Finite-Time Terminal Sliding Mode-Based Formation Control Scheme for a Robotic Fish
This article proposes a robotic fish formation control scheme that is based on finite-time terminal sliding mode to achieve coordinated tracking of multiple target paths under external disturbances and internal parameter perturbations. The method explores the lateral sliding mechanism of each body in the surge and sway directions by constructing a directional compensation guidance strategy that is based on a finite-time disturbance observer, thus enabling the precise coordinated movement of multiple robotic fish. Furthermore, this article acknowledges that the highly coupled dynamics of the robotic fish are susceptible to external environmental influences and modeling accuracy. Hence, a rapid global terminal sliding mode fuzzy controller that considers tangential displacement is introduced, and fuzzy adaptive methods are utilized to fit complex uncertainties. This approach mitigates the chattering problems commonly associated with traditional sliding mode control and enhances the error convergence speed and accuracy of the robotic fish formation system.
Authors
- Rob Law (ORCID: https://orcid.org/0000-0001-7199-3757)
- Yuxiang Sun (ORCID: https://orcid.org/0000-0002-7704-0559)
- Yuanqing Xu
- Edmond Q. Wu (ORCID: https://orcid.org/0000-0001-8611-8736)
- Dongfang Li (ORCID: https://orcid.org/0000-0001-9863-4172)
- Linlin Zeng
- Limin Zhu (ORCID: https://orcid.org/0000-0003-3194-6731)
Institutions
- Beijing Institute of Technology (CN)
- Shanghai Jiao Tong University (CN)
- University of Macau (MO)
- Fuzhou University (CN)
Publication Details
- Journal
- IEEE Transactions on Industrial Informatics
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1109/tii.2025.3556064
- Citations
- 1
- Primary Topic
- Underwater Vehicles and Communication Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.15
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province
- Key Laboratory of System Control and Information Processing