Editorial

7 pages, 167 KiB

Open AccessEditorial

New Techniques in Motion Control and Path Planning of Marine Vehicles

by Bowen Xing and Bing Li

J. Mar. Sci. Eng. 2024, 12(1), 176; https://doi.org/10.3390/jmse12010176 - 17 Jan 2024

Viewed by 781

Currently, with the continuous improvements and advancements in artificial intelligence, wireless data transmission, and sensing technologies, increasing amounts of marine vehicles are being designed and applied to promote the marine economy and protect the environment [...] Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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20 pages, 2959 KiB

Open AccessArticle

Smooth Sliding Mode Control for Path Following of Underactuated Surface Vehicles Based on LOS Guidance

by Yuchao Wang, Yinsong Qu, Shiquan Zhao, Ricardo Cajo and Huixuan Fu

J. Mar. Sci. Eng. 2023, 11(12), 2214; https://doi.org/10.3390/jmse11122214 - 22 Nov 2023

Cited by 2 | Viewed by 869

Abstract

In this paper, a solution to the problem of following a curved path for underactuated unmanned surface vehicles (USVs) with unknown sideslip angle and model uncertainties is studied. A novel smooth sliding mode control (SSMC) based on a finite-time extended state observer (FTESO) [...] Read more.

In this paper, a solution to the problem of following a curved path for underactuated unmanned surface vehicles (USVs) with unknown sideslip angle and model uncertainties is studied. A novel smooth sliding mode control (SSMC) based on a finite-time extended state observer (FTESO) for heading control is proposed. Firstly, the model of a USV with rudderless double thrusters is established. Secondly, the path-following error dynamics of a USV is established in a path-tangential reference frame. Thirdly, a finite-time observer is introduced to estimate the unidentified sideslip angle, and the line-of-sight (LOS) guidance law is applied to produce the desired heading angle. Finally, an SSMC controller is proposed to force USV tracking at the desired heading angle and surge speed, in which FTESO is used to estimate and compensate the unknown disturbance in sliding mode dynamics. The theoretical analysis for FTESO-SSMC verifies that the controller can provide finite-time convergence to and stability on the sliding surface. Simulation studies and contrast test are conducted to demonstrate the robustness and rapidity of the proposed FTESO-SSMC controller. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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27 pages, 8339 KiB

Open AccessArticle

Distributed Dual Closed-Loop Model Predictive Formation Control for Collision-Free Multi-AUV System Subject to Compound Disturbances

by Mingyao Zhang, Zheping Yan, Jiajia Zhou and Lidong Yue

J. Mar. Sci. Eng. 2023, 11(10), 1897; https://doi.org/10.3390/jmse11101897 - 29 Sep 2023

Cited by 1 | Viewed by 840

Abstract

This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to [...] Read more.

This paper focuses on the collision-free formation tracking of autonomous underwater vehicles (AUVs) with compound disturbances in complex ocean environments. We propose a novel finite-time extended state observer (FTESO)-based distributed dual closed-loop model predictive control scheme. Initially, a fast FTESO is designed to accurately estimate both model uncertainties and external disturbances for each subsystem. Subsequently, the outer-loop and inner-loop formation controllers are developed by integrating disturbance compensation with distributed model predictive control (DMPC) theory. With full consideration of the input and state constraints, we resolve the local information-based DMPC optimization problem to obtain the control inputs for each AUV, thereby preventing actuator saturation and collisions among AUVs. Moreover, to mitigate the increased computation caused by the control structure, the Laguerre orthogonal function is applied to alleviate the computational burden in time intervals. We also demonstrate the stability of the closed-loop system by applying the terminal state constraint. Finally, based on a connected directed topology, comparative simulations are performed under various control schemes to verify the robustness and superior performance of the proposed scheme. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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19 pages, 7727 KiB

Open AccessArticle

Path Planning of Deep-Sea Landing Vehicle Based on the Safety Energy-Dynamic Window Approach Algorithm

by Zuodong Pan, Wei Guo, Hongming Sun, Yue Zhou and Yanjun Lan

J. Mar. Sci. Eng. 2023, 11(10), 1892; https://doi.org/10.3390/jmse11101892 - 28 Sep 2023

Viewed by 783

Abstract

To ensure the safety and energy efficiency of autonomous sampling operations for a deep-sea landing vehicle (DSLV), the Safety Energy-Dynamic Window Approach (SE-DWA) algorithm was proposed. The safety assessment sub-function formed from the warning obstacle zone and safety factor addresses the safety issue [...] Read more.

