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Hybrid systems. --- System theory --- Dynamic systems, Hybrid --- Hybrid dynamic systems
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Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- System theory
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This book focuses on the observability of hybrid systems. It enables the reader to determine whether and how a hybrid system's state can be reconstructed from sometimes necessarily partial information. By explaining how available measurements can be used to deduce past and future behaviours of a system, the authors extend this study of observability to embrace the properties of diagnosability and predictability.H-systemsshows how continuous and discrete dynamics and their interaction affect the observability of this general class of hybrid systems and demonstrates that hybrid characteristics are not simply generalizations of well-known aspects of traditional dynamics. The authors identify conditions for state reconstruction, prediction and diagnosis of the occurrence of possibly faulty states. The formal approach to proving those properties for hybrid systems is accompanied by simple illustrative examples. For readers who are interested in the use of state estimation for controller design, the book also provides design methods for hybrid state observers and covers their application in some industrial cases.The book's tutorial approach to the various forms of observability of hybrid systems helps to make H-systemsof interest to academic researchers and graduate students working in control and to practitioners using control in an industrial environment.
Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- System theory
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Setting out core theory and reviewing a range of new methods, theoretical problems and applications, this handbook shows how hybrid dynamical systems can be modelled and understood. Sixty expert authors involved in the recent research activities and industrial application studies provide practical insights on topics ranging from the theoretical investigations over computer-aided design to applications in energy management and the process industry. Structured into three parts, the book opens with a thorough introduction to hybrid systems theory, illustrating new dynamical phenomena through numerous examples. Part II then provides a survey of key tools and tool integration activities. Finally, Part III is dedicated to applications, implementation issues and system integration, considering different domains such as industrial control, automotive systems and digital networks. Three running examples are referred to throughout the book, together with numerous illustrations, helping both researchers and industry professionals to understand complex theory, recognise problems and find appropriate solutions.
System theory --- Hybrid systems --- Control theory --- Systems, Theory of --- Systems science --- Science --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- Dynamics --- Machine theory --- Philosophy --- System theory. --- Hybrid systems. --- Control theory.
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This book presents recent research work on stochastic jump hybrid systems. Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems. Some sufficient conditions are first established respectively for the stability and performances of those kinds of stochastic jump hybrid systems in terms of solution of linear matrix inequalities (LMIs). Based on the derived analysis conditions, the filtering and control problems are addressed. The book presents up-to-date research developments and novel methodologies on stochastic jump hybrid systems. The contents can be divided into two parts: the first part is focused on robust filter design problem, while the second part is put the emphasis on robust control problem. These methodologies provide a framework for stability and performance analysis, robust controller design, and robust filter design for the considered systems. Solutions to the design problems are presented in terms of LMIs. The book is a timely reflection of the developing area of filtering and control theories for Markovian jump hybrid systems with various kinds of imperfect information. It is a collection of a series of latest research results and therefore serves as a useful textbook for senior and/or graduate students who are interested in knowing 1) the state-of-the-art of linear filtering and control areas, and 2) recent advances in stochastic jump hybrid systems. The readers will also benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.
Mechanical Engineering - General --- Mechanical Engineering --- Engineering & Applied Sciences --- Jump processes. --- Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- Processes, Jump --- System theory --- Markov processes --- Systems theory. --- Control and Systems Theory. --- Systems Theory, Control. --- Control engineering. --- System theory. --- Systems, Theory of --- Systems science --- Science --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Philosophy
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Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview of the interaction between system identification, machine learning and pattern recognition fields in explaining and analysing hybrid system identification. It emphasises the optimization and computational complexity issues that lie at the core of the problems considered and sets them aside from standard system identification problems. The book presents practical methods that leverage this complexity, as well as a broad view of state-of-the-art machine learning methods. The authors illustrate the key technical points using examples and figures to help the reader understand the material. The book includes an in-depth discussion and computational analysis of hybrid system identification problems, moving from the basic questions of the definition of hybrid systems and system identification to methods of hybrid system identification and the estimation of switched linear/affine and piecewise affine models. The authors also give an overview of the various applications of hybrid systems, discuss the connections to other fields, and describe more advanced material on recursive, state-space and nonlinear hybrid system identification. Hybrid System Identification includes a detailed exposition of major methods, which allows researchers and practitioners to acquaint themselves rapidly with state-of-the-art tools. The book is also a sound basis for graduate and undergraduate students studying this area of control, as the presentation and form of the book provides the background and coverage necessary for a full understanding of hybrid system identification, whether the reader is initially familiar with system identification related to hybrid systems or not.
