Robust Kalman Filtering for Signals and Systems with Large Uncertainties: Control Engineering
Autor Ian R. Petersen, Andrey V. Savkinen Limba Engleză Paperback – 6 noi 2012
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Specificații
ISBN-13: 9781461272090
ISBN-10: 1461272092
Pagini: 220
Ilustrații: X, 207 p.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.31 kg
Ediția:Softcover reprint of the original 1st ed. 1999
Editura: Birkhäuser Boston
Colecția Birkhäuser
Seria Control Engineering
Locul publicării:Boston, MA, United States
ISBN-10: 1461272092
Pagini: 220
Ilustrații: X, 207 p.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.31 kg
Ediția:Softcover reprint of the original 1st ed. 1999
Editura: Birkhäuser Boston
Colecția Birkhäuser
Seria Control Engineering
Locul publicării:Boston, MA, United States
Public țintă
ResearchCuprins
1 Introduction.- 2 Continuous-Time Quadratic Guaranteed Cost Filtering.- 3 Discrete-Time Quadratic Guaranteed Cost Filtering.- 4 Continuous-Time Set-Valued State Estimation and Model Validation.- 5 Discrete-Time Set-Valued State Estimation.- 6 Robust State Estimation with Discrete and Continuous Measurements.- 7 Set-Valued State Estimation with Structured Uncertainty.- 8 Robust H? Filtering with Structured Uncertainty.- 9 Robust Fixed Order H? Filtering.- 10 Set-Valued State Estimation for Nonlinear Uncertain Systems.- 11 Robust Filtering Applied to Induction Motor Control.- References.
Recenzii
"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 Math