Submit to JMSE Review for JMSE Propose a Special Issue

Journal Menu

Journal Browser

Optimal Maneuvering and Control of Ships

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

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 December 2023) | Viewed by 21784

Share This Special Issue

Special Issue Editors

Prof. Dr. Guoqing Zhang

E-Mail Website
Guest Editor

Navigation College, Dalian Maritime University, Dalian 116026, China
Interests: robust control; ship motion control
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Weidong Zhang

E-Mail Website
Guest Editor

Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: nonlinear system; robust control; control of marine vehicles
Special Issues, Collections and Topics in MDPI journals

Dr. Caoyang Yu

E-Mail Website
Guest Editor

School of Oceanography, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: maneuvering; guidance and control of marine vehicles; identification theory and application

Special Issue Information

Dear Colleagues,

In recent years, marine surface vehicles have attracted a lot of attention and prevailed in diversified scenarios, such as marine environmental monitoring, autonomous cruise and maritime surveillance, etc. A large amount of meaningful research progress has been acquired for the maneuvering and control of marine surface vehicles, including the path following control, the formation control, the obstacle avoidance control, the cooperative maneuvering for the multi vehicles, and so on. This progress may facilitate the application of theoretical algorithms in the intelligent navigation and cooperative maneuvering. The purpose of special session at the journal of marine science and engineering is to provide the latest research results in fields of the optimal maneuvering and control of ships. The Special Issue includes, but is not limited to, the following topics: marine surface vehicles, maneuvering in marine environment, course keeping and path following control, cooperative control mission for multi vehicles, dynamic positioning and other advanced techniques in automatic navigation.

Dr. Guoqing Zhang
Prof. Dr. Weidong Zhang
Dr. Caoyang Yu
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

marine surface vehicles
maneuvering in marine environment
course keeping and path following control
cooperative control mission for multi vehicles
dynamic positioning
other advanced techniques in automatic navigation

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (11 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

17 pages, 1329 KiB

Open AccessArticle

Nonlinear Model Predictive Control for a Dynamic Positioning Ship Based on the Laguerre Function

by Xiaobin Qian, Helong Shen, Yong Yin and Dongdong Guo

J. Mar. Sci. Eng. 2024, 12(2), 294; https://doi.org/10.3390/jmse12020294 - 7 Feb 2024

Cited by 2 | Viewed by 1497

Abstract

In this paper, we present a novel nonlinear model predictive control (NMPC) algorithm based on the Laguerre function for dynamic positioning ships to solve the problems of input saturation, unknown time-varying disturbances, and heavy computation. The nonlinear model of a dynamic positioning ship is presented as a linear model, transformed from a standard affine nonlinear state-space model by precise feedback linearization. The environmental disturbance is overcome using an integrator. The time cost of the proposed nonlinear control algorithm is decreased by inducing the Laguerre function to describe the feedback-linearization system input increments. The Laguerre function reduces the matrix dimensions of the nonlinear optimization problem. The simulation results for a DP supply vessel showed that the novel algorithm maintained the effective control performance of the original nonlinear model predictive control algorithm and had a reduced computation load to satisfy the requirements of real-time operation. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

18 pages, 2982 KiB

Open AccessArticle

Cooperative Maritime Search of Multi-Ship Based on Improved Robust Line-of-Sight Guidance

by Weili Guo, Cheng Liu and Ting Sun

J. Mar. Sci. Eng. 2024, 12(1), 105; https://doi.org/10.3390/jmse12010105 - 5 Jan 2024

Cited by 3 | Viewed by 1190

Abstract

In this paper, an improved robust line-of-sight (RLOS) guidance-based fuzzy sliding mode controller is presented to control underactuated ships to conduct the cooperative maritime search operation under the presented improved creeping line search method. First, considering that the ship cannot perform turning with corners, an improved creeping line search method is presented by integrating the Bezier method into the traditional creeping line search method to smooth the transition points with corners and employing the cubic spline interpolation method to generate continuous reference paths. Second, an improved RLOS guidance method is presented for the first time by exploring the idea of robust adaptive control to mitigate the chattering effect of the RLOS guidance. Third, the fuzzy logic system with approximate ability is integrated into the design of sliding mode controller to handle unknown nonlinear model dynamics and environmental disturbances. Finally, an improved RLOS guidance-based fuzzy sliding mode controller is presented. The closed-loop stability is guaranteed by the Lyapunov theorem. Comparative simulations are conducted to illustrate the advantages and verify the effectiveness of the presented method. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

