Open AccessRobust Kalman filtering for discrete‐time systems with stochastic uncertain time‐varying parameters
Author(s) -
Abolhasani M.,
Rahmani M.
Publication year - 2017
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2016.2520
Subject(s) - kalman filter , control theory (sociology) , discrete time and continuous time , noise (video) , mathematics , filter (signal processing) , upper and lower bounds , computer science , invariant extended kalman filter , fast kalman filter , alpha beta filter , variance (accounting) , extended kalman filter , moving horizon estimation , statistics , artificial intelligence , accounting , business , mathematical analysis , control (management) , image (mathematics) , computer vision
A robust Kalman filter is proposed for time‐varying discrete‐time linear systems with uncertainties in state, input noise, and measurement matrices. The filter is obtained by solving an optimisation problem such that the upper bound on the variance of estimation error to be minimised for all admissible uncertainties. A numerical example is presented to show the performance of the proposed robust filter.