Process Monitoring, Fault Diagnosis, and Tolerant Control for Complex Industrial Systems

A Festschrift in Honor of Professor Steven X. Ding on the Occasion of His Retirement
Erscheinungsjahr 2025
ISBN: 978-981-969032-9
Verlag: Springer Nature Singapore

Buch, Englisch, 745 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Control and Information Sciences

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.

Zielgruppe

Research

Autoren/Hrsg.

Luo, Hao

Chen, Zhiwen

Li, Linlin

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technische Instrumentierung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Fertigungstechnik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik

Inhaltsverzeichnis

Preface.- Operator-in-the-Loop Bayesian Optimization Towards Optimal Process Operation.- Simultaneous State and Fault Estimation Over Bandwidth-constrained Networks: A Relay-aided Binary Encoding Strategy.- Adaptive Neural Fault-tolerant Observer-based Stabilization of Uncertain MIMO Time-delay Nonlinear Systems with Dead-zones and Faults in Actuators.- Nonlinear Fault-tolerant Tracking Control for DC-DC Boost Converters with Measurement Faults.- Mirror Attacks on Cyber-Physical Systems.

Über Autor(innen)

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