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Applied Sciences
Volume 14
Issue 9
10.3390/app14093664
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Open AccessArticle
by Yang Sun SciProfilesScilitPreprints.orgGoogle Scholar Haonan Ning SciProfilesScilitPreprints.orgGoogle Scholar Haiyang Wang SciProfilesScilitPreprints.orgGoogle Scholar Chao Wang SciProfilesScilitPreprints.orgGoogle Scholar Jiushuai Zheng SciProfilesScilitPreprints.orgGoogle Scholar
Yang SunHaonan Ning
, Haiyang WangChao WangJiushuai Zheng
1
College of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
2
Key Laboratory of Intelligent Industrial Equipment Technology of Hebei Province, Handan 056038, China
3
Handan Key Laboratory of Intelligent Vehicles, Handan 056038, China
4
ji*zhong Energy Fengfeng Group Co., Ltd., Handan 056038, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(9), 3664; https://doi.org/10.3390/app14093664
Submission received: 2 April 2024/Revised: 21 April 2024/Accepted: 24 April 2024/Published: 25 April 2024
(This article belongs to the Topic Vehicle Dynamics and Control)
Abstract
With the rapid development of today’s society, the traffic environment has become more and more complex. As an essential part of intelligent vehicles, trajectory tracking has attracted significant attention for its stability and safety. It is prone to poor accuracy and instability in extreme working conditions like high speed. In this paper, a trajectory tracking control strategy to ensure lateral stability at a high speed and low attachment limit conditions is proposed for distributed drive vehicles. The model predictive controller (MPC) was used to control the front wheel angle, and the particle swarm optimization (PSO) algorithm was designed to optimize the MPC control parameters adaptively. The sliding mode controller controls the rear wheel angle, and the vehicle instability degree is judged by analyzing the β − phase plane. The controllers of different instability degrees are designed herein. Finally, a torque divider is designed to consider the actuation anti-slip. The designed controller is verified by Carsim and MATLAB-Simulink co-simulation. The results show that the trajectory tracking controller designed in this paper effectively improves the tracking accuracy under the premise of ensuring stability.
Keywords: distributed driving vehicle; model predictive control; particle swarm optimization algorithm; trajectory tracking; phase plane
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MDPI and ACS Style
Sun, Y.; Ning, H.; Wang, H.; Wang, C.; Zheng, J.Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis. Appl. Sci. 2024, 14, 3664.https://doi.org/10.3390/app14093664
AMA Style
Sun Y, Ning H, Wang H, Wang C, Zheng J.Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis. Applied Sciences. 2024; 14(9):3664.https://doi.org/10.3390/app14093664
Chicago/Turabian Style
Sun, Yang, Haonan Ning, Haiyang Wang, Chao Wang, and Jiushuai Zheng.2024. "Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis" Applied Sciences 14, no. 9: 3664.https://doi.org/10.3390/app14093664
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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MDPI and ACS Style
Sun, Y.; Ning, H.; Wang, H.; Wang, C.; Zheng, J.Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis. Appl. Sci. 2024, 14, 3664.https://doi.org/10.3390/app14093664
AMA Style
Sun Y, Ning H, Wang H, Wang C, Zheng J.Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis. Applied Sciences. 2024; 14(9):3664.https://doi.org/10.3390/app14093664
Chicago/Turabian Style
Sun, Yang, Haonan Ning, Haiyang Wang, Chao Wang, and Jiushuai Zheng.2024. "Trajectory Tracking Control Design for 4WS Vehicle Based on Particle Swarm Optimization and Phase Plane Analysis" Applied Sciences 14, no. 9: 3664.https://doi.org/10.3390/app14093664
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Appl. Sci.,EISSN 2076-3417,Published by MDPI
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