State feedback robust stabilisation for discrete-time fuzzy singularly perturbed systems with parameter uncertainty
State feedback robust stabilisation for discrete-time fuzzy singularly perturbed systems with parameter uncertainty
- Author(s): J. Chen ; F. Sun ; Y. Yin ; C. Hu
- DOI: 10.1049/iet-cta.2010.0142
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- Author(s): J. Chen 1, 2, 3 ; F. Sun 2 ; Y. Yin 1 ; C. Hu 1
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View affiliations
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Affiliations:
1: Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, People's Republic of China
2: State Key Laboratory of Intelligence Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Bejing, People's Republic of China
3: Automation Research and Design, Institute of Metallurgical Industry, China Iron and Steel Research Institute Group, Beijing, People's Republic of China
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Affiliations:
1: Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, People's Republic of China
- Source:
Volume 5, Issue 10,
7 July 2011,
p.
1195 – 1202
DOI: 10.1049/iet-cta.2010.0142 , Print ISSN 1751-8644, Online ISSN 1751-8652
This study investigates the problem of state feedback robust stabilisation for discrete-time fuzzy singularly perturbed systems (SPSs) with parameter uncertainty. The considered system is approximated by Takagi–Sugeno fuzzy model. Based on a matrix spectral norm approach, new sufficient conditions, which ensure the existence of state feedback controller such that the resulting closed-loop system is asymptotically stable, are given. The gains of controllers are obtained by solving a set of ɛ-independent linear matrix inequalities (LMIs) such that, the ill-conditioned problems caused by ɛ can be easily avoided. In contrast to the existing results, the proposed method can be applied to both certain and uncertain SPSs with greater singular perturbation parameter ɛ. A numerical example is provided to illustrate the reduced conservatism of the authors’ results.
Inspec keywords: asymptotic stability; uncertain systems; discrete time systems; fuzzy systems; linear matrix inequalities; state feedback; robust control; singularly perturbed systems
Other keywords:
Subjects: Discrete control systems; Optimal control; Linear algebra (numerical analysis); Fuzzy control; Stability in control theory
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