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A New Approach to Fault Estimation of Discrete-Time Markov Jump Fuzzy Systems with Iterative Current Observers

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Abstract

This paper is concentrated on the fault estimation of discrete-time Markov jump fuzzy systems via iterative learning based on current observers. A new approach is proposed to construct the observers with system outputs and covers the traditional one as a special case. With the help of a matched transformation and a structure separation technique, conditions for the resultant observer error systems to be stochastically stable are established in terms of linear matrix inequalities. It is shown that the proposed method is less conservative than the existing one. A numerical example is provided to verify the effectiveness of the proposed method.

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Authors and Affiliations

  1. School of Automation, Southeast University, Nanjing, 210018, Jiangsu, China

    Yongsheng Ma, Wen Shi, Yongming Huang & Guobao Zhang

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  1. Yongsheng Ma
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  2. Wen Shi
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  3. Yongming Huang
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  4. Guobao Zhang
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Correspondence to Guobao Zhang.

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Ma, Y., Shi, W., Huang, Y. et al. A New Approach to Fault Estimation of Discrete-Time Markov Jump Fuzzy Systems with Iterative Current Observers. Int. J. Fuzzy Syst. 25, 3162–3176 (2023). https://doi.org/10.1007/s40815-023-01561-7

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