Enhancing data-driven input reconstruction via optimized sensor balancing-Reference-Cited by-同舟云学术

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Enhancing data-driven input reconstruction via optimized sensor balancing

Published:2024-04 Issue: Volume:211 Page:111184
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Zapata Luis M.^ORCID,Tuerlinckx Théo^ORCID,De Smet Jasper,Naets Frank^ORCID

Funder

Flanders Make

KU Leuven

Publisher

Elsevier BV

Reference34 articles.

1. Experimental validation of the Kalman-type filters for online and real-time state and input estimation;Azam;J. Vib. Control,2017

2. Multibody model based estimation of multiple loads and strain field on a vehicle suspension system;Risaliti;Mech. Syst. Signal Process.,2019

3. Combined impulse-response/Kalman filtering (CIRKF) for input/state estimation;Zapata;Mech. Syst. Signal Process.,2022

4. Kalman Filtering: Theory and Practice with MATLAB;Grewal,2014

5. Review of force reconstruction techniques;Sanchez;J. Sound Vib.,2014

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