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Asymptotic stability criteria for T-S fuzzy neural networks with discrete interval and distributed time-varying delays

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Abstract

The aim of this paper is to study the problem of asymptotic stability analysis for T-S fuzzy neural networks with discrete interval and distributed time-varying delays by employing a further improved free-weighting matrix approach. Based on the new Lyapunov–Krasovskii functional with triple-integral term, using some integral inequality and convex combination technique, a new delay-dependent stability criteria are obtained in terms of linear matrix inequalities (LMIs) that can be checked easily by the LMI Control Toolbox in MATLAB. Finally, numerical examples are given to illustrate the strength of the proposed method and an improvement over some existing results.

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Acknowledgments

The authors are very much thankful to the editors and anonymous reviewers for their careful reading, constructive comments and fruitful suggestions to improve this manuscript. This work was supported by the National Board for Higher Mathematics, Department of Atomic Energy grant on Ref. No. 2/48(8)/2010/RD II/11191.

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Authors and Affiliations

  1. School of Mathematics, Madurai Kamaraj University, Madurai, 625 021, Tamilnadu, India

    S. Muralisankar, A. Manivannan & N. Gopalakrishnan

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  1. S. Muralisankar
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  2. A. Manivannan
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  3. N. Gopalakrishnan
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Correspondence to S. Muralisankar.

Additional information

The work of author was supported by NBHM-DAE grant on Ref. No. 2/48(8)/2010/RD II/11191.

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Muralisankar, S., Manivannan, A. & Gopalakrishnan, N. Asymptotic stability criteria for T-S fuzzy neural networks with discrete interval and distributed time-varying delays. Neural Comput & Applic 21 (Suppl 1), 357–367 (2012). https://doi.org/10.1007/s00521-012-0936-z

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  • DOI: https://doi.org/10.1007/s00521-012-0936-z

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