A discussion of robust control and filtering for time-delay systems. It provides information on approaches to stability, stabilization, control design, and filtering aspects of electronic and computer systems - explicating the developments in time-delay systems and uncertain time-delay systems. There are appendices detailing important facets of matrix theory, standard lemmas and mathematical results, and applications of industry-tested software.

Based on the many approaches available for dealing with large-scale systems (LSS), Decentralized Control and Filtering in Interconnected Dynamical Systems supplies a rigorous framework for studying the analysis, stability, and control problems of LSS. Providing an overall assessment of LSS theories, it addresses model order reduction, parametric uncertainties, time delays, and control estimator gain perturbations. Taking readers on a guided tour through LSS, the book examines recent trends and approaches and reviews past methods and results from a contemporary perspective. It traces the progress of research along three eras: Fundamental era in which the basic conceptual frameworks, major ideas, and operational methodologies are laid down Contemporary era in which several of the workable methods and techniques are established and applied to many application areas Advanced era in which different high-level schemes and configurations are being developed to meet accelerated technological advancements Focusing on robust, reliable, and/or resilient decentralized design methods based on linear matrix inequalities framework, the author offers suggestions for improvements to current approaches. He addresses the dominating sources of difficulties due to dimensionality, information structure constraints, uncertainties, and time delays. Drawing attention to key issues, the text is supported by proofs, efficient computational methods, end-of-chapter problems, and approximately 1,300 equations.

Based on the many approaches available for dealing with large-scale systems (LSS), Decentralized Control and Filtering in Interconnected Dynamical Systems supplies a rigorous framework for studying the analysis, stability, and control problems of LSS. Providing an overall assessment of LSS theories, it addresses model order reduction, parametric uncertainties, time delays, and control estimator gain perturbations. Taking readers on a guided tour through LSS, the book examines recent trends and approaches and reviews past methods and results from a contemporary perspective. It traces the progress of research along three eras: 1. Fundamental era in which the basic conceptual frameworks, major ideas, and operational methodologies are laid down 2. Contemporary era in which several of the workable methods and techniques are established and applied to many application areas 3. Advanced era in which different high-level schemes and configurations are being developed to meet accelerated technological advancements Focusing on robust, reliable, and/or resilient decentralized design methods based on linear matrix inequalities framework, the author offers suggestions for improvements to current approaches. He addresses the dominating sources of difficulties due to dimensionality, information structure constraints, uncertainties, and time delays. Drawing attention to key issues, the text is supported by proofs, efficient computational methods, end-of-chapter problems, and approximately 1,300 equations.

By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. Networked Filtering and Fusion in Wireless Sensor Networks introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems. The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies. Complete with research supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs. The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help you broaden your understanding of prospective applications and how to address such problems in practice. After reading the book, you will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.

By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. Networked Filtering and Fusion in Wireless Sensor Networks introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems. The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies. Complete with research supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs. The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help you broaden your understanding of prospective applications and how to address such problems in practice. After reading the book, you will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.

This up-to-the-minute reference/text provides vital information on new approaches to stability, stabilization, control design, and filtering of electronics and computer systems-explicating the latest developments in time-delay systems (TDS) and uncertain time-delay systems (UTDS). Features helpful appendices detailing important facets of matrix theory, standard lemmas and mathematical results, and applications of industry-tested software Utilizing mathematical formality to foster intuitive understanding, Robust Control and Filtering for Time-Delay Systems discusses finite capabilities of data processing and transmission throughout systems analyzes inherent physical phenomena and computational delays impacting system performance showcases the state-space approach in systems representation and analysis defines and delineates concepts of robustness, robust performance, and robust design highlights linear and many classes of nonlinear system theory, matrix theory, and modern control theory describes delays as constant or time-varying, known or unknown, deterministic or stochastic assesses continuous-time and discrete-time systems independently and in relation to each other elucidates stability analysis and control synthesis supplies unification of results on control design and filtering and more Containing over 300 bibliographic citations and more than 1500 equations, Robust Control and Filtering for Time-Delay Systems is a must-read reference for electrical, electronics, computer, and control engineers, and an exceptional text for upper-level undergraduate and graduate students in these disciplines.

Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value. It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.

This book offers a transdisciplinary perspective on the concept of "smart villages" Written by an authoritative group of scholars, it discusses various aspects that are essential to fostering the development of successful smart villages. Presenting cutting-edge technologies, such as big data and the Internet-of-Things, and showing how they have been successfully applied to promote rural development, it also addresses important policy and sustainability issues. As such, this book offers a timely snapshot of the state-of-the-art in smart village research and practice.

This book offers a transdisciplinary perspective on the concept of "smart villages" Written by an authoritative group of scholars, it discusses various aspects that are essential to fostering the development of successful smart villages. Presenting cutting-edge technologies, such as big data and the Internet-of-Things, and showing how they have been successfully applied to promote rural development, it also addresses important policy and sustainability issues. As such, this book offers a timely snapshot of the state-of-the-art in smart village research and practice.

This textbook explains the principles of fuzzy systems in some depth together with information useful in realizing them within computational processes. The various algorithms and example problem solutions are a well-balanced and pertinent aid for research projects, laboratory work and graduate study. In addition to its worked examples, the book also uses end-of-chapter exercises as an instructional aid. The content of the book is developed and extended from material taught for four years in the author's classes. The text provides a broad overview of fuzzy control, estimation and fault diagnosis. It ranges over various classes of target system and modes of control and then turns to filtering, stabilization, and fault detection and diagnosis. Applications, simulation tools and an appendix on algebraic inequalities complete a unified approach to the analysis of single and interconnected fuzzy systems. Fuzzy Control, Estimation and Fault Detection is a guide for final-year undergraduate and graduate students of electrical and mechanical engineering, computer science and information technology, and will also be instructive for professionals in the information technology sector.

In an uncertain and complex environment, to ensure secure and stable operations of large-scale power systems is one of the biggest challenges that power engineers have to address today. Traditionally, power system operations and decision-making in controls are based on power system computations of physical models describing the behavior of power systems. Largely, physical models are constructed according to some assumptions and simplifications, and such is the case with power system models. However, the complexity of power system stability problems, along with the system's inherent uncertainties and nonlinearities, can result in models that are impractical or inaccurate. This calls for adaptive or deep-learning algorithms to significantly improve current control schemes that solve decision and control problems. Cyberphysical Infrastructures in Power Systems: Architectures and Vulnerabilities provides an extensive overview of CPS concepts and infrastructures in power systems with a focus on the current state-of-the-art research in this field. Detailed classifications are pursued highlighting existing solutions, problems, and developments in this area.

This text is an introduction to the use of control in distributed power generation. It shows the reader how reliable control can be achieved so as to realize the potential of small networks of diverse energy sources, either singly or in coordination, for meeting concerns of energy cost, energy security and environmental protection. The book demonstrates how such microgrids, interconnecting groups of generating units and loads within a local area, can be an effective means of balancing electrical supply and demand. It takes advantage of the ability to connect and disconnect microgrids from the main body of the power grid to give flexibility in response to special events, planned or unplanned. In order to capture the main opportunities for expanding the power grid and to present the plethora of associated open problems in control theory Control and Optimization of Distributed Generation Systems is organized to treat three key themes, namely: system architecture and integration; modelling and analysis; and communications and control. Each chapter makes use of examples and simulations and appropriate problems to help the reader study. Tools helpful to the reader in accessing the mathematical analysis presented within the main body of the book are given in an appendix. Control and Optimization of Distributed Generation Systems will enable readers new to the field of distributed power generation and networked control, whether experienced academic migrating from another field or graduate student beginning a research career, to familiarize themselves with the important points of the control and regulation of microgrids. It will also be useful for practising power engineers wishing to keep abreast of changes in power grids necessitated by the diversification of generating methods.

