Model-Based Fault Diagnosis - Methods for State-Space Systems

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.

List of contents

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.

Product details

• Authors: Yi Shen, Zhenhua Wang
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 12.11.2023
• EAN: 9789811967085
• ISBN: 978-981-1967-08-5
• No. of pages: 200
• Dimensions: 155 mm x 10 mm x 235 mm
• Illustrations: XV, 200 p. 70 illus., 60 illus. in color.
• Series: Studies in Systems, Decision and Control; Studies in Systems, Decision a
• Subject: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering