CLC number: TP273
On-line Access: 2020-07-10
Received: 2019-04-08
Revision Accepted: 2019-09-16
Crosschecked: 2020-06-03
Cited: 0
Clicked: 6534
Citations: Bibtex RefMan EndNote GB/T7714
Hong-chao Wang, Wei-wei Zhang, Xun-cheng Wu, Hao-tian Cao, Qiao-ming Gao, Su-yun Luo. A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(7): 1059-1073.
@article{title="A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions",
author="Hong-chao Wang, Wei-wei Zhang, Xun-cheng Wu, Hao-tian Cao, Qiao-ming Gao, Su-yun Luo",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="7",
pages="1059-1073",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1900185"
}
%0 Journal Article
%T A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions
%A Hong-chao Wang
%A Wei-wei Zhang
%A Xun-cheng Wu
%A Hao-tian Cao
%A Qiao-ming Gao
%A Su-yun Luo
%J Frontiers of Information Technology & Electronic Engineering
%V 21
%N 7
%P 1059-1073
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900185
TY - JOUR
T1 - A double-layered nonlinear model predictive control based control algorithm for local trajectory planning for automated trucks under uncertain road adhesion coefficient conditions
A1 - Hong-chao Wang
A1 - Wei-wei Zhang
A1 - Xun-cheng Wu
A1 - Hao-tian Cao
A1 - Qiao-ming Gao
A1 - Su-yun Luo
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 7
SP - 1059
EP - 1073
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1900185
Abstract: We present a double-layered control algorithm to plan the local trajectory for automated trucks equipped with four hub motors. The main layer of the proposed control algorithm consists of a main layer nonlinear model predictive control (MLN-MPC) controller and a secondary layer nonlinear MPC (SLN-MPC) controller. The MLN-MPC controller is applied to plan a dynamically feasible trajectory, and the SLN-MPC controller is designed to limit the longitudinal slip of wheels within a stable zone to avoid the tire excessively slipping during traction. Overall, this is a closed-loop control system. Under the off-line co-simulation environments of AMESim, Simulink, dSPACE, and TruckSim, a dynamically feasible trajectory with collision avoidance operation can be generated using the proposed method, and the longitudinal wheel slip can be constrained within a stable zone so that the driving safety of the truck can be ensured under uncertain road surface conditions. In addition, the stability and robustness of the method are verified by adding a driver model to evaluate the application in the real world. Furthermore, simulation results show that there is lower computational cost compared with the conventional PID-based control method.
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