Ship course-keeping control of marine vessels using dual nonlinear modification strategy

Abstract Aiming at the high energy consumption and severe actuator wear associated with ship heading-keeping control under complex sea conditions, this paper proposes a dual nonlinear modified heading-keeping control algorithm. A second-order nonlinear Nomoto model considering speed reduction is established to better characterize ship maneuvering dynamics. Based on this model, a concise and robust controller is designed using the closed-loop gain shaping algorithm (CGSA). To further improve control performance, a bipolar S-function and a tangent function are introduced to nonlinearly modify the original linear feedback law, forming a dual nonlinear feedback structure. This modification preserves the steady-state performance of the system while enhancing robustness and reducing excessive rudder activity. Simulations are conducted in Simulink using the “ Yukun ” vessel as a case study, where Sea State 6 and Sea State 7 disturbances are modeled by a second-order oscillatory system driven by white noise. Compared with the linear CGSA controller, the proposed method reduces the maximum rudder angle by 31%, the MIA index by 28%, the MTV index by 15%, and the energy index by 51%. The results demonstrate that the proposed strategy can effectively maintain heading stability while significantly reducing control effort and energy consumption, indicating its potential for engineering application.

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Publication Details

Journal
Scientific Reports
Published
2026-08-24
DOI
https://doi.org/10.1038/s41598-026-64442-7
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Ship course-keeping control of marine vessels using dual nonlinear modification strategy

Xianku Zhang, Wenxuan Ma
Scientific Reports
Adaptive Control of Nonlinear Systems
article

Ship course-keeping control of marine vessels using dual nonlinear modification strategy

Xianku Zhang, Wenxuan Ma
article en

Abstract

Abstract Aiming at the high energy consumption and severe actuator wear associated with ship heading-keeping control under complex sea conditions, this paper proposes a dual nonlinear modified heading-keeping control algorithm. A second-order nonlinear Nomoto model considering speed reduction is established to better characterize ship maneuvering dynamics. Based on this model, a concise and robust controller is designed using the closed-loop gain shaping algorithm (CGSA). To further improve control performance, a bipolar S-function and a tangent function are introduced to nonlinearly modify the original linear feedback law, forming a dual nonlinear feedback structure. This modification preserves the steady-state performance of the system while enhancing robustness and reducing excessive rudder activity. Simulations are conducted in Simulink using the “ Yukun ” vessel as a case study, where Sea State 6 and Sea State 7 disturbances are modeled by a second-order oscillatory system driven by white noise. Compared with the linear CGSA controller, the proposed method reduces the maximum rudder angle by 31%, the MIA index by 28%, the MTV index by 15%, and the energy index by 51%. The results demonstrate that the proposed strategy can effectively maintain heading stability while significantly reducing control effort and energy consumption, indicating its potential for engineering application.

Scientific Reports
Dalian Maritime University (CN)
National Science Foundation, National Natural Science Foundation of China, Ministry of Education of the People's Republic of China, China Scholarship Council, Dalian Maritime University, Department of Science and Technology of Liaoning Province, Higher Education Discipline Innovation Project, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 14%
Adaptive Control of Nonlinear Systems
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Ship course-keeping control of marine vessels using dual nonlinear modification strategy — Xianku Zhang, Wenxuan Ma · Scientific Reports (2026) | TGRS Research Map | TGRS