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Parameter/Fault Estimation in Nonlinear Systems and Adaptive Observers

  • Gildas Besançon
Chapter
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 363)

Contents

Modeling and monitoring processes are clearly part of an overall control problem, as well as they can be considered by themselves, and each of them can be seen from an observer viewpoint: for the first one indeed, whenever the model structure is given, the problem amounts to that of estimating the model parameters. Even if this problem has been widely studied in the framework of identification [15, 13, ...], it can be recast in an observer formulation, by simply considering unknown parameters as constant state variables. For the second one, it has clearly also been very widely studied, in the community of fault detection and diagnosis [20, 7, ...]. But one can also use an observer to detect possible faults, for instance by comparing an observer output to the corresponding measured one. When taking into account possible faults through parameter changes in a model, fault detection (and isolation) can even be solved via parameter estimation.

Keywords

Fault Detection Fault Diagnosis Observer Design Adaptive Observer Observer Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Gildas Besançon
    • 1
  1. 1.Control Systems Department (former Laboratoire d’Automatique de Grenoble), GIPSA-lab. ENSIEG BP 46, 38402 Saint-Martin d’HèresFrance

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