In many practical applications we deal with a wide class of dynamical systems that are comprised of a family of continuous-time or discrete-time subsystems and a rule orchestrating the switching between the subsystems. This class of systems is frequently called switched system. Switched linear systems provide a framework that bridges the linear systems and the complex and/or uncertain systems. The mo- vation for investigating this class of systems is twofold: ?rst, it has an inherent multi-modal behavior in the sense that several dynamical subsystems are required to describe their behavior, which might depend on various environmental factors. Second, the methods of intelligent control systems are based on the idea of swit- ing between different controllers. Looked at in this light, switched systems provide an integral framework to deal with complex system behaviors such as chaos and multiple limit cycles and gain more insights into powerful tools such as intelligent control, adaptive control, and robust control. Switched systems have been inves- gated for a long time in the control and systems literature and have increasingly attracted more attention for the past three decades. The number of journal articles, books, and conference papers have grown exponentially and a number of fundam- tal concepts and powerful tools have been developed. It has been pointed out that switched systems have been studied from various viewpoints.

Decentralized Control and Filtering provides a rigorous framework for examining the analysis, stability and control of large-scale systems, addressing the difficulties that arise because dimensionality, information structure constraints, parametric uncertainty and time-delays. This monograph serves three purposes: it reviews past methods and results from a contemporary perspective; it examines presents trends and approaches and to provide future possibilities; and it investigates robust, reliable and/or resilient decentralized design methods based on a framework of linear matrix inequalities. As well as providing an overview of large-scale systems theories from the past several decades, the author presents key modern concepts and efficient computational methods. Representative numerical examples, end-of-chapter problems, and typical system applications are included, and theoretical developments and practical applications of large-scale dynamical systems are discussed in depth.

This book provides a rigorous framework in which to study problems in the analysis, stability and design of networked control systems. Four dominant sources of difficulty are considered: packet dropouts, communication bandwidth constraints, parametric uncertainty, and time delays. Past methods and results are reviewed from a contemporary perspective, present trends are examined, and future possibilities proposed. Emphasis is placed on robust and reliable design methods. New control strategies for improving the efficiency of sensor data processing and reducing associated time delay are presented. The coverage provided features: * an overall assessment of recent and current fault-tolerant control algorithms; * treatment of several issues arising at the junction of control and communications; * key concepts followed by their proofs and efficient computational methods for their implementation; and * simulation examples (including TrueTime simulations) to provide hands-on experience. In addition to the theoretical coverage, the author describes a number of applications that demonstrate the real-world relevance of this material, and these include: * a servo system; * a triple inverted pendulum; * power system control; * wireless control of a cart with inverted pendulum and wireless servo application with emphasis on controller area networks; and * switched ethernet and wireless area networks. Researchers and graduate students working in networked and distributed control will find this text a useful guide in avoiding and ameliorating common and serious problems with these systems. The increasing prevalence of networks in many fields of engineering will make Control and Estimation Methods over Communication Networks of interest to practitioners with backgrounds in communications, process engineering, robotics, power, automotive and other areas.

Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers' assimilation of the material discussed is assisted by the provision of problems and examples. Most of these exercises use MATLAB (R) to make computation and visualization more straightforward. Applied Control System Design will be of interest to academic researchers for its comparison of different systems models and their response to different control methods and will assist graduate students in learning the practical necessities of advanced control system design. The consistent reference to real systems coupled with self-learning tools will assist control practitioners who wish to keep up to date with the latest control design ideas.

More and more digital devices are being used for informa tion processing and control purposes in a variety of systems applications, including industrial processes, power networks, biological systems and communication networks. This trend has been helped by the advent of microprocessors and the consequent availability of cheap distributed computing power. For those applications, where digital devices are used, it is reasonable to model the system in discrete-time. In addition there are other application areas, e.g. econometric systems, business systems, certain command and control systems, environmental systems, where the underlying models are in discrete-time and here discrete-time approaches to analysis and control are the most appropriate. In order to deal with these two situations, there has been a lot of interest in developing techLiques which allow us to do analysis, design and control of discrete-time systems. This book provides a comprehensive treatment of discrete time dynamical systems. It covers the topics of modelling, optimization techniques and control design. The book is designed to serve as a text for teaching at the first year graduate level. The material included is organized into eight chapters."

This book is about time-domain modelling, stability, stabilization, control design and filtering for JTDS. It gives readers a thorough understanding of the basic mathematical analysis and fundamentals, offers a straightforward treatment of the different topics and provides broad coverage of the recent methodologies.

