Continuous Robust Trajectory Tracking Control for Autonomous Ground Vehicles Considering Lateral and Longitudinal Kinematics and Dynamics via Recursive Backstepping
Ming Xin, Yue Yin, Kai Zhang, David Lackner, Zhongchao Ren, Mark Minor
Abstract
Maintaining lateral and longitudinal trajectory tracking accuracy is challenging for autonomous ground vehicles (AGVs). This paper considers kinematics and dynamics of longitudinal and lateral motion to form a novel composite structure considering the cross-impacts of acceleration and steering commands on tracking errors in the lateral and longitudinal directions, respectively. The multi-tiered structure uses backstepping with smooth robust control to iteratively map kinematics-based velocity and yaw rate commands to slip-yaw dynamics-based acceleration and steering commands. In kinematics, longitudinal tracking error is stabilized by sliding mode control (SMC) while variable structure control (VSC) stabilizes lateral tracking error and balances tracking accuracy and steering gracefulness. Backstepping extends these commands through vehicle dynamics to provide robust steering and acceleration commands. Cross impacts between lateral and longitudinal motion is addressed by vehicle modeling and controller designs. A robust observer is applied for sideslip estimation to reject uncertainties. Peaking from the high gain observer and robust control is addressed. Stability analysis is provided and field experiments on an open road demonstrate and validate effectiveness of the controllers.
BibTeX
@inproceedings{iros2021_continuousrobust,
title = {Continuous Robust Trajectory Tracking Control for Autonomous Ground Vehicles Considering Lateral and Longitudinal Kinematics and Dynamics via Recursive Backstepping},
author = {Ming Xin and Yue Yin and Kai Zhang and David Lackner and Zhongchao Ren and Mark Minor},
booktitle = {IROS 2021},
year = {2021}
}