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Locally Exponential Stability of Discrete-time Complex Networks with Impulsive Input Saturation

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  • Control Theory and Applications
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Abstract

In this paper, the problem of exponential stabilization for a class of discrete-time complex network with saturated impulse input is investigated. Based on the inductive method, convex analysis, and auxiliary matrix, several Lyapunov-type stability criteria are derived for exponential stability of discrete-time complex network with impulsive input saturation. Two examples are also presented to illustrate the effectiveness and the feasibility of the obtained results.

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Author information

Authors and Affiliations

  1. College of Electronic and Information Engineering, Southwest university, Chongqing, 400715, China

    Keyu Chen & Liangliang Li

  2. National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology, Chongqing, 400715, China

    Keyu Chen

  3. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic Information Engineering, Southwest University, Chongqing, 400715, China

    Chuandong Li

  4. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, and also with School of Mathematics and Statistics, Chongqing Three Gorges University, Chongqing, 404100, China

    Liangliang Li

Authors
  1. Keyu Chen
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  3. Liangliang Li
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Corresponding author

Correspondence to Chuandong Li.

Additional information

Recommended by Editor Jessie (Ju H.) Park. This work was supported by the National Natural Science Foundation of China under Grants 61873213 and 61633011, and in part by the Chongqing Research Program of Basic Research and Frontier Technology of cstc2015jcyjBX0052.

Keyu Chen received the B.S. degree in Electrical Engineering from North China institute of Science & Technology in 2017. He is currently pursuing towards the M.S. degree with College of Electronic and Information Engineering, Southwest University, Chongqing, China. His research interests include nonlinear control systems, the stability of dynamical systems, and complex networks.

Chuangdong Li received his B.S. degree in Applied Mathematics from Sichuan University, Chengdu, China in 1992, and an M.S. degree in operational research and control theory and a Ph.D. degree in Computer Software and Theory from Chongqing University, Chongqing, China, in 2001 and in 2005, respectively. He has been a Professor at the College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China, since 2012, and been the IEEE Senior member since 2010. From November 2006 to November 2008, he serves as a research fellow in the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China. He has published about more than 100 journal papers. His current research interest covers computational intelligence, neural networks, memristive systems, chaos control and synchronization, and impulsive dynamical systems.

Liangliang Li received the B.S. Degree in Hefei Normal University, Hefei, China, in 2012 and his M.S. degree in Mathematics from China Three Gorges University, Yichang, China, in 2015. Currently, he is working towards the Ph.D. degree at the College of Electronic and Information Engineering, Southwest University, Chongqing, China. His current research interests include stability of dynamical systems, nonlinear control systems, and neural networks.

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Chen, K., Li, C. & Li, L. Locally Exponential Stability of Discrete-time Complex Networks with Impulsive Input Saturation. Int. J. Control Autom. Syst. 17, 948–956 (2019). https://doi.org/10.1007/s12555-018-0608-6

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  • DOI: https://doi.org/10.1007/s12555-018-0608-6

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