Fault detection and isolation of nonlinear systems : an unknown input observer approach with sum-of-squares techniques
This paper presents a novel nonlinear unknown input observer (UIO) design method for fault detection and isolation (FDI) of a class of nonlinear affine systems. By using sum-of-squares (SOS) theory and Lie geometry as the main tools, we demonstrate how to relax the rank constraint in the traditional...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/107330 http://hdl.handle.net/10220/17033 http://dx.doi.org/10.1115/1.4006074 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | This paper presents a novel nonlinear unknown input observer (UIO) design method for fault detection and isolation (FDI) of a class of nonlinear affine systems. By using sum-of-squares (SOS) theory and Lie geometry as the main tools, we demonstrate how to relax the rank constraint in the traditional UIO approach and simplify the design procedure, especially for the polynomial nonlinear systems. Meanwhile, we show that the detection and isolation thresholds based on the L2 gains can be easily obtained via optimization formulated in terms of SOS. Simulation examples are given to illustrate the design procedure and the advantages. |
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