To ensure the safety and energy efficiency of autonomous sampling operations for a deep-sea landing vehicle (DSLV), the Safety Energy-Dynamic Window Approach (SE-DWA) algorithm was proposed. The safety assessment sub-function formed from the warning obstacle zone and safety factor addresses the safety issue arising from the excessive range measurement error of forward-looking sonar. The trajectory comparison evaluation sub-function with the effect of reducing energy consumption achieves a reduction in path length by causing the predicted trajectory to deviate from the historical trajectory when encountering “U”-shaped obstacles. The pseudo-power evaluation sub-function with further energy consumption reduction ensures optimal linear and angular velocities by minimizing variables when encountering unknown obstacles. The simulation results demonstrate that compared with the Minimum Energy Consumption-DWA algorithm, the SE-DWA algorithm improves the minimum distance to an actual obstacle zone by 68% while reducing energy consumption by 11%. Both the SE-DWA algorithm and the Maximum Safety-DWA (MS-DWA) algorithm ensure operational safety with minimal distance to the actual obstacle zone, yet the SE-DWA algorithm achieves a 24% decrease in energy consumption. In conclusion, the path planned by the SE-DWA algorithm ensures not only safety but also energy consumption reduction during autonomous sampling operations by a DSLV in the deep sea. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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17 pages, 2539 KiB

Open AccessArticle

Trajectory Tracking Predictive Control for Unmanned Surface Vehicles with Improved Nonlinear Disturbance Observer

by Huixuan Fu, Wenjing Yao, Ricardo Cajo and Shiquan Zhao

J. Mar. Sci. Eng. 2023, 11(10), 1874; https://doi.org/10.3390/jmse11101874 - 26 Sep 2023

Cited by 3 | Viewed by 1081

Abstract

The motion of unmanned surface vehicles (USVs) is frequently disturbed by ocean wind, waves, and currents. A poorly designed controller will cause failures and safety problems during actual navigation. To obtain a satisfactory motion control performance for the USVs, a model predictive control [...] Read more.

The motion of unmanned surface vehicles (USVs) is frequently disturbed by ocean wind, waves, and currents. A poorly designed controller will cause failures and safety problems during actual navigation. To obtain a satisfactory motion control performance for the USVs, a model predictive control (MPC) method based on an improved Nonlinear Disturbance Observer (NDO) is proposed. First, the USV model is approximately linearized and MPC is designed for the multivariable system with constraints. To compensate for the influence of disturbances, an improved NDO is designed where the calculation time for MPC is reduced. Finally, comparison simulations are conducted between MPC with the original NDO and MPC with an improved NDO, and the results show that they have similar performances to the USVs. However, the proposed method has fewer parameters that need to be tuned and is much more time-saving compared to MPC with a traditional NDO. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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18 pages, 3659 KiB

Open AccessArticle

Underwater Acoustically Guided Docking Method Based on Multi-Stage Planning

by Hongli Xu, Hongxu Yang, Zhongyu Bai and Xiangyue Zhang

J. Mar. Sci. Eng. 2023, 11(8), 1629; https://doi.org/10.3390/jmse11081629 - 21 Aug 2023

Cited by 3 | Viewed by 1024

Abstract

Autonomous underwater vehicles (AUVs) are important in areas such as underwater scientific research and underwater resource collection. However, AUVs suffer from data portability and energy portability problems due to their physical size limitation. In this work, an acoustic guidance method for underwater docking [...] Read more.

