Trajectory-Tracking for Mobile Vehicle Based on Iterative Learning Control
Trajectory tracking is currently one of the hot topics in the automotive field and has significant importance. Trajectory tracking mainly refers to the consistency between the path traveled within a specified time and a predetermined reference path. It is necessary to ensure that the mobile vehicle with no collisions and less time consumption during this time. Trajectory tracking has difficulties modeling and slowly algorithm. In view of the above situation, this article designs a disturbance PD type Iterative Learning Control (ILC) algorithm for trajectory tracking. When the mobile vehicle encounters obstacles or disturbances by the trajectory, it also can quickly adjust its planned by the system stability.
Authors
- Dongjie Tan (ORCID: https://orcid.org/0000-0002-0785-5015)
- Zhenxian Zheng (ORCID: https://orcid.org/0000-0002-6546-2324)
- Tengyue Yan (ORCID: https://orcid.org/0009-0006-3086-7870)
- Bohan Xu (ORCID: https://orcid.org/0000-0001-5876-1740)
- Xiaoxiao Du (ORCID: https://orcid.org/0000-0003-1504-966X)
- Lu Song (ORCID: https://orcid.org/0000-0002-4742-7816)
- Hao Ding (ORCID: https://orcid.org/0000-0001-9932-2971)
- Liyan Li (ORCID: https://orcid.org/0000-0002-7551-1476)
- Yueheng Li (ORCID: https://orcid.org/0000-0003-1327-3334)
- Jinzhuang Dou (ORCID: https://orcid.org/0000-0003-0090-4264)
Institutions
- Chinese Academy of Sciences (CN)
- Institute of Automation (CN)
Publication Details
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/ic2ecs64405.2024.10928317
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00