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Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems

Overview of attention for book
Cover of 'Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Prologue
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    Chapter 2 Wind Turbine Fault Localization: A Practical Application of Model-Based Diagnosis
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    Chapter 3 Fault Detection and Localization Using Modelica and Abductive Reasoning
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    Chapter 4 Robust Data-Driven Fault Detection in Dynamic Process Environments Using Discrete Event Systems
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    Chapter 5 Critical States Distance Filter Based Approach for Detection and Blockage of Cyberattacks in Industrial Control Systems
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    Chapter 6 Active Diagnosis for Switched Systems Using Mealy Machine Modeling
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    Chapter 7 Secure Diagnosability of Hybrid Dynamical Systems
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    Chapter 8 Diagnosis in Cyber-Physical Systems with Fault Protection Assemblies
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    Chapter 9 Passive Diagnosis of Hidden-Mode Switched Affine Models with Detection Guarantees via Model Invalidation
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    Chapter 10 Diagnosability of Discrete Faults with Uncertain Observations
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    Chapter 11 Abstractions Refinement for Hybrid Systems Diagnosability Analysis
Attention for Chapter 6: Active Diagnosis for Switched Systems Using Mealy Machine Modeling
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Citations

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Chapter title
Active Diagnosis for Switched Systems Using Mealy Machine Modeling
Chapter number 6
Book title
Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-74962-4_6
Book ISBNs
978-3-31-974961-7, 978-3-31-974962-4
Authors

Jeremy Van Gorp, Alessandro Giua, Michael Defoort, Mohamed Djemaï

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 50%
Student > Ph. D. Student 1 25%
Professor > Associate Professor 1 25%
Readers by discipline Count As %
Engineering 2 50%
Unknown 2 50%

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