Autonomous underwater vehicles (AUVs) are important in areas such as underwater scientific research and underwater resource collection. However, AUVs suffer from data portability and energy portability problems due to their physical size limitation. In this work, an acoustic guidance method for underwater docking is proposed to solve the problem of persistent underwater operation. A funnel docking station and an autonomous remotely operated vehicle (ARV) are used as the platform for designing the guidance algorithms. First, the underwater docking guidance is divided into three stages: a long-range approach stage, a mid-range adjustment stage and a short-range docking stage. Second, the relevant guidance strategy is designed for each stage to improve the docking performance. Third, a correction method based on an ultra-short baseline (USBL) system is proposed for the ARV’s estimate of the depth, relative position and orientation angle of the docking station. To verify the feasibility of the docking guidance method, in this work, tests were performed on a lake and in a shallow sea. The success rate of autonomous navigation docking on the lake was 4 out of 7. The success rate of acoustic guidance docking on the lake and in the shallow sea were 11 out of 14 and 6 out of 8, respectively. The experimental results show the effectiveness of the docking guidance method in lakes and shallow seas. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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28 pages, 9001 KiB

Open AccessArticle

Optimal Path Planning Method for Unmanned Surface Vehicles Based on Improved Shark-Inspired Algorithm

by Jingrun Liang and Lisang Liu

J. Mar. Sci. Eng. 2023, 11(7), 1386; https://doi.org/10.3390/jmse11071386 - 07 Jul 2023

Cited by 7 | Viewed by 1215

Abstract

As crucial technology in the auto-navigation of unmanned surface vehicles (USVs), path-planning methods have attracted scholars’ attention. Given the limitations of White Shark Optimizer (WSO), such as convergence deceleration, time consumption, and nonstandard dynamic action, an improved WSO combined with the dynamic window [...] Read more.

As crucial technology in the auto-navigation of unmanned surface vehicles (USVs), path-planning methods have attracted scholars’ attention. Given the limitations of White Shark Optimizer (WSO), such as convergence deceleration, time consumption, and nonstandard dynamic action, an improved WSO combined with the dynamic window approach (DWA) is proposed in this paper, named IWSO-DWA. First, circle chaotic mapping, adaptive weight factor and the simplex method are used to improve the initial solution and spatial search efficiency and accelerate the convergence of the algorithm. Second, optimal path information planned by the improved WSO is put into the DWA to enhance the USV’s navigation performance. Finally, the COLREGs rules are added to the global dynamic optimal path planning method to ensure the USV’s safe navigation. Compared with the WSO, the experimental simulation results demonstrate that the path length cost, steering cost and time cost of the proposed method are decreased by 13.66%, 18.78% and 79.08%, respectively, and the improvement in path smoothness cost amounts to 19.85%. Not only can the proposed IWSO-DWA plan an optimal global navigation path in an intricate marine environment, but it can also help a USV avoid other ships dynamically in real time and meets the COLREGs rules. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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18 pages, 1635 KiB

Open AccessArticle

An Experimental Study on Trajectory Tracking Control of Torpedo-like AUVs Using Coupled Error Dynamics

by Gun Rae Cho, Hyungjoo Kang, Min-Gyu Kim, Mun-Jik Lee, Ji-Hong Li, Hosung Kim, Hansol Lee and Gwonsoo Lee

J. Mar. Sci. Eng. 2023, 11(7), 1334; https://doi.org/10.3390/jmse11071334 - 30 Jun 2023

Cited by 2 | Viewed by 1064

Abstract

In this paper, we propose a trajectory tracking controller with experimental verification for torpedo-like autonomous underwater vehicles (AUVs) with underactuation characteristics. The proposed controller overcomes the underactuation problem by designing the desired error dynamics in a coupled form using state variables in body-fixed [...] Read more.

In this paper, we propose a trajectory tracking controller with experimental verification for torpedo-like autonomous underwater vehicles (AUVs) with underactuation characteristics. The proposed controller overcomes the underactuation problem by designing the desired error dynamics in a coupled form using state variables in body-fixed and world coordinates. Unlike the back-stepping control requiring high-order derivatives of state variables, the proposed controller only requires the first derivatives of the states, which can alleviate noise magnification issues due to differentiation. We adopt time delay estimation to estimate the dynamics indirectly using control inputs and vehicle outputs, making the proposed controller relatively easy to apply without requiring the all of the vehicle dynamics. We also address some practical issues that commonly arise in experimental environments: handling measurement noises and actuation limits. To mitigate the effects of noise on the controller, a filtering technique using a moving window average is employed. Additionally, to account for the actuation limits, we design an anti-windup structure that takes into consideration the nonlinearity between the thrusting force and rotating speed of the thruster. We verify the tracking performance of the proposed controller through experimentation using an AUV. The experimental results show that the 3D motion control of the proposed controller exhibits an RMS error of 0.3216 m and demonstrate that the proposed controller achieves accurate tracking performance, making it suitable for survey missions that require tracking errors of less than one meter. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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16 pages, 3608 KiB

