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Volume 25
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10.3390/s25030679
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Multi-Observer Fusion Based Minimal-Sensor Adaptive Control for Ship Dynamic Positioning Systems

by
Yanbin Wu
1,
Xiaomeng He
2,*,
Linlong Shi
3 and
Shengli Dong
4
1
College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
2
College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
3
Shanghai KeLiang InformationTechnology, Co., Shanghai 200233, China
4
Shanghai Ship and Shipping Research Institute Co., Shanghai 200135, China
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(3), 679; https://doi.org/10.3390/s25030679
Submission received: 19 December 2024 / Revised: 17 January 2025 / Accepted: 21 January 2025 / Published: 23 January 2025
(This article belongs to the Special Issue Intelligent Sensing and Control Technology for Unmanned Vehicles)
Versions Notes

Abstract

This paper proposes an adaptive dynamic positioning (DP) control method based on a multi-observer fusion architecture with minimal sensor requirements. A sliding mode observer is designed based on a high- and low-frequency superposition model to filter high-frequency state variables, while a finite-time convergence disturbance observer estimates unknown time-varying low-frequency disturbances online. For efficient handling of model uncertainties, a single-parameter learning neural network is implemented that requires only one parameter to be estimated online. The control system employs auxiliary dynamic systems to handle input saturation constraints and considers thruster system dynamics. Theoretical analysis demonstrates the stability of the observer-fusion control strategy, while simulation results based on the SimuNPS platform validate its effectiveness in state estimation and disturbance rejection compared to traditional sensor-dependent methods.
Keywords: multi-observer; minimal-sensor control; adaptive dynamic positioning; neural network learning; SimuNPS multi-observer; minimal-sensor control; adaptive dynamic positioning; neural network learning; SimuNPS

Share and Cite

MDPI and ACS Style

Wu, Y.; He, X.; Shi, L.; Dong, S. Multi-Observer Fusion Based Minimal-Sensor Adaptive Control for Ship Dynamic Positioning Systems. Sensors 2025, 25, 679. https://doi.org/10.3390/s25030679

AMA Style

Wu Y, He X, Shi L, Dong S. Multi-Observer Fusion Based Minimal-Sensor Adaptive Control for Ship Dynamic Positioning Systems. Sensors. 2025; 25(3):679. https://doi.org/10.3390/s25030679

Chicago/Turabian Style

Wu, Yanbin, Xiaomeng He, Linlong Shi, and Shengli Dong. 2025. "Multi-Observer Fusion Based Minimal-Sensor Adaptive Control for Ship Dynamic Positioning Systems" Sensors 25, no. 3: 679. https://doi.org/10.3390/s25030679

APA Style

Wu, Y., He, X., Shi, L., & Dong, S. (2025). Multi-Observer Fusion Based Minimal-Sensor Adaptive Control for Ship Dynamic Positioning Systems. Sensors, 25(3), 679. https://doi.org/10.3390/s25030679

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