Resilient Fuzzy Output‐Feedback Formation Control for Marine Harbor Unmanned Transport Vehicle Under Partial Information and DoS Attacks
ABSTRACT This study explores the issue of fuzzy adaptive resilient formation control for a marine harbor unmanned transport vehicle (UTV) platoon with partial state information and denial‐of‐service (DoS) attacks. Fuzzy logic systems (FLSs) are utilized to approximate the nonlinear dynamics of the considered vehicle model, and a fuzzy state observer is established to estimate the vehicle's unmeasurable states. To acquire estimations of unknown leader state information caused by DoS attacks, a distributed resilient formation observer is designed. Then, utilizing the introduced fuzzy state observer and resilient formation observer, a novel fuzzy adaptive output‐feedback resilient formation control method is formulated through the command‐filtered backstepping control technique. It is established that the proposed control approach can ensure individual stability and achieve convergence of formation tracking errors for the marine harbor UTV platoon under unmeasurable states and DoS attacks. Finally, comparative experiments under identical conditions further demonstrate that the proposed resilient control method can effectively counteract DoS attacks, ensuring platoon stability. In contrast, existing methods without DoS attack resistance result in divergent simulations and unstable platoon behavior, thus verifying the effectiveness of our designed distributed resilient formation controller.
Authors
- Shuo Ma (ORCID: https://orcid.org/0009-0007-7729-187X)
- Jun Ning (ORCID: https://orcid.org/0000-0002-5828-1322)
- Kewen Li (ORCID: https://orcid.org/0000-0003-0925-3314)
- Yongming Li (ORCID: https://orcid.org/0000-0003-1789-8278)
Institutions
- Liaoning University of Technology (CN)
- Dalian Maritime University (CN)
Publication Details
- Journal
- International Journal of Adaptive Control and Signal Processing
- Published
- 2025-11-19
- DOI
- https://doi.org/10.1002/acs.4097
- Primary Topic
- Distributed Control Multi-Agent Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00