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Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

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Abstract

This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach.

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Authors and Affiliations

  1. Department of Information Communication, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, 21004, China

    Tao Li

  2. School of Instrument Science and Opto-Electronics Engineering, Beihang University, Bejing, 100083, China

    Lei Guo

  3. Research Institute of Automation, Southeast University, Nanjing, 210096, China

    Lingyao Wu & Changyin Sun

Authors
  1. Tao Li
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  2. Lei Guo
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  3. Lingyao Wu
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  4. Changyin Sun
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Corresponding author

Correspondence to Tao Li.

Additional information

Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Young-Hoon Joo. This work was supported by the National Science foundation of China under Grant no. 60774013 and Key Laboratory of Education Ministry for Image Processing and Intelligent Control under grant no. 200805.

Tao Li received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in Department of Information and Communication, Nanjing University of Information Science and Technology. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis.

Lei Guo received the Ph.D. degree in the Research Institute of Automation Southeast University, China. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now He is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. His current research interests include robust control, fault detection and diagnosis.

Lingyao Wu received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis.

Changyin Sun received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a Professor in the Research Institute of Automation Southeast University. His current research interests include timedelay systems, neural networks.

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Li, T., Guo, L., Wu, L. et al. Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties. Int. J. Control Autom. Syst. 7, 281–287 (2009). https://doi.org/10.1007/s12555-009-0214-8

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  • DOI: https://doi.org/10.1007/s12555-009-0214-8

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