Hybrid neural network - prior knowledge model in temperature control of a semi-batch polymerization process

Ng, C.W. and Hussain, Mohd Azlan (2004) Hybrid neural network - prior knowledge model in temperature control of a semi-batch polymerization process. Chemical Engineering and Processing - Process Intensification, 43 (4). pp. 559-570. ISSN 0255-2701

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Official URL: https://doi.org/10.1016/S0255-2701(03)00109-0


Nonlinear process control is a challenging research topic at present. In recent years, neural network and hybrid neural networks have been much studied especially for modeling of nonlinear system. It has however been applied mainly as an estimator in parts of various control systems and the idea of utilizing it directly as a neural-controller has not been studied. Hence the contribution of this work is to use an inverse neural network in hybrid with a first principle model for the direct control of a nonlinear semi-batch polymerization process. These hybrid models were utilized in the direct inverse control strategy to track the set point of the temperature of the polymerization reactor under nominal condition and with various disturbances. For comparison purposes, the standard neural network and proportional-integral-derivative controller were also implemented in these control strategies. Adaptation mechanisms to improve the results have also been carried out to test the capability of these hybrid methods in control. The simulation results show the advantages and robustness of utilizing the neural network in this hybrid strategy especially when an adaptive algorithm is implemented.

Item Type: Article
Additional Information: Cited By (since 1996): 43 Export Date: 5 March 2013 Source: Scopus CODEN: CENPE Language of Original Document: English Correspondence Address: Ng, C.W.; Department of Chemical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; email: mohdazlan@um.edu.my References: Joseph, S.F., Pradeep, B.D., Kenneth, W.L., (1993) Control of Polymerization Reactors, , Madison Avenue NY: Marcel Dekker; Hussain, M.A., Review of the applications of neural networks in chemical process control-simulation and on-line implementation (1999) Artif. Intell. Eng., 13, pp. 55-68; Kurt, M., Marcel, R., Intelligent modeling in the chemical process industry with neural networks: A case study (1998) Comput. Chem. Eng., 22, pp. S587-S593; Joachim, H., Trajectory tracking of a batch polymerization reactor based on input-output-linearization of a neural process model (2001) Comput. Chem. Eng., 25, pp. 1561-1567; Hussain, M.A., Kershenbaum, L.S., Implementation of an inverse-model-base control strategy using neural networks on a partially simulated exothermic reactor (2000) Trans. IchemE, 78, pp. 299-311; Hussain, M.A., Ng, C.W., Aziz, N., Mujtaba, I.M., (2002) Neural Network Techniques and Application in Chemical Process Control Systems, Intelligent Systems Techniques and Application, 5, pp. V326-V362. , NJ: CRC Press LLC; Aziz, N., Hussain, M.A., Mujtaba, I.M., Optimal control of batch reactors using Generic Model Control (GMC) and Neural Network (2000) Proceedings of the European Symposium on Computer Aided Process Engineering-10, p. 175. , S. Pierucci. (Ed.), 7-10 May 2000, Elsevier Science B.V., Florence, Italy; Tsen, Y.-D.A., Shi, S.H., David, S.H.W., Predictive control of quality in batch polymerization using hybrid ANN models (1996) AIChE J., 42, pp. 455-465; Vega, M.P., Lima, E.L., Pinto, J.C., Modeling and control of tubular solution polymerization process (1997) Comput. Chem. Eng., 21, pp. S1049-S1054; Qi, H., Zhu, X.-G., Liu, L.-H., Yuan, W.-K., A hybrid neural network-first principles model for fixed-bed reactor (1999) Chem. Eng. Sci., 54, pp. 2521-2526; Psichogios, D.C., Ungar, L.H., A hybrid neural network-first principle approach using artificial neural networks (1992) Ind. Eng. Chem. Res., 30, p. 2564; Kramer, M.A., Thompson, M.L., Bhagat, P.M., Embedding theorical model in neural networks (1992) ACC/WA, 14, p. 475; Thompson, M.L., Kramer, M.A., Modeling chemical processes using prior knowledge and neural networks (1994) AIChE J., 40 (8), pp. 1328-1340; Chylla, R.W., Haase, D.R., Temperature control of semibatch polymerization reactor (1993) Comput. Chem. Eng., 17, pp. 257-264; Astrom, K.J., Wittenmark, B., (1990) Computer-Controlled Systems: Theory and Design, p. 187. , second ed. NJ: Prentice-Hall, Englewood Cliffs; Caracotsios, M., Stewart, W.E., Sensitivity analysis of initial value problems with mixed ODEs and algebraic equations (1985) Comput. Chem. Eng., 9, pp. 359-365
Uncontrolled Keywords: Artificial neural network; Hybrid neural network; polymerization; Adaptive algorithms; Knowledge based systems; Mathematical models; Neural networks; Nonlinear control systems; Robustness (control systems); Three term control systems; Hybrid neural networks; Temperature control; control system; hybrid system; neural network; process control.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jul 2013 06:28
Last Modified: 04 Nov 2019 08:38
URI: http://eprints.um.edu.my/id/eprint/7061

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