A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation

Taiheng Ma; Weida Wang; Chao Yang; Yuhang Zhang; Ying Li

doi:10.1109/CCDC55256.2022.10034178

A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation

Taiheng Ma^*, Weida Wang, Chao Yang, Yuhang Zhang, Ying Li

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Path following control is of significance to the realization of automated driving. However, the constantly existing uncertainties may cause tracking deviation for autonomous vehicle (AV) during path following process. Motivated by this issue, a path following scheme using modified sliding mode prediction control (SMPC) is proposed for AV. Firstly, a SMPC framework is built, which introduces the prediction process into the approaching process of sliding mode control. Then, a lumped uncertainty term containing parameter fluctuation and external disturbance is added in the prediction process of the SMPC framework. The accurate estimation of lumped uncertainty aforementioned is realized through an extended state observer (ESO). Finally, typical driving maneuvers are performed in simulation to verify the effectiveness of the proposed scheme. Compared with existing methods, the proposed control scheme can improve the tracking accuracy up to 36.3%.

Original language	English
Title of host publication	Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	22-27
Number of pages	6
ISBN (Electronic)	9781665478960
DOIs	https://doi.org/10.1109/CCDC55256.2022.10034178
Publication status	Published - 2022
Event	34th Chinese Control and Decision Conference, CCDC 2022 - Hefei, China Duration: 15 Aug 2022 → 17 Aug 2022

Publication series

Name	Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

Conference

Conference	34th Chinese Control and Decision Conference, CCDC 2022
Country/Territory	China
City	Hefei
Period	15/08/22 → 17/08/22

Keywords

Autonomous vehicles
path following
sliding mode prediction control (SMPC)
uncertainty estimation

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10.1109/CCDC55256.2022.10034178

Cite this

Ma, T., Wang, W., Yang, C., Zhang, Y., & Li, Y. (2022). A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation. In Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022 (pp. 22-27). (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC55256.2022.10034178

Ma, Taiheng ; Wang, Weida ; Yang, Chao et al. / A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation. Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 22-27 (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022).

@inproceedings{d133bc94a6b544aeb5fded2ee952a634,

title = "A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation",

abstract = "Path following control is of significance to the realization of automated driving. However, the constantly existing uncertainties may cause tracking deviation for autonomous vehicle (AV) during path following process. Motivated by this issue, a path following scheme using modified sliding mode prediction control (SMPC) is proposed for AV. Firstly, a SMPC framework is built, which introduces the prediction process into the approaching process of sliding mode control. Then, a lumped uncertainty term containing parameter fluctuation and external disturbance is added in the prediction process of the SMPC framework. The accurate estimation of lumped uncertainty aforementioned is realized through an extended state observer (ESO). Finally, typical driving maneuvers are performed in simulation to verify the effectiveness of the proposed scheme. Compared with existing methods, the proposed control scheme can improve the tracking accuracy up to 36.3%.",

keywords = "Autonomous vehicles, path following, sliding mode prediction control (SMPC), uncertainty estimation",

author = "Taiheng Ma and Weida Wang and Chao Yang and Yuhang Zhang and Ying Li",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 34th Chinese Control and Decision Conference, CCDC 2022 ; Conference date: 15-08-2022 Through 17-08-2022",

year = "2022",

doi = "10.1109/CCDC55256.2022.10034178",

language = "English",

series = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "22--27",

booktitle = "Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022",

address = "United States",

}

Ma, T, Wang, W , Yang, C, Zhang, Y & Li, Y 2022, A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation. in Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022, Institute of Electrical and Electronics Engineers Inc., pp. 22-27, 34th Chinese Control and Decision Conference, CCDC 2022, Hefei, China, 15/08/22. https://doi.org/10.1109/CCDC55256.2022.10034178

A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation. / Ma, Taiheng; Wang, Weida ; Yang, Chao et al.
Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 22-27 (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation

AU - Ma, Taiheng

AU - Wang, Weida

AU - Yang, Chao

AU - Zhang, Yuhang

AU - Li, Ying

PY - 2022

Y1 - 2022

N2 - Path following control is of significance to the realization of automated driving. However, the constantly existing uncertainties may cause tracking deviation for autonomous vehicle (AV) during path following process. Motivated by this issue, a path following scheme using modified sliding mode prediction control (SMPC) is proposed for AV. Firstly, a SMPC framework is built, which introduces the prediction process into the approaching process of sliding mode control. Then, a lumped uncertainty term containing parameter fluctuation and external disturbance is added in the prediction process of the SMPC framework. The accurate estimation of lumped uncertainty aforementioned is realized through an extended state observer (ESO). Finally, typical driving maneuvers are performed in simulation to verify the effectiveness of the proposed scheme. Compared with existing methods, the proposed control scheme can improve the tracking accuracy up to 36.3%.

AB - Path following control is of significance to the realization of automated driving. However, the constantly existing uncertainties may cause tracking deviation for autonomous vehicle (AV) during path following process. Motivated by this issue, a path following scheme using modified sliding mode prediction control (SMPC) is proposed for AV. Firstly, a SMPC framework is built, which introduces the prediction process into the approaching process of sliding mode control. Then, a lumped uncertainty term containing parameter fluctuation and external disturbance is added in the prediction process of the SMPC framework. The accurate estimation of lumped uncertainty aforementioned is realized through an extended state observer (ESO). Finally, typical driving maneuvers are performed in simulation to verify the effectiveness of the proposed scheme. Compared with existing methods, the proposed control scheme can improve the tracking accuracy up to 36.3%.

KW - Autonomous vehicles

KW - path following

KW - sliding mode prediction control (SMPC)

KW - uncertainty estimation

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U2 - 10.1109/CCDC55256.2022.10034178

DO - 10.1109/CCDC55256.2022.10034178

M3 - Conference contribution

AN - SCOPUS:85149520343

T3 - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

SP - 22

EP - 27

BT - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 34th Chinese Control and Decision Conference, CCDC 2022

Y2 - 15 August 2022 through 17 August 2022

ER -

Ma T, Wang W , Yang C, Zhang Y, Li Y. A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation. In Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 22-27. (Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022). doi: 10.1109/CCDC55256.2022.10034178

A Path Following Scheme using Sliding Mode Prediction Control for Autonomous Vehicle with Uncertainty Estimation

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