Diagnosis and Fault-tolerant Control Volume 2 E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This book presents recent advances in fault diagnosis and fault-tolerant control of dynamic processes. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique and sustainable control, especially for those demanding systems that require reliability, availability, maintainability, and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical. Diagnosis and Fault-tolerant Control 2 also presents and compares different fault diagnosis and fault-tolerant schemes, using well established, innovative strategies for modeling the behavior of the dynamic process under investigation. An updated treatise of diagnosis and fault-tolerant control is addressed with the use of essential and advanced methods including signal-based, model-based and data-driven techniques. Another key feature is the application of these methods for dealing with robustness and reliability.
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Seitenzahl: 420
Veröffentlichungsjahr: 2021
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Table of Contents
Cover
Title Page
Copyright
1 Nonlinear Methods for Fault Diagnosis
1.1. Introduction
1.2. Fault diagnosis tasks
1.3. Model-based fault diagnosis
1.4. Data-driven fault diagnosis
1.5. Model-based and data-driven integrated fault diagnosis
1.6. Robust fault diagnosis problem
1.7. Summary
1.8. References
2 Linear Parameter Varying Methods
2.1. Introduction
2.2. Preliminaries: a classical approach
2.3. Problem statement
2.4. Robust active fault-tolerant control design
2.5. Application: an anaerobic bioreactor
2.6. Conclusion
2.7. References
3 Fuzzy and Neural Network Approaches
3.1. Introduction
3.2. Fuzzy model design
3.3. Neural model design
3.4. Fault estimation and diagnosis
3.5. Fault-tolerant control
3.6. Illustrative examples
3.7. Conclusion
3.8. Acknowledgment
3.9. References
4 Model Predictive Control Methods
4.1. Introduction
4.2. Idea of MPC
4.3. Robustness of MPC
4.4. Neural-network-based robust MPC
4.5. Robust control of a pneumatic servo
4.6. Conclusion
4.7. References
5 Nonlinear Modeling for Fault-tolerant Control
5.1. Introduction
5.2. Fault-tolerant control strategies
5.3. Fault diagnosis and tolerant control
5.4. Summary
5.5. References
6 Virtual Sensors and Actuators
6.1. Introduction
6.2. Problem statement
6.3. Virtual sensors and virtual actuators
6.4. LMI-based design
6.5. Additional considerations
6.6. Application example
6.7. Conclusion
6.8. References
7 Conclusions
7.1. Introduction
7.2. Closing remarks
7.3. References
8 Open Research Issues
8.1. Further works and open problems
8.2. Summary
8.3. References
List of Authors
Index
Summary of Volume 1
End User License Agreement
Guide
Cover
Table of Contents
Title page
Copyright
Begin Reading
List of Authors
Index
Summary of Volume 1
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1. Fault diagnosis module
Figure 1.2. Model-based fault diagnosis strategy
Figure 1.3. Residual generation strategy
Figure 1.4. Residual generator input–output form
Figure 1.5. Parity vector approach
Figure 1.6. MIMO parity vector
Figure 1.7. Diagnostic residual observer
Figure 1.8. Data-driven fault diagnosis
Figure 1.9. Neuron representation example
Figure 1.10. Nonlinear ARX neural network
Figure 1.11. Example of dynamic neural network
Figure 1.12. Fault diagnosis approach integration
Figure 1.13. Online estimation for fault diagnosis
Chapter 2
Figure 2.1. Anaerobic bioreactor
Figure 2.2. The referential inputs
Figure 2.3. The system output y
1
(t): nominal output, output without FTC and out...
Figure 2.4. The system output y2 (t): nominal output, output without FTC and out...
Figure 2.5. The real actuator fault and its estimated
Figure 2.6. The real actuator fault and its estimated
Chapter 3
Figure 3.1. The structure of the developed RNN
Figure 3.2. Robust predictive FT scheme
Figure 3.3. Comparison between nonlinear and Takagi–Sugeno response of the syste...
Figure 3.4. Actuator faults f
a,1
(a) and f
a,2
(b). For a color version of this ...
Figure 3.5. Sensor faults f
s,1
(a) and f
s,2
(b). For a color version of this fi...
Figure 3.6. State variables ω
v
(a) and ω
h
(b). For a color version of this figur...
Figure 3.7. State variables ω
v
(a) and ω
h
(b). For a color version of this figur...
Figure 3.8. Main and tail rotor angular position based on FTC and non-FTC (a) as...
Figure 3.9. Appropriate control inputs u
1
and u
2
. For a color version of this fi...
Chapter 4
Figure 4.1. Idea of MPC. For a color version of this figure, see www.iste.co.uk/...
Figure 4.2. Neural network with external dynamics
Figure 4.3. Scheme of pneumatic servomechanism
Figure 4.4. Modeling: process output (blue-solid) and model output (red-dashed)....
Figure 4.5. Uncertainty modeling: process output (black-solid), fundamental mode...
Figure 4.6. Control performance for random steps: reference profile (black-dashe...
Figure 4.7. Control performance for the ramp signal: reference profile (black-da...
Figure 4.8. Control performance for harmonic steps: reference profile (black-das...
Chapter 6
Figure 6.1. The quadruple-tank system
Figure 6.2. Virtual actuator results. For a color version of this figure, see ww...
Figure 6.3. Virtual sensor results. For a color version of this figure, see www....
Chapter 8
Figure 8.1. Key points of sustainable approach
Figure 8.2. Link between objectives, overall goals and impacts
Figure 8.3. Sustainable control design tasks
Figure 8.4. Sustainable design strategy tasks and targets
List of Tables
Chapter 1
Table 1.1. Training algorithm examples
Chapter 2
Table 2.1. Constant parameter values
Chapter 4
Table 4.1. Control results for RNMPC
Table 4.2. Control quality
Chapter 6
Table 6.1. Model parameters
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SCIENCES
Systems and Industrial Engineering, Field Director – Jean-Paul Bourrières
Reliability, Diagnosis, Safety and Maintenance of Systems, Subject Head – Jean-Marie Flaus
Diagnosis and Fault-tolerant Control 2
From Fault Diagnosis to Fault-tolerant Control
Coordinated by
Vicenç Puig
Silvio Simani
First published 2021 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK
www.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA
www.wiley.com
© ISTE Ltd 2021The rights of Vicenç Puig and Silvio Simani to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Library of Congress Control Number: 2021941902
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78945-059-0
ERC code:
PE7 Systems and Communication Engineering
PE7_1 Control engineering
