Foreword [to Robust and Fault-Tolerant Control. Neural-Network-Based Solutions]

This monograph aims at presenting some novel ideas, concepts and results in robust fault tolerant control. The rapid development of control technology has an impact on all areas of the control discipline: new theory, advanced control solutions, new industrial processes, computer methods and implementations, new applications, new philosophies, and new challenges. Much of this development work resides in industrial reports, feasibility study papers and reports of advanced collaborative projects. Therefore, this monograph offers an opportunity for researchers, practitioners and students to have an extended and clear exposition of new investigations in all aspects of robust fault tolerant control for wider and rapid dissemination. As many technological systems become more complex, widespread and integrated, the effects of system faults can be simply devastating to the infrastructure of modem society. Feedback control is just one important component of total system supervision. Fault tolerant control represents further components with extensive commercial, industrial and societal implications if only we could work out how to do it in a robust and inexpensive manner. The model-based approach is the usual solution of the practical fault tolerant control design, but as the author Krzysztof Patan has highlighted in this monograph, neural network based methodologies can be successfully exploited. The search for reliable, robust and inexpensive fault tolerant control methods has been active since the early 1980s. Since 1991, the International Federation of Automatic Control (IFAC) has created the SAFEPROCESS Steering Committee to promote research, developments and applications in the fault tolerant control field. The last decade has seen the formalisation of several theoretical approaches accompanied by some attempts to standardise nomenclature in the field. The related literature does not have many entries from this important research area, even if several monographs can represent interesting contributions on fault tolerant control, even if they use quite different ideas and principles. To these we can now add this monograph by Krzysztof Patan. Key features of this text include useful survey material, new approaches based on data-driven and neural network based methodologies, as well as application studies that help to understand advantages and drawbacks of the suggested strategies and tools. Different groups of readers ranging from industrial engineers wishing to gain insight into the applications potential of new fault tolerant control methods relying on artificial intelligence tools, to the academic control community looking for new problems to tackle will find much to learn from this monograph.