issue (1): 145-161.DOI: 10.1016/j.cjche.2014.10.002

• PROCESS SYSTEMS ENGINEERING • Previous Articles Next Articles

Application of pH control to a tubular flow reactor

?. Halil Vural¹, Ayla Altinten², Hale Hapo?lu¹, Sebahat Erdo?an², Mustafa Alpbaz¹

1 Ankara University, Faculty of Engineering, Department of Chemical Engineering, Tandogan, Ankara 06100, Turkey;
2 Gazi University, Faculty of Engineering, Department of Chemical Engineering, Maltepe, Ankara 06570, Turkey

Received:2013-02-22 Revised:2013-10-08 Online:2015-01-24 Published:2015-01-28
Contact: Ayla Altinten

Application of pH control to a tubular flow reactor

?. Halil Vural¹, Ayla Altinten², Hale Hapo?lu¹, Sebahat Erdo?an², Mustafa Alpbaz¹

1 Ankara University, Faculty of Engineering, Department of Chemical Engineering, Tandogan, Ankara 06100, Turkey;
2 Gazi University, Faculty of Engineering, Department of Chemical Engineering, Maltepe, Ankara 06570, Turkey

通讯作者: Ayla Altinten

Abstract

Abstract: Tubular flow reactors are mainly used in chemical industry and waste water discharged units. Control of output variables is very difficult because of the existence of high dead-time in these types of reactors. In the present work, sodium hydroxide and acetic acid solutions were sent to the tubular flow reactor. The aim was to control pH at 7 in the nonlinear region. The pH control of a tubular flow reactor with high time delay and a highly nonlinear behavior in pH neutralization reaction was investigated experimentally in the face of the various load and set point changes. Firstly, efficiency of conventional Proportional-Integral-Derivative (PID) algorithm in the experiments was tested. Then self-tuning PID (STPID) control system was applied by using the ARMAX model. The model parameters were calculated from input-output data by using PRBS signal as disturbance and Bierman algorithm. Lastly, the experimental fuzzy control of pH based on fuzzy model was achieved to compare the success of fuzzy approach with the performance of other control cases studied.

Key words: Tubular flow reactor, pH control, Self tuning PID control, PID control, Fuzzy control

摘要： Tubular flow reactors are mainly used in chemical industry and waste water discharged units. Control of output variables is very difficult because of the existence of high dead-time in these types of reactors. In the present work, sodium hydroxide and acetic acid solutions were sent to the tubular flow reactor. The aim was to control pH at 7 in the nonlinear region. The pH control of a tubular flow reactor with high time delay and a highly nonlinear behavior in pH neutralization reaction was investigated experimentally in the face of the various load and set point changes. Firstly, efficiency of conventional Proportional-Integral-Derivative (PID) algorithm in the experiments was tested. Then self-tuning PID (STPID) control system was applied by using the ARMAX model. The model parameters were calculated from input-output data by using PRBS signal as disturbance and Bierman algorithm. Lastly, the experimental fuzzy control of pH based on fuzzy model was achieved to compare the success of fuzzy approach with the performance of other control cases studied.

关键词: Tubular flow reactor, pH control, Self tuning PID control, PID control, Fuzzy control

İ. Halil Vural, Ayla Altinten, Hale Hapoğlu, Sebahat Erdoğan, Mustafa Alpbaz . Application of pH control to a tubular flow reactor[J]. Chin.J.Chem.Eng., 2015, 23(1): 145-161.

İ. Halil Vural, Ayla Altinten, Hale Hapoğlu, Sebahat Erdoğan, Mustafa Alpbaz . Application of pH control to a tubular flow reactor[J]. Chinese Journal of Chemical Engineering, 2015, 23(1): 145-161.

References

[1] T. Gustafsson, K. Waller, Dynamic modeling and reaction invariant control of pH, Chem. Eng. Sci. 38 (1983) 389-398.

[2] B.D. Kulkarni, S.S. Tambe, N.V. Shulka, B. Deshpande, Non-linear pH control, Chem. Eng. Sci. 46 (4) (1991) 995-1003.

[3] A.W. Wright, C. Kravaris, Nonlinear control of pH processes using the strong acid equivalent, Ind. Eng. Chem. Res. 30 (7) (1991) 1561-1572.

