Solving Fault Diagnosis Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Solving Fault Diagnosis Problems write by Andreas Varga. This book was released on 2017-02-14. Solving Fault Diagnosis Problems available in PDF, EPUB and Kindle. This book addresses fault detection and isolation topics from a computational perspective. Unlike most existing literature, it bridges the gap between the existing well-developed theoretical results and the realm of reliable computational synthesis procedures. The model-based approach to fault detection and diagnosis has been the subject of ongoing research for the past few decades. While the theoretical aspects of fault diagnosis on the basis of linear models are well understood, most of the computational methods proposed for the synthesis of fault detection and isolation filters are not satisfactory from a numerical standpoint. Several features make this book unique in the fault detection literature: Solution of standard synthesis problems in the most general setting, for both continuous- and discrete-time systems, regardless of whether they are proper or not; consequently, the proposed synthesis procedures can solve a specific problem whenever a solution exists Emphasis on the best numerical algorithms to solve the synthesis problems for linear systems in generalized state-space form (also known as descriptor systems) Development of general synthesis procedures relying on new computational paradigms, such as factorization-based design based on filter updating techniques and nullspace-based synthesis Availability of a comprehensive set of free accompanying software tools for descriptor systems, which allows readers to easily implement all synthesis procedures presented in the book and ensures that all results are reproducible This book is primarily intended for researchers and advanced graduate students in the areas of fault diagnosis and fault-tolerant control. It will also appeal to mathematicians with an interest in control-oriented numerics.
Fault Diagnosis Inverse Problems: Solution with Metaheuristics
Fault Diagnosis Inverse Problems: Solution with Metaheuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fault Diagnosis Inverse Problems: Solution with Metaheuristics write by Lídice Camps Echevarría. This book was released on 2018-05-28. Fault Diagnosis Inverse Problems: Solution with Metaheuristics available in PDF, EPUB and Kindle. This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence. This methodology, known as fault diagnosis – inverse problem methodology or FD-IPM, unifies the results of several years of work of the authors in the fields of fault detection and isolation (FDI), inverse problems and optimization. The book clearly and systematically presents the main ideas, concepts and results obtained in recent years. By formulating fault diagnosis as an inverse problem, and by solving it using metaheuristics, the authors offer researchers and students a fresh, interdisciplinary perspective for problem solving in these fields. Graduate courses in engineering, applied mathematics and computing also benefit from this work.
Intelligent Problem Solving. Methodologies and Approaches
Intelligent Problem Solving. Methodologies and Approaches - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Intelligent Problem Solving. Methodologies and Approaches write by Rasiah Logananthara. This book was released on 2003-07-31. Intelligent Problem Solving. Methodologies and Approaches available in PDF, EPUB and Kindle. The focus of the papers presented in these proceedings is on employing various methodologies and approaches for solving real-life problems. Although the mechanisms that the human brain employs to solve problems are not yet completely known, we do have good insight into the functional processing performed by the human mind. On the basis of the understanding of these natural processes, scientists in the field of applied intelligence have developed multiple types of artificial processes, and have employed them successfully in solving real-life problems. The types of approaches used to solve problems are dependant on both the nature of the problem and the expected outcome. While knowledge-based systems are useful for solving problems in well-understood domains with relatively stable environments, the approach may fail when the domain knowledge is either not very well understood or changing rapidly. The techniques of data discovery through data mining will help to alleviate some problems faced by knowledge-based approaches to solving problems in such domains. Research and development in the area of artificial intelligence are influenced by opportunity, needs, and the availability of resources. The rapid advancement of Internet technology and the trend of increasing bandwidths provide an opportunity and a need for intelligent information processing, thus creating an excellent opportunity for agent-based computations and learning. Over 40% of the papers appearing in the conference proceedings focus on the area of machine learning and intelligent agents - clear evidence of growing interest in this area.
Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems
Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems write by Steven X. Ding. This book was released on 2014-04-12. Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems available in PDF, EPUB and Kindle. 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.
Model-Based Fault Diagnosis Techniques
Model-Based Fault Diagnosis Techniques - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Model-Based Fault Diagnosis Techniques write by Steven X. Ding. This book was released on 2012-12-20. Model-Based Fault Diagnosis Techniques available in PDF, EPUB and Kindle. Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: • new material on fault isolation and identification and alarm management; • extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; • addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and • enhanced discussion of residual evaluation which now deals with stochastic processes. Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.
