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portada Networked Nonlinear Stochastic Time-Varying Systems
Type
Physical Book
Publisher
Author
Language
English
Pages
278
Format
Paperback
ISBN13
9781032038803
Edition No.
1

Networked Nonlinear Stochastic Time-Varying Systems

Hongli Dong; Zidong Wang; Nan Hou (Author) · Crc Press · Paperback

Networked Nonlinear Stochastic Time-Varying Systems - Hongli Dong; Zidong Wang; Nan Hou

New Book Imported to South Africa
Delivery: 13 Jul - 05 Aug Shipping: 4 to 5 business days.
R 1,434
R 1,434

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Synopsis "Networked Nonlinear Stochastic Time-Varying Systems"

Networked Non-linear Stochastic Time-Varying Systems: Analysis and Synthesis copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, the book discusses the finite-horizon filtering, fault estimation and reliable control, and randomly occurring nonlinearities/uncertainties followed by designing of distributed state and fault estimators, and distributed filters. The third part includes problems of variance-constrained H∞ state estimation, partial-nodes-based state estimation and recursive filtering for nonlinear time-varying complex networks with randomly varying topologies, and random coupling strengths. Offers a comprehensive treatment of the topics related to Networked Nonlinear Stochastic Time-Varying Systems with rigorous math foundation and derivation Unifies existing and emerging concepts concerning control/filtering/estimation and distributed filtering Provides a series of latest results by drawing on the conventional theories of systems science, control engineering and signal processing Deal with practical engineering problems such as event triggered H∞ filtering, non-fragile distributed estimation, recursive filtering, set-membership filtering Demonstrates illustrative examples in each chapter to verify the correctness of the proposed results This book is aimed at engineers, mathematicians, scientists, and upper-level students in the fields of control engineering, signal processing, networked control systems, robotics, data analysis, and automation.

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