22 pages, 10237 KiB

Open AccessArticle

Adaptive Fuzzy Quantized Control for a Cooperative USV-UAV System Based on Asynchronous Separate Guidance

by Yingshuo Xing, Guoqing Zhang and Jiqiang Li

J. Mar. Sci. Eng. 2023, 11(12), 2331; https://doi.org/10.3390/jmse11122331 - 9 Dec 2023

Cited by 4 | Viewed by 1429

Abstract

This paper focuses predominantly on the multi-tasks carried out by the cooperative unmanned surface vehicle-unmanned aerial vehicle (USV-UAV) system in which the input quantization is considered. The proposed cooperative scheme consists of the asynchronous separate guidance and adaptive fuzzy quantized control algorithm. The proposed guidance law takes full advantage of subsystems whilst considering the maneuverability of these subsystems in order to achieve the goal of executing multi-tasks. In contrast to previous guidance laws, although the same waypoint path is planned, the calculation for guidance law proposed is based on speed rather than time, which in reality is more relevant. As for the controls, an adaptive fuzzy quantized controller was developed to reduce undue exertion on the actuator. By fusing the dynamic surface control (DSC) and fuzzy logic system (FLS), a hysteresis quantizer has been introduced to reduce the transmission load. By properly adjusting the quantization density, the number of quantizations was reduced whilst maintaining a favorable control performance. All of the stated variables are semi-global uniform ultimate bounded (SGUUB) and the stability of the USV-UAV system is proofed through the Lyapunov theorem. Finally, the advantages of the proposed scheme are evaluated by two simulative experiments, exhibiting the favorable tracking accuracy and reduced wear on the actuators. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

16 pages, 4810 KiB

Open AccessArticle

A Numerical Study on Modeling Ship Maneuvering Performance Using Twin Azimuth Thrusters

by Tunbiao Wu, Ronghui Li, Qinglong Chen, Guiyuan Pi, Shijie Wan and Qiao Liu

J. Mar. Sci. Eng. 2023, 11(11), 2167; https://doi.org/10.3390/jmse11112167 - 13 Nov 2023

Cited by 4 | Viewed by 2660

Abstract

A methodology of mathematical testing is proposed for a ship with twin azimuth thrusters based on numerical calculations. An unmanned surface vessel (USV) powered by two azimuth thrusters is considered, which is a model-scale configuration. The Ship Maneuvering Mathematical Model Group (MMG) model is introduced to describe forces on the hull and propellers. A set of captive tests (planar motion mechanism (PMM) and open-water tests) were simulated using STAR-CCM+ (16.06.008-R8) software to obtain hull hydrodynamic derivatives and azimuth thruster hydrodynamic coefficients. A maneuvering test of the model-scale ship with two azimuth thrusters is built based on numerical results, and numerical results are compared with the model-scale experimental data to validate the feasibility of numerical methods. The findings show that the usability of the developed mathematical test in predicting the maneuvering ability of ships with two azimuth thrusters is confirmed through numerical calculations. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

19 pages, 5707 KiB

Open AccessArticle

Nonparametric Modeling and Control of Ship Steering Motion Based on Local Gaussian Process Regression

by Zi-Lu Ouyang, Zao-Jian Zou and Lu Zou

J. Mar. Sci. Eng. 2023, 11(11), 2161; https://doi.org/10.3390/jmse11112161 - 13 Nov 2023

Cited by 3 | Viewed by 1519

Abstract

This paper aims to study the nonparametric modeling and control of ship steering motion. Firstly, the black box response model is derived based on the Nomoto model. Then, the establishment of a nonparametric response model and prediction of ship steering motion are realized by applying the local Gaussian process regression (LGPR) algorithm. To assess the performance of LGPR, two cases are studied, including a Mariner class vessel by using simulation data and a KVLCC2 tanker model by using experimental data. The results reveal that the response model identified by LGPR presents good prediction accuracy and low computational burden. Finally, the identified response model is used as the basis for developing the ship heading controller, and the results demonstrate that the proposed controller is able to achieve good dynamic performance. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

24 pages, 12215 KiB

Open AccessArticle

Trajectory Tracking Design for Unmanned Surface Vessels: Robust Control Approach

by Yung-Hsiang Chen, Ming-Zhen Ellis-Tiew, Yu-Hsiang Chan, Guan-Wun Lin and Yung-Yue Chen

