Fault Diagnosis for Linear Discrete Time-Varying Systems and Its Applications
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71 001 Ft
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Product details:
- Edition number 1st ed. 2023
- Publisher Springer Nature Singapore
- Date of Publication 3 November 2023
- Number of Volumes 1 pieces, Book
- ISBN 9789811954405
- Binding Paperback
- See also 9789811954375
- No. of pages406 pages
- Size 235x155 mm
- Weight 652 g
- Language English
- Illustrations XIX, 406 p. 103 illus., 94 illus. in color. Illustrations, black & white 509
Categories
Applied mathematics
Mathematics in engineering and natural sciences
Taxonomy, systematics
Engineering in general
Electrical engineering and telecommunications, precision engineering
Mechanical Engineering Sciences
Further readings in the field of computing
Applied mathematics (charity campaign)
Mathematics in engineering and natural sciences (charity campaign)
Taxonomy, systematics (charity campaign)
Engineering in general (charity campaign)
Electrical engineering and telecommunications, precision engineering (charity campaign)
Mechanical Engineering Sciences (charity campaign)
Further readings in the field of computing (charity campaign)
Long description:
This book focuses on fault diagnosis for linear discrete time-varying (LDTV) systems and its applications in modern engineering processes, with more weighting placed on the development of theory and methodologies. A comprehensive and systematic study on fault diagnosis for LDTV systems is provided, covering H∞-optimization-based fault diagnosis, H∞-filtering-based fault diagnosis, parity space-based fault diagnosis, Krein space technique-aided fault detection and fault estimation, and their typical applications in linear/nonlinear processes such as satellite attitude control systems and INS/GPS systems. This book benefits researchers, engineers, and graduate students in the fields of control engineering, electrical and electronic engineering, instrumentation science, and optoelectronic engineering.
Table of Contents:
Chapter 1. Introduction.- Chapter 2. Paradigm of model-based fault detection and diagnosis.- Chapter 3. LDTV systems, and fault detection and estimation for LDTV systems.- Chapter 4. Krein space and Krein space-based optimization technique.- Chapter 5. H2 optimization-based fault detection for LDTV systems.- Chapter 6. Optimal fault detection for LDTV systems.- Chapter 7. A projection-based method of fault detection for LDTV systems.- Chapter 8. An Hi/H∞-optimization scheme of fault detection for LDTV systems.- Chapter 9. An Hi/H∞-optimization approach to event-triggered fault detection for LDTV systems.- Chapter 10. A scheme of optimal fault detection for LDTV systems with delayed state.- Chapter 11. A krein space approach to H∞ fault estimation of LDTV systems.- Chapter 12. On designing H∞ fault detection filter for LDTV systems.- Chapter 13. Krein space based H∞ fault detection for LDTV systems with delayed state.- Chapter 14. Parity space-based fault detection for LDTV systemswith unknown input.- Chapter 15. Parity space-based fault estimation for LDTV systems.- Chapter 16. Event-triggered parity space approach to fault detection for LDTV systems.- Chapter 17. Stationary wavelet transform aided fault detection for LDTV systems.- Chapter 18. An extended H-/H∞ optimization approach to fault detection for a class of nonlinear systems.- Chapter 19. Probability analysis of fault diagnosis performance for satellite attitude control systems.- Chapter 20. Hi/H∞ optimization based fault detection for INS/GPS-integrated systems.- Chapter 21. Krein space based H∞ fault estimation for discrete-time nonlinear systems.- Chapter 22. Adaptive in-flight alignment of INS/GPS systems for aerial mapping.- Chapter 23. On real time performance evaluation of the inertial sensors for INS/GPS integrated systems.- Chapter 24. Summary.
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