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Improved Results on Stability Analysis for Delayed Neural Network

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  • Intelligent Control and Applications
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Abstract

This paper deals with the delay-dependent stability analysis problem for neural network with a time-varying delay. A proper Lyapunov-Krasovskii functional (LKF) is established by revealing the features of the improved Jensen integral inequality and considering two complementary integral couples with more cross information. Based on the improved Jensen inequality, a generalized integral inequality involving more free matrices is developed. With the help of the new LKF and integral inequality, some improved stability conditions with less conservatism are derived in terms of linear matrix inequality (LMI). The efficiency of theoretical results is verified by three typical numerical examples.

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Author information

Authors and Affiliations

  1. School of Electronic and Information Engineering, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Jian-An Wang, Li Fan & Xin-Yu Wen

  2. Shanxi Key Laboratory of Advanced Control and Equipment Intelligence, Taiyuan, 030024, China

    Jian-An Wang, Li Fan & Xin-Yu Wen

Authors
  1. Jian-An Wang
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  2. Li Fan
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  3. Xin-Yu Wen
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Correspondence to Jian-An Wang.

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Recommended by Editor Jessie (Ju H.) Park. The work is supported by Shanxi Province Science Foundation for Youths (Grant No. 201701D221107), Natural Science Foundation of Shanxi Province (Grant No. 201801D121132), Key R&D program of Shanxi Province (International Cooperation, 201903D421045), Open project of coal mine electrical equipment and intelligent control key laboratory of Shanxi province (Grant No. MEI201604).

Jian-An Wan received his B.S. degree from Jiangxi Normal University, Nanchang, China, in 2005, and a Ph.D. degree from University of Science and Technology Beijing, China, in 2011. He is currently an associate professor with the School of Electronics Information Engineering, Taiyuan University of Science and Technology. His research interests include the time-delay system, complex network and multi-agent system.

Li Fan received her Bachelor degree from Taiyuan University of Science and Technology, Taiyuan, China, in {dy2018}. She is currently pursuing an M.S. degree with Taiyuan University of Science and Technology. Her current research interests include the time-delay system and multiagent system.

Xin-Yu Wen received his Ph.D. degree from Southeast University, Nanjing, China, in 2011. He is currently an associate professor in Taiyuan University of Science and Technology. His research interests include nonlinear system, robust control, and disturbance observer.

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Wang, JA., Fan, L. & Wen, XY. Improved Results on Stability Analysis for Delayed Neural Network. Int. J. Control Autom. Syst. 18, 1853–1862 (2020). https://doi.org/10.1007/s12555-019-0536-0

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  • DOI: https://doi.org/10.1007/s12555-019-0536-0

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