Details
| Original language | English |
|---|---|
| Article number | 7040172 |
| Pages (from-to) | 5015-5020 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Volume | 2015-February |
| Issue number | February |
| Publication status | Published - 2014 |
| Event | 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States Duration: 15 Dec 2014 → 17 Dec 2014 |
Abstract
In order to improve vehicle's active safety systems accurate knowledge about the vehicle's driving stability is necessary. Especially the exact determination of the side-slip angle can be of great importance, since it has major potential for improving current control algorithms. Therefore, a model-based methodology for online estimation of vehicle's lateral dynamics is presented, while generalizations of the Kalman Filter algorithm, the Extended and Unscented Kalman Filters are used due to the highly non-linear model behavior. The results of the introduced methodologies are presented for two different driving maneuvers and validated comparing to measurements taken with a VW Golf GTI. Furthermore, a qualitative comparison between Extended and Unscented Kalman Filter is realized.
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Mathematics(all)
- Modelling and Simulation
- Mathematics(all)
- Control and Optimization
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In: Proceedings of the IEEE Conference on Decision and Control, Vol. 2015-February, No. February, 7040172, 2014, p. 5015-5020.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - State estimation of vehicle's lateral dynamics using unscented Kalman filter
AU - Wielitzka, Mark
AU - Dagen, Matthias
AU - Ortmaier, Tobias
PY - 2014
Y1 - 2014
N2 - In order to improve vehicle's active safety systems accurate knowledge about the vehicle's driving stability is necessary. Especially the exact determination of the side-slip angle can be of great importance, since it has major potential for improving current control algorithms. Therefore, a model-based methodology for online estimation of vehicle's lateral dynamics is presented, while generalizations of the Kalman Filter algorithm, the Extended and Unscented Kalman Filters are used due to the highly non-linear model behavior. The results of the introduced methodologies are presented for two different driving maneuvers and validated comparing to measurements taken with a VW Golf GTI. Furthermore, a qualitative comparison between Extended and Unscented Kalman Filter is realized.
AB - In order to improve vehicle's active safety systems accurate knowledge about the vehicle's driving stability is necessary. Especially the exact determination of the side-slip angle can be of great importance, since it has major potential for improving current control algorithms. Therefore, a model-based methodology for online estimation of vehicle's lateral dynamics is presented, while generalizations of the Kalman Filter algorithm, the Extended and Unscented Kalman Filters are used due to the highly non-linear model behavior. The results of the introduced methodologies are presented for two different driving maneuvers and validated comparing to measurements taken with a VW Golf GTI. Furthermore, a qualitative comparison between Extended and Unscented Kalman Filter is realized.
UR - http://www.scopus.com/inward/record.url?scp=84988259225&partnerID=8YFLogxK
U2 - 10.1109/cdc.2014.7040172
DO - 10.1109/cdc.2014.7040172
M3 - Conference article
AN - SCOPUS:84988259225
VL - 2015-February
SP - 5015
EP - 5020
JO - Proceedings of the IEEE Conference on Decision and Control
JF - Proceedings of the IEEE Conference on Decision and Control
SN - 0743-1546
IS - February
M1 - 7040172
T2 - 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Y2 - 15 December 2014 through 17 December 2014
ER -