Control Over Communication Networks

Control over Communication Networks Advanced and systematic examination of the design and analysis of networked control systems and multi-agent systems Control Over Communication Networks provides a systematic and nearly self-contained description of the analysis and design of networked control systems (NCSs) and multi-agent systems (MASs) over imperfect communication networks, with a primary focus on fading channels and delayed channels. The text characterizes the effect of communication channels on the stability and performance of NCSs, and further studies the joint impact of communication channels and network topology on the consensus of MASs. By integrating communication and control theory, the four highly-qualified authors present fundamental results concerning the stabilization of NCSs over power-constrained fading channels and Gaussian finite-state Markov channels, linear-quadratic optimal control of NCSs with random input gains, optimal state estimation with intermittent observations, consensus of MASs with communication delay and packet dropouts, and synchronization of delayed Vicsek models. Simulation results are given in each chapter to demonstrate the developed analysis and synthesis approaches. The references are comprehensive and up-to-date, enabling further study for readers. Topics covered in Control Over Communication Networks include: Basic foundational knowledge, including control theory, communication theory, and graph theory, to enable readers to understand more complex topics The stabilization, optimal control, and remote state estimation problems of linear systems over channels with fading, signal-to-noise constraints, or intermittent measurements Consensus problems of MASs over fading/delayed channels, with directed and undirected communication graphs Control Over Communication Networks provides a valuable unified platform for understanding the analysis and design of NCSs and MASs for researchers, control engineers working on control systems over communication networks, and mechanical engineers working on unmanned systems. Preliminary knowledge of linear system theory and matrix analysis is required.

This book presents a systematic theory of estimation and control over communication networks. It develops a theory that utilizes communications, control, information and dynamical systems theory motivated and applied to advanced networking scenarios. The book establishes theoretically rich and practically important connections among modern control theory, Shannon information theory, and entropy theory of dynamical systems originated in the work of Kolmogorov. This self-contained monograph covers the latest achievements in the area. It contains many real-world applications and the presentation is accessible.

This book presents a systematic theory of estimation and control over communication networks. It develops a theory that utilizes communications, control, information and dynamical systems theory motivated and applied to advanced networking scenarios. The book establishes theoretically rich and practically important connections among modern control theory, Shannon information theory, and entropy theory of dynamical systems originated in the work of Kolmogorov. This self-contained monograph covers the latest achievements in the area. It contains many real-world applications and the presentation is accessible.

This informative text/reference presents a detailed review of the state of the art in industrial sensor and control networks. The book examines a broad range of applications, along with their design objectives and technical challenges. The coverage includes fieldbus technologies, wireless communication technologies, network architectures, and resource management and optimization for industrial networks. Discussions are also provided on industrial communication standards for both wired and wireless technologies, as well as for the Industrial Internet of Things (IIoT). Topics and features: describes the FlexRay, CAN, and Modbus fieldbus protocols for industrial control networks, as well as the MIL-STD-1553 standard; proposes a dual fieldbus approach, incorporating both CAN and ModBus fieldbus technologies, for a ship engine distributed control system; reviews a range of industrial wireless sensor network (IWSN) applications, from environmental sensing and condition monitoring, to process automation; examines the wireless networking performance, design requirements, and technical limitations of IWSN applications; presents a survey of IWSN commercial solutions and service providers, and summarizes the emerging trends in this area; discusses the latest technologies and open challenges in realizing the vision of the IIoT, highlighting various applications of the IIoT in industrial domains; introduces a logistics paradigm for adopting IIoT technology on the Physical Internet. This unique work will be of great value to all researchers involved in industrial sensor and control networks, wireless networking, and the Internet of Things.

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.

In modern communication networks with stored program control the implementation of sophisticated traffic control rules is worthwhile. This allows efficient sharing of existing resources and often defers network extension. Moreover, the flexible control adapts well to changing load conditions during periods of overload and equipment failure. When these benefits become evident, many network administrations start to implement corresponding solutions. This book attempts to provide a systematic approach to the analysis and synthesis of advanced traffic control concepts. Because the book is oriented toward engineering applications, mathematical concepts are often illustrated with examples. The reader is assumed to be familiar with advanced calculus, differential equations and probability theory to engineering level.

A modern mathematical approach to the design of communication networks for graduate students, blending control, optimization, and stochastic network theories alongside a broad range of performance analysis tools. Practical applications are illustrated by making connections to network algorithms and protocols. End-of-chapter problems covering a range of difficulties support student learning.

COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.