Open AccessArticle

Long-Term Trajectory Prediction for Oil Tankers via Grid-Based Clustering

by Xuhang Xu, Chunshan Liu, Jianghui Li, Yongchun Miao and Lou Zhao

J. Mar. Sci. Eng. 2023, 11(6), 1211; https://doi.org/10.3390/jmse11061211 - 11 Jun 2023

Cited by 2 | Viewed by 1157

Abstract

Vessel trajectory prediction is an important step in route planning, which could help improve the efficiency of maritime transportation. In this article, a high-accuracy long-term trajectory prediction algorithm is proposed for oil tankers. The proposed algorithm extracts a set of waymark points that [...] Read more.

Vessel trajectory prediction is an important step in route planning, which could help improve the efficiency of maritime transportation. In this article, a high-accuracy long-term trajectory prediction algorithm is proposed for oil tankers. The proposed algorithm extracts a set of waymark points that are representative of the key traveling patterns in an area of interest by applying DBSCAN clustering to historical AIS data. A novel path-finding algorithm is then developed to sequentially identify a subset of waymark points, from which the predicted trajectory to a fixed destination is produced. The proposed algorithm is tested using real data offered by the Danish Maritime Authority. Numerical results demonstrate that the proposed algorithm outperforms state-of-the-art vessel trajectory prediction algorithms and is able to make high-accuracy long-term trajectory predictions. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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20 pages, 4297 KiB

Open AccessArticle

Optimized APF-ACO Algorithm for Ship Collision Avoidance and Path Planning

by Mingze Li, Bing Li, Zhigang Qi, Jiashuai Li and Jiawei Wu

J. Mar. Sci. Eng. 2023, 11(6), 1177; https://doi.org/10.3390/jmse11061177 - 04 Jun 2023

Cited by 7 | Viewed by 1788

Abstract

The primary objective of this study is to investigate maritime collision avoidance and trajectory planning in the presence of dynamic and static obstacles during navigation. Adhering to safety regulations is crucial when executing ship collision avoidance tasks. To address this issue, we propose [...] Read more.

The primary objective of this study is to investigate maritime collision avoidance and trajectory planning in the presence of dynamic and static obstacles during navigation. Adhering to safety regulations is crucial when executing ship collision avoidance tasks. To address this issue, we propose an optimized APF-ACO algorithm for collision avoidance and path planning. First, a ship collision avoidance constraint model is constructed based on COLREGs to enhance the safety and applicability of the algorithm. Then, by introducing factors such as velocity, position, and shape parameters, the traditional APF method is optimized, creating a dynamic APF gradient for collision avoidance decision making in the face of dynamic obstacles. Furthermore, the optimized APF method is integrated with the ant colony optimization algorithm, the latter modified to overcome the inherent local optimality issues in the APF method. Ultimately, validations are conducted in three areas: static avoidance and planning in restricted sea areas, avoidance under conditions of mixed static and dynamic obstacles, and avoidance in situations of multiple ship encounters. These serve to illustrate the feasibility and efficacy of the proposed algorithm in achieving dynamic ship collision avoidance while simultaneously completing path-planning tasks. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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14 pages, 8056 KiB

Open AccessArticle

A Novel Algorithm for Ship Route Planning Considering Motion Characteristics and ENC Vector Maps

by Qinghua He, Zhenyu Hou and Xiaoxiao Zhu

J. Mar. Sci. Eng. 2023, 11(6), 1102; https://doi.org/10.3390/jmse11061102 - 23 May 2023

Cited by 3 | Viewed by 1553

Abstract

Global route planning is a pivotal function of unmanned surface vehicles (USVs). For ships, the safety of navigation is the priority. This paper presents the VK-RRT* algorithm as a way of designing the planned route automatically. Different from other algorithms or studies, this [...] Read more.

