弹道
控制理论(社会学)
模型预测控制
PID控制器
跟踪(教育)
跟踪误差
平滑度
车辆动力学
计算机科学
控制工程
工程类
控制(管理)
人工智能
数学
汽车工程
温度控制
教育学
物理
数学分析
心理学
天文
作者
Delin Chu,Haoran Li,Chenyang Zhao,Tuqiang Zhou
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:: 1-12
被引量:14
标识
DOI:10.1109/tits.2022.3150365
摘要
The simplified vehicle model often results in inaccuracy with respect to the conventional model predictive control (MPC) as it causes steady error in tracking control, which has negative implications for vehicle cornering. This study presents a trajectory planning and tracking framework, which applies artificial potential to obtain target trajectory and MPC with PID feedback to effectively track planned trajectory. The experimental and simulation results are then presented to demonstrate the improved performance in tracking accuracy and steering smoothness compared to that of the conventional MPC control. Especially during negotiating a curve, its steady state error is close to 0.
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