Event-Based State Estimation
Event-Based State Estimation

Author: Dawei Shi

Publisher: Springer

Published: 2015-11-19

Total Pages: 215

ISBN-13: 3319266063

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This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.

Event-Trigger Dynamic State Estimation for Practical WAMS Applications in Smart Grid
Event-Trigger Dynamic State Estimation for Practical WAMS Applications in Smart Grid

Author: Zhen Li

Publisher: Springer Nature

Published: 2020-06-03

Total Pages: 294

ISBN-13: 3030456587

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This book describes how dynamic state estimation application in wide-area measurement systems (WAMS) are crucial for power system reliability, to acquire precisely power system dynamics. The event trigger DSE techniques described by the authors provide a design balance between the communication rate and estimation performance, by selectively sending the innovational data. The discussion also includes practical problems for smart grid applications, such as the non-Gaussian process/measurement noise, packet dropout, computation burden of accurate DSE, robustness to the system variation, etc. Readers will learn how the event trigger DSE can facilitate the effective reduction of communication rates, with guaranteed accuracy under a variety of practical conditions in smart grid applications.

Event-based state-feedback control of physically interconnected systems
Event-based state-feedback control of physically interconnected systems

Author: Christian Stöcker

Publisher: Logos Verlag Berlin GmbH

Published: 2014

Total Pages: 228

ISBN-13: 3832536825

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Event-based control is a means to restrict the feedback in control loops to event time instants that are determined by a well-defined triggering mechanism. The aim of this control strategy is to adapt the communication over the feedback link to the system behavior. In this thesis, a state-feedback approach to event-based control is extended to systems that are composed of physically interconnected subsystems. The main concern of this thesis is disturbance rejection in interconnected systems, which is supposed to be best accomplished by a continuous state feedback. This consideration leads to the idea that the event-based state-feedback system should approximate the disturbance rejection behavior of a continuous state-feedback system with adjustable precision. Various methods for the event-based control of physically interconnected systems are investigated. In particular, decentralized, distributed and centralized state feedback is studied, which differ with respect to the effort for the communication between the components of the event-based controller over the communication network. The main results concern the design and analysis of event-based state-feedback control methods for physically interconnected systems. For all approaches the disturbance behavior of a continuous state-feedback system is shown to be approximated with adjustable accuracy by the event-based state-feedback system. The novel event-based control methods are tested and evaluated in experiments on a continuous flow process implemented on a large-scale pilot plant.

State Estimation and Fault Diagnosis under Imperfect Measurements
State Estimation and Fault Diagnosis under Imperfect Measurements

Author: Yang Liu

Publisher: CRC Press

Published: 2022-08-31

Total Pages: 223

ISBN-13: 1000641066

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The objective of this book is to present the up-to-date research developments and novel methodologies on state estimation and fault diagnosis (FD) techniques for a class of complex systems subject to closed-loop control, nonlinearities, and stochastic phenomena. It covers state estimation design methodologies and FD unit design methodologies including framework of optimal filter and FD unit design, robust filter and FD unit design, stability, and performance analysis for the considered systems subject to various kinds of complex factors. Features: Reviews latest research results on the state estimation and fault diagnosis issues. Presents comprehensive framework constituted for systems under imperfect measurements. Includes quantitative performance analyses to solve problems in practical situations. Provides simulation examples extracted from practical engineering scenarios. Discusses proper and novel techniques such as the Carleman approximation and completing the square method is employed to solve the mathematical problems. This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement.

Event-Based Control and Signal Processing
Event-Based Control and Signal Processing

Author: Marek Miskowicz

Publisher: CRC Press

Published: 2018-09-03

Total Pages: 558

ISBN-13: 1482256568

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Event-based systems are a class of reactive systems deployed in a wide spectrum of engineering disciplines including control, communication, signal processing, and electronic instrumentation. Activities in event-based systems are triggered in response to events usually representing a significant change of the state of controlled or monitored physical variables. Event-based systems adopt a model of calls for resources only if it is necessary, and therefore, they are characterized by efficient utilization of communication bandwidth, computation capability, and energy budget. Currently, the economical use of constrained technical resources is a critical issue in various application domains because many systems become increasingly networked, wireless, and spatially distributed. Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers: Methods of analysis and design of event-based control and signal processing Event-driven control and optimization of hybrid systems Decentralized event-triggered control Periodic event-triggered control Model-based event-triggered control and event-triggered generalized predictive control Event-based intermittent control in man and machine Event-based PID controllers Event-based state estimation Self-triggered and team-triggered control Event-triggered and time-triggered real-time architectures for embedded systems Event-based continuous-time signal acquisition and DSP Statistical event-based signal processing in distributed detection and estimation Asynchronous spike event coding technique with address event representation Event-based processing of non-stationary signals Event-based digital (FIR and IIR) filters Event-based local bandwidth estimation and signal reconstruction Event-Based Control and Signal Processing is the first extensive study on both event-based control and event-based signal processing, presenting scientific contributions at the cutting edge of modern science and engineering.

Multisensor Fusion Estimation Theory and Application
Multisensor Fusion Estimation Theory and Application

Author: Liping Yan

Publisher: Springer Nature

Published: 2020-11-11

Total Pages: 229

ISBN-13: 9811594260

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This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.

Control and State Estimation for Dynamical Network Systems with Complex Samplings
Control and State Estimation for Dynamical Network Systems with Complex Samplings

Author: Bo Shen

Publisher: CRC Press

Published: 2022-09-14

Total Pages: 307

ISBN-13: 1000635457

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This book focuses on the control and state estimation problems for dynamical network systems with complex samplings subject to various network-induced phenomena. It includes a series of control and state estimation problems tackled under the passive sampling fashion. Further, it explains the effects from the active sampling fashion, i.e., event-based sampling is examined on the control/estimation performance, and novel design technologies are proposed for controllers/estimators. Simulation results are provided for better understanding of the proposed control/filtering methods. By drawing on a variety of theories and methodologies such as Lyapunov function, linear matrix inequalities, and Kalman theory, sufficient conditions are derived for guaranteeing the existence of the desired controllers and estimators, which are parameterized according to certain matrix inequalities or recursive matrix equations. Covers recent advances of control and state estimation for dynamical network systems with complex samplings from the engineering perspective Systematically introduces the complex sampling concept, methods, and application for the control and state estimation Presents unified framework for control and state estimation problems of dynamical network systems with complex samplings Exploits a set of the latest techniques such as linear matrix inequality approach, Vandermonde matrix approach, and trace derivation approach Explains event-triggered multi-rate fusion estimator, resilient distributed sampled-data estimator with predetermined specifications This book is aimed at researchers, professionals, and graduate students in control engineering and signal processing.

Stability Analysis and State Estimation of Memristive Neural Networks
Stability Analysis and State Estimation of Memristive Neural Networks

Author: Hongjian Liu

Publisher: CRC Press

Published: 2021-08-16

Total Pages: 237

ISBN-13: 1000415007

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In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks. In each chapter, the analysis problems are firstly considered, where the stability, synchronization and other performances (e.g., robustness, disturbances attenuation level) are investigated within a unified theoretical framework. In this stage, some novel notions are put forward to reflect the engineering practice. Then, the estimator design issues are discussed where sufficient conditions are derived to ensure the existence of the desired estimators with guaranteed performances. Finally, the theories and techniques developed in previous parts are applied to deal with some issues in several emerging research areas. The book Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks Exploits a unified framework for analysis and synthesis by designing new tools and techniques in combination with conventional theories of systems science, control engineering and signal processing Gives simulation examples in each chapter to reflect the engineering practice