Titlebook: Robust Model-Based Fault Diagnosis for Dynamic Systems; Jie Chen,Ron J. Patton Book 1999 Springer Science+Business Media New York 1999 dia

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,Frequency Domain Design and H∞ Optimization Methods For Robust Fault Diagnosis,ns, for eliminating or minimizing disturbance and modeling error effects on residual and hence for achieving robustness in FDI. Whilst these techniques are different, one feature is common among them, the original frameworks of these methods were developed for ideal systems or with a special uncerta

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Fault Diagnosis of Non-Linear Dynamic Systems,aditionally approached in two steps. Firstly, the model is linearized at an operating point, and then robust techniques are applied to generate residual signals which are insensitive to model parameter variations within a small neighborhood of the operating point. The robustness issue is tackled usi

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Determination of Disturbance Distribution Matrices for Robust Residual Generation,very accurate model. However, in order to design a robust FDI scheme, one should have a description (i.e. some information or knowledge) about the system uncertainty, e.g. its distribution matrix or spectral bandwidth, etc. Furthermore, this description should provide assistance for robust FDI design, i.e. it can be handled in a systematic manner.

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Book 1999cal systems of nuclear reactors and aircraft where safety is paramount important, to systems such as autonomous vehicles and fast railways where the system availability is vital. It is clear that fault diagnosis (including fault detection and isolation, FDI) has been becoming an important subject in

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