Journal of Marine Science and Engineering

Research

18 pages, 19214 KiB

Open AccessArticle

Enhancing Robust Adaptive Dynamic Positioning of Full-Actuated Surface Vessels: Reinforcement Learning Approach for Unknown Hydrodynamics

by Jiqiang Li, Wanjin Huang, Chenfeng Huang and Guoqing Zhang

J. Mar. Sci. Eng. 2025, 13(5), 993; https://doi.org/10.3390/jmse13050993 - 21 May 2025

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Abstract

In this article, a robust adaptive dynamic position-control problem is addressed for full-actuated surface vessels under coupled uncertainties from unmodeled hydrodynamic effects and time-varying external disturbances. To obtain a high-performance dynamic position controller, a reinforcement learning (RL) weights law involving actor and critic [...] Read more.

In this article, a robust adaptive dynamic position-control problem is addressed for full-actuated surface vessels under coupled uncertainties from unmodeled hydrodynamic effects and time-varying external disturbances. To obtain a high-performance dynamic position controller, a reinforcement learning (RL) weights law involving actor and critic networks is designed without knowledge of the model dynamics and the disturbance parameters. This can enhance the robustness of the closed-loop control system. Furthermore, dynamic surface control is integrated to diminish the design complexity resulting from the derivative of the kinematics, while ensuring semi-global uniformly ultimately bounded (SGUUB) stability through Lyapunov-based synthesis. Simulations are carried out to evaluate the superiority and feasibility of the proposed algorithm. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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22 pages, 8658 KiB

Open AccessArticle

Research on the On-Line Identification of Ship Maneuvering Motion Model Parameters and Adaptive Control

by Jinlai Liu, Lubin Chang, Luping Xu, Fang He and Yixiong He

J. Mar. Sci. Eng. 2025, 13(4), 753; https://doi.org/10.3390/jmse13040753 - 9 Apr 2025

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Abstract

This study aims to improve control accuracy across various ship types, speeds, and external interference scenarios using conventional control methods. The ship’s maneuvering model is identified online and the identified parameters are applied for self-adaptive course and track control, laying the groundwork for [...] Read more.

This study aims to improve control accuracy across various ship types, speeds, and external interference scenarios using conventional control methods. The ship’s maneuvering model is identified online and the identified parameters are applied for self-adaptive course and track control, laying the groundwork for intelligent ship control. A response-type ship maneuvering model is used, with a forgetting factor incorporated into the recursive least squares (RLS) algorithm based on the iterative least squares (ILS) method. This addresses the limitations of the ordinary least squares (OLS) method and the RLS algorithm’s reduced update speed with data accumulation. The forgetting factor recursive least squares (FFRLS) algorithm is employed to identify the maneuverability index parameters (K and T). Data for identification are obtained via a maneuvering simulator and the impact of different forgetting factors on the identification process is evaluated. The identified results are then used to calculate real-time optimal PID (OP-PID) parameters, leading to the development of a Self-adaptive OP-PID course control method. Simulations of course and track control are conducted with various ship types and environments, comparing the Self-adaptive OP-PID with existing OP-PID methods. Results show that the Self-adaptive OP-PID outperforms the OP-PID in course stability, convergence time, and track deviation under the same conditions. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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19 pages, 7695 KiB

Open AccessArticle

Nonlinear Compound Function-Based Course-Keeping Control for Ships in Rough Seas

by Guoshuai Li, Shimiao Wang, Xianku Zhang, Wenjun Zhang and Zhenhuan Zhang

J. Mar. Sci. Eng. 2025, 13(3), 534; https://doi.org/10.3390/jmse13030534 - 11 Mar 2025

Viewed by 392

Abstract

To ensure the safe navigation of ships in rough seas while reducing steering gear energy consumption and losses, a steering control system with small rudder output angles, low steering frequency, and high control performance was designed. A third-order closed-loop gain-shaping algorithm was employed [...] Read more.

To ensure the safe navigation of ships in rough seas while reducing steering gear energy consumption and losses, a steering control system with small rudder output angles, low steering frequency, and high control performance was designed. A third-order closed-loop gain-shaping algorithm was employed in the development of the controller, with the ultimate control strategy derived by embedding a nonlinear compound function between the proportional derivative (PD) controller and the second-order oscillation link to enhance control effectiveness. A nonlinear Nomoto model of the “Yupeng” ship was employed for simulation validation. The simulation results illustrated a 14.5% improvement in overall control performance achieved by the proposed controller compared to a nonlinear feedback controller. The controller’s robustness was additionally validated through the application of the Norrbin ship model. The proposed controller enhances the stability of ships in rough seas, effectively limiting the maximum rudder angle during turns and reducing the average rudder angle and steering frequency during navigation. This design aligns with practical requirements for maritime operations in heavy weather, contributing significantly to the economic, safe, and efficient navigation of ships. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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20 pages, 8044 KiB

