Model-Based Fault Diagnosis by Wang, Zhenhua; Shen, Yi;

Methods for State-Space Systems

Series: Studies in Systems, Decision and Control; 221;

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Product details:

Edition number 1st ed. 2023
Publisher Springer Nature Singapore
Date of Publication 29 October 2022
Number of Volumes 1 pieces, Book

ISBN 9789811967054
Binding Hardback
No. of pages200 pages
Size 235x155 mm
Weight 534 g
Language English
Illustrations XV, 200 p. 70 illus., 60 illus. in color. Illustrations, black & white

Long description:

This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.

Introduction.- Modelling for Fault Diagnosis.- Observer-Based Residual Generation.- Robust Residual Generation Based on Unknown Input Observer.- Optimal Robust Residual Generation.- Residual Evaluation Based on Threshold Computation.- Fault Isolation Based on Structured Residual Generation.- Fault Isolation Based on Directional Residual Generation.- Observer-Based Fault Estimation.- Kalman Filter-Based Fault Diagnosis.- Parity Space Approaches.

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