Robust Kalman filter for systems subject to parametric uncertainties
type: Item
instance of: scholarly article
title: Robust Kalman filter for systems subject to parametric uncertainties
zbMATH Open document ID: 1485.93594
author: Kaio D. T. Rocha
author: Marco H. Terra
published in: Systems \& Control Letters
publication date: 2021-12-14T00:00:00Z
review text: In this paper, the authors give a robust Kalman filter for uncertain linear discrete-time systems. They reduce the filter problem to a robust regularized least-squares estimation problem. The filter is given by both in a symmetric matrix arrangement and as explicit algebraic expressions in a Kalman-like structure that is suitable for online applications. They show that the steady-state filter is stable and guarantees a bounded error variance for quadratically stable systems. At last, a numerical example is given. The main novelty of the result in this paper is that there may be some uncertainty in the model.
reviewed by: Qi Lü
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93E24
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 93C05
zbMATH DE Number: 7444389
zbMATH Keywords: robust filtering
zbMATH Keywords: parametric uncertainties
zbMATH Keywords: Kalman filtering
zbMATH Keywords: least-squares
MaRDI profile type: Publication
full work available at URL: j.sysconle.2021.105034
OpenAlex ID: W3202327736
cites work: H∞ estimation for discrete‐time linear uncertain systems
cites work: H2 and $H_\infty$ Robust Filtering for Discrete-Time Linear Systems
cites work: Improved robust \(H_{2}\) and \(H_{\infty}\) filtering for uncertain discrete-time systems
cites work: Robust Kalman filtering for uncertain discrete-time systems
cites work: Optimal guaranteed cost filtering for uncertain discrete-time linear systems
cites work: Design and analysis of discrete-time robust Kalman filters
cites work: Optimization of stochastic linear systems with additive measurement and process noise using exponential performance criteria
cites work: A contraction analysis of the convergence of risk-sensitive filters
cites work: Robust Kalman Filtering Under Model Perturbations
cites work: Q4263635
cites work: A framework for state-space estimation with uncertain models
cites work: A Kalman Filter Design Based on the Performance/Robustness Tradeoff
cites work: Optimal robust filtering for systems subject to uncertainties
cites work: Linear and nonlinear programming.
cites work: A uniqueness result concerning a robust regularized least-squares solution
DOI: 10.1016/J.SYSCONLE.2021.105034
description: scientific article; zbMATH DE number 7444389