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dc.title | Semi-batch reactor predictive control using artificial neural network | en |
dc.contributor.author | Sámek, David | |
dc.contributor.author | Macků, Lubomír | |
dc.relation.ispartof | 2008 Mediterranean Conference on Control Automation, Vols 1-4 | |
dc.identifier.isbn | 978-1-4244-2504-4 | |
dc.date.issued | 2008 | |
dc.citation.spage | 1035 | |
dc.citation.epage | 1040 | |
dc.event.title | 16th Mediterranean Conference on Control and Automation | |
dc.event.location | Ajaccio | |
utb.event.state-en | France | |
utb.event.state-cs | Francie | |
dc.event.sdate | 2008-06-25 | |
dc.event.edate | 2008-06-27 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | The Institute of Electrical and Electronics Engineers (IEEE) | en |
dc.identifier.doi | 10.1109/MED.2008.4602140 | |
dc.relation.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4602140 | |
dc.description.abstract | This paper deals with model predictive control (MPC) of chemical exothermic semi-batch reactor. A first order chemical reaction is considered to be running in the reactor. The reaction is strongly exothermic so the in-reactor temperature is rising very fast due to reaction component dosing. Thus, the temperature control is necessary. The simulation model of the plant was developed in the MATLAB/Simulink. The system is nonlinear because of chemical reaction kinetics, so its control is difficult by classical methods. The classical MPC objective function was modified in order to improve the control. The WC controller uses an artificial neural network as a predictor. | en |
utb.faculty | Faculty of Technology | |
dc.identifier.uri | http://hdl.handle.net/10563/1001890 | |
utb.identifier.rivid | RIV/70883521:28110/08:63507443!RIV09-MSM-28110___ | |
utb.identifier.obdid | 18553162 | |
utb.identifier.scopus | 2-s2.0-52949141858 | |
utb.identifier.wok | 000261534400173 | |
utb.source | d-wok | |
dc.date.accessioned | 2011-08-09T07:34:09Z | |
dc.date.available | 2011-08-09T07:34:09Z | |
utb.contributor.internalauthor | Sámek, David | |
utb.contributor.internalauthor | Macků, Lubomír | |
utb.fulltext.affiliation | David Samek and Lubomir Macku D. Samek is with the Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Mostni 5139, 76001 Zlin, Czech Republic (corresponding author to provide phone: +420-576-035-157; fax: +420-576-035-176; e-mail: samek@ft.utb.cz). L. Macku is with the Department of Electrotechnics and Measurements, Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 76005 Zlin, Czech Republic (e-mail: macku@fai.utb.cz). | |
utb.fulltext.dates | Manuscript received January 2, 2008 | |
utb.fulltext.references | [1] B. Srinivasan and D. Bonvin, “Controllability and stability of repetitive batch processes,” Journal of Process Control, vol. 17, no 3, pp. 285-295, Mar. 2007. [2] K. Kolomaznik, M. Mladek, and F. Langmaier, “The approach to production of hydrolysate of animal protein waste,” C.R. Patent 280655, March 13, 1996. [3] L. Macku, “Modelling of tanning salts regeneration process,” in Proceeding of The 15th Int. Conference Process Control 2005, pp. 127/1-127/4. [4] J. R. Richards and J. P. Congalidis, “Measurement and control of polymerization reactors,” Computers and Chemical Engineering, vol. 30, no. 10-12, pp. 1447-1463, Sep. 2006. [5] C. E. Garcia, D. M. Prett, and M. Morari, “Model predictive control: theory and practice – a survey,” Automatica, vol. 25, no. 3, pp. 335-348, May 1989. [6] P. P. Kanjilal, Adaptive prediction and predictive control. London: P. Perengrinus Ltd., 1995. [7] R. E. M. Verdurmen and P. de Jong, “Optimising product quality and process control for powdered dairy products,” in Dairy processing: Improving quality. G. Smith Ed., Cambridge: Woodhead Publishing Limited, 2003, ch. 16. [8] M. A. Hussain, “Review of the application of neural networks in chemical process control – simulation and online implementation,” Artificial Intelligence in Engineering, vol. 13, no. 1, pp. 55-68, Jan. 1999. [9] M. Hagan, H. Demuth, and O. D. Jesus, “An Introduction to the Use of Neural Networks in Control Systems,” Int. Journal of Robust and Nonlinear Control, vol. 12, no. 11, pp. 959-985, Sep. 2002. | |
utb.fulltext.sponsorship | This work was supported by the Grant Agency of the Czech Republic under grant 102/07/P137 and by the Ministry of Education, Youth and Sports of the Czech Republic under grant MSM 7088352102. This support is gratefully acknowledged. | |
utb.fulltext.projects | GACR 102/07/P137 | |
utb.fulltext.projects | MSM 7088352102 |