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Stochastic control and filtering ove...

He, Xiao.

Stochastic control and filtering over constrained communication networks

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stochastic control and filtering over constrained communication networksby Qinyuan Liu, Zidong Wang, Xiao He.
作者:	Liu, Qinyuan.
其他作者:	Wang, Zidong.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xvii, 222 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Stochastic control theory.
電子資源:	https://doi.org/10.1007/978-3-030-00157-5
ISBN:	9783030001575$q(electronic bk.)

Stochastic control and filtering over constrained communication networks
Liu, Qinyuan.

Stochastic control and filtering over constrained communication networks[electronic resource] /by Qinyuan Liu, Zidong Wang, Xiao He. - Cham :Springer International Publishing :2019. - xvii, 222 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.1782198-4182 ;. - Studies in systems, decision and control ;v.3..

Introduction -- Fundamental Limitations of Networked Systems over Fading Channels -- Event-based H∞ Consensus Control of Multi-agent Systems -- Event-Triggered Resilient Filtering with Measurement Quantization -- Event-based Distributed Filtering of Continuous-time Nonlinear Systems -- Event-based Distributed Filtering over Markovian Switching Topologies -- Event-based Recursive Distributed Filtering -- A Resilient Approach to Distributed Recursive Filter Design -- Consensus-based Recursive Distributed Filtering -- On Kalman-Consensus Filtering with Random Link Failures -- Moving-Horizon Estimation with Binary Encoding Schemes -- Conclusion and Further Work.

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: recursive Riccati equations; matrix decomposition; optimal estimation theory; and mathematical optimization methods. 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.

ISBN: 9783030001575$q(electronic bk.)

Standard No.: 10.1007/978-3-030-00157-5doiSubjects--Topical Terms:

183121
Stochastic control theory.

LC Class. No.: TK5102.9 / .L587 2019

Dewey Class. No.: 621.3822

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505 0 $a Introduction -- Fundamental Limitations of Networked Systems over Fading Channels -- Event-based H∞ Consensus Control of Multi-agent Systems -- Event-Triggered Resilient Filtering with Measurement Quantization -- Event-based Distributed Filtering of Continuous-time Nonlinear Systems -- Event-based Distributed Filtering over Markovian Switching Topologies -- Event-based Recursive Distributed Filtering -- A Resilient Approach to Distributed Recursive Filter Design -- Consensus-based Recursive Distributed Filtering -- On Kalman-Consensus Filtering with Random Link Failures -- Moving-Horizon Estimation with Binary Encoding Schemes -- Conclusion and Further Work.
520 $a 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: recursive Riccati equations; matrix decomposition; optimal estimation theory; and mathematical optimization methods. 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.
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