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|Title:||Cubature H-∞ Information Filter and its Extension|
Chandra, K. P. B.
|Publisher:||Elsevier for European Control Association|
|Citation:||European Journal of Control, 2016 (Accepted, In Press)|
|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∞|
|Embargo on file until:||1-Jan-10000|
|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 http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Description:||The file associated with this record is under a 24-month embargo from publication in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.|
|Appears in Collections:||Published Articles, Dept. of Engineering|
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|CHIF_leicester.pdf||Post-review (final submitted)||1.53 MB||Adobe PDF||View/Open|
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