Kontaktujte nás | Jazyk: čeština English
Název: | Two step, PID and model predictive control using artificial neural network applied on semi-batch reactor | ||||||||||
Autor: | Macků, Lubomír; Sámek, David | ||||||||||
Typ dokumentu: | Recenzovaný odborný článek (English) | ||||||||||
Zdrojový dok.: | WSEAS Transactions on Systems. 2010, vol. 9, issue 10, p. 1039-1049 | ||||||||||
ISSN: | 1109-2777 (Sherpa/RoMEO, JCR) | ||||||||||
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Abstrakt: | The article deals with the control of the semi-batch reactor that is used in chromium waste recycling process based on the enzymatic hydrolysis. The chromium waste comes from the chromium salt tanning while processing the natural leather. The recycling technique separates chrome in the form of chromium filter cake from protein. All products of this procedure are utilisable thus it is a waste free technology. The reactor deals with a problem of chromium sludge (chromium filter cake) reusing. However, the control of the semi-batch reactor is highly complex because the chemical reaction in the reactor is strongly exothermic and the in-reactor temperature is rising very fast depending on the reaction component dosing. To simulate the real process a mathematical model including reaction kinetics was used. The parameters of the achieved model were obtained and verified by experiments. Three different approaches are applied to the temperature control problem: two step control without and with penalization, PID control and model predictive control. The system control is generally difficult because of its nonlinear behaviour. | ||||||||||
Plný text: | http://www.wseas.us/e-library/transactions/systems/2010/88-386.pdf | ||||||||||
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