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- W2029384580 abstract "ABSTRACTThis paper presents a novel eigenstructure assignment approach for synthesizing robust fault detection and isolation (FDI) systems with known inputs. After formulating the FDI problem in eigenstructure assignment, we proceed to developa parametric characterization of all allowable eigenspaces for disturbance decoupling to achieve robust fault detection. In addition to the structured uncertainties. the robustness of the diagnostic observer to unstructured modeling errors isdiscussed. A numerical algorithm is further proposed to suppress the effects due to the unstructured uncertainties. The overall robustness of the diagnostic strategy is verified through simulation studies on jet engine systems. Keyword: fault detection and isolation. unknown inputs, eigenstructure assignment. unstructured uncertainties. 1. DTRODUCTION The methodology of analytical redundancy is widely employed to economically perform fault detection and isolation(FDI) on controlled systems. The FDI concept based on analytical redundancy uses a mathematical model of the dynamic" @default.
- W2029384580 created "2016-06-24" @default.
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- W2029384580 date "1995-05-30" @default.
- W2029384580 modified "2023-09-27" @default.
- W2029384580 title "<title>Robust diagnostic approach for uncertain systems: an example for the jet engine sensor systems</title>" @default.
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- W2029384580 doi "https://doi.org/10.1117/12.210518" @default.
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