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Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays

Muthukumar, P, Subramanian, K and Lakshmanan, S 2016, Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays, Journal of the Franklin Institute, vol. 353, no. 16, pp. 4091-4113, doi: 10.1016/j.jfranklin.2016.07.006.

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Title Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays
Author(s) Muthukumar, P
Subramanian, K
Lakshmanan, SORCID iD for Lakshmanan, S orcid.org/0000-0002-4622-3782
Journal name Journal of the Franklin Institute
Volume number 353
Issue number 16
Start page 4091
End page 4113
Total pages 23
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2016-11
ISSN 0016-0032
Summary This paper investigates the problem of robust finite time stabilization for a uncertain neural networks with leakage delay and probabilistic time-varying delays. By introducing a stochastic variable which satisfies Bernoulli distribution, the information of probabilistic time-varying delay is equivalently transformed into the deterministic time-varying delay with stochastic parameters. The main objective of this paper is to design a memoryless state feedback control such that the resulting proposed system is robustly finite time stable with admissible uncertainties. Based on a suitable Lyapunov–Krasovskii functional, model transformation technique and Wirtinger-based double integral inequality, the general framework is obtained in terms of linear matrix inequalities to determine the finite time stability and to achieve the control design. Finally, three numerical examples are presented to validate the effectiveness and less conservatism of the proposed method.
Language eng
DOI 10.1016/j.jfranklin.2016.07.006
Field of Research 0102 Applied Mathematics
0906 Electrical And Electronic Engineering
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2016, The Franklin Institute
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089101

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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