Research

17 pages, 1647 KiB

Open AccessArticle

DCA-Based Collision Avoidance Path Planning for Marine Vehicles in Presence of the Multi-Ship Encounter Situation

by Jiagen Yu, Zhengjiang Liu and Xianku Zhang

J. Mar. Sci. Eng. 2022, 10(4), 529; https://doi.org/10.3390/jmse10040529 - 12 Apr 2022

Cited by 7 | Viewed by 1938

The problem of ship collision avoidance path planning is one of the key problems in the ship motion control field. Aiming at the high computational time problem of path planning in multi-ship encounter situations and the impact of the target ship’s action changes [...] Read more.

The problem of ship collision avoidance path planning is one of the key problems in the ship motion control field. Aiming at the high computational time problem of path planning in multi-ship encounter situations and the impact of the target ship’s action changes on path planning, this paper proposes a dynamic path-planning method based on dynamic cluster analysis (DCA), which is used to dynamically cluster target ships with similar attributes into a group ship, reducing the number of calculated targets and improving the efficiency of path planning. Taking into full consideration the action requirements of the International Regulations for Preventing Collisions at Sea (COLREGs), the course alteration action matrix (CAAM) for collision avoidance is established to limit the space of candidate solutions. On the basis of the rapid optimization capability of the deterministic optimization algorithm (DOA), a dynamic monitoring mechanism is introduced to establish a multi-ship encounter intelligent collision avoidance decision-making model that meets the needs of real-time collision avoidance. The simulation results showed that the method can obtain a dynamic collision avoidance path that is safe and feasible. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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16 pages, 4483 KiB

Open AccessArticle

Adaptive Formation Control of Unmanned Underwater Vehicles with Collision Avoidance under Unknown Disturbances

by Zheping Yan, Anzuo Jiang and Chonglang Lai

J. Mar. Sci. Eng. 2022, 10(4), 516; https://doi.org/10.3390/jmse10040516 - 08 Apr 2022

Cited by 1 | Viewed by 1479

Abstract

In this paper, the formation control problem for a group of unmanned underwater vehicles (UUVs) is investigated considering collision avoidance and environment disturbances. To address the external force effect of the environment, such as waves and currents, a sliding mode disturbance observer is [...] Read more.

In this paper, the formation control problem for a group of unmanned underwater vehicles (UUVs) is investigated considering collision avoidance and environment disturbances. To address the external force effect of the environment, such as waves and currents, a sliding mode disturbance observer is designed to compensate for the unknown dynamic disturbances in finite time. A bounded artificial potential field is incorporated into the control law to ensure collision avoidance among UUVs. The form of an artificial potential function is much simpler and convenient for engineering applications. A controller is devised to guarantee all the error signals are bounded, and the formation pattern can be achieved in finite time after collision avoidance. The stability of UUV formation with collision avoidance is proven by using the Lyapunov theorem, and the scheme has been shown to be convergent using Barbalat’s lemma. Comparative simulations are presented to demonstrate the effectiveness of the proposed method in 2-D and 3-D environments. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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22 pages, 3943 KiB

Open AccessArticle

Application of Radar Image Fusion Method to Near-Field Sea Ice Warning for Autonomous Ships in the Polar Region

by Tsung-Hsuan Hsieh, Bo Li, Shengzheng Wang and Wei Liu

J. Mar. Sci. Eng. 2022, 10(3), 421; https://doi.org/10.3390/jmse10030421 - 14 Mar 2022

Cited by 2 | Viewed by 2324

Abstract

Mastering the real-time dynamics of near-field sea ice is the primary condition to guaranteeing the navigation safety of autonomous ships in the polar region. In this study, a radar image fusion process combining marine radar and ice radar is proposed, which can effectively [...] Read more.