Systems theory. --- Computer network architectures. --- Control and Systems Theory. --- Systems Theory, Control. --- Computer System Implementation. --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- System theory --- Control engineering. --- System theory. --- Architecture, Computer. --- Architecture, Computer --- Systems, Theory of --- Systems science --- Science --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Philosophy
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Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then treats issues representing the different faces of SRA: · stochastic reachability based on Markov process theory; · martingale methods; · stochastic reachability as an optimal stopping problem; and · dynamic programming. The book is rounded off by an appendix providing mathematical underpinning on subjects such as ordinary differential equations, probabilistic measure theory and stochastic modeling, which will help the non-expert-mathematician to appreciate the text. Stochastic Reachability Analysis of Hybrid Systems characterizes a highly interdisciplinary area of research and is consequently of significant interest to academic researchers and graduate students from a variety of backgrounds in control engineering, applied mathematics and computer science.
Hybrid systems. --- Hybrid systems --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Computer Science --- Operations Research --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- Mathematics. --- Computer science --- System theory. --- Control engineering. --- Systems Theory, Control. --- Control. --- Math Applications in Computer Science. --- System theory --- Systems theory. --- Computer science. --- Control and Systems Theory. --- Informatics --- Science --- Computer science—Mathematics. --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Systems, Theory of --- Systems science --- Philosophy
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This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.
Artificial intelligence. --- Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Engineering. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Construction --- Industrial arts --- Technology --- Artificial Intelligence. --- System theory --- Knowledge representation (Information theory)
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This book is the first to present the application of the hybrid system theory to systems with EPCA (equations with piecewise continuous arguments). The hybrid system paradigm is a valuable modeling tool for describing a wide range of real-world applications. Moreover, although new technology has produced, and continues to produce highly hierarchical sophisticated machinery that cannot be analyzed as a whole system, hybrid system representation can be used to reduce the structural complexity of these systems. That is to say, hybrid systems have become a modeling priority, which in turn has led to the creation of a promising research field with several application areas. As such, the book explores recent developments in the area of deterministic and stochastic hybrid systems using the Lyapunov and Razumikhin–Lyapunov methods to investigate the systems’ properties. It also describes properties such as stability, stabilization, reliable control, H-infinity optimal control, input-to-state stability (ISS)/stabilization, state estimation, and large-scale singularly perturbed systems.
Hybrid systems. --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- System theory --- Systems theory. --- Mathematical physics. --- Statistical physics. --- Control and Systems Theory. --- Systems Theory, Control. --- Applications of Nonlinear Dynamics and Chaos Theory. --- Mathematical Methods in Physics. --- Statistical Physics and Dynamical Systems. --- Mathematical Physics. --- Physics --- Mathematical statistics --- Physical mathematics --- Statistical methods --- Mathematics --- Control engineering. --- System theory. --- Physics. --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Systems, Theory of --- Systems science --- Science --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Philosophy
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This book describes recent advances on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There are also some papers that present theory and practice of meta-heuristics in different areas of application. Another group of papers describes diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition problems.
Computational intelligence. --- Artificial intelligence. --- Computational Intelligence. --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Hybrid systems. --- Fuzzy logic. --- Industrial applications. --- Nonlinear logic --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems --- Cognitive computing --- Computational intelligence --- Dynamic systems, Hybrid --- Hybrid dynamic systems --- System theory
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