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Modeling and Control of Marine Craft
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Modeling and Control of Marine Craft

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (25 August 2024) | Viewed by 4617

Special Issue Editors

Prof. Tieshan Li

E-Mail Website
Guest Editor
School of automation engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: intelligent control theory and application of complex nonlinear systems; multi-agent system theory; ocean vehicle motion modeling and control
Dr. Xin Hu

E-Mail Website
Guest Editor
School of Mathematics and Statistics Science, Ludong University, Yantai 264025, China
Interests: motion control for marine vehicles; intelligent ship control theory and technology; anti-disturbance control
Dr. Nagi Abdussamie

E-Mail Website
Guest Editor
Australian Maritime College, University of Tasmania, Launceston, TAS 7250, Australia
Interests: offshore renewable energy structures (wind and wave); computational fluid dynamics; flow in porous media; wave-induced loads on offshore platforms and ships; risk and safety assessment of marine and mechanical systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To meet the needs of the development of marine crafts (vessels and underwater vehicles) in recent years, new research is being carried out all over the world to develop a variety of system identification methods and control strategies applicable to marine craft, such as adaptive control, fuzzy or neural-based control, sliding mode control, model prediction-based control, and so on. Several offshore operations of marine crafts require high-accuracy control in position and heading, such as oil drilling, hydrographic surveying, and wrecking. Intelligent control of the marine craft refers to the technology that achieves automatic control and autonomous operation of the marine craft using computers, sensors, networks, and machine learning. The motion control of marine craft also requires the rejection of time-varying unknown disturbances due to environmental conditions. The advances in new control technologies in marine craft bring key operational advantages, including intelligence, autonomy, greenness, safety, stability, efficiency, and low cost. The development of path planning, navigation, and control systems using advanced algorithms and data-driven and data-processing techniques is also a huge advantage in achieving intelligent ship control technology. This call for papers aims to provide an opportunity for researchers and practitioners to exchange the latest theoretical and technical achievements in the modeling and control techniques of marine craft and intelligent ships.

Prof. Tieshan Li
Dr. Xin Hu
Dr. Nagi Abdussamie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • dynamic positioning of marine craft
  • ocean vehicle motion modeling and control
  • intelligent ship control theory and technology
  • multi-intelligent cooperative control of marine craft
  • integrated energy system for ships
  • fault diagnosis and fault-tolerant control of marine craft
  • relevant review or technical papers

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Published Papers (5 papers)

