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Set-Membership Filtering for Time-Varying Complex Networks with Randomly Varying Nonlinear Coupling Structure

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Abstract

This paper is concerned with set-membership filtering for time-varying complex networks with randomly varying nonlinear coupling structure. A novel coupling model governed by a sequence of Bernoulli stochastic variables is proposed. The connection relationships among multiple nodes of complex networks are nonlinear. Utilizing the mathematical induction method, a sufficient condition is derived to remain the filtering error within an ellipsoid region at each time step. Subsequently, the desired filter gain is obtained by minimizing the ellipsoid constraint matrix (in the sense of trace) according to a recursive linear matrix inequalities algorithm. Finally, a simulation example is presented to illustrate the effectiveness of the proposed theory.

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Acknowledgements

This work was supported in part by Key Area Research and Development Program of Guangdong Province (2021B0101410005), the National Natural Science Foundation of China under Grants (62276070, 62027817), the Natural Science Foundation of Guangdong Province, China (2022A1515110104), the China Postdoctoral Science Foundation (2022TQ0084), and the Local Innovative and Research Teams Project of Guangdong Special Support Program (2019BT02X353).

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Authors and Affiliations

  1. Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou, 510006, China

    Ming Lin, Jie Li, Yan-Ni Zeng, Chang Liu & Hongxia Rao

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  1. Ming Lin
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  2. Jie Li
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  4. Chang Liu
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Correspondence to Chang Liu.

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Lin, M., Li, J., Zeng, YN. et al. Set-Membership Filtering for Time-Varying Complex Networks with Randomly Varying Nonlinear Coupling Structure. Circuits Syst Signal Process 42, 5233–5251 (2023). https://doi.org/10.1007/s00034-023-02371-w

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