On-line fault detection in uncertain nonlinear systems using diagnostic observers: a survey
作者:
PAULM. FRANK,
期刊:
International Journal of Systems Science
(Taylor Available online 1994)
卷期:
Volume 25,
issue 12
页码: 2129-2154
ISSN:0020-7721
年代: 1994
DOI:10.1080/00207729408949341
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
The paper discusses the principles of model-based fault detection and isolation (FDI) in nonlinear and time-varying uncertain dynamic systems. Such systems are typical for such complex plants as, for example, in the chemical process industries or in advanced transportation technology. For a model-based fault diagnosis in such situations, robust or even adaptive strategies are needed. In this paper the theory of robust linear observer-based residual generation for FDI is reviewed from a general point of view. The structural equivalence between the parity space approach and observer-based approach is shown in a new simple graphical way by showing that the observer-based FDI concept can easily be transformed into an equivalent extended parity space configuration, without claiming, however, equivalence of the underlying design techniques. The unknown input observer approach known as a most powerful and comprehensive framework for robust residual generation for FDI in uncertain linear systems is extended to classes of nonlinear and time-varying systems. For such plants an adaptive nonlinear unknown input observer scheme is proposed. Finally, appropriate residual evaluation techniques are outlined and suggestions are made to increase the robustness, for instance by using adaptive thresholds.
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