Open AccessArticle

Distributed Improved RILOS Guidance-Based Formation Control of Underactuated ASVs for Cooperative Maritime Search

by Weili Guo, Cheng Liu, Feng Xu and Ting Sun

J. Mar. Sci. Eng. 2024, 12(11), 1911; https://doi.org/10.3390/jmse12111911 - 25 Oct 2024

Viewed by 824

Abstract

A distributed improved robust integral line-of-sight (RILOS) guidance-based sliding mode controller is designed for multiple underactuated autonomous surface vessels (ASVs) to perform cooperative maritime search operations. First, a parallel circle search pattern is designed based on the detection range of ASVs, which can [...] Read more.

A distributed improved robust integral line-of-sight (RILOS) guidance-based sliding mode controller is designed for multiple underactuated autonomous surface vessels (ASVs) to perform cooperative maritime search operations. First, a parallel circle search pattern is designed based on the detection range of ASVs, which can provide the reference formation shape. Second, an improved RILOS method is presented by introducing an integral term into the improved robust LOS method, which can counteract the disadvantageous effect of the unknown sideslip angle and kinematic discrepancy simultaneously. Third, distributed improved RILOS guidance is presented by integrating the extended second-order consensus algorithm into the improved RILOS method; then, the desired heading angle and desired velocity are generated for the control system simultaneously. Finally, the fuzzy logic system is integrated into the sliding mode control (SMC) method to approximate the unknown nonlinear function; then, a distributed improved RILOS guidance-based SMC controller is presented for multiple ASVs. The closed-loop signals are proved to be stable by the Lyapunov theory. The effectiveness of the presented method is verified by multiple simulations. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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16 pages, 5837 KiB

Open AccessArticle

A Fuzzy Fusion Method for Multi-Ship Collision Avoidance Decision-Making with Merchant and Fishing Vessels

by Xudong Gai, Qiang Zhang, Yancai Hu and Gang Wang

J. Mar. Sci. Eng. 2024, 12(10), 1822; https://doi.org/10.3390/jmse12101822 - 12 Oct 2024

Cited by 2 | Viewed by 1092

Abstract

In multi-vessel collision avoidance decision-making, the collision between merchant and fishing vessels is a significant challenge. This paper proposes a fuzzy fusion method for making avoidance decisions under the influence of the navigation environment. First, C-means clustering was used to collect and analyze [...] Read more.

In multi-vessel collision avoidance decision-making, the collision between merchant and fishing vessels is a significant challenge. This paper proposes a fuzzy fusion method for making avoidance decisions under the influence of the navigation environment. First, C-means clustering was used to collect and analyze Automatic Identification System (AIS) data from fishing vessels. On this basis, the environment collision risk was determined using fuzzy reasoning. Second, the basic collision risk is obtained by calculating the DCPA and TCPA, and the integrated Collision Risk Index (CRI) is concluded by fuzzy logic through basic collision risk and the environment collision risk. The similar cases are extracted from the fuzzy case database, and collision avoidance decisions for merchant vessels are formulated following fuzzy adjustments. Finally, to validate the method, data from Chengshantou coastal waters is employed for verification. The results show that it can provide theoretical guidance and practical value for merchant vessels in making collision avoidance decisions. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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22 pages, 17770 KiB

Open AccessArticle

Unmanned Surface Vessel–Unmanned Aerial Vehicle Cooperative Path Following Based on a Predictive Line of Sight Guidance Law

by Hugan Zhang, Jiaming Fan, Xianku Zhang, Haitong Xu and C. Guedes Soares

J. Mar. Sci. Eng. 2024, 12(10), 1818; https://doi.org/10.3390/jmse12101818 - 12 Oct 2024

Viewed by 1346

Abstract

This paper explores the cooperative control of unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) in maritime rescue and coastal surveillance. The USV-UAV system faces challenges of disturbances and substantial inertia-induced overshooting during path following. A novel position prediction line of sight [...] Read more.

