This open access book details fault diagnosis, prognosis, and tolerant control for complex industrial systems. It is also dedicated to Professor Steven X. Ding for his retirement. This book proposes data-driven quality-related fault diagnosis schemes based on space projection for linear/nonlinear systems. It also introduces credible and efficient fault prognosis techniques for complex industrial systems. It combines fault detection and re-configuration toward the design of fault-tolerant control methods. It will be a useful reference for students and researchers working on fault diagnosis.
Series
Language
Place of publication
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Illustrations
2 s/w Abbildungen, 227 farbige Abbildungen
XXVII, 746 p. 248 illus., 230 illus. in color. In 2 volumes, not available separately.
Dimensions
Height: 243 mm
Width: 164 mm
Thickness: 51 mm
Weight
ISBN-13
978-981-96-9032-9 (9789819690329)
DOI
10.1007/978-981-96-9033-6
Schweitzer Classification
Prof. Hao Luo received the B.E. degree in electrical engineering from Xi'an Jiaotong University, Xi'an, China, in 2007, and the M.Sc. and Ph.D. degrees in electrical engineering and information technology from the University of Duisburg-Essen, Duisburg, Germany, in 2012 and 2016, respectively. He is currently Professor with the School of Astronautics, Harbin Institute of Technology, Harbin, China. His research interests include model-based and data-driven fault diagnosis, fault-tolerant systems, and their plug-and-play application on industrial systems.
Prof. Zhiwen Chen received the B.E. degree in electronic information science and technology and the M.Sc. degree in electronic information and technology from Central South University, Changsha, China, in 2008 and 2012, respectively, and the Ph.D. degree in electrical engineering and information technology from the University of Duisburg-Essen, Duisburg, Germany, in 2016. He is currently Professor at Central South University, Changsha, Hunan. His research interests include model-based and data-driven fault diagnosis, process monitoring, machine learning, and its application in industry.
Prof. Linlin Li received the B.E. degree in automation from Xi'an Jiaotong University, Xi'an, China, in 2008, the M.E. degree in mechanical systems and control from Peking University, Beijing, China, in 2011, and the Ph.D. degree in automatic control from the Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany. She is now Professor with the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing. Her research interests include fault diagnosis and fault-tolerant control, fuzzy control, and estimation for nonlinear systems