Global route planning is a pivotal function of unmanned surface vehicles (USVs). For ships, the safety of navigation is the priority. This paper presents the VK-RRT* algorithm as a way of designing the planned route automatically. Different from other algorithms or studies, this study employs electronic navigation chart (ENC) vector data instead of grid maps as the basis of the search, which reduces data error when converting the vector map into the grid map. In addition, Delaunay triangulation is employed to organize vector data, in which the depth value is taken as a factor to ensure the safety of the planning route. Furthermore, the initial planned route is not suitable for ship tracking as it does not consider the ship motion characteristics. Therefore, the planned route needs to be further optimized. In the final part, we also conducted experiments to verify the effectiveness and advantages of the proposed algorithm. The results show that the proposed algorithm could reduce the lengths of paths by about 23% on average and save planning time; these are largely dependent on the environment. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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23 pages, 596 KiB

Open AccessArticle

A Novel Robust IMM Filtering Method for Surface-Maneuvering Target Tracking with Random Measurement Delay

by Chen Chen, Weidong Zhou and Lina Gao

J. Mar. Sci. Eng. 2023, 11(5), 1047; https://doi.org/10.3390/jmse11051047 - 14 May 2023

Cited by 1 | Viewed by 1025

Abstract

A proper filtering method for jump Markov system (JMS) is an effective approach for tracking a maneuvering target. Since the coexisting of heavy-tailed measurement noises (HTMNs) and one-step random measurement delay (OSRMD) in the complex scenarios of the surface maneuvering target tracking, the [...] Read more.

A proper filtering method for jump Markov system (JMS) is an effective approach for tracking a maneuvering target. Since the coexisting of heavy-tailed measurement noises (HTMNs) and one-step random measurement delay (OSRMD) in the complex scenarios of the surface maneuvering target tracking, the effectiveness of typical interacting multiple model (IMM) techniques may decline severely. To solve the state estimation problem in JMSs with HTMN and OSRMD simultaneously, this article designs a novel robust IMM filter utilizing the variational Bayesian (VB) inference framework. This algorithm models the HTMNs as student’s t-distribuitons, and presents a random Bernoulli variable to describe the OSRMD in JMSs. By transforming measurement likelihood function form from weighted summation to exponential product, this paper constructs hierarchical Gaussian state space models. Then, the state vectors, random Bernoulli vairable, and model probability are inferred jointly according to VB inference. The surface maneuvering target tracking simulation example result indicates that the presented IMM filter achieves superior target state estimation accuracy among existing IMM filters. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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20 pages, 4543 KiB

Open AccessArticle

Three-Dimensional Trajectory Tracking of AUV Based on Nonsingular Terminal Sliding Mode and Active Disturbance Rejection Decoupling Control

by Wei Zhang, Wenhua Wu, Zixuan Li, Xue Du and Zheping Yan

J. Mar. Sci. Eng. 2023, 11(5), 959; https://doi.org/10.3390/jmse11050959 - 30 Apr 2023

Cited by 8 | Viewed by 1239

Abstract

This paper presents a nonsingular terminal sliding mode and active disturbance rejection decoupling control (NTSM-ADRDC) scheme for the three-dimensional (3D) trajectory tracking of autonomous underwater vehicles (AUV). Firstly, the AUV model is decoupled into five independent single input–single output (SISO) channels using ADRDC [...] Read more.

This paper presents a nonsingular terminal sliding mode and active disturbance rejection decoupling control (NTSM-ADRDC) scheme for the three-dimensional (3D) trajectory tracking of autonomous underwater vehicles (AUV). Firstly, the AUV model is decoupled into five independent single input–single output (SISO) channels using ADRDC technology. Secondly, the NTSM-ADRDC controller is designed. The linear extended state observer (LESO) is used to observe the AUV state variables, and estimate the total disturbance of the system. In addition, to improve the system error convergence rate, the combination of exponential reaching rate and NTSM constitutes a nonlinear states error feedback control law for the controller. Finally, the stability of the proposed control law is proved using the Lyapunov theory. The simulation results demonstrate the effectiveness and robustness of the designed NTSM-ADRDC trajectory tracking approach. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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22 pages, 5645 KiB

Open AccessArticle

Multi-AUV Formation Predictive Control Based on CNN-LSTM under Communication Constraints

by Juan Li, Zhenyang Tian, Gengshi Zhang and Wenbo Li

J. Mar. Sci. Eng. 2023, 11(4), 873; https://doi.org/10.3390/jmse11040873 - 20 Apr 2023

Cited by 4 | Viewed by 1188

Abstract

For the problem of hydroacoustic communication constraints in multi-AUV leader follower formation, this paper designs a formation control method combining CNN-LSTM prediction and backstepping sliding mode control. First, a feedback linearization method is used to transform the AUV nonlinear model into a second-order [...] Read more.

