Unmanned surface vehicle cluster turning consistency control method based on dynamic regression expansion mechanism

By constructing a multi-agent directed network and a virtual reference model through a dynamic regression expansion mechanism, designing an adaptive gain control protocol, and combining an unknown parameter identifier for online compensation, the problem of decreased following accuracy and difficulty in stability analysis caused by uncertainty in maritime communication of unmanned surface vessel swarms was solved, and leader-following consistency control was achieved.

CN121785331BActive Publication Date: 2026-06-16NANJING TECH UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NANJING TECH UNIV
Filing Date
2026-03-08
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

In maritime communication, unmanned surface vessel swarms face challenges due to uncertainties such as changes in hydrodynamic parameters and wave and current disturbances, leading to decreased tracking accuracy and difficulties in stability analysis, making it hard to achieve consistent control of the leader's following.

⚗Method used

A control method based on dynamic regression expansion mechanism is adopted to construct a multi-agent directed network and a virtual reference model, design an adaptive gain control protocol, and combine an unknown parameter identifier for online compensation to achieve consistent steering control of unmanned surface vessel swarms.

🎯Benefits of technology

It improves following accuracy and stability in directed communication topology, reduces dependence on global information, and enhances applicability and steady-state consistency performance in maritime communication-constrained scenarios.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application relates to a dynamic regression expansion mechanism-based unmanned ship cluster turning consistency control method, which comprises the following steps: constructing an actual unmanned ship turning control physical model; constructing a multi-agent following unmanned ship directed network and a leader unmanned ship model with parameter uncertainty; constructing a multi-agent directed graph; constructing a virtual reference model and designing a control protocol to realize tracking of the virtual reference model to the leader unmanned ship; designing a control law of the following agent to realize tracking of the following unmanned ship to the virtual reference model; and designing an unknown parameter identifier to estimate an unknown parameter matrix of the following agent and realize unmanned ship cluster turning consistency cyclic control. The application solves the problem of following precision decline and stability analysis difficulty caused by the uncertainty of water power parameter change, wave flow disturbance and the like through directed information flow propagation in the traditional method, and realizes uncertain unmanned ship leader-following consistency control under the directed communication topology.
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