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Model-Based Fault Diagnosis: Methods for State-Space Systems: Studies in Systems, Decision and Control, cartea 221

Autor Zhenhua Wang, Yi Shen
en Limba Engleză Paperback – 29 oct 2023
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.
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Specificații

ISBN-13: 9789811967085
ISBN-10: 9811967083
Pagini: 200
Ilustrații: XV, 200 p. 70 illus., 60 illus. in color.
Dimensiuni: 155 x 235 mm
Ediția:1st ed. 2023
Editura: Springer Nature Singapore
Colecția Springer
Seria Studies in Systems, Decision and Control

Locul publicării:Singapore, Singapore

Cuprins

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.

Notă biografică

Dr. Zhenhua Wang received his B.Sc. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2008 and his M.Sc. and Ph.D. degrees from Harbin Institute of Technology, Harbin, China, in 2010 and 2014, respectively. He is an associate professor with the Department of Control Science and Engineering at Harbin Institute of Technology. His research interests include fault diagnosis, set-membership estimation, and fault-tolerant control. Since 2012, Dr. Wang has published more than 30 peer-reviewed technical papers in international journals. He is a member of IEEE and served as a reviewer of several international journals and an IPC member of the 28th, 29th, 30th Mediterranean Conference on Control and Automation.  
Dr. Yi Shen received his B.Sc., M.Sc., and Ph.D. degrees from Harbin Institute of Technology in 1985, 1988, and 1995, respectively. He is a professor at Harbin Institute of Technology. His research interests include fault diagnosis, flight vehicle control, and ultrasound signal processing. 

Textul de pe ultima copertă

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.

Caracteristici

Gives a comprehensive and detailed introduction of the model-based fault diagnosis methods Studies the principles and implementations of model-based fault diagnosis methods in the state-space approach Integrates the residual generation and residual evaluation in the fault detection and isolation