
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Birkhauser Boston Inc (Publisher)
1st Edition
Published on 10. November 1999
Book
Hardback
X, 207 pages
978-0-8176-4089-7 (ISBN)
Description
The Kalman Filter gives an optimal estimate of the state of the given process based on output measurements. The aim of this text is to cover the theory of robust state estimation for the case in which the process model contains significant uncertainties and non-linearities.
Reviews / Votes
"The book is primarily a research monograph which presents, in a unified fashion, some recent research on robust Kalman filtering. The book is intended for researchers in robust control and filtering theory, advanced postgraduate students, and engineers with an interest in applying the latest techniques of robust Kalman filtering. Robust Kalman filtering extends the Kalman filtering and the extended Kalman filtering to systems that contain uncertain parameters in addition to the usual white Gaussian noise.. Several examples are given, showing the robust Kalman filters outperforming the regular Kalman filter or the extended Kalman filter. Each of the first ten chapters covers a specific topic, usually with a major theorem characterizing the robust filter followed by an example. The final chapter addresses its application to a particular problem." -Zentralblatt MathMore details
Series
Edition
1., 999
Language
English
Place of publication
Secaucus
United States
Target group
College/higher education
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
X, 207 p.
26 black & white illustrations
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 18 mm
Weight
500 gr
ISBN-13
978-0-8176-4089-7 (9780817640897)
DOI
10.1007/978-1-4612-1594-3
Schweitzer Classification
Other editions
Additional editions

Ian R. Petersen | Andrey V. Savkin
Robust Kalman Filtering for Signals and Systems with Large Uncertainties
Book
11/2012
Springer-Verlag New York Inc.
€90.94
Shipment within 15-20 days
Previous edition
Ian Petersen | Andrey Savkin
Robust Kalman Filtering For Signals and Systems with Large Uncertainties
Book
02/1999
Birkhäuser Verlag GmbH
€66.85
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Content
Continuous-time quadratic guaranteed cost filtering; discrete-time quadratic guaranteed cost filtering; continuous-time set valued state estimation and model validation; discrete-time set valued estimation and model validation; robust state estimation with discrete and continuous measurements; set valued state estimation with structured uncertainty; robust H-infinity filtering with structured uncertainty; robust fixed order H-infinity filtering; set valued state estimation for nonlinear uncertain systems; robust filtering applied to an induction motor.