Decentralized Control and Filtering provides a rigorous framework for examining the analysis, stability and control of large-scale systems, addressing the difficulties that arise because dimensionality, information structure constraints, parametric uncertainty and time-delays.This monograph serves three purposes: it reviews past methods and results from a contemporary perspective; it examines presents trends and approaches and to provide future possibilities; and it investigates robust, reliable and/or resilient decentralized design methods based on a framework of linear matrix inequalities. As well as providing an overview of large-scale systems theories from the past several decades, the author presents key modern concepts and efficient computational methods. Representative numerical examples, end-of-chapter problems, and typical system applications are included, and theoretical developments and practical applications of large-scale dynamical systems are discussed in depth.

This monograph provides a complete description of resilient control theory. It unifies the methods for developing resilient controllers and filters for a class of uncertain dynamical systems and reports recent advances in design methodologies. The book presents an introductory and comprehensive treatment of resilient controller design methods placing great emphasis on the derivation of necessary and sufficient design conditions and on the use of linear matrix inequalities as a convenient computational tool. The book can be used as a graduate-level textbook in control engineering or applied mathematics as well as a reference for practicing engineers, researchers and students.

The main objective of this monograph is to develop efficient techniques for tackling the control problems of partially-known dynamical systems. This broad class of systems has a fundamental feature: Knowledge of the dynamic characteristics of the control plant is not complete. In one category, the missing knowledge is due to the unmodeled high-frequency parasitics (adaptive systems). In another category, some of the model parameters are unknown-but-bounded (uncertain systems). The book concentrates on reduced-order adaptive control schemes and deterministic stabilizing control methodologies. Special emphasis has been placed on presenting new results, establishing efficient control laws and treating both small-scale and large-scale problems. Effects of external disturbances, state parameter errors and interconnection patterns have been investigated and dealt with in contructing various controller structures.

Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs.

This textbook explains the principles of fuzzy systems in some depth together with information useful in realizing them within computational processes. The various algorithms and example problem solutions are a well-balanced and pertinent aid for research projects, laboratory work and graduate study. In addition to its worked examples, the book also uses end-of-chapter exercises as an instructional aid. The content of the book is developed and extended from material taught for four years in the author's classes. The text provides a broad overview of fuzzy control, estimation and fault diagnosis. It ranges over various classes of target system and modes of control and then turns to filtering, stabilization, and fault detection and diagnosis. Applications, simulation tools and an appendix on algebraic inequalities complete a unified approach to the analysis of single and interconnected fuzzy systems. Fuzzy Control, Estimation and Fault Detection is a guide for final-year undergraduate and graduate students of electrical and mechanical engineering, computer science and information technology, and will also be instructive for professionals in the information technology sector.

In many practical applications we deal with a wide class of dynamical systems that are comprised of a family of continuous-time or discrete-time subsystems and a rule orchestrating the switching between the subsystems. This class of systems is frequently called switched system. Switched linear systems provide a framework that bridges the linear systems and the complex and/or uncertain systems. The mo- vation for investigating this class of systems is twofold: ?rst, it has an inherent multi-modal behavior in the sense that several dynamical subsystems are required to describe their behavior, which might depend on various environmental factors. Second, the methods of intelligent control systems are based on the idea of swit- ing between different controllers. Looked at in this light, switched systems provide an integral framework to deal with complex system behaviors such as chaos and multiple limit cycles and gain more insights into powerful tools such as intelligent control, adaptive control, and robust control. Switched systems have been inves- gated for a long time in the control and systems literature and have increasingly attracted more attention for the past three decades. The number of journal articles, books, and conference papers have grown exponentially and a number of fundam- tal concepts and powerful tools have been developed. It has been pointed out that switched systems have been studied from various viewpoints.

New Trends in Observer-Based Control: A Practical Guide to Process and Engineering Applications presents a concise introduction to the latest advances in observer-based control design. The book gives a comprehensive tutorial on new trends in the design of observer-based controllers for which the separation principle is well established. It covers a wide range of applications, also including worked examples that make it ideal for both advanced courses and researchers starting work in the field. This book is also particularly suitable for engineers who want to quickly and efficiently enter the field.