J. Mar. Sci. Eng. 2023, 11(8), 1612; https://doi.org/10.3390/jmse11081612 - 17 Aug 2023

Cited by 3 | Viewed by 1399

Abstract

We propose a robust nonlinear trajectory tracking design by integrating a nonlinear model transformation, robust disturbance eliminator, and trajectory generator for unmanned surface vessels influenced by modeling uncertainties and ocean environmental disturbances. We designed this nonlinear control law to help control unmanned surface vessels following any designated sail trajectory constructed by the trajectory generator. With cubic spline interpolation, this trajectory generator can generate arbitrary smooth trajectories. Simulation results show that the proposed nonlinear robust control law has precise trajectory tracking performance and a robustness property for unmanned surface vessels under harsh ocean environmental disturbances and modeling uncertainties. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

17 pages, 3802 KiB

Open AccessArticle

Sparse Bayesian Relevance Vector Machine Identification Modeling and Its Application to Ship Maneuvering Motion Prediction

by Yao Meng, Xianku Zhang, Guoqing Zhang, Xiufeng Zhang and Yating Duan

J. Mar. Sci. Eng. 2023, 11(8), 1572; https://doi.org/10.3390/jmse11081572 - 9 Aug 2023

Cited by 1 | Viewed by 1567

Abstract

In order to establish a sparse and accurate ship motion prediction model, a novel Bayesian probability prediction model based on relevance vector machine (RVM) was proposed for nonparametric modeling. The sparsity, effectiveness, and generalization of RVM were verified from two aspects: (1) the processed Sinc function dataset, and (2) the tank test dataset of the KRISO container ship (KCS) model. The KCS was taken as the main research plant, and the motion prediction models of KCS were obtained. The

ε

-support vector regression and

υ

-support vector regression were taken as the compared algorithms. The sparsity, effectiveness, and generalization of the three algorithms were analyzed. According to the trained prediction models of the three algorithms, the number of relevance vectors was compared with the number of support vectors. From the prediction results of the Sinc function and tank test datasets, the highest percentage of relevance vectors in the trained sample was below 17%. The final prediction results indicated that the proposed nonparametric models had good prediction performance. They could ensure good sparsity while ensuring high prediction accuracy. Compared with the SVR, the prediction accuracy can be improved by more than 14.04%, and the time consumption was also relatively lower. A training model with good sparsity can reduce prediction time. This is essential for the online prediction of ship motion. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

23 pages, 742 KiB

Open AccessArticle

Robust IMM Filtering Approach with Adaptive Estimation of Measurement Loss Probability for Surface Target Tracking

by Chen Chen, Weidong Zhou and Lina Gao

J. Mar. Sci. Eng. 2023, 11(6), 1243; https://doi.org/10.3390/jmse11061243 - 17 Jun 2023

Viewed by 1919

Abstract

A suitable jump Markov system (JMS) filtering approach provides an efficient technique for tracking surface targets. In complex surface target tracking situations, due to the joint influences of lost measurements with an unknown probability and heavy-tailed measurement noise (HTMN), the estimation accuracy of conventional interacting multiple model (IMM) methods may be seriously degraded. Aiming to address the filtering issues in JMSs with HTMNs and random measurement losses, this paper presents an IMM filtering approach with the adaptive estimation of unknown measurement loss probability. In this study, we assumed that the measurement noises obey student’s t-distributions and then proposed Bernoulli random variables (BRVs) to characterize the random measurement loss. Notably, by converting the two likelihood functions from the weighted sum form to exponential multiplication, we established hierarchical Gaussian state space models to directly utilize the variational inference method. The system state vectors, unknown distribution parameters, BRVs, and unknown measurement loss probabilities were estimated simultaneously according to the variational Bayesian inference in the IMM framework. The results of maneuvering target tracking simulations verified that the presented filtering approach demonstrated superior estimation accuracy compared to existing IMM filters. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

