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Cubature H∞ information filter and its extensions

Lookup NU author(s): Emeritus Professor Ian Postlethwaite

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Abstract

© 2016 European Control Association. Published by Elsevier Ltd. All rights reserved. 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∞ filter, and the cubature Kalman filter (CKF). The proposed estimator is called the cubature H∞ information filter (CH∞IF); it has the capability to deal with highly nonlinear systems like the CKF, like the 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∞IF is developed and extended to multiple sensors. The CH∞IF is implemented to estimate the states of a nonlinear permanent magnet synchronous motor model. Comparisons are made with an extended H∞ information filter.

Publication metadata

Author(s): Chandra KPB, Gu D-W, Postlethwaite I

Publication type: Article

Publication status: Published

Journal: European Journal of Control

Year: 2016

Volume: 29

Pages: 17-32

Print publication date: 01/05/2016

Online publication date: 02/03/2016

Acceptance date: 18/02/2016

ISSN (print): 0947-3580

ISSN (electronic): 1435-5671

Publisher: European Control Association

URL: https://doi.org/10.1016/j.ejcon.2016.02.001

DOI: 10.1016/j.ejcon.2016.02.001

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