[4] L.A. Minim, R.M. Filho, Modeling and adaptive-control of L-Asparaginase reactor, Comput. Chem. Eng. 18 (Suppl. S) (1994) S693-S697.

[5] M.A. Henson, D.E. Seborg, Adaptive non-linear control of a pH neutralization process, IEEE Trans. Control Syst. Technol. 2 (3) (1994) 169-182.

[6] M.C. Palancar, J.M. Aragon, J.A.Miguan, J.S. Torrecilla, Application of amodel reference adaptive control system to pH control: Effects of lag and dead-time, Ind. Eng. Chem. Res. 35 (1996) 4100-4140.

[7] N. Bharathi, E. Sivakurnar, J. Shanmugam, Control of pH in fed-batch neutralization processes, IEEE International Conference on Industrial Technology, 1-6, 2006, pp. 1821-1825.

[8] J.C. Gomez, A. Jutan, F. Baeyens,Wiener model identification and predictive control of a pH neutralisation process, IEE Proc. Control Theory Appl. 151 (3) (2004) 329-338.

[9] A. Altinten, Generalized predictive control applied to a pH neutralization process, Comput. Chem. Eng. 31 (10) (2007) 1199-1204.

[10] G. Balasubramanian, N. Sivakumaran, T.K. Radhakrishnan, Adaptive control of neutralization process using neural networks, Instrum. Sci. Technol. 36 (2008) 146-160.

[11] B. Meenakshipriya, K. Saravanan, S. Somasundaram, P. Kanthabhabha, CDM-based PI-P control strategy in pH neutralization system, Instrum. Sci. Technol. 39 (2011) 273-287.

[12] G.J. Klir, B. Yuan, On nonspecificity of fuzzy sets with continuous membership functions, IEEE International Conference on Systems, Man and Cybernetics, 1-5, 1995, pp. 25-29.

[13] B. Kelkar, B. Postlethwaite, Fuzzy-model based pH control, IEEE International Conference on Fuzzy Systems, 1, 1994, pp. 661-666.

[14] Y.Wang, G. Rong, X. Jin, Nonlinear internal model control strategy for fuzzy models and its application on pH neutralization process control, J. Chem. Ind. Eng. 48 (1997) 347-353 (in Chinese).

[15] J.M. Sousa, R. Babuska, H.B. Verbruggen, Internal model control with a fuzzy model: Application to an air-conditioning system, IEEE International Conference on Fuzzy Systems, 1, 1997, pp. 207-212.

[16] A. Altinten, S. Erdo?an, H. Hapo?lu, M. Alpbaz, Control of polymerization reactor by fuzzy control method with genetic algorithm, Comput. Chem. Eng. 27 (7) (2003) 1031-1040.

[17] R. Ibrahim, D.J. Murray-Smith, Design, implementation and performance evaluation of a fuzzy control system for a pH neutralisation process pilot plant, International Conference on Intelligent and Advanced Systems, 1-3, 2007, pp. 1001-1006.

[18] J. Chen, Y. Peng, W. Han, M. Guo, Adaptive fuzzy sliding mode control in pH neutralization process, Procedia Eng. 15 (2011) 954-958.

[19] ?.H. Vural, Application of Nonlinear pH Control to a Tubular Flow Reactor(Ph.D. Thesis) Ankara University, Ankara, Turkey, 2002.

[20] P.E. Wellstead, M.B. Zarrop, Self-tuning Systems: Control and Signal Processing, Wiley, Sussex (U.K.), 1991.

[21] G.J. Bierman, Measurement updating using the U-D factorization, Automatica 12 (4) (1976) 375-382.

[22] B.P. Graham, R.B. Newell, Fuzzy adaptive control of a first-order process, Fuzzy Sets Syst. 31 (1989) 47-65.

[23] R.B. Newell, P.L. Lee, Applied Process Control: A Case Study, Prentice Hall, Sydney, 1989.

[24] A. Drager, S. Engell, Nonlinear model predictive control using neural net plant models, Methods Model Based Process Control 293 (IV) (1995) 627-639.

Application of pH control to a tubular flow reactor

Application of pH control to a tubular flow reactor

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