17 pages, 4498 KiB

Open AccessArticle

Advanced Marine Craft Model Identification via Multi-Kernel Weighted Least Square Support Vector Machine and Characteristic Model Techniques

by Tianqi Pei, Caoyang Yu, Yiming Zhong, Junjun Cao and Lian Lian

J. Mar. Sci. Eng. 2023, 11(5), 1091; https://doi.org/10.3390/jmse11051091 - 22 May 2023

Cited by 3 | Viewed by 1703

Abstract

This paper combines the piecewise Cubic Hermite (CH) interpolation algorithm and the weighted least square support vector machine (WLS-SVM) to improve identification accuracy for marine crafts built based on the characteristic model. The characteristic model is first used to describe the heading dynamics of marine crafts and is a superior model to the traditional response model in both accuracy and complexity. Especially in order to improve identification accuracy, a CH-based data preprocessing strategy is utilized to densify and smooth data for further accurate identification. Subsequently, the combination of the linear kernel function and the Gaussian kernel function is introduced in the conventional WLS-SVM method, which renders global and local performance improvements compared with the conventional WLS-SVM method. Finally, informative maneuvers composed of Zigzag and Sine are carried out to test the performance of the improved identification method. Compared to the conventional LS-SVM method based on the response model, the root mean square error of the proposed CH-MK-WLS-SVM method based on the characteristic model is reduced by an order of magnitude in the presence of sensor noise. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

23 pages, 7333 KiB

Open AccessArticle

Intervehicle Security-Based Robust Neural Formation Control for Multiple USVs via APS Guidance

by Guoqing Zhang, Shilin Yin, Chenfeng Huang and Weidong Zhang

J. Mar. Sci. Eng. 2023, 11(5), 1020; https://doi.org/10.3390/jmse11051020 - 10 May 2023

Cited by 5 | Viewed by 1759

Abstract

This paper focuses on the intervehicle security-based robust formation control of unmanned surface vehicles (USVs) to implement the formation switch mission. In the scheme, a novel adaptive potential ship (APS)-based guidance principle is developed to prevent intervehicle collisions, which is common and threatening when maneuvering a formation switch. By employing the artificial potential field (APF), the APS can program the real-time attitude reference for USVs by using the security intervehicle distance while achieving the path-following task. As for the control part, a robust adaptive formation control algorithm is proposed to effectively stabilize the USVs to the APS via the fusion of the disturbance observer (DOB) and by using the robust neural damping technique. Regarding the merits of the improved design of the DOB, the weight compression of the neural networks can effectively simplify the structure of the DOB and enhance the observation accuracy of the external disturbance. This can facilitate the avoidance of intervehicle collisions and guarantee the application of the theoretical algorithm in engineering practice. Considerable effort has been made to obtain the semiglobally uniform ultimate bounded (SGUUB) stability via theoretical analysis. Finally, with the sailing scene in a narrow channel, the simulated experiment is illustrated to verify the security performance of the proposed strategy. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Figure 1

32 pages, 15071 KiB

Open AccessArticle

Optimal Route Generation and Route-Following Control for Autonomous Vessel

by Min-Kyu Kim, Jong-Hwa Kim and Hyun Yang

J. Mar. Sci. Eng. 2023, 11(5), 970; https://doi.org/10.3390/jmse11050970 - 2 May 2023

Cited by 3 | Viewed by 3273

Abstract

In this study, basic research was conducted regarding the era of autonomous vessels and artificial intelligence (deep learning, big data, etc.). When a vessel is navigating autonomously, it must determine the optimal route by itself and accurately follow the designated route using route-following control technology. First, the optimal route should be generated in a manner that ensures safety and reduces fuel consumption by the vessel. To satisfy safety requirements, sea depth, under-keel clearance, and navigation charts are used; algorithms capable of determining and shortening the distance of travel and removing unnecessary waypoints are used to satisfy the requirements for reducing fuel consumption. In this study, a reinforcement-learning algorithm-based machine learning technique was used to generate an optimal route while satisfying these two sets of requirements. Second, when an optimal route is generated, the vessel must have a route-following controller that can accurately follow the set route without deviation. To accurately follow the route, a velocity-type fuzzy proportional–integral–derivative (PID) controller was established. This controller can prevent deviation from the route because overshoot rarely occurs, compared with a proportional derivative (PD) controller. Additionally, because the change in rudder angle is smooth, energy loss by the vessel can be reduced. Here, a method for determining the presence of environmental disturbance using the characteristics of the Kalman filter innovation process and estimating environmental disturbance with a fuzzy disturbance estimator is presented, which allows the route to be accurately maintained even under conditions involving environmental disturbance. The proposed approach can automatically set the vessel’s optimal route and accurately follow the route without human intervention, which is useful and can contribute to maritime safety and efficiency improvement. Full article

(This article belongs to the Special Issue Optimal Maneuvering and Control of Ships)

► Show Figures

Journal Menu

Journal Browser

Optimal Maneuvering and Control of Ships

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (11 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI