Vehicle State Estimation Based on Unscented Kalman Filtering and a Genetic-particle Swarm Algorithm-Reference-Cited by-同舟云学术

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Vehicle State Estimation Based on Unscented Kalman Filtering and a Genetic-particle Swarm Algorithm

Published:2021-01-21 Issue:2 Volume:102 Page:447-469
ISSN:2250-0545
Container-title:Journal of The Institution of Engineers (India): Series C
language:en
Short-container-title:J. Inst. Eng. India Ser. C

Author:

Liu Ying-Jie^ORCID,Dou Chun-Hong,Shen Fapeng,Sun Qiu-Yun

Funder

Science and Technology Program Foundation of Weifang

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Ocean Engineering,Aerospace Engineering

Link

http://link.springer.com/content/pdf/10.1007/s40032-021-00663-1.pdf

Reference33 articles.

1. Mark W., Matthias D (2017) “State and maximum friction coefficient estimation in vehicle dynamics using UKF”. American Control Conference (ACC), Seattle, WA, USA. 24–26. DOI: https://doi.org/10.23919/ACC.2017.7963620.

2. C. Jie, S. Jian, L. Liang et al., UKF-based adaptive variable structure observer for vehicle sideslip with dynamic correction. IET Control Theory Appl. 10, 1641–1652 (2017). https://doi.org/10.1049/iet-cta.2015.1030

3. Z.F. Wang, Y.C. Qin, L. Gu et al., Vehicle System State Estimation Based on Adaptive Unscented Kalman Filtering Combing With Road Classification. IEEE Access 5, 27786–27799 (2017). https://doi.org/10.1109/ACCESS.2017.2771204

4. W. Liu, H.W. He, F.C. Sun, Vehicle state estimation based on Minimum Model Error criterion combining with Extended Kalman Filter. J. Franklin Inst. 353, 834–856 (2016)

5. You C. X., Panagiotis T (2017) “Vehicle modeling and parameter estimation using adaptive limited memory joint-state UKF”. American Control Conference (ACC), Seattle, WA, USA, 24–26. DOI: https://doi.org/10.23919/ACC.2017.7962973.

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