Efficient anti-disturbance with collision-obstacle avoidance for under-actuated ships under signal quantization
•Collision-obstacle avoidance is achieved in formation of under-actuated ships.•Anti-disturbance compensation mechanism improves formation control accuracy.•State and input quantization with event-triggering enables efficient formation result. This paper presents a high-execution efficient anti-dist...
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| Veröffentlicht in: | Ocean engineering Jg. 343; S. 123123 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
15.01.2026
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| Schlagworte: | |
| ISSN: | 0029-8018 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •Collision-obstacle avoidance is achieved in formation of under-actuated ships.•Anti-disturbance compensation mechanism improves formation control accuracy.•State and input quantization with event-triggering enables efficient formation result.
This paper presents a high-execution efficient anti-disturbance formation scheme with collision-obstacle avoidance for under-actuated ships with signal quantization. The formation scheme is built on an improved artificial potential field method and an event-triggered mechanism for underactuated unmanned surface vehicles (USVs), incorporating signal quantization and actuator fault tolerance simultaneously. Firstly, this scheme introduces an improved artificial potential field repulsive function to achieve collaborative collision avoidance and obstacle avoidance at the dynamic level. Secondly, the strategy uses an extended state observer (ESO) to estimate each USV’s quantized state and model uncertainty without needing quantizer parameters. A linear model to describe input quantization with actuator faults is also considered. Subsequently, an event-triggered collision avoidance control strategy is proposed to further reduce the communication burden. The proposed formation control strategy’s stability and effectiveness are rigorously proven via input-to-state stability theory and validated through simulations. |
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| ISSN: | 0029-8018 |
| DOI: | 10.1016/j.oceaneng.2025.123123 |