Volume 7 Number 10 (Oct. 2012)
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JCP 2012 Vol.7(10): 2557-2563 ISSN: 1796-203X
doi: 10.4304/jcp.7.10.2557-2563

Multiple Model Predictive Control of Component Content in Rare Earth Extraction Process

Hui Yang1, Rongxiu Lu1, Kunpeng Zhang1, Xin Wang2
1School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang, 330013, China
2School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, 200240, China

Abstract—Aiming at the complicated characteristic of rare earth extraction process and combining the material balance model, a multiple models modeling and control method is proposed. Based on the data collected in an industrial field, an improved subtractive clustering algorithm is employed to obtain steady operation points for the process; the recuresive least squares algorithm is adopted to identify submodel parameters and establish multiple linear models. According to the model switching index, an online optimal predictive model is obtained. And the efficiency of the model is verified by taking a certain rare earth company extraction as an example. In the end, generalized predictive controller of the corresponding sub-model is designed, so that component content is controlled in real time and accurately. Simulation results show the effectiveness of the method above.

Index Terms—Rare earth extraction process, complicated characteristic, multiple models, generalized predictive control.

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Cite: Hui Yang, Rongxiu Lu, Kunpeng Zhang, Xin Wang, "Multiple Model Predictive Control of Component Content in Rare Earth Extraction Process," Journal of Computers vol. 7, no. 10, pp. 2557-2563, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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