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Special Issues
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: 25 August 2024 | Viewed by 646

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

Published Papers (2 papers)

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Research

21 pages, 2893 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 187
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)
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
Viewed by 272
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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