Diagnosis, fault detection and tolerant control

Diagnosis, fault detection and tolerant control [electronic resource] / Nabil Derbel, Jawhar Ghommam, Quanmin Zhu, editors.

Saved in:
Bibliographic Details
Online Access: Full Text (via Springer)
Other Authors: Derbel, Nabil, Ghommam, Jawhar, Zhu, Quanmin
Format: Electronic eBook
Language:English
Published: Singapore : Springer, 2020.
Series:Studies in systems, decision and control ; v. 269.
Subjects:
Fault-tolerant computing.
Table of Contents:
  • Intro
  • Preface
  • Contents
  • 1 A Nondestructive Technique to Identify and Localize Microscopic Defects on a Microstrip Line
  • 1.1 Introduction
  • 1.2 The Transmission Lines
  • 1.2.1 Definition
  • 1.2.2 Types of Transmission Lines
  • 1.3 Microstrip Line Model
  • 1.3.1 Modelling of a Microstrip Line
  • 1.3.2 Particular Case: Lossless Line
  • 1.3.3 The Impedance and the Reflection Coefficient
  • 1.4 The S Parameters
  • 1.4.1 Definition
  • 1.4.2 The S Matrix
  • 1.4.3 The S Matrix for a Two-Port Network
  • 1.4.4 The S Matrix Properties
  • 1.5 The Used Model of the Microstrip Line.
  • 1.6 Defects Description
  • 1.6.1 The Narrow Transverse Slit
  • 1.6.2 The Overflow
  • 1.7 The Solution Description
  • 1.8 The Simulation Results with CST Software
  • 1.8.1 The Simulation of Undamaged Microstrip Line
  • 1.8.2 The Simulation of a Microstrip Line with an Overflow
  • 1.8.3 The Simulation of a Microstrip Line with a Narrow Transverse Slit
  • 1.9 The Experimental Results
  • 1.9.1 The Experimental Prototype
  • 1.9.2 Analysis of Experimental Results
  • 1.10 Conclusion
  • References
  • 2 Sensor Fault Detection and Isolation Based on Variable Moving Window KPCA
  • 2.1 Introduction.
  • 2.2 Kernel Principal Component Analysis
  • 2.2.1 Identification of the KPCA Model
  • 2.2.2 Scaling
  • 2.2.3 Fault Detection Indices
  • 2.3 Online KPCA Methods for Fault Detection
  • 2.3.1 Moving Window Kernel PCA (MWKPCA)
  • 2.3.2 Variable Moving Window Kernel PCA (VMWKPCA)
  • 2.4 Fault Isolation
  • 2.5 Application to an Air Quality Monitoring Network
  • 2.6 Conclusion
  • References
  • 3 Sensor Fault Detection and Estimation Based on UIO for LPV Time Delay Systems Using Descriptor Approach
  • 3.1 Introduction
  • 3.2 System Description
  • 3.3 UIO Design.
  • 3.4 Method of Calculating the Observer Gains
  • 3.5 Simulation Studies
  • 3.6 Conclusion
  • References
  • 4 Fault Diagnosis of Linear Switched Systems Based on Hybrid Observer
  • 4.1 Introduction
  • 4.2 Motivation, Related Work, and Objectives
  • 4.3 Hybrid Dynamical Systems
  • 4.3.1 Presentation of Hybrid Dynamical System
  • 4.3.2 Different Classes of Hybrid Systems
  • 4.4 System Diagnosis
  • 4.4.1 Definition
  • 4.4.2 Different Stages of the Diagnosis of a System
  • 4.4.3 Diagnosis Methods
  • 4.5 Proposed Diagnosis Approach
  • 4.5.1 Switched Linear System Model.
  • 4.5.2 Fault Detection Based on a Hybrid Observer
  • 4.6 Case Study
  • 4.6.1 Studied System
  • 4.6.2 Implementation of the Hybrid Observer
  • 4.6.3 Simulation Results
  • 4.7 Conclusion
  • References
  • 5 Neutral Time-Delay System: Diagnosis and Prognosis Using UIO Observer
  • 5.1 Introduction
  • 5.2 Diagnosis of a Linear Neutral Delay System
  • 5.3 Prognosis for a Class of Neutral Time-Delay System
  • 5.3.1 Model Class for Prognosis
  • 5.3.2 System Description and Problem Formulation
  • 5.4 Transmission Line Diagnosis and Prognosis
  • 5.4.1 Diagnostic Study
  • 5.4.2 Prognosis Study.

Similar Items