Use of Flexible Models in Extended Kalman Filtering Applied to Vehicle Body Force Estimation

2016 ◽  
pp. 259-275
Author(s):  
Sebastiaan van Aalst ◽  
Frank Naets ◽  
Johan Theunissen ◽  
Wim Desmet
Keyword(s):  
Kalman Filtering ◽  
Body Force ◽  
Vehicle Body ◽  
Force Estimation ◽  
Extended Kalman Filtering ◽  
Flexible Models

scholarly journals Online state and input force estimation for multibody models employing extended Kalman filtering

2013 ◽  
Vol 32 (3) ◽  
pp. 317-336 ◽  
Author(s):  
Frank Naets ◽  
Roland Pastorino ◽  
Javier Cuadrado ◽  
Wim Desmet
Keyword(s):  
Kalman Filtering ◽  
Force Estimation ◽  
Extended Kalman Filtering ◽  
Input Force

scholarly journals Upgraded Kalman Filtering of Cutting Forces in Milling

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5397 ◽  
Author(s):  
Giovanni Totis ◽  
Zoltan Dombovari ◽  
Marco Sortino
Keyword(s):  
Kalman Filtering ◽  
High Speed ◽  
State Of The Art ◽  
Force Measurement ◽  
Frequency Bandwidth ◽  
Force Estimation ◽  
Extended Kalman Filtering ◽  
Force Application Point ◽  
Cutting Force Measurement ◽  
Identification Phase

Advanced piezoelectric dynamometers with a wide frequency bandwidth are required for cutting force measurement in high-speed milling and micromilling applications. In many applications, the signal bandwidth is limited by the dynamic response of the mechanical system, thus compensation techniques are necessary. The most effective compensation techniques for a full 3D force correction require an accurate and complex identification phase. Extended Kalman filtering is a better alternative for input force estimation in the presence of unknown dynamic disturbances. The maximum bandwidth that can be currently achievable by Kalman filtering is approximately 2 kHz, due to crosstalk disturbances and complex dynamometer’s dynamics. In this work, a novel upgraded Kalman filter based on a more general model of dynamometer dynamics is conceived, by also taking into account the influence of the force application point. By so doing, it was possible to extend the frequency bandwidth of the device up to more than 5 kHz along the main directions and up to more than 3 kHz along the transverse directions, outperforming state-of-the-art methods based on Kalman filtering.

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