Research on the Identification of Tubular-Furnace Based on CARIMA Model

Zai Ping Chen; Xing Jun Li; En Zeng Dong

doi:10.4028/www.scientific.net/AMR.383-390.151

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 383-390Research on the Identification of Tubular-Furnace...

Research on the Identification of Tubular-Furnace Based on CARIMA Model

Abstract:

Atmospheric and vacuum furnace is a complex control object, in particular, combustion system and multi-branch feeding the outlet temperature control system is interconnected multiple-input and multiple-output coupling multivariable time-varying systems. Using multivariable decoupling control methods will have better control effect, but in fact, because of the nonlinear time-varying systems, and other factors, it is difficult to obtain more accurate mathematical model of the system. Based on CARIMA model, a distributed lags model is constructed in this paper. In the numerical simulation, the proposed model has a excellent recognition result, can achieve an arbitrary precision according to actual requirements.

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Manufacturing Science and Technology, ICMST2011

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Periodical:

Advanced Materials Research (Volumes 383-390)

Pages:

151-156

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.383-390.151

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Online since:

November 2011

Authors:

Zai Ping Chen, Xing Jun Li, En Zeng Dong

Keywords:

CARIMA Model, Least Square (LS), System Identification, Tubular-Furnace

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References

[1] X.Y. Li,Z.G. Han, Advances in nonlinear system identification [J]. Techniques of Automation&Application, 2004, 23(10): 5-7.

Google Scholar

[2] S.A. Liu,F. Tang, Study on system identification method based on genetic algorithms[J]. System EngineeringTheory and Practice, 2007, 16(3): 134-139.

Google Scholar

[3] X.Q. Deng. Application of Particle Swarm OptimizationAlgorithm in Point-Pattern Matching [J]. Computing Technology and Automation, 2008, 27(1): 45-48.

Google Scholar

[4] Wu H J, Zhou F D, Wu Y Y. Intelligent Identification System of Flow Regime of Oil-Gas-Water Multiphase flow. International Journal of Multiphase Flow, 2001, 27(3): 459-475.

DOI: 10.1016/s0301-9322(00)00022-7

Google Scholar

[5] S.B. Chen Y.J. Lou,L. Wu,D.B. Zhao, Intelligent methodologyfor sensing, modeling and control of pulsed GTAW: Part I-Bead-on-plate welding, Welding Journal, 79(6): 151-163 JUN (2000).

Google Scholar

[6] Perlman,R. Models for IP multicast. Proceedings. 12th IEEE International Conference on Networks, 2004(2): 678-682.

Google Scholar

[7] Peiyong Duan, YuMing Zhang, CMAC-based modeling for HPDDL welding process control, Special Issue on Advanced Sensing, Modeling and Control of Welding Processes, International Journal of Modeling, Identification and Control, 1(2): 107-114, (2006).

DOI: 10.1109/wcica.2006.1713090

Google Scholar

[8] R. Haber, Nonlinear System Identification-Input-OutputModeling Approach Vol. 1 Nonlinear System Parameter Identification, Springer, 2000.

Google Scholar