Robust Filtering for Uncertain Systems: A Parameter-Dependent Approach by Huijun GaoRobust Filtering for Uncertain Systems: A Parameter-Dependent Approach by Huijun Gao

Robust Filtering for Uncertain Systems: A Parameter-Dependent Approach

byHuijun Gao, Xianwei Li

Hardcover | April 24, 2014

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This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like H2 filtering and H¥ filtering, are addressed and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features:

·        design approaches to robust filters arranged according to varying complexity level and emphasizing robust filtering in the parameter-dependent framework for the first time;

·        guidance on the use of special realistic phenomena or factors to describe problems more accurately and to improve filtering performance;

·        a unified linear matrix inequality formulation of design approaches for easy and effective filter design;

·        demonstration of the techniques of matrix decoupling technique, the generalized Kalman?Yakubovich?Popov lemma, the free weighting matrix technique and the delay modelling approach, in robust filtering;

·        numerous easy-to-follow simulation examples, graphical and tabular illustrations to help the reader understand the filter design approaches developed; and

·        an account of emerging issues on robust filtering for research to inspire future investigation.

Robust Filtering for Uncertain Systems will be of interest to academic researchers specializing in linear, robust and optimal control and estimation and to practitioners working in tracking and network control or signal filtering, detection and estimation. Graduate students learning control and systems theory, signal processing or applied mathematics will also find the book to be a valuable resource.

 

Professor Huijun Gao received the Ph.D. degree in control science and engineering from Harbin Institute of Technology, China, in 2005. From November 2003 to August 2004, he was a Research Associate with the Department of Mechanical Engineering, The University of Hong Kong. From October 2005 to September 2007, he was an Alberta Ingenuit...
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Title:Robust Filtering for Uncertain Systems: A Parameter-Dependent ApproachFormat:HardcoverDimensions:253 pagesPublished:April 24, 2014Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319059025

ISBN - 13:9783319059020

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Table of Contents

Introduction.- Part I Quadratic and Parameter-Dependent Filter Design.- Quadratic Robust Filter Design.- Parameter-Dependent Robust Filter Design.- Part II Robust Filtering for Time-Delay Systems and 2-D Systems.- Robust Filtering for Continuous-Time Time-Delay Systems.- Robust Filtering for Discrete-Time Time-Delay Systems.- Robust Filtering for Uncertain 2-D Systems.- Part III New Problems in Robust Filtering.- Robust Estimation with Limited Communication Capacity.- Finite-Frequency H-infinity Filtering for Time-Delay Systems.- Conclusion.

Editorial Reviews

"In order to help the reader to get a better understanding of the presented material, in each section there are included numerous algorithms associated to the theorems and tables summarizing the properties which appear in illustrative examples . . references are given at the end of each chapter . . The book is very dense in its content. . The book aims to offer the research engineers and graduate students an excellent tool." (Dumitru Stanomir, zbMATH 1335.93001, 2016)