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On-line Access: 2011-03-09

Received: 2010-07-03

Revision Accepted: 2010-10-15

Crosschecked: 2011-01-25

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Journal of Zhejiang University SCIENCE A 2011 Vol.12 No.3 P.190-200

http://doi.org/10.1631/jzus.A1000316


Multi-loop adaptive internal model control based on a dynamic partial least squares model


Author(s):  Zhao Zhao, Bin Hu, Jun Liang

Affiliation(s):  State Key Lab of Industrial Control Technology, Department of Control Science & Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   jliang@iipc.zju.edu.cn

Key Words:  Partial least squares (PLS), Adaptive internal model control (IMC), Recursive least squares (RLS)


Zhao Zhao, Bin Hu, Jun Liang. Multi-loop adaptive internal model control based on a dynamic partial least squares model[J]. Journal of Zhejiang University Science A, 2011, 12(3): 190-200.

@article{title="Multi-loop adaptive internal model control based on a dynamic partial least squares model",
author="Zhao Zhao, Bin Hu, Jun Liang",
journal="Journal of Zhejiang University Science A",
volume="12",
number="3",
pages="190-200",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1000316"
}

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%T Multi-loop adaptive internal model control based on a dynamic partial least squares model
%A Zhao Zhao
%A Bin Hu
%A Jun Liang
%J Journal of Zhejiang University SCIENCE A
%V 12
%N 3
%P 190-200
%@ 1673-565X
%D 2011
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1000316

TY - JOUR
T1 - Multi-loop adaptive internal model control based on a dynamic partial least squares model
A1 - Zhao Zhao
A1 - Bin Hu
A1 - Jun Liang
J0 - Journal of Zhejiang University Science A
VL - 12
IS - 3
SP - 190
EP - 200
%@ 1673-565X
Y1 - 2011
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1000316


Abstract: 
A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace, once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model. Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.

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