Abstract
This thesis focuses on the asynchronous deconvolution fuzzy filtering for time-varying delays Lur’e singular Markov jump fuzzy systems via the Takagi–Sugeno fuzzy control technique. The stochastic admissibility and \(H_\infty\) performance index of Lur’e singular Markov jump fuzzy systems are obtained by establishing mode-dependent Lyapunov-Krasovskill functional. In addition, the asynchrony phenomenon between the original system modes and filter modes is described by a hidden Markov model. The parallel distribute compensation approach is used to design an asynchronous deconvolution fuzzy filter, and the desired filter parameters are achieved via solving linear matrix inequalities. Lastly, the validity and practicality of the proposed method are shown by a numerical example and a single-link robot arm.









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The data used to support the findings of this study are available from the corresponding author upon request.
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Acknowledgements
The authors would like to thank the Editors and the Referees for the important comments and valuable suggestions for improving the paper. This work was supported by National Natural Science Foundation of China under Grants 62173174, 61773191, 62173183, 61973148; Support Plan for Outstanding Youth Innovation Team in Shandong Higher Education Institutions under Grant 2019KJI010; Natural Science Foundation of Shandong Province for Key Projects under Grant ZR2020KA010; Graduate education high-quality curriculum construction project for Shandong Province under Grant SDYKC20185.
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Conditions of Theorem 2
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Yin, Y., Zhuang, G., Xia, J. et al. H∞ Asynchronous Deconvolution Fuzzy Filter Design for Nonlinear Singular Markov Jump Systems with Time-Varying Delays. Int. J. Fuzzy Syst. 25, 763–779 (2023). https://doi.org/10.1007/s40815-022-01400-1
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DOI: https://doi.org/10.1007/s40815-022-01400-1