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Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and demonstrated on industrial case systems. Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems will be of interest to process and control engineers, engineering students and researchers with a control engineering background.
List of contents
From the Contents: Introduction.- Objectives, tasks and basic concepts.- An introduction to the representative technical processes.- Data-driven realization of the basic GLR scheme.- Principal component analysis, its variations and applications.- Partial least squares, its variations and applications.
About the author
In 1986, Steven X. Ding begun with the Ph D study/investigation on model-based FDI isusses. During his three years stay in industry, he had gained experiences with the applications of FDI techniques in real technical processes. In the last 17 years, he has been, as a university professor and institute head, involved in numerous national and international research grants and industrial projects in developing advanced FDI methods and their applications in different industrial sectors. He holds a lecture on fault diagnosis and fault-tolerant systems for master students and seminars on advanced FDI methods for PhD students at the University Duisburg-Essen and gives guest lectures/courses at other universities and research institutes. He has published more than 80 journal and 130 conference papers in this thematic area.
Summary
Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and demonstrated on industrial case systems. Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems will be of interest to process and control engineers, engineering students and researchers with a control engineering background.