For the problem of hydroacoustic communication constraints in multi-AUV leader follower formation, this paper designs a formation control method combining CNN-LSTM prediction and backstepping sliding mode control. First, a feedback linearization method is used to transform the AUV nonlinear model into a second-order integral model; then, the influence of hydroacoustic communication constraints on the multi-AUV formation control problem is analyzed, and a sliding window-based formation prediction control strategy is designed; for the characteristics of AUV motion trajectory with certain temporal order, the CNN-LSTM prediction model is selected to predict the trajectory state of the leader follower and compensate the effect of communication delay on formation control, and combine the backstepping method and sliding mode control to design the formation controller. Finally, the simulation experimental results show that the proposed CNN-LSTM prediction and backstepping sliding mode control can improve the effect of hydroacoustic communication constraints on formation control. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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16 pages, 4104 KiB

Open AccessArticle

Output Feedback Tracking Control with Collision Avoidance for Dynamic Positioning Vessel under Input Constraint

by Benwei Zhang and Guoqing Xia

J. Mar. Sci. Eng. 2023, 11(4), 811; https://doi.org/10.3390/jmse11040811 - 11 Apr 2023

Cited by 2 | Viewed by 1022

Abstract

This dissertation presents a fresh control strategy for dynamic positioning vessels exposed to model uncertainty, various external disturbances, and input constraint. The vessel is supposed to work in a particular situation surrounding a lighthouse or a submerged reef, where collision avoidance must be [...] Read more.

This dissertation presents a fresh control strategy for dynamic positioning vessels exposed to model uncertainty, various external disturbances, and input constraint. The vessel is supposed to work in a particular situation surrounding a lighthouse or a submerged reef, where collision avoidance must be prevented. The control strategy involves making the vessel navigate under the action of modified artificial potential functions (MAPFs) along a smooth trajectory. To achieve this goal, we put forward a collision-avoidance control strategy, which consists of the backstepping technique, an extended state observer (ESO), and an active dynamic positioning control technique. The MAPFs, together with a strategy, are applied to realize collision avoidance. To address the input constraint problem, an auxiliary dynamic system (ADS) is constructed. Entire related signals of the control system could converge to a small neighboring zone of the equilibrium state via Lyapunov deduction. Simulation outcomes verify the effectiveness of the presented control strategy. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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18 pages, 19469 KiB

Open AccessArticle

Horizontal Trajectory Tracking Control for Underactuated Autonomous Underwater Vehicles Based on Contraction Theory

by Caipeng Ma, Jinjun Jia, Tiedong Zhang, Shaoqun Wu and Dapeng Jiang

J. Mar. Sci. Eng. 2023, 11(4), 805; https://doi.org/10.3390/jmse11040805 - 10 Apr 2023

Cited by 2 | Viewed by 1321

Abstract

In this paper, contraction theory is applied to design a control law to address the horizontal trajectory tracking problem of an underactuated autonomous underwater vehicle. Suppose that the vehicle faces challenges such as model uncertainties, external environmental disturbances, and actuator saturation. Firstly, a [...] Read more.

In this paper, contraction theory is applied to design a control law to address the horizontal trajectory tracking problem of an underactuated autonomous underwater vehicle. Suppose that the vehicle faces challenges such as model uncertainties, external environmental disturbances, and actuator saturation. Firstly, a coordinate transformation is introduced to solve the problem of underactuation. Then, a disturbance observer is designed to estimate the total disturbances, which are composed of model uncertainties and external environmental disturbances. Next, a saturated controller is designed based on singular perturbation theory and contraction theory. Meanwhile, contraction theory is used to analyse the convergence properties of the observer and the full singular perturbation system, and make quantitative analysis of the estimation error and the tracking error. Finally, the results of numerical simulations prove that the method in this paper enables the vehicle to track the desired trajectory with relatively high accuracy, while the control inputs do not exceed the limitations of the actuators. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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19 pages, 720 KiB

