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Journal ArticleDOI

Nonlinear system fault diagnosis based on adaptive estimation

TLDR
An approach to fault diagnosis for a class of nonlinear systems is proposed, based on a new adaptive estimation algorithm for recursive estimation of the parameters related to faults, designed in a constructive manner through a nontrivial combination of a high gain observer and a recently developed linear adaptive observer.
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This article is published in Automatica.The article was published on 2004-07-01. It has received 205 citations till now. The article focuses on the topics: Adaptive algorithm & Observer (quantum physics).

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Citations
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Journal ArticleDOI

Brief paper: Nonlinear robust fault reconstruction and estimation using a sliding mode observer

TL;DR: This paper considers fault detection and estimation issues for a class of nonlinear systems with uncertainty, using an equivalent output error injection approach, and a particular design of sliding mode observer is presented for which the parameters can be obtained using LMI techniques.
Journal ArticleDOI

Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation

TL;DR: This paper presents a fault detection and isolation (FDI) scheme for a class of Lipschitz nonlinear systems with nonlinear and unstructured modeling uncertainty that significantly extends previous results by considering a more general class of system nonlinearities which are modeled as functions of the system input and partially measurable state variables.
Journal ArticleDOI

Model-based fault diagnosis for aerospace systems: a survey:

TL;DR: In this article, a survey of model-based fault detection methods for aerospace systems is presented, focusing on those methods that are applicable to aerospace systems and highlighting the characteristics of aerospace models, generic non-linear dynamical modelling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented.
Journal ArticleDOI

Brief paper: Adaptive observers for nonlinearly parameterized class of nonlinear systems

TL;DR: In this article, the adaptive observers for a class of uniformly observable MIMO nonlinear systems with general nonlinear parameterizations were proposed and the state and unknown parameters of the considered systems are supposed to lie in bounded domains which size can be arbitrarily large and the exponential convergence of the observers is shown to result under a well defined persistent excitation condition.
Journal ArticleDOI

How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems

TL;DR: This paper focuses on the construction of a fuzzy adaptive output feedback control based on any observer (high-gain (HG) observer, sliding mode (like) observer), for a class of single-input-single-output (SISO) uncertain or ill-defined affine nonlinear systems.
References
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Book

Linear systems

Book

Stochastic Processes and Filtering Theory

TL;DR: In this paper, a unified treatment of linear and nonlinear filtering theory for engineers is presented, with sufficient emphasis on applications to enable the reader to use the theory for engineering problems.
Book

Robust Model-Based Fault Diagnosis for Dynamic Systems

TL;DR: Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research.
Journal ArticleDOI

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

Paul M. Frank
- 01 May 1990 - 
TL;DR: In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.
Journal ArticleDOI

Paper: A survey of design methods for failure detection in dynamic systems

TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
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