Title
On robust Kalman filter for two-dimensional uncertain linear discrete time-varying systems: A least squares method.
Abstract
The robust Kalman filter design problem for two-dimensional uncertain linear discrete time-varying systems with stochastic noises is investigated in this study. First, we prove that the solution to a certain deterministic regularized least squares problem constrained by the nominal two-dimensional system model is equivalent to the generalized two-dimensional Kalman filter. Then, based on this relationship, the robust state estimation problem for two-dimensional uncertain systems with stochastic noises is interpreted as a deterministic robust regularized least squares problem subject to two-dimensional dynamic constraint. Finally, by solving the robust regularized least squares problem and using a simple approximation, a recursive robust two-dimensional Kalman filter is determined. A heat transfer process serves as an example to show the properties and efficacy of the proposed filter.
Year
DOI
Venue
2019
10.1016/j.automatica.2018.10.029
Automatica
Keywords
Field
DocType
Two-dimensional systems,Kalman filter,Uncertain systems,Time-varying systems,Least squares method
Least squares,Applied mathematics,Regularized least squares,Control theory,Heat transfer,Kalman filter,Discrete time and continuous time,Uncertain systems,System model,Recursion,Mathematics
Journal
Volume
Issue
ISSN
99
1
0005-1098
Citations 
PageRank 
References 
5
0.40
13
Authors
5
Name
Order
Citations
PageRank
dong zhao19512.68
Steven X. Ding21792124.79
H. R. Karimi33569223.59
Yueyang Li412412.98
Youqing Wang522025.81