Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
Abstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a suf...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-05-01
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| Series: | IET Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/sil2.12016 |
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| Summary: | Abstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a sufficient condition which ensures that the conic‐type dynamic FFDF system is asymptotically stable. After that, using linear matrix inequalities techniques, the FFDF design problem is transformed into an optimization algorithm. Finally, the simulation results demonstrate that the designed FFDF is effective for detecting the faults. |
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| ISSN: | 1751-9675 1751-9683 |