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H∞ Exponential Synchronization of Switched Cellular Neural Networks Based on Disturbance Observer-based Control

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Abstract

The problem of H∞ exponential synchronization for switched cellular neural networks that are subjected to multiple exogenous disturbances is investigated. The exogenous disturbances are rejected and attenuated by combining disturbance observer-based control with H∞ control. Based on the admissible edge-dependent average dwell time scheme and the Lyapunov-Krasovskii functional technique, a synchronization criterion formulated by linear matrix inequalities is procured for switched cellular neural networks with external disturbances. Finally, the effectiveness of the obtained results is verified through a numerical simulation.

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Authors and Affiliations

  1. School of Computer Science, Qufu Normal University, Rizhao, 276826, China

    Linlin Hou, Pengfei Ma & Xuan Ma

  2. College of Engineering, Qufu Normal University, Rizhao, 276826, China

    Haibin Sun

Authors
  1. Linlin Hou
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Correspondence to Linlin Hou.

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The authors declare that there is no competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.

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This work was supported in part by National Natural Science Foundation of China under grants (61873331,62173205,62203248), Natural Science Foundation Program of Shandong Province (ZR2020YQ48, ZR2023MF049), and the Young Taishan Scholar Project of Shandong Province of China.

Linlin Hou received her master’s and Ph.D. degrees in Institute of Automation from Qufu Normal University, Qufu, China, in 2009 and 2012, respectively. She was a visiting scholar with the School of Engineering, RMIT University, Melbourne, Australia. Her research interests include analysis and control of switched systems, time-delay systems, and neural networks.

Pengfei Ma received her bachelor’s degree from the School of Computer Science from Qufu Normal University, Rizhao, China, in 2020. Now she is pursuing a master’s degree in the School of Computer Science, Qufu Normal University, Rizhao, China. Her current research interests include stability, control and synchronization of switched neural networks.

Xuan Ma received her bachelor’s degree in the School of Computer Science from Qufu Normal University, Rizhao, China, in 2019. Now she is pursuing a master’s degree in the School of Computer Science, Qufu Normal University, Rizhao, China. Her current research interests include analysis and control of networked control systems, switched systems, and neural networks.

Haibin Sun is a professor in the School of Engineering, Qufu Normal University. He received his Ph.D. degree in control theory and application from Southeast University in 2013. He was a Postdoctor with the School of Automation, Beihang University, Beijing, from 2013 to 2014. In 2017, he was a Visiting Scholar with the School of Engineering, RMIT University, Melbourne, Australia. In 2019, he was a Visiting Scholar with the School of IEEE, Nanyang Technological University, Singapore. His research interests mainly lie in switched control, anti-disturbance control and its application.

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Hou, L., Ma, P., Ma, X. et al. H∞ Exponential Synchronization of Switched Cellular Neural Networks Based on Disturbance Observer-based Control. Int. J. Control Autom. Syst. 22, 1430–1441 (2024). https://doi.org/10.1007/s12555-022-0917-7

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  • DOI: https://doi.org/10.1007/s12555-022-0917-7

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