A high-speed unmanned surface vehicle path tracking control method based on improved EMPC

By improving the EMPC control method and the egret flock optimization algorithm, the problems of control accuracy loss and drift angle in high-speed unmanned surface vessel path tracking were solved, achieving higher control accuracy and adaptability, and enhancing resistance to environmental disturbances.

CN115951581BActive Publication Date: 2026-03-20JIANGSU UNIV OF SCI & TECH
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Patent Information

Application Number
CN202310018545.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-01-06
Publication Date
2026-03-20
Estimated Expiration
2043-01-06

AI Technical Summary

Technical Problem

Existing technologies for path tracking control of high-speed unmanned surface vessels suffer from problems such as loss of control accuracy, weak adaptive capability of guidance parameters, and susceptibility to drift angle caused by environmental interference.

Method used

An improved model predictive control (EMPC) combined with the egret flock optimization algorithm is adopted. By optimizing the LOS forward radius and disturbance compensation, an adaptive path tracking controller is designed. The egret flock optimization algorithm is used to solve the optimal control law offline, and real-time control is performed online.

Benefits of technology

It improves the accuracy and adaptability of path tracking control, reduces lateral deviation, enhances resistance to environmental disturbances, and improves the real-time performance and robustness of control.

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Abstract

The application discloses a high-speed unmanned ship path tracking control method based on improved EMPC, and comprises the following steps: step 1, constructing the basic model and the coordinate system of the underactuated high-speed unmanned ship on water surface; step 2, in the guidance method, the LOS front-view garden radius is optimized by the dynamic line-of-sight method in combination with the current ship speed, and the desired heading angle is obtained on the basis of the optimized LOS front-view garden radius in combination with the lateral deviation rate; step 3, in the offline state of the EMPC controller, the optimal control law is solved for each state partition in the offline state by the heron optimization algorithm, and the linear control law on each state partition and the corresponding partition is obtained; step 4, in the online state of the EMPC controller, the linear control law on the corresponding partition obtained in step 3 is found by the reachable partition searching method, the unmanned ship is controlled to run and track the last desired path point, and the tracking is completed. The application improves the control precision, reduces the lateral deviation and improves the adaptive ability of the guidance parameters.
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