New Analysis on H Control for Exponential Stability of Artificial Neural Network with Mixed Time-Varying Delays via Hybrid Feedback Control

Authors

  • C. Chantawat, T. Botmart, and W. Weera Author

Keywords:

Artificial neural networks, exponential stability, H control, hybrid feedback control.

Abstract

This paper is concerned the problem of H 
control for artificial neural networks with mixed time-varying delays which comprising different interval and distributed time-varying delays via hybrid feedback control. The interval and distributed time-varying delays are not necessary to be differentiable. The main purpose of this research is to estimate exponential stability of artificial neural network with H performance attenuation level  . The key features of the approach include the introduction of a new Lyapunov- Krasovskii functional with triple integral terms, the employment of a tighter bounding technique, some slack matrices and newly introduced convex combination condition in 
the calculation, improved delay-dependent sufficient conditions for the H control with exponential stability of the system are obtained in terms of linear matrix inequalities (LMIs). The results of this paper complement the previously known ones. Finally, a numerical example is presented to show the effectiveness of the proposed methods.

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Published

25.09.2018

How to Cite

New Analysis on H Control for Exponential Stability of Artificial Neural Network with Mixed Time-Varying Delays via Hybrid Feedback Control. (2018). International Journal of Information and Electronics Engineering, 8(3), 23-29. https://ijiee.org/index.php/ijiee/article/view/261