Title
Unbiased Minimum Variance Fault and State Estimation for Linear Discrete Time-Varying Two-Dimensional Systems.
Abstract
The fault and state estimation problem is addressed for a class of linear discrete time-varying two-dimensional systems subject to state and measurement noises. Two estimators are proposed to compute the estimation of the system state and/or fault recursively, both of which are unbiased with minimum variance. Through formulating the estimation problem as the solvability problem of the corresponding matrix equations of estimator gains and system constraint, the necessary and sufficient condition of the existence and the solution for the proposed estimators are given. An example is used to demonstrate the effectiveness of the proposed estimators.
Year
DOI
Venue
2017
10.1109/TAC.2017.2697210
IEEE Trans. Automat. Contr.
Keywords
Field
DocType
State estimation,Kalman filters,Time-varying systems,Noise measurement,Mathematical model,Two dimensional displays
Minimum-variance unbiased estimator,Mathematical optimization,Noise measurement,Matrix (mathematics),Control theory,Kalman filter,Discrete time and continuous time,Recursion,Mathematics,Estimator
Journal
Volume
Issue
ISSN
62
10
0018-9286
Citations 
PageRank 
References 
29
0.83
16
Authors
4
Name
Order
Citations
PageRank
Youqing Wang122025.81
dong zhao29512.68
Yueyang Li312412.98
Steven X. Ding41792124.79