A Trajectory Tracking Method for Deep-Sea Mining Vehicle

被引:0
作者
Wu, Senyuan [1 ]
Liu, Yuntao [1 ]
Cui, Can [1 ]
机构
[1] Ocean Univ China Qingdao, Coll Engn, Qingdao, Peoples R China
来源
PROCEEDINGS OF THE 2024 3RD INTERNATIONAL SYMPOSIUM ON INTELLIGENT UNMANNED SYSTEMS AND ARTIFICIAL INTELLIGENCE, SIUSAI 2024 | 2024年
关键词
Model predictive control; Deep-sea mining; Slip control; Trajectory tracking;
D O I
10.1145/3669721.3669732
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper innovatively proposes an MPC based trajectory tracking method that considers slip constraints (MPC-SC) for deep-sea mining vehicles during operation. Analyze the force on the mining vehicle and establish a dynamic model to calculate the slip rate online. Based on the relationship between traction force and slip rate, a reasonable slip rate constraint interval can be determined. A trajectory tracking method based on model predictive control is proposed to address the problem of large trajectory deviation in the trajectory tracking process of mining vehicles. The optimal predictive control is applied to the speed of the driving wheels on both sides of the mining vehicle at each time step. At the same time, a new slip rate control strategy is proposed to reasonably constrain the slip rate of the tracks on both sides to improve the driving performance of the mining vehicle. A reasonable slip rate threshold is set. When exceeding the threshold, the slip rate is constrained by reducing the speed of the driving wheels on both sides. In order to ensure smooth movement of the mining vehicle, a certain constraint control is applied to the speed difference between the driving wheels on both sides. Through simulation experiments, it has been verified that the proposed trajectory tracking method has a small trajectory tracking error, and the proposed slip control strategy can effectively reduce the slip rate of the tracks on both sides.
引用
收藏
页码:330 / 333
页数:4
相关论文
共 8 条
[1]  
AHMAD M, 2000, P P 2000 ICRA MILL C
[2]   A path following controller for deep-sea mining vehicles considering slip control and random resistance based on improved deep deterministic policy gradient [J].
Chen, Qihang ;
Yang, Jianmin ;
Mao, Jinghang ;
Liang, Zhixuan ;
Lu, Changyu ;
Sun, Pengfei .
OCEAN ENGINEERING, 2023, 278
[3]   Trajectory Tracking of Autonomous Vehicle Based on Model Predictive Control With PID Feedback [J].
Chu, Duanfeng ;
Li, Haoran ;
Zhao, Chenyang ;
Zhou, Tuqiang .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (02) :2239-2250
[4]   MPC: Current practice and challenges [J].
Darby, Mark L. ;
Nikolaou, Michael .
CONTROL ENGINEERING PRACTICE, 2012, 20 (04) :328-342
[5]   Anti-slip Control for Unmanned Underwater Tracked Bulldozer Based on Active Disturbance Rejection Control [J].
He, Dingchang ;
Li, Yong ;
Meng, Xiangpeng ;
Si, Qiaorui .
MECHATRONICS, 2022, 84
[6]   Position Control Considering Slip Motion of Tracked Vehicle Using Driving Force Distribution and Lateral Disturbance Suppression [J].
Kuwahara, Hiroaki ;
Murakami, Toshiyuki .
IEEE ACCESS, 2022, 10 :20571-20580
[7]   A brief review of recent progress on deep sea mining vehicle [J].
Leng, Dingxin ;
Shao, Shuai ;
Xie, Yingchun ;
Wang, Honghui ;
Liu, Guijie .
OCEAN ENGINEERING, 2021, 228 (228)
[8]   A Nonlinear Optimal Control Approach for Tracked Mobile Robots [J].
Rigatos, Gerasimos .
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2021, 34 (04) :1279-1300