Nonlinear Sliding-Mode Super-Twisting Reaching Law for Unmanned Surface Vessel Formation Control Under Coupling Deception Attacks
In this paper, a nonlinear sliding-mode super-twisting reaching law algorithm is designed to address the problem of coupling interference under deception attacks and actuator physical faults in USV formations during cooperative mining operations of a USVs-ROVs system. First, a USV model with attacks and disturbances is established, and a leader–follower formation system is designed. Then, based on the reaching law, the state error dynamic chatter can be effectively solved when it is far away from and reaches the sliding surface; a nonlinear sliding super-twisting reaching law is designed to improve the chatter characteristics of the sliding surface. Furthermore, to solve the problems of low fitting accuracy regarding control anomaly information and the difficulty of fending off signal-data interference attacks, a nonlinear saturation fault-tolerant filtering mechanism and a nonlinear fitting factor are designed. Finally, the stability of the algorithm is verified through Lyapunov theory. Under the same coupling deception probability, the nonlinear sliding-mode super-twisting reaching law algorithm designed in this paper enables the leader ship and each follower ship to reach stability within about 12s, and the formation system maintains its formation while also improving the control accuracy of each individual ship.
Authors
- Yancai Hu (ORCID: https://orcid.org/0000-0002-2215-3337)
- Yaping Zhu
- Xin Hu (ORCID: https://orcid.org/0000-0001-9043-9639)
- Qiang Zhang (ORCID: https://orcid.org/0000-0001-6765-930X)
- Yifan Wang (ORCID: https://orcid.org/0000-0003-1663-3120)
Institutions
- Ludong University (CN)
- Shandong Jiaotong University (CN)
Publication Details
- Journal
- Journal of Marine Science and Engineering
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3390/jmse13030561
- Citations
- 3
- Primary Topic
- Guidance and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 14.98
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province