@inproceedings{66b337a830614d7f9a7a080156f6f477,
title = "Trajectory tracking control for 4WD vehicles using MPC and adaptive fuzzy control",
abstract = "This paper proposes a control scheme considering both vehicle velocity responses and trajectory tracking performance for four wheels drive (4WD) vehicles, subject to the actuator constraints, external disturbance and various physical limits. The presented hierarchical control architecture consists of the trajectory planning module based on model predictive control (MPC) technique and dynamics control module based on direct adaptive fuzzy control approach. The upper layer MPC-based planner is utilized to achieve arbitrary reference trajectory tracking for the 4WD vehicle given by earth-fixed frame, as well as meeting various physical limits. Meanwhile, direct adaptive fuzzy controller is employed to track desired velocity signals generated by the upper planning module in the lower layer, sequentially the global asymptotical convergence of fuzzy adaptive controller is strictly guaranteed in sense of stability theorem. Simulation results are performed to validate feasibility of the presented control scheme and effectiveness of the developed control approaches.",
keywords = "4WD vehicle, Direct adaptive fuzzy control, Model predict control, Trajectory tracking",
author = "Lu Yang and Ming Yue and Teng Ma and Xiaoqiang Hou",
note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.23919/ChiCC.2017.8028850",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "9367--9372",
editor = "Tao Liu and Qianchuan Zhao",
booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",
address = "United States",
}