This book contains a collection of 13 carefully selected papers contributed by researches in technical and partial medical diagnostics as well as fault-tolerant control and constitutes a comprehensive study of the field. Nowadays technical diagnostics and fault-tolerant control are a field of intensive scientific research that covers well-established topics along with emerging developments in control engineering, artificial intelligence, applied mathematics and statistics. At the same time, a growing number of applications of different fault diagnosis methods, especially in the electrical, mechanical, chemical and medical areas, are being observed. The aim of the book is to show the bridge between technical and medical diagnosis based on analytical and artificial intelligence methods and techniques. The book is divided into three parts: I. Fault-Tolerant Control and Reconfiguration, II. Fault Diagnosis of Processes and Systems, III. Medical Applications. The book is of interest to scientists, engineers and academics dealing with the problems of designing technical diagnosis and fault-tolerant control systems. Its target readers are also junior researchers and students of control, artificial intelligence and computer engineering.

This book contains a collection of 13 carefully selected papers contributed by researches in technical and partial medical diagnostics as well as fault-tolerant control and constitutes a comprehensive study of the field. Nowadays technical diagnostics and fault-tolerant control are a field of intensive scientific research that covers well-established topics along with emerging developments in control engineering, artificial intelligence, applied mathematics and statistics. At the same time, a growing number of applications of different fault diagnosis methods, especially in the electrical, mechanical, chemical and medical areas, are being observed. The aim of the book is to show the bridge between technical and medical diagnosis based on analytical and artificial intelligence methods and techniques. The book is divided into three parts: I. Fault-Tolerant Control and Reconfiguration, II. Fault Diagnosis of Processes and Systems, III. Medical Applications. The book is of interest to scientists, engineers and academics dealing with the problems of designing technical diagnosis and fault-tolerant control systems. Its target readers are also junior researchers and students of control, artificial intelligence and computer engineering.

This book gathers 30 papers presented at the 21st PCBBE, which was hosted by the University of Zielona Gora, Poland, and offered a valuable forum for exchanging ideas and presenting the latest developments in all areas of biomedical engineering. Biocybernetics and biomedical engineering are currently considered one of the most promising ways to improve health care and, consequently, the quality of life. Innovative technical solutions can better meet physicians' needs and stimulate the development of medical diagnostics and therapy. We are currently witnessing a profound change in the role of medicine, which is becoming ubiquitous in everyday life thanks to technological advances. Further, the development of civilization manifests itself in efforts to unlock the secrets of the human body, and to mimic biological systems in engineering. The biannual Polish Conference on Biocybernetics and Biomedical Engineering (PCBBE) has been held for nearly four decades and has attracted scientists and professionals in the fields of engineering, medicine, physics, and computer science. Gathering the outcomes of this conference, the book introduces the reader to recent developments and achievements in biocybernetics and biomedical engineering.

Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.

An unappealing characteristic of all real-world systems is the fact that they are vulnerable to faults, malfunctions and, more generally, unexpected modes of - haviour. This explains why there is a continuous need for reliable and universal monitoring systems based on suitable and e?ective fault diagnosis strategies. This is especially true for engineering systems, whose complexity is permanently growing due to the inevitable development of modern industry as well as the information and communication technology revolution. Indeed, the design and operation of engineering systems require an increased attention with respect to availability, reliability, safety and fault tolerance. Thus, it is natural that fault diagnosis plays a fundamental role in modern control theory and practice. This is re?ected in plenty of papers on fault diagnosis in many control-oriented c- ferencesand journals.Indeed, a largeamount of knowledgeon model basedfault diagnosis has been accumulated through scienti?c literature since the beginning of the 1970s. As a result, a wide spectrum of fault diagnosis techniques have been developed. A major category of fault diagnosis techniques is the model based one, where an analytical model of the plant to be monitored is assumed to be available