Open AccessArticle

An Algorithm of Complete Coverage Path Planning for Unmanned Surface Vehicle Based on Reinforcement Learning

by Bowen Xing, Xiao Wang, Liu Yang, Zhenchong Liu and Qingyun Wu

J. Mar. Sci. Eng. 2023, 11(3), 645; https://doi.org/10.3390/jmse11030645 - 19 Mar 2023

Cited by 12 | Viewed by 3279

Abstract

A deep reinforcement learning method to achieve complete coverage path planning for an unmanned surface vehicle (USV) is proposed. This paper firstly models the USV and the workspace required for complete coverage. Then, for the full-coverage path planning task, this paper proposes a [...] Read more.

A deep reinforcement learning method to achieve complete coverage path planning for an unmanned surface vehicle (USV) is proposed. This paper firstly models the USV and the workspace required for complete coverage. Then, for the full-coverage path planning task, this paper proposes a preprocessing method for raster maps, which can effectively delete the blank areas that are impossible to cover in the raster map. In this paper, the state matrix corresponding to the preprocessed raster map is used as the input of the deep neural network. The deep Q network (DQN) is used to train the complete coverage path planning strategy of the agent. The improvement of the selection of random actions during training is first proposed. Considering the task of complete coverage path planning, this paper replaces random actions with a set of actions toward the nearest uncovered grid. To solve the problem of the slow convergence speed of the deep reinforcement learning network in full-coverage path planning, this paper proposes an improved method of deep reinforcement learning, which superimposes the final output layer with a dangerous actions matrix to reduce the risk of selection of dangerous actions of USVs during the learning process. Finally, the designed method validates via simulation examples. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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20 pages, 7770 KiB

Open AccessArticle

Autonomous Underwater Vehicle Path Tracking Based on the Optimal Fuzzy Controller with Multiple Performance Indexes

by Qunhong Tian, Tao Wang, Yuming Song, Yunxia Wang and Bing Liu

J. Mar. Sci. Eng. 2023, 11(3), 463; https://doi.org/10.3390/jmse11030463 - 21 Feb 2023

Cited by 3 | Viewed by 1328

Abstract

Autonomous underwater vehicles (AUVs) are increasingly being used in missions involving submarine cable detection, underwater archaeology, pipeline inspection, military reconnaissance, and so on. It is very important to realize AUV path tracking to accomplish these missions. In this paper, a fuzzy controller based [...] Read more.

Autonomous underwater vehicles (AUVs) are increasingly being used in missions involving submarine cable detection, underwater archaeology, pipeline inspection, military reconnaissance, and so on. It is very important to realize AUV path tracking to accomplish these missions. In this paper, a fuzzy controller based on the established kinematic and dynamic models of AUV systems is presented to solve the AUV path-tracking problem. In order to design the fuzzy controller to exhibit good performance, we select the path length, smoothness, and cross-track position error as the multiple optimization performance indexes for the fuzzy controller. We propose the particle swarm optimization (PSO) algorithm to determine the parameters of the membership functions. Different scenarios are presented to test the performance of the proposed algorithm, including the straight line, sine curve, half-moon shape, Archimedean spiral, and practical paths. The results are given to illustrate the effectiveness and feasibility of the fuzzy controller with the optimization of multiple performance indexes. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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21 pages, 10541 KiB

Open AccessArticle

Finite Time Trajectory Tracking with Full-State Feedback of Underactuated Unmanned Surface Vessel Based on Nonsingular Fast Terminal Sliding Mode

by Donghao Xu, Zipeng Liu, Jiuzhen Song and Xueqian Zhou

J. Mar. Sci. Eng. 2022, 10(12), 1845; https://doi.org/10.3390/jmse10121845 - 01 Dec 2022

Cited by 4 | Viewed by 1216

Abstract

Marine transportation and operations have attracted the attention of more and more countries and scholars in recent years. A full-state finite time feedback control scheme is designed for the model parameters uncertainty, unknown ocean environment disturbances, and unmeasured system states in the underactuated [...] Read more.

