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Nonlinear Observers and Applications [electronic resource] / by Gildas Besançon.

By: Contributor(s): Series: Lecture Notes in Control and Information Sciences ; 363Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Description: XII, 224 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540735038
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 629.8 23
LOC classification:
  • TJ210.2-211.495
  • TJ163.12
Online resources:
Contents:
An Overview on Observer Tools for Nonlinear Systems -- Uniform Observability and Observer Synthesis -- Adaptive-Gain Observers and Applications -- Immersion-Based Observer Design -- Nonlinear Moving Horizon Observers: Theory and Real-Time Implementation -- Asymptotic Analysis and Observer Design in the Theory of Nonlinear Output Regulation -- Parameter/Fault Estimation in Nonlinear Systems and Adaptive Observers.
In: Springer eBooksSummary: The problem of state reconstruction in dynamical systems, known as observer problem, is undoubtedly crucial for controlling or just monitoring processes. For linear systems, the corresponding theory has been quite well established for several years now, and the purpose of the present book is to propose an overview on possible tools in that respect for nonlinear systems. Basic observability notions and observer structures are first recalled, together with ingredients for advanced designs on this basis. A special attention is then paid to the well-known high gain techniques with a summary of various corresponding recent results. A focus on the celebrated Extended Kalman filter is also given, in the perspectives of both nonlinear filtering and high gain observers, leading to so-called adaptive-gain observers. The more specific immersion approach for observer design is then emphasized, while optimization-based methods are also presented as an alternative to analytic observers. Various practical application examples are included in those discussions, and some fields of application are further considered: first the problem of nonlinear output regulation is reformulated in a perspective of observers, and then the problem of parameter or fault estimation is briefly mentioned through some adaptive observer tools.
Item type: eBooks
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An Overview on Observer Tools for Nonlinear Systems -- Uniform Observability and Observer Synthesis -- Adaptive-Gain Observers and Applications -- Immersion-Based Observer Design -- Nonlinear Moving Horizon Observers: Theory and Real-Time Implementation -- Asymptotic Analysis and Observer Design in the Theory of Nonlinear Output Regulation -- Parameter/Fault Estimation in Nonlinear Systems and Adaptive Observers.

The problem of state reconstruction in dynamical systems, known as observer problem, is undoubtedly crucial for controlling or just monitoring processes. For linear systems, the corresponding theory has been quite well established for several years now, and the purpose of the present book is to propose an overview on possible tools in that respect for nonlinear systems. Basic observability notions and observer structures are first recalled, together with ingredients for advanced designs on this basis. A special attention is then paid to the well-known high gain techniques with a summary of various corresponding recent results. A focus on the celebrated Extended Kalman filter is also given, in the perspectives of both nonlinear filtering and high gain observers, leading to so-called adaptive-gain observers. The more specific immersion approach for observer design is then emphasized, while optimization-based methods are also presented as an alternative to analytic observers. Various practical application examples are included in those discussions, and some fields of application are further considered: first the problem of nonlinear output regulation is reformulated in a perspective of observers, and then the problem of parameter or fault estimation is briefly mentioned through some adaptive observer tools.

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