Описание: Focusing on groundbreaking interpolating control methods that are computationally simpler than model predictive control, particularly for high-order systems, this text includes a wealth of worked examples and a collection of adaptable MATLAB (R) script files.
Автор: Mohinder S. Grewal,Angus P. Andrews Название: Kalman Filtering: Theory and Practice with MATLAB ISBN: 1118851218 ISBN-13(EAN): 9781118851210 Издательство: Wiley Рейтинг: Цена: 18050.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The definitive textbook and professional reference on Kalman Filtering fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering.
Описание: This book focuses on the basic control and filtering synthesis problems for discrete-time switched linear systems under time-dependent switching signals.
Автор: Dan Zhang; Qing-Guo Wang; Li Yu Название: Filtering and Control of Wireless Networked Systems ISBN: 3319531220 ISBN-13(EAN): 9783319531229 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Introduction.- Fundamentals.- H∞ filtering with time-varying transmissions.- H∞ filtering with energy constraint and stochastic gain variations.- H∞ Filtering with Stochastic Signal Transmissions.- H∞ filtering with stochastic sampling and measurement size reduction.- Distributed filtering with communication reduction.- Distributed filtering with stochastic sampling.- Distributed filtering with random filter gain variations.- Distributed filtering with measurement size reduction and filter gain variations.- Distributed control with controller gain variations.- Distributed control with measurement size reduction and random fault.- Distributed control with communication reduction.- Distributed control with event-based communication and topology switching
Описание: 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.
Описание: ?Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including:
Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing. Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks.
Описание: ?Stochastic Control and Filtering over Constrained Communication Networks presents up-to-date research developments and novel methodologies on stochastic control and filtering for networked systems under constrained communication networks. It provides a framework of optimal controller/filter design, resilient filter design, stability and performance analysis for the systems considered, subject to various kinds of communication constraints, including signal-to-noise constraints, bandwidth constraints, and packet drops. Several techniques are employed to develop the controllers and filters desired, including:
Readers will benefit from the book’s new concepts, models and methodologies that have practical significance in control engineering and signal processing. Stochastic Control and Filtering over Constrained Communication Networks is a practical research reference for engineers dealing with networked control and filtering problems. It is also of interest to academics and students working in control and communication networks.
Автор: W. H. Fleming; L. G. Gorostiza Название: Advances in Filtering and Optimal Stochastic Control ISBN: 3662135310 ISBN-13(EAN): 9783662135310 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique.
Описание: "Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique.
Автор: Fanbiao Li; Peng Shi; Ligang Wu Название: Control and Filtering for Semi-Markovian Jump Systems ISBN: 3319471988 ISBN-13(EAN): 9783319471983 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.
Автор: Xiuming Yao; Ligang Wu; Wei Xing Zheng Название: Filtering and Control of Stochastic Jump Hybrid Systems ISBN: 3319319140 ISBN-13(EAN): 9783319319148 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems.
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