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Annular Finite-Time \(H_{\infty }\) Filtering for Mean-Field Stochastic Systems

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Abstract

This article presents an annular finite-time \(H_{\infty }\) filtering approach for continuous-time mean-field stochastic systems (MFSSs). Our attention is focused on obtaining a set of stability criteria for analyzing the \(H_{\infty }\) performance and the annular finite-time boundedness of the filtering error system. Sufficient conditions in the form of linear matrix inequality (LMI) are established to guarantee the existence of the designed filter. Then, the filter gains are derived through a convex optimization problem. Through a simulation example, the validity of the obtained results is demonstrated.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 61972236), Natural Science Foundation of Shandong Province (No. ZR2022MF233). The authors gratefully acknowledge the Associate Editor and the anonymous reviewers who read the drafts and provided many helpful suggestions.

Funding

Funding was provided by National Natural Science Foundation of China (61972236), Natural Science Foundation of Shandong Province (ZR2022MF233)

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Authors and Affiliations

  1. College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266590, Shandong, China

    Jijing Zhuang & Xikui Liu

  2. Department of Electrical Engineering and Information Technology, Shandong University of Science and Technology, Jinan, 250031, Shandong, China

    Yan Li & Xikui Liu

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  1. Jijing Zhuang
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  2. Yan Li
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Correspondence to Xikui Liu.

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This work was supported by the National Natural Science Foundation of China (No. 61972236), Natural Science Foundation of Shandong Province (No. ZR2022MF233).

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Zhuang, J., Li, Y. & Liu, X. Annular Finite-Time \(H_{\infty }\) Filtering for Mean-Field Stochastic Systems. Circuits Syst Signal Process 43, 2115–2129 (2024). https://doi.org/10.1007/s00034-023-02568-z

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