This paper explores the cooperative control of unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) in maritime rescue and coastal surveillance. The USV-UAV system faces challenges of disturbances and substantial inertia-induced overshooting during path following. A novel position prediction line of sight (LOS) guidance law is proposed to address these issues for USV path following control. Radial basis function-based neural networks (RBF-NNs) are used to estimate disturbances, and a high-order differentiator is used to design a velocity observer for unknown USV velocity. The UAV control system employs proportional–derivative (PD) control with feedforward compensation for quadrotor control design and utilizes a finite-time converging third-order differentiator to differentiate non-continuous functions. The simulation results demonstrate strong robustness in the proposed USV-UAV cooperative control algorithm. It achieves path following control in the presence of wind and wave disturbances and exhibits minimal overshoot. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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17 pages, 1274 KiB

Open AccessArticle

Concise Adaptive Fault-Tolerant Formation Scaling Control for Autonomous Vehicles with Bearing Measurements

by Yu Lu and Ruisheng Sun

J. Mar. Sci. Eng. 2024, 12(8), 1407; https://doi.org/10.3390/jmse12081407 - 16 Aug 2024

Viewed by 1045

Abstract

In the bearing-based formation control of autonomous surface vehicles, the scaling maneuver capability is greatly limited when faced with actuator faults and uncertainties. Under these circumstances, to better realize the formation scaling maneuver, a concise adaptive fault-tolerant formation scaling control scheme is proposed [...] Read more.

In the bearing-based formation control of autonomous surface vehicles, the scaling maneuver capability is greatly limited when faced with actuator faults and uncertainties. Under these circumstances, to better realize the formation scaling maneuver, a concise adaptive fault-tolerant formation scaling control scheme is proposed for autonomous vehicles with bearing measurements. By means of dynamic surface control, parameter integration and the adaptive technique, the tedious derivative calculation of virtual control signals is avoided and the prescribed formation scaling maneuver is achieved without knowing specific information about the faults and models. It is shown that both yaw angle tracking errors and bearing errors are able, ultimately, to be made uniformly bounded using this scheme. Meanwhile, only one control parameter and one adaptive parameter need to be updated during the formation scaling process. Stability analysis and comparative results are provided to verify the validity of the developed scheme. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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24 pages, 5638 KiB

Open AccessArticle

Consensus Control of Heterogeneous Uncertain Multiple Autonomous Underwater Vehicle Recovery Systems in Scenarios of Implicit Reduced Visibility

by Zixuan Li, Wei Zhang, Wenhua Wu and Yefan Shi

J. Mar. Sci. Eng. 2024, 12(8), 1332; https://doi.org/10.3390/jmse12081332 - 6 Aug 2024

Viewed by 1105

Abstract

This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV [...] Read more.

This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV dynamics. Our main contributions include developing a feedback linearization model for heterogeneous multi-AUV systems that accounts for uncertainties, introducing an adaptive consensus controller based on relative positioning that effectively manages implicit visual interaction limitations and validating our strategies through stability analysis and numerical simulations. Our simulations demonstrate approximately a 60% improvement in accuracy compared to previous algorithms, highlighting the practical value of our approach in AUV recovery operations. These advancements provide a robust solution for consensus control in complex underwater environments. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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15 pages, 8718 KiB

Open AccessArticle

Refinement of Norrbin Model via Correlations between Dimensionless Cross-Flow Coefficient and Hydrodynamic Derivatives

by Guoshuai Li, Yifan Chen, Bingzheng Yan and Xianku Zhang

J. Mar. Sci. Eng. 2024, 12(5), 752; https://doi.org/10.3390/jmse12050752 - 30 Apr 2024

Viewed by 1286

Abstract

To develop a simplified and highly accurate ship motion model, this study thoroughly investigated the relationship between the dimensionless cross-flow coefficient and the four hydrodynamic derivatives of the Norrbin model. Eight different types of ships were simulated to explore the impact of dimensionless [...] Read more.

To develop a simplified and highly accurate ship motion model, this study thoroughly investigated the relationship between the dimensionless cross-flow coefficient and the four hydrodynamic derivatives of the Norrbin model. Eight different types of ships were simulated to explore the impact of dimensionless cross-flow coefficients and individual hydrodynamic derivatives on the ship’s turning circle. A set of precise formulas is proposed to depict the interplay between these variables. The simulation outcomes indicate that the average deviation in the agreement between the turning circles produced by adjusting the dimensionless cross-flow coefficient and those predicted by modifying the four hydrodynamic derivatives was only 2.70%. Furthermore, the similarities between the two circles and the sea trail were significantly higher at 91.45% and 92.87% compared with the original Norrbin model’s accuracy of 78.12%. Adjusting the dimensionless cross-flow coefficients enabled the rapid identification of a curve that closely mirrored the sea trail. This research aimed to improve the accuracy of the Norrbin model and resolve issues related to determining the magnification of the hydrodynamic derivatives, laying a robust foundation for subsequent studies and applications in relevant domains. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships—2nd Edition)

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