CLC number: O436.1
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 17
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ZHANG Yan-hu, YAN Wen-jun, LU Jian-ning, ZHAO Guang-zhou. Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain[J]. Journal of Zhejiang University Science A, 2005, 6(100): 87-93.
@article{title="Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain",
author="ZHANG Yan-hu, YAN Wen-jun, LU Jian-ning, ZHAO Guang-zhou",
journal="Journal of Zhejiang University Science A",
volume="6",
number="100",
pages="87-93",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.AS0087"
}
%0 Journal Article
%T Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain
%A ZHANG Yan-hu
%A YAN Wen-jun
%A LU Jian-ning
%A ZHAO Guang-zhou
%J Journal of Zhejiang University SCIENCE A
%V 6
%N 100
%P 87-93
%@ 1673-565X
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.AS0087
TY - JOUR
T1 - Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain
A1 - ZHANG Yan-hu
A1 - YAN Wen-jun
A1 - LU Jian-ning
A1 - ZHAO Guang-zhou
J0 - Journal of Zhejiang University Science A
VL - 6
IS - 100
SP - 87
EP - 93
%@ 1673-565X
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.AS0087
Abstract: Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of LMI (Linear Matrix Inequality) characterizations are further generalized to cope with the robust analysis for convex polytopic uncertain system. Robust state-feedback controller synthesis conditions are also derived for this class of uncertain systems. Using the above results, multi-objective state-feedback controller synthesis procedures which involve the LMI optimization technique are developed and less conservative than the existing one. An illustrative example verified the validity of the approach.
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