Marine transportation and operations have attracted the attention of more and more countries and scholars in recent years. A full-state finite time feedback control scheme is designed for the model parameters uncertainty, unknown ocean environment disturbances, and unmeasured system states in the underactuated Unmanned Surface Vessel (USV) trajectory tracking control. The external wind, wave and current environmental disturbances and model parameters perturbation are extended by Nonlinear Extended State Observer (NESO) to the state of the system, namely complex disturbances. The complex disturbances, positions and velocities of USV can be observed by NESO and feedback to USV control system. Next, the underactuated USV error model is obtained by operating the obtained feedback information and the virtual ship model. According to the error model, a Nonsingular Fast Terminal Sliding Model surface (NFTSM) is constructed to realize finite-time control. The control law is deduced through the Lyapunov stability theory to ensure the stability of the system. The results of MATLAB numerical simulations under different disturbances show that the trajectory tracking algorithm has fast responses, and a good convergence of the errors is observed, which verifies the effectiveness of the designed scheme. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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18 pages, 7451 KiB

Open AccessArticle

Distributed Robust Fast Finite-Time Formation Control of Underactuated ASVs in Presence of Information Interruption

by Guoqing Zhang, Jun Han, Jiqiang Li and Xianku Zhang

J. Mar. Sci. Eng. 2022, 10(11), 1775; https://doi.org/10.3390/jmse10111775 - 18 Nov 2022

Cited by 1 | Viewed by 1096

Abstract

To adapt to complex navigation conditions, this paper addresses the coordination formation of autonomous surface vehicles (ASVs) with the constraint of information interruption. For this purpose, a distributed robust fast finite-time formation control algorithm is proposed by fusion of the directed graph and [...] Read more.

To adapt to complex navigation conditions, this paper addresses the coordination formation of autonomous surface vehicles (ASVs) with the constraint of information interruption. For this purpose, a distributed robust fast finite-time formation control algorithm is proposed by fusion of the directed graph and neural network method. In the strategy, the graph theory is utilized for the channel of information transmission to maintain the stability of the formation system. In addition, the radial basic function (RBF) neural network is employed to approximate the structure uncertainty. Due to the merits of the robust neural damping technique, only two adaptive parameters are designed to compensate the perturbation from the model uncertainty and external environmental. Furthermore, an improved dynamic surface control (DSC) technology is developed for constituting the exponential term of the Lyapunov function. It is proven that the proposed scheme is able to achieve consensus tracking in finite time quickly, and the errors rapidly approach a small region around the origin. Finally, the feasibility and effectiveness of the algorithm are verified by two numerical simulations. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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Open AccessReview

A Review of Path Planning for Unmanned Surface Vehicles

by Bowen Xing, Manjiang Yu, Zhenchong Liu, Yinchao Tan, Yue Sun and Bing Li

J. Mar. Sci. Eng. 2023, 11(8), 1556; https://doi.org/10.3390/jmse11081556 - 06 Aug 2023

Cited by 5 | Viewed by 3472

Abstract

With the continued development of artificial intelligence technology, unmanned surface vehicles (USVs) have attracted the attention of countless domestic and international specialists and academics. In particular, path planning is a core technique for the autonomy and intelligence process of USVs. The current literature [...] Read more.

With the continued development of artificial intelligence technology, unmanned surface vehicles (USVs) have attracted the attention of countless domestic and international specialists and academics. In particular, path planning is a core technique for the autonomy and intelligence process of USVs. The current literature reviews on USV path planning focus on the latest global and local path optimization algorithms. Almost all algorithms are optimized by concerning metrics such as path length, smoothness, and convergence speed. However, they also simulate environmental conditions at sea and do not consider the effects of sea factors, such as wind, waves, and currents. Therefore, this paper reviews the current algorithms and latest research results of USV path planning in terms of global path planning, local path planning, hazard avoidance with an approximate response, and path planning under clustering. Then, by classifying USV path planning, the advantages and disadvantages of different research methods and the entry points for improving various algorithms are summarized. Among them, the papers which use kinematic and dynamical equations to consider the ship’s trajectory motion planning for actual sea environments are reviewed. Faced with multiple moving obstacles, the literature related to multi-objective task assignment methods for path planning of USV swarms is reviewed. Therefore, the main contribution of this work is that it broadens the horizon of USV path planning and proposes future directions and research priorities for USV path planning based on existing technologies and trends. Full article

(This article belongs to the Special Issue Motion Control and Path Planning of Marine Vehicles)

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