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Research

19 pages, 13252 KiB  
Article
Distributed Optimization-Based Path Planning for Multiple Unmanned Surface Vehicles to Pass through Narrow Waters
by Shuo Li, Fei Teng, Geyang Xiao and Haoran Zhao
J. Mar. Sci. Eng. 2024, 12(8), 1246; https://doi.org/10.3390/jmse12081246 - 23 Jul 2024
Viewed by 689
Abstract
Safety and efficiency are important when Unmanned Surface Vehicles (USVs) pass through narrow waters in complex marine environments. This paper considers the issue of path planning for USVs passing through narrow waterways. We propose a distributed optimization algorithm based on a polymorphic network [...] Read more.
Safety and efficiency are important when Unmanned Surface Vehicles (USVs) pass through narrow waters in complex marine environments. This paper considers the issue of path planning for USVs passing through narrow waterways. We propose a distributed optimization algorithm based on a polymorphic network architecture, which maintains connectivity and avoids collisions between USVs while planning optimal paths. Firstly, the initial path through the narrow waterway is planned for each USV using the narrow water standard route method, and then the interpolating spline method is used to determine its corresponding functional form and rewrite the function as a local cost function for the USV. Secondly, a polymorphic network architecture and a distributed optimization algorithm were designed for multi-USVs to maintain connectivity and avoid collisions between USVs, and to optimize the initial paths of the multi-USV system. The effectiveness of the algorithm is demonstrated by Lyapunov stability analysis. Finally, Lingshui Harbor of Dalian Maritime University and a curved narrow waterway were selected for the simulation experiments, and the results demonstrate that the paths planned by multiple USVs were optimal and collision-free, with velocities achieving consistency within a finite time. Full article
(This article belongs to the Special Issue Modeling and Control of Marine Craft)
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19 pages, 22286 KiB  
Article
USVs Path Planning for Maritime Search and Rescue Based on POS-DQN: Probability of Success-Deep Q-Network
by Lu Liu, Qihe Shan and Qi Xu
J. Mar. Sci. Eng. 2024, 12(7), 1158; https://doi.org/10.3390/jmse12071158 - 10 Jul 2024
Viewed by 1158
Abstract
Efficient maritime search and rescue (SAR) is crucial for responding to maritime emergencies. In traditional SAR, fixed search path planning is inefficient and cannot prioritize high-probability regions, which has significant limitations. To solve the above problems, this paper proposes unmanned surface vehicles (USVs) [...] Read more.
Efficient maritime search and rescue (SAR) is crucial for responding to maritime emergencies. In traditional SAR, fixed search path planning is inefficient and cannot prioritize high-probability regions, which has significant limitations. To solve the above problems, this paper proposes unmanned surface vehicles (USVs) path planning for maritime SAR based on POS-DQN so that USVs can perform SAR tasks reasonably and efficiently. Firstly, the search region is allocated as a whole using an improved task allocation algorithm so that the task region of each USV has priority and no duplication. Secondly, this paper considers the probability of success (POS) of the search environment and proposes a POS-DQN algorithm based on deep reinforcement learning. This algorithm can adapt to the complex and changing environment of SAR. It designs a probability weight reward function and trains USV agents to obtain the optimal search path. Finally, based on the simulation results, by considering the complete coverage of obstacle avoidance and collision avoidance, the search path using this algorithm can prioritize high-probability regions and improve the efficiency of SAR. Full article
(This article belongs to the Special Issue Modeling and Control of Marine Craft)
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20 pages, 2541 KiB  
Article
Distributed Energy Dispatch for Geo-Data Centers Port Microgrid
by Qi Qu, Fei Teng, Qi Xu and Yushuai Li
J. Mar. Sci. Eng. 2024, 12(6), 916; https://doi.org/10.3390/jmse12060916 - 30 May 2024
Viewed by 549
Abstract
With the development of port automation and artificial intelligence, coordination with multi-geographic data centers (Geo-DCs) has become a viable solution to address the issue of limited port computing resources. This study proposes a distributed energy dispatch method for the port microgrid coordinated with [...] Read more.
With the development of port automation and artificial intelligence, coordination with multi-geographic data centers (Geo-DCs) has become a viable solution to address the issue of limited port computing resources. This study proposes a distributed energy dispatch method for the port microgrid coordinated with Geo-DCs (Geo-DCPM), aimed at reducing port carbon emissions and operational costs. Consider the single point of failure problem and high construction costs of centralized data centers. Geo-DCs are first introduced to solve the problem of insufficient computing resources in ports. An energy consumption calculation model for Geo-DCs is established, considering the data load delay constraint and the data space transfer constraint caused by specific delay-sensitive loads in the port microgrid. Then, an energy dispatch model (EDM) is constructed for the Geo-DCPM, taking into account carbon capture costs. Moreover, based on mixed-integer linear programming, a distributed algorithm is proposed to solve the EDM problem. Finally, the simulation results verify the effectiveness of the proposed method. Compared with the centralized algorithm, the packet loss rate of the distributed algorithm combined with Geo-DCs is significantly lower, reduced by about 70%. Full article
(This article belongs to the Special Issue Modeling and Control of Marine Craft)
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21 pages, 11395 KiB  
Article
Event-Triggered Supercavitating Vehicle Terminal Sliding Mode Control Based on Non-Recursive Observation
by Zichen Zhang, Xiaogang Wang, Zhicheng Wang and Shuai Wang
J. Mar. Sci. Eng. 2024, 12(6), 865; https://doi.org/10.3390/jmse12060865 - 23 May 2024
Viewed by 670
Abstract
Supercavitating vehicles present significant issues in controller design due to their multiphase flow-coupling characteristics. This study addresses force analysis and the construction of a 6-degree-of-freedom mathematical model for a supercavitating vehicle. A terminal sliding mode control law is intended to guarantee the quick [...] Read more.
Supercavitating vehicles present significant issues in controller design due to their multiphase flow-coupling characteristics. This study addresses force analysis and the construction of a 6-degree-of-freedom mathematical model for a supercavitating vehicle. A terminal sliding mode control law is intended to guarantee the quick tracking of the command signal for high-precision attitude control. To drastically lower the frequency of actuation and communication, a mechanism to trigger events is also introduced into the control link. A disturbance observer, which estimates system uncertainty using a non-recursive differentiator, improves the robustness of the system. The Lyapunov approach is used to prove that the system is stable. Numerical simulation results validate that the proposed method enhances control accuracy and robustness. The event-trigger mechanism reduces the execution frequency to 18.59%, effectively reducing the communication burden. Full article
(This article belongs to the Special Issue Modeling and Control of Marine Craft)
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25 pages, 6102 KiB  
Article
Distributed Formation Maneuvering Quantized Control of Under-Actuated Unmanned Surface Vehicles with Collision and Velocity Constraints
by Wei Wang, Yang Wang and Tieshan Li
J. Mar. Sci. Eng. 2024, 12(5), 848; https://doi.org/10.3390/jmse12050848 - 20 May 2024
Cited by 1 | Viewed by 854
Abstract
This paper focuses on a distributed cooperative time-varying formation maneuvering issue of under-actuated unmanned surface vehicles (USVs). A fleet of USVs is guided by a parameterized path with a time-varying formation while avoiding collisions and preserving the connectivity in the environment with multiple [...] Read more.
This paper focuses on a distributed cooperative time-varying formation maneuvering issue of under-actuated unmanned surface vehicles (USVs). A fleet of USVs is guided by a parameterized path with a time-varying formation while avoiding collisions and preserving the connectivity in the environment with multiple obstacles. In some surface missions, due to the obstacles in the external environment, the bandwidth limitations of the communication channel, and the hardware components/performance constraints of the USVs themselves, each vehicle is considered to be subject to model uncertainty, actuator quantization, sensor dead zone, and velocity constraints. During the control design process, the radial basis function (RBF) neural networks (NNs) are utilized to deal with nonlinear terms. Based on a nonlinear decomposition method, the relationship between the control signal and the quantization one is established, which overcomes the difficulty arising from actuator quantization. A Nussbaum function is introduced to handle the unknown output dead zone problem caused by reduced sensor sensitivity. Moreover, a universal-constrained function is employed to satisfy both the constrained and unconstrained requirements during formation keeping and obstacle avoidance. The Lyapunov stability theory confirmed that the error signals are uniformly ultimately bounded (UUB). The simulation results demonstrate the effectiveness of the proposed distributed formation control of multiple USVs. Full article
(This article belongs to the Special Issue Modeling and Control of Marine Craft)
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