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A Hybrid System Approach for High Consumption Industrial Furnace Control

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DOI: 10.4236/ica.2012.34044    2,974 Downloads   4,223 Views   Citations


In this paper we describe a hybrid system approach for high consumption industrial furnace control. The problem is observed in systematic way starting from the need for modeling this system as hybrid. For description of this behavior we use the Hybrid System Description Language. After that, we design an optimal controller for the furnace and we simulate and compare the controller with other relevant predictive controllers. We have shown that using the hybrid approach for control of industrial furnaces leads to significant improvement of the control system performances.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

G. Stojanovski and M. Stankovski, "A Hybrid System Approach for High Consumption Industrial Furnace Control," Intelligent Control and Automation, Vol. 3 No. 4, 2012, pp. 404-412. doi: 10.4236/ica.2012.34044.


[1] J. Rhine and R. Tucker, “Modelling of Gas-Fired Furnaces and Boilers,” McGraw-Hill, Boston, 1991.
[2] G. Dimirovski, A. Dourado, N. Gough, B. Ribeiro, M. Stankovski, I. Ting, and E. Tulunay, “On Learning Control in Industrial Furnaces and Boilers,” Proceedings of the IEEE International Symposium on Intelligence Control, Patras, 17-19 July 2000, pp. 67-72.
[3] M. Stankovski, “Non-Conventional Control of Industrial Energy Processes in Large Heating Furnaces,” Ph.D. Dissertation, Ss. Cyril and Methodius University, Skopje, 1997.
[4] F. Torrisi and A. Bemporad, “HYSDEL—A Tool for Generating Computational Hybrid Models for Analysis and Synthesis Problems,” IEEE Transactions on Control Systems Technology, Vol. 12, 2004, pp. 235-249. doi:10.1109/TCST.2004.824309
[5] A. Bemporad, S. Di Cairano and N. Giorgetti, “Model Predictive Control of Hybrid Systems with Applications to Supply Chain Management,” Congress of ANIPLA Associazione Nazionale per LAutomazione, Napoli, 23-24 November 2005, pp. 1-15.
[6] A. Bemporad and M. Morari, “Control of Systems Integrating Logic, Dynamics, and Constraints,” Automatica, Vol. 35, No. 3, 1999, pp. 407-427. doi:10.1016/S0005-1098(98)00178-2
[7] G. Stojanovski, M. Stankovski and G. Dimirovski, “Multiple-Model Model Predictive Control for High Consumption Industrial Furnaces,” FACTA UNIVERSITATIS Series: Automatic Control and Robotics, Vol. 9, No. 1, 2010, pp. 131-139.
[8] G. Stojanovski and M. Stankovski, “Advanced Industrial Control Using Fuzzy-Model Predictive Control on a Tunnel Klin Brick Production,” Proceedings of the 18th World Congress, The International Federation of Automatic Control Milano (Italy), 2011, pp. 10733-10738.
[9] A. Bemporad, W. Heemels and B. De Schutter, “On Hybrid Systems and Closed-Loop MPC Systems,” IEEE Transactions on Automatic Control, Vol. 47, No. 5, 2002, pp. 863-869. doi:10.1109/TAC.2002.1000287
[10] D. Q. Mayne, J. B. Rawlings, C. V. Rao and P. O. M. Scokaert, “Constrained Model Predictive Control: Stability and Optimality,” Automatica, Vol. 36, No. 6, 200, pp. 789-814. doi:10.1016/S0005-1098(99)00214-9
[11] E. Camacho and C. Bordons, “Model Predictive Control,” Springer-Verlag, London, 2004.
[12] J. Maciejowski, “Predictive Control with Constraints,” Prentice Hall, Upper Saddle River, 2002.
[13] A. Bemporad, “Hybrid Toolbox—User Guide,” 2004. bemporad/hybrid/toolbox

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