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Journal of Zhejiang University SCIENCE C 2011 Vol.12 No.1 P.25-35

http://doi.org/10.1631/jzus.C0910779


Wiener model identification and nonlinear model predictive control of a pH neutralization process based on Laguerre filters and least squares support vector machines


Author(s):  Qing-chao Wang, Jian-zhong Zhang

Affiliation(s):  School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, China, SINOPEC Safety Engineering Institute, Qingdao 266071, China

Corresponding email(s):   zjzhit1984@163.com

Key Words:  Wiener model, Nonlinear model predictive control (NMPC), pH neutralization process, Laguerre filters, Least squares support vector machines (LSSVM)


Qing-chao Wang, Jian-zhong Zhang. Wiener model identification and nonlinear model predictive control of a pH neutralization process based on Laguerre filters and least squares support vector machines[J]. Journal of Zhejiang University Science C, 2011, 12(1): 25-35.

@article{title="Wiener model identification and nonlinear model predictive control of a pH neutralization process based on Laguerre filters and least squares support vector machines",
author="Qing-chao Wang, Jian-zhong Zhang",
journal="Journal of Zhejiang University Science C",
volume="12",
number="1",
pages="25-35",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910779"
}

%0 Journal Article
%T Wiener model identification and nonlinear model predictive control of a pH neutralization process based on Laguerre filters and least squares support vector machines
%A Qing-chao Wang
%A Jian-zhong Zhang
%J Journal of Zhejiang University SCIENCE C
%V 12
%N 1
%P 25-35
%@ 1869-1951
%D 2011
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910779

TY - JOUR
T1 - Wiener model identification and nonlinear model predictive control of a pH neutralization process based on Laguerre filters and least squares support vector machines
A1 - Qing-chao Wang
A1 - Jian-zhong Zhang
J0 - Journal of Zhejiang University Science C
VL - 12
IS - 1
SP - 25
EP - 35
%@ 1869-1951
Y1 - 2011
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C0910779


Abstract: 
This paper deals with wiener model based predictive control of a pH neutralization process. The dynamic linear block of the wiener model is parameterized using laguerre filters while the nonlinear block is constructed using least squares support vector machines (LSSVM). Input-output data from the first principle model of the pH neutralization process are used for the wiener model identification. Simulation results show that the proposed wiener model has higher prediction accuracy than Laguerre-support vector regression (SVR) wiener models, Laguerre-polynomial wiener models, and linear Laguerre models. The identified wiener model is used here for nonlinear model predictive control (NMPC) of the pH neutralization process. The set-point tracking performance of the proposed NMPC is compared with those of the Laguerre-SVR wiener model based NMPC, Laguerre-polynomial wiener model based NMPC, and linear model predictive control (LMPC). Validation results show that the proposed NMPC outperforms the other three controllers.

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