Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle
How to improve the velocity tracking accuracy is a core and difficult problem in autonomous driving, especially while some core parameters of the controlled vehicle cannot be measured or obtained accurately enough. Without employing a complex longitudinal dynamic model and some difficultly obtained...
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doaj-04ca99d2511e41e8886741f4cddccf5d2021-03-30T00:26:32ZengIEEEIEEE Access2169-35362019-01-01717671217671810.1109/ACCESS.2019.29565478917638Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous VehicleMingxing Li0https://orcid.org/0000-0002-6751-0342Yaqiong Xu1https://orcid.org/0000-0003-4406-9125Ming Lei2https://orcid.org/0000-0003-1304-2536Bin Zhou3https://orcid.org/0000-0002-1141-5557Seventh Research Division, Beihang University, Beijing, ChinaSeventh Research Division, Beihang University, Beijing, ChinaKey Laboratory of Public Safety Emergency Information Technology of Anhui Province, China Electronic Technology Group Corporation 38th Research Institute, Hefei, ChinaSchool of Electronic and Information Engineering, Beihang University, Beijing, ChinaHow to improve the velocity tracking accuracy is a core and difficult problem in autonomous driving, especially while some core parameters of the controlled vehicle cannot be measured or obtained accurately enough. Without employing a complex longitudinal dynamic model and some difficultly obtained engine parameters, a numerical reasonable model is established based on the off-line data of the vehicle motion. And based on this model, a feed-forward and feedback control scheme is presented and a parameter-varying controller with high robustness is designed. To verify the tracking performance, the electric vehicle model in Matlab2018b is used in the simulating process and results conclude that the new control strategy is very effective.https://ieeexplore.ieee.org/document/8917638/Velocity trackingnumerical reasonable modelautonomous vehicle |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mingxing Li Yaqiong Xu Ming Lei Bin Zhou |
spellingShingle |
Mingxing Li Yaqiong Xu Ming Lei Bin Zhou Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle IEEE Access Velocity tracking numerical reasonable model autonomous vehicle |
author_facet |
Mingxing Li Yaqiong Xu Ming Lei Bin Zhou |
author_sort |
Mingxing Li |
title |
Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle |
title_short |
Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle |
title_full |
Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle |
title_fullStr |
Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle |
title_full_unstemmed |
Velocity Tracking Control Based on Throttle-Pedal-Moving Data Mapping for the Autonomous Vehicle |
title_sort |
velocity tracking control based on throttle-pedal-moving data mapping for the autonomous vehicle |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
How to improve the velocity tracking accuracy is a core and difficult problem in autonomous driving, especially while some core parameters of the controlled vehicle cannot be measured or obtained accurately enough. Without employing a complex longitudinal dynamic model and some difficultly obtained engine parameters, a numerical reasonable model is established based on the off-line data of the vehicle motion. And based on this model, a feed-forward and feedback control scheme is presented and a parameter-varying controller with high robustness is designed. To verify the tracking performance, the electric vehicle model in Matlab2018b is used in the simulating process and results conclude that the new control strategy is very effective. |
topic |
Velocity tracking numerical reasonable model autonomous vehicle |
url |
https://ieeexplore.ieee.org/document/8917638/ |
work_keys_str_mv |
AT mingxingli velocitytrackingcontrolbasedonthrottlepedalmovingdatamappingfortheautonomousvehicle AT yaqiongxu velocitytrackingcontrolbasedonthrottlepedalmovingdatamappingfortheautonomousvehicle AT minglei velocitytrackingcontrolbasedonthrottlepedalmovingdatamappingfortheautonomousvehicle AT binzhou velocitytrackingcontrolbasedonthrottlepedalmovingdatamappingfortheautonomousvehicle |
_version_ |
1724188298291707904 |