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.