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Sinopsis
This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system’s stability and performance. This book discusses how to deal with such constraints to guarantee the system’s design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.
This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.
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This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the systems stability and performance. This book discusses how to deal with such constraints to guarantee the systems design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.
This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals (Studies in Systems, Decision and Control, 170)
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Recent Advances in Control and Filtering of Dynamic Systems With Constrained Signals
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals (Paperback)
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Springer Nature Switzerland AG, Cham, 2018
ISBN 10: 3030071545
ISBN 13: 9783030071547
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Paperback. Condición: new. Paperback. This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the systems stability and performance. This book discusses how to deal with such constraints to guarantee the systems design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems. This book discusses how to deal with such constraints to guarantee the systems design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783030071547
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals (Studies in Systems, Decision and Control, 170)
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals (Studies in Systems, Decision and Control, 170)
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
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Springer International Publishing Dez 2018, 2018
ISBN 10: 3030071545
ISBN 13: 9783030071547
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system's stability and performance. This book discusses how to deal with such constraints to guarantee the system's design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems. 256 pp. Englisch. Nº de ref. del artículo: 9783030071547
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Recent Advances in Control and Filtering of Dynamic Systems With Constrained Signals
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
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Springer International Publishing, 2018
ISBN 10: 3030071545
ISBN 13: 9783030071547
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent research trends and practical examples in control and filtering of dynamic systems with constrained signals Demonstrates various dynamic system models in continuous or discrete-time domain such as Networke. Nº de ref. del artículo: 448670433
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals (Studies in Systems, Decision and Control, 170)
Librería: California Books, Miami, FL, Estados Unidos de America
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Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals
Publicado por
Springer International Publishing, Springer International Publishing Dez 2018, 2018
ISBN 10: 3030071545
ISBN 13: 9783030071547
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. Neuware -This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system¿s stability and performance. This book discusses how to deal with such constraints to guarantee the system¿s design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques.This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch. Nº de ref. del artículo: 9783030071547
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