Distributed Fuzzy Leader–Follower Vehicular Formation Control With Appointed-Time Performances and Obstacle Avoidance
In this paper, the formation control problem for a group of (both connected and unconnected) vehicles with appointed-time performances and obstacle avoidance is addressed. In the leader-follower framework, each follower is controlled to track its leader and achieve the prescribed formation configuration by maintaining a desired relative distance and a desired bearing angle with its leader. To ensure the convergence of formation errors to a preassigned steady-state zone within an appointed time frame, a novel piecewise continuous performance constraint function is proposed instead of the conventional exponential decay approach used in traditional prescribed performance control (PPC). In addition, an improved obstacle avoidance algorithm is designed to avoid static and moving obstacles on the path and to solve the problem of collision avoidance with unconnected vehicles within the formation. On this basis, combined with sliding-mode control (SMC) technology and fuzzy logic system (FLS) technology, a distributed appointed-time prescribed performance control (APPC) strategy is developed, which can not only achieve the designed formation within an appointed time, but also maintain connectivity and avoid collisions both within the formation and with the obstacles. Finally, simulation experiments are carried out to illustrate the effectiveness and advantages of the proposed control strategy and algorithm.
Authors
- XU Wei-dong
- Xiang‐Gui Guo (ORCID: https://orcid.org/0000-0002-3428-9362)
- Xiangpeng Xie (ORCID: https://orcid.org/0000-0003-4822-3134)
- Jianliang Wang (ORCID: https://orcid.org/0000-0002-7265-4391)
- Zheng‐Guang Wu (ORCID: https://orcid.org/0000-0002-7054-0008)
Institutions
- University of Nottingham Ningbo China (CN)
- Nanjing University of Posts and Telecommunications (CN)
- Zhejiang University (CN)
- Beihang University (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- IEEE Transactions on Vehicular Technology
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1109/tvt.2024.3462409
- Citations
- 10
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 3.28
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
- Basic and Applied Basic Research Foundation of Guangdong Province