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Dynamic estimation and control is a fast growing and widely researched field of study that lays the foundation for a new generation of technologies that can dynamically, adaptively and automatically stabilize power systems. This book provides a comprehensive introduction to research techniques for real-time estimation and control of power systems. Dynamic Estimation and Control of Power Systems coherently and concisely explains key concepts in a step by step manner, beginning with the fundamentals and building up to the latest developments of the field. Each chapter features examples to illustrate the main ideas, and effective research tools are presented for signal processing-based estimation of the dynamic states and subsequent control, both centralized and decentralized, as well as linear and nonlinear. Detailed mathematical proofs are included for readers who desire a deeper technical understanding of the methods. This book is an ideal research reference for engineers and researchers working on monitoring and stability of modern grids, as well as postgraduate students studying these topics. It serves to deliver a clear understanding of the tools needed for estimation and control, while also acting as a basis for readers to further develop new and improved approaches in their own research. - Offers the first concise, single resource on dynamic estimation and control of power systems - Provides both an understanding of estimation and control concepts and a comparison of results - Includes detailed case-studies, including MATLAB codes, to explain and demonstrate the concepts presented
This book nds its origin in the WIDE PhD School on Networked Control Systems, which we organized in July 2009 in Siena, Italy. Having gathered experts on all the aspects of networked control systems, it was a small step to go from the summer school to the book, certainly given the enthusiasm of the lecturers at the school. We felt that a book collecting overviewson the important developmentsand open pr- lems in the eld of networked control systems could stimulate and support future research in this appealing area. Given the tremendouscurrentinterests in distributed control exploiting wired and wireless communication networks, the time seemed to be right for the book that lies now in front of you. The goal of the book is to set out the core techniques and tools that are ava- able for the modeling, analysis and design of networked control systems. Roughly speaking, the book consists of three parts. The rst part presents architectures for distributed control systems and models of wired and wireless communication n- works. In particular, in the rst chapter important technological and architectural aspects on distributed control systems are discussed. The second chapter provides insight in the behavior of communication channels in terms of delays, packet loss and information constraints leading to suitable modeling paradigms for commu- cation networks.
Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima
Control and Dynamic Systems: Advances in Theory and Applications, Volume 57: Multidisciplinary Engineering Systems: Design and Optimization Techniques and their Application deals with techniques used in the design and optimization of future engineering systems. Comprised of 11 chapters, this book covers techniques for improving product design quality in multidisciplinary systems. These techniques include decomposition techniques for synthesis process; optimization for aircraft systems; actuator and sensor placement; and robust techniques in system design and control process. Students, research workers, and practising engineers will find this book invaluable.
The Air Force's master tenet of centralized control, decentralized execution is in danger of becoming dogma. Airmen have difficulty communicating the meaning of this phrase in a joint setting. This is partially due to our limited understanding of its history and the imprecise meaning of the words involved. Furthermore, the irregular conflicts in Afghanistan and Iraq (and the ongoing service debates in the Pacific) have demonstrated the need for a deeper understanding of this master tenet to advocate effectively for airpower solutions. We must get this right, as it is critical to maximizing airpower's potential. Getting it right, however, requires moving beyond sound bites and bumper stickers.
A comprehensive overview of integrated vehicle system dynamics exploring the fundamentals and new and emerging developments This book provides a comprehensive coverage of vehicle system dynamics and control, particularly in the area of integrated vehicle dynamics control. The book consists of two parts, (1) development of individual vehicle system dynamic model and control methodology; and (2) development of integrated vehicle dynamic model and control methodology. The first part focuses on investigating vehicle system dynamics and control according to the three directions of vehicle motions, including longitudinal, vertical, and lateral. Corresponding individual control systems, e.g. Anti-lock Brake System (ABS), Active Suspension, Electric Power Steering System (EPS), are introduced and developed respectively. Particular attention is paid in the second part of the book to develop integrated vehicle dynamic control system. Integrated vehicle dynamics control system is an advanced system that coordinates all the chassis control systems and components to improve the overall vehicle performance including safety, comfort, and economy. Integrated vehicle dynamics control has been an important research topic in the area of vehicle dynamics and control over the past two decades. The research topic on integrated vehicle dynamics control is investigated comprehensively and intensively in the book through both theoretical analysis and experimental study. In this part, two types of control architectures, i.e. centralized and multi-layer, have been developed and compared to demonstrate their advantages and disadvantages. Integrated vehicle dynamics control is a hot topic in automotive research; this is one of the few books to address both theory and practice of integrated systems Comprehensively explores the research area of integrated vehicle dynamics and control through both theoretical analysis and experimental study Addresses a full range of vehicle system topics including tyre dynamics, chassis systems, control architecture, 4 wheel steering system and design of control systems using Linear Matrix Inequality (LMI) Method
The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamics. The book includes numerous references to the most recent literature. Many methods are illustrated by numerical examples or experimental results.
Decentralized Control of Complex Systems
Control and Dynamic Systems: Advances in Theory and Application, Volume 23: Decentralized/Distributed Control and Dynamic Systems, Part 2 of 3 is a second volume of a trilogy that deals with the advances in techniques for the analysis and synthesis of decentralized or distributed control and dynamic systems. It includes chapters on techniques dealing with complex computational issues in decentralized control systems. This book discusses the time allocation of time-critical resources of decentralized but coordinated systems. It also deals with issues of reliable or robust decentralized control systems, model reduction for large-scale systems, and linear quadratic control problem. This book ends with powerful techniques for solving problems in decentralized control systems. Many practitioners will find this text useful because of its various complex real-world applications.
This book is about Computer Aided Control System Design (CACSD) of the direct process controller. Various methods and tools, representing an up-to-date level of development, are presented by leading experts. Several articles describe main principles and problems associated with modern direct control and with CACSD. Existing tools are presented, including packages for stability analysis of nonlinear systems, adaptive control design and integrated analysis, and simulation and tuning of controllers. The reader can observe that it is possible to develop CACSD tools by using open general packages such as Matlab or Simulab, or by providing specialised software. He can then compare both approaches and get an improved understanding of their respective advantages and disadvantages. The leading article by the editors presents CACSD Methods and tools in a broader context. There is also detailed material on upper control layers, hierarchical control, and real-time systems.