Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32722
Identification of Nonlinear Predictor and Simulator Models of a Cement Rotary Kiln by Locally Linear Neuro-Fuzzy Technique

Authors: Masoud Sadeghian, Alireza Fatehi


One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro- Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

Keywords: Cement rotary kiln, nonlinear identification, Locally Linear Neuro-Fuzzy model.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1966


[1] Devedzic, H., Knowledge-Based Control of Rotary Kiln, the proceedings of the International IEEE/IAS Conference on Industrial Automation and Control: Emerging Technologies, pp. 452 - 458, Taipei, 1995.
[2] Akalp, M., Dominguez, A. L. and Longchamp, R., Supervisory Fuzzy Control of a Rotary Cement Kiln, the Proceedings IEEE Electrotechnical Conference, vol. 2, pp. 754-757, 1994.
[3] Lu, J., Huang, L., Hu, Z., Wang, S., Simulation of gas-solid, two phase flow, coal combustion and raw meal calcination in a pre-calciner. ZKG International 57 (2), 55-63, 2004.
[4] Mastorakos, E., Massias, A., Tsakiroglou, C.D., Goussis, D.A., Burganos, V.N., CFD predictions for cement kiln including flame modeling, heat transfer and clinker chemistry. Applied Mathematical Modeling 23, 55-76, 1999.
[5] Mujumdar, K.S., Ranade, V.V., Coupling of CFD models with different time scalesÔÇöa case study of rotary cement kiln. In FLUENT Users Group Meeting held at Pune, 2003.
[6] Modigell, M.; Liebig D.; Munstermann, S. Calculation of the clinker burning process using thermochemical process simulation. ZKG Int., 55 (7), 38-46, 2002.
[7] Mujumdar, K.S., Ranade, V.V., Simulation of rotary cement kilns using a one-dimensional model. Transactions of IChemE, Part A, Chemical Engineering Research and Design 84 (A3), 165-177, 2006.
[8] T. Takagi, M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Tran. Systems, Man and Cybernetics, vol. 15, pp. 116-132, 1985.
[9] J. R. Jang, "ANFIS: Adaptive network based fuzzy inference system," IEEE Tran. Systems, Man and Cybernetics, vol. 23, no. 3, , pp. 665-685, 1993.
[10] O. Nelles, Nonlinear system identification. Berlin: Springer Verlag, 2001.
[11] O. Nelles, "Local linear model tree for on-line identification of time variant nonlinear dynamic systems," International Conference on Artificial Neural Networks (ICANN), pp. 115-120, Bochum-Germany, 1996.
[12] Noshiravani, R., Identification of a Rotary Cement Kilns, Master of Science thesis (in Farsi), K. N. Toosi University of Technology, Tehran, Iran, 2005.
[13] Iman Makaremi, Alireza Fatehi, Babak Nadjar Araabi, Morteza Azizi, Ahmad Cheloeian, "Identification and Abnormal Condition Detection of a Cement Rotary Kiln," 17th IFAC world congress, Seoul, Korea, July 6- 11, 2008.
[14] Maryam Fallahpour, Alireza Fatehi, Babak Nadjar Araabi, Morteza Azizi"A neuro-fuzzy Controller for Rotory cement Kiln," the 17th World Congress The International Federation of Automatic ControlSeoul, Korea, July 6-11, 2008.
[15] I. Makaremi, "Intelligent Condition Monitoring of a Cement Rotary Kiln", M.Sc. Thesis,KN Toosi Univ. of Tech, Feb 2007.
[16] Fallahpour, M., Fuzzy Controllers for Rotary Cement Kilns, Master of Science thesis (in Farsi), K. N. Toosi University of Technology, Tehran, Iran, 2007.
[17] Y.Zhu, Multivariable system identification for process control. Elsevier science Ltd, 2001.
[18] Iman Makaremi, Alireza Fatehi, Babak Nadjar Araabi, "Lipschitz Numbers: A Medium for Delay Estimation," 17th IFAC world congress, Seoul, Korea, July 6-11 2008.
[19] O. Nelles and R. Isermann, "Basis function networks for interpolation of local linear models," Proc. of IEEE Conference on Decision and Control, pp. 470-475, Kobe, Japan, 1996.