Fault Detection and State Estimation in Automatic Control PDF Download
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Author: Sheng Du
Publisher: Mdpi AG
ISBN: 9783036597560
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
Fault detection and state estimation are essential tasks for ensuring the reliability, safety and performance of automatic control systems. They play a critical role in detecting and isolating faults quickly and accurately, enabling timely corrective action and preventing system failures. The field of fault detection and state estimation has seen significant advances in recent years, driven by the integration of advanced methodologies with cutting-edge technologies, in particular artificial intelligence and deep learning. These techniques have demonstrated remarkable capabilities in fault diagnosis, state estimation and fault-tolerant control, especially in complex multi-sensor systems. This Special Issue highlights and discusses the design and application of fault detection algorithms, the design and application of state estimation methods, the design and application of machine learning algorithms, the analysis of automatic control system characteristics, and the design and application of intelligent control systems. Nevertheless, many challenges remain and require attention, including scalability, computational efficiency, online implementation, fault isolation, fault recovery and fault-tolerant control. Additional research efforts are therefore essential to advance both the theory and practice of this critical task.
Author: Sheng Du
Publisher: Mdpi AG
ISBN: 9783036597560
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
Fault detection and state estimation are essential tasks for ensuring the reliability, safety and performance of automatic control systems. They play a critical role in detecting and isolating faults quickly and accurately, enabling timely corrective action and preventing system failures. The field of fault detection and state estimation has seen significant advances in recent years, driven by the integration of advanced methodologies with cutting-edge technologies, in particular artificial intelligence and deep learning. These techniques have demonstrated remarkable capabilities in fault diagnosis, state estimation and fault-tolerant control, especially in complex multi-sensor systems. This Special Issue highlights and discusses the design and application of fault detection algorithms, the design and application of state estimation methods, the design and application of machine learning algorithms, the analysis of automatic control system characteristics, and the design and application of intelligent control systems. Nevertheless, many challenges remain and require attention, including scalability, computational efficiency, online implementation, fault isolation, fault recovery and fault-tolerant control. Additional research efforts are therefore essential to advance both the theory and practice of this critical task.
Author: Yang Liu
Publisher: CRC Press
ISBN: 1000641066
Category : Technology & Engineering
Languages : en
Pages : 223
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Book Description
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.
Author: Rolf Isermann
Publisher: Springer Science & Business Media
ISBN: 3540303685
Category : Technology & Engineering
Languages : en
Pages : 478
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Book Description
With increasing demands for efficiency and product quality plus progress in the integration of automatic control systems in high-cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role. The book gives an introduction into advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, it considers the reliability, availability, safety and systems integrity of technical processes. Then fault-detection methods for single signals without models such as limit and trend checking and with harmonic and stochastic models, such as Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals such as parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems. Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire demonstrate applications.
Author: Ye Wang
Publisher: Springer Nature
ISBN: 303052440X
Category : Technology & Engineering
Languages : en
Pages : 252
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Book Description
This book presents theoretical and practical findings on the state estimation, diagnosis and control of complex systems, especially in the mathematical form of descriptor systems. The research is fully motivated by real-world applications (i.e., Barcelona’s water distribution network), which require control systems capable of taking into account their specific features and the limits of operations in the presence of uncertainties stemming from modeling errors and component malfunctions. Accordingly, the book first introduces a complete set-based framework for explicitly describing the effects of uncertainties in the descriptor systems discussed. In turn, this set-based framework is used for state estimation and diagnosis. The book also presents a number of application results on economic model predictive control from actual water distribution networks and smart grids. Moreover, the book introduces a fault-tolerant control strategy based on virtual actuators and sensors for such systems in the descriptor form.
Author: Yang Liu
Publisher: CRC Press
ISBN: 1000641112
Category : Technology & Engineering
Languages : en
Pages : 277
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Book Description
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.
Author: Yong Zhang
Publisher: CRC Press
ISBN: 1000835944
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
This book unifies existing and emerging concepts concerning state estimation, fault detection, fault isolation and fault estimation on industrial systems with an emphasis on a variety of network-induced phenomena, fault diagnosis and remaining useful life for industrial equipment. It covers state estimation/monitor, fault diagnosis and remaining useful life prediction by drawing on the conventional theories of systems science, signal processing and machine learning. Features: Unifies existing and emerging concepts concerning robust filtering and fault diagnosis with an emphasis on a variety of network-induced complexities. Explains theories, techniques, and applications of state estimation as well as fault diagnosis from an engineering-oriented perspective. Provides a series of latest results in robust/stochastic filtering, multidate sample, and time-varying system. Captures diagnosis (fault detection, fault isolation and fault estimation) for time-varying multi-rate systems. Includes simulation examples in each chapter to reflect the engineering practice. This book aims at graduate students, professionals and researchers in control science and application, system analysis, artificial intelligence, and fault diagnosis.
Author: Heidar A. Talebi
Publisher: Springer
ISBN: 1441914382
Category : Technology & Engineering
Languages : en
Pages : 166
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Book Description
"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Author: EDELMAYER ANDRÁS.
Publisher:
ISBN:
Category :
Languages : hu
Pages : 0
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Book Description
Author: Ch. Venkateswarlu
Publisher: Elsevier
ISBN: 0323900682
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines. Describes various classical and advanced versions of mechanistic model based state estimation algorithms Describes various data-driven model based state estimation techniques Highlights a number of real applications of mechanistic model based and data-driven model based state estimators/soft sensors Beneficial to those associated with process monitoring, fault diagnosis, online optimization, control and related areas
Author: Christoforos N. Hadjicostis
Publisher: Springer Nature
ISBN: 3030308219
Category : Technology & Engineering
Languages : en
Pages : 357
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Book Description
Estimation and Inference in Discrete Event Systems chooses a popular model for emerging automation systems—finite automata under partial observation—and focuses on a comprehensive study of the key problems of state estimation and event inference. The text includes treatment of current, delayed, and initial state estimation. Related applications for assessing and enforcing resiliency—fault detection and diagnosis—and security—privacy and opacity—properties are discussed, enabling the reader to apply these techniques in a variety of emerging applications, among them automated manufacturing processes, intelligent vehicle/highway systems, and autonomous vehicles. The book provides a systematic development of recursive algorithms for state estimation and event inference. The author also deals with the verification of pertinent properties such as: the ability to determine the exact state of a system, “detectability”; the ability to ensure that certain classes of faults can be detected/identified, “diagnosability”; and the ability to ensure that certain internal state variables of the system remain “hidden” from the outside world regardless of the type of activity that is taking place, “opacity”. This book allows students, researchers and practicing engineers alike to grasp basic aspects of state estimation in discrete event systems, aspects like distributivity and probabilistic inference, quickly and without having to master the entire breadth of models that are available in the literature.
