Please use this identifier to cite or link to this item:
Title: Cubature H-∞ Information Filter and its Extension
Authors: Chandra, Kumar Pakki Bharani
Gu, Da-Wei
Postlethwaite, Ian
First Published: 2-Mar-2016
Publisher: Elsevier for European Control Association
Citation: European Journal of Control, 2016, 29, pp. 17-32
Abstract: State estimation for nonlinear systems with Gaussian or non-Gaussian noises, and with single and multiple sensors, is presented. The key purpose is to propose a derivative free estimator using concepts from the information filter, the H∞H∞ filter, and the cubature Kalman filter (CKF). The proposed estimator is called the cubature H∞H∞ information filter (CH∞IFCH∞IF); it has the capability to deal with highly nonlinear systems like the CKF, like the H∞H∞ filter it can estimate states with stochastic or deterministic noises, and similar to the information filter it can be easily extended to handle measurements from multiple sensors. A numerically stable square-root CH∞IFCH∞IF is developed and extended to multiple sensors. The CH∞IFCH∞IF is implemented to estimate the states of a nonlinear permanent magnet synchronous motor model. Comparisons are made with an extended H∞
DOI Link: 10.1016/j.ejcon.2016.02.001
ISSN: 0947-3580
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016 European Control Association. Published by Elsevier Ltd. All rights reserved. This manuscript version is made available after the end of the embargo period under the CC-BY-NC-ND 4.0 license 
Appears in Collections:Published Articles, Dept. of Engineering

Files in This Item:
File Description SizeFormat 
CHIF_leicester.pdfPost-review (final submitted)1.53 MBAdobe PDFView/Open

Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.