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Article Dans Une Revue IEEE Transactions on Fuzzy Systems Année : 2023

An Improved Zonotopic Approach Applied to Fault Detection for Takagi-Sugeno Fuzzy Systems

Résumé

In this work, an actuator fault detection problem for discrete-time Takagi-Sugeno fuzzy systems is tackled in a bounded error context where both state disturbances and measurement noise are assumed to be unknown but bounded with known bounds. First, a peak-to-peak performance synthesis method is applied to design a robust residual generator against the considered process disturbances and measurement noise. Meanwhile, an improved zonotopic approach is proposed to compute tight adaptive thresholds for residual evaluation. Then, a reliable set-membership fault detection strategy with the aid of generated residual signals and adaptive thresholds is introduced. Finally, the viability of the proposed method is demonstrated via a numerical simulation. Then, an experimentation on a 3D Crane system is performed to show its practicability.
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Dates et versions

hal-04236218 , version 1 (10-10-2023)

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Youdao Ma, Zhenhua Wang, Nacim Meslem, Tarek Raïssi, Yi Shen. An Improved Zonotopic Approach Applied to Fault Detection for Takagi-Sugeno Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 2023, 31 (11), pp.3762-3774. ⟨10.1109/TFUZZ.2023.3267076⟩. ⟨hal-04236218⟩
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