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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d Wirtschaftsforschung. Eine Entwicklung, die auch für die empirische Organisationsforschung und ihre zunehmend komplexer werdenden Datenstrukturen (Paneldaten, Mehrebenen- und Mixed-Methods-Designs, Verknüpfung von Datens?tzen und -quellen) von Bedeutung ist. Zudem gewinnt die Frage einer nachhalti

解開(kāi)

監(jiān)禁

勛章

978-1-4613-7344-5Springer Science+Business Media New York 1999

鋼盔

苦惱

Basic Principles of Model-Based Fault Diagnosis,esearch context and also in the domain of application studies on real processes. There are a great variety of methods in the literature, based on the use of mathematical models of the monitored processes and modern control theory.

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培養(yǎng)

協(xié)奏曲

Robust Residual Generation Using Unknown Input Observers,ce de-coupling based approaches are the dominant approaches for robust residual generation. For those approaches, uncertain factors in system modeling are considered to act via an unknown input (or disturbance) on a linear system model. Although the unknown input vector is unknown, its distribution

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Robust Residual Generation by the Assignment of Observer Eigenstructure,proaches is to make the state estimation error be independent of disturbances (or unknown inputs). The residual is defined as the (weighted) output estimation error which is a linear transformation of the state estimation error. The residual generated by UIOs is also independent of disturbances, if