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Robust Model-Based Fault Diagnosis for Dynamic Systems

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TLDR
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.
Abstract
There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field 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 The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world

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Citations
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Journal ArticleDOI

Fault diagnosis based on analytical models for linear and nonlinear systems - a tutorial

TL;DR: Two methods for residual generation are presented in a tutorial way: the parity space and the observer based approaches for linear and nonlinear models are successively considered.
Journal ArticleDOI

Fault detection and diagnosis for railway track circuits using neuro-fuzzy systems

TL;DR: It is shown that the proposed method correctly detects and diagnoses the most commonly occurring track circuit failures in a laboratory test rig of one type of audio frequency jointless track circuit.
Journal ArticleDOI

Mechatronic systems—Innovative products with embedded control

TL;DR: In this article, the authors summarized ongoing developments for mechatronic systems, showed design approaches and examples of mechatronics products and considered various embedded control functions and system's integrity.
Journal ArticleDOI

Analysis and Design of Robust $H_\infty $ Fault Estimation Observer With Finite-Frequency Specifications for Discrete-Time Fuzzy Systems

TL;DR: The performance of the presented fault estimation observer is further enhanced by adding the degree of freedom, and two examples are presented to illustrate the effectiveness of the proposed strategy.
Journal ArticleDOI

Model-based fault diagnosis in PEM fuel cell systems

TL;DR: In this article, a model-based fault diagnosis methodology for PEM fuel cell systems is presented, which is based on computing residuals, indicators that are obtained comparing measured inputs and outputs with analytical relationships, which are obtained by system modelling.
References
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Genetic algorithms in search, optimization, and machine learning

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Fuzzy identification of systems and its applications to modeling and control

TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
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Linear Matrix Inequalities in System and Control Theory

Edwin E. Yaz
TL;DR: In this paper, the authors present a brief history of LMIs in control theory and discuss some of the standard problems involved in LMIs, such as linear matrix inequalities, linear differential inequalities, and matrix problems with analytic solutions.
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The approximation of one matrix by another of lower rank

TL;DR: In this paper, the problem of approximating one matrix by another of lower rank is formulated as a least-squares problem, and the normal equations cannot be immediately written down, since the elements of the approximate matrix are not independent of one another.
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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.