Networked Nonlinear Stochastic Time-Varying Systems
Author | : Hongli Dong |
Publisher | : CRC Press |
Total Pages | : 278 |
Release | : 2021-09-09 |
ISBN-13 | : 9781000433722 |
ISBN-10 | : 1000433722 |
Rating | : 4/5 (22 Downloads) |
Download or read book Networked Nonlinear Stochastic Time-Varying Systems written by Hongli Dong and published by CRC Press. This book was released on 2021-09-09 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.