Mastering the real-time dynamics of near-field sea ice is the primary condition to guaranteeing the navigation safety of autonomous ships in the polar region. In this study, a radar image fusion process combining marine radar and ice radar is proposed, which can effectively solve the problems of redundant information and spatial registration during image fusion. Then, using the fused radar images, this study proposes a set of near-field sea ice risk assessment and warning processes applicable to both low- and high-sea-ice-concentration situations. The sea ice risk indexes in these two situations are constructed by using four variables: sea ice area, sea ice grayscale, distance between sea ice and the own-ship, and relative bearing of sea ice and the own-ship. Finally, visualization processing is carried out according to the size of the risk index values of each piece of sea ice to achieve a better near-field sea ice risk assessment and warning effect. According to the example demonstration results, through the radar image fusion process and the set of near-field sea ice risk assessment and warning processes proposed in this study, the sea ice risk distribution in the near-field area of the ship can be well obtained, which provides effective support for the assisted decision-making of autonomous navigation in the polar region. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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14 pages, 16547 KiB

Open AccessArticle

Ship Steering Adaptive CGS Control Based on EKF Identification Method

by Wei Guan, Haowen Peng, Xianku Zhang and Hui Sun

J. Mar. Sci. Eng. 2022, 10(2), 294; https://doi.org/10.3390/jmse10020294 - 20 Feb 2022

Cited by 15 | Viewed by 2056

Abstract

In recent years, marine autonomous surface vessels (MASS) have grown into a ship research issue to increase the level of autonomy of ship behavior decision-making and control while sailing at sea. This paper focuses on the MASS motion control module design that aims [...] Read more.

In recent years, marine autonomous surface vessels (MASS) have grown into a ship research issue to increase the level of autonomy of ship behavior decision-making and control while sailing at sea. This paper focuses on the MASS motion control module design that aims to improve the accuracy and reliability of ship steering control systems. Nevertheless, the stochastic sea and wind environment have led to the extensive use of filters and state observers for estimating the ship-motion-related parameters, which are important for ship steering control systems. In particular, the ship maneuverability Nomoto index, which primarily determines the designed ship steering controller’s performance, cannot be observed directly due to the model errors and the external environment disturbance in the process of sailing. Hence, an adaptive robust ship steering controller based on a closed-loop gain shaping (CGS) scheme and an extended Kalman filter (EKF) on-line identification method is explored in this paper. To verify the effectiveness of the proposed steering controller design scheme, the motor vessel YUKUN was taken as the control plant and a series of simulation experiments were carried out. The results show the advantages of the dynamic response performance of the proposed steering controller compared with the classical PD and traditional CGS controllers. Therefore, the proposed adaptive CGS steering controller would be a good solution for MASS motion control module design. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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18 pages, 586 KiB

Open AccessArticle

Adaptive Auto-Berthing Control of Underactuated Vessel Based on Barrier Lyapunov Function

by Yang Liu, Nam-kyun Im, Qiang Zhang and Guibing Zhu

J. Mar. Sci. Eng. 2022, 10(2), 279; https://doi.org/10.3390/jmse10020279 - 17 Feb 2022

Cited by 5 | Viewed by 1876

Abstract

This paper investigates the automatic berthing problem of underactuated surface vessels in the case of uncertain dynamics and yaw rate limitation, given the importance of yaw rate control and the unmeasurable hydrodynamic parameters of the vessel at low speeds. First, we use the [...] Read more.

This paper investigates the automatic berthing problem of underactuated surface vessels in the case of uncertain dynamics and yaw rate limitation, given the importance of yaw rate control and the unmeasurable hydrodynamic parameters of the vessel at low speeds. First, we use the differential homeomorphism coordinate transformation to solve the problem of underactuation. Second, a radial basis function network (RBF) is introduced to approximate unknown nonlinear functions. Third, we apply the barrier Lyapunov function (BLF) approach to limit the yaw rate within a safe range. Fourth, we use dynamic surface control (DSC) technology and minimum learning parameters (MLP) to tackle the differential explosion problems in backstepping and computational complexity. Finally, Lyapunov stability theory proves that signals produced by the designed control scheme are bounded and effective. The simulation results show that, compared with the control scheme without BLF, the proposed method can effectively limit the yaw rate within a specific range and effectively solves the influence of the model uncertainly. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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22 pages, 3741 KiB

Open AccessArticle

Robust Composite Dynamic Event-Triggered Control for Multiple USVs with DLLOS Guidance

by Guoqing Zhang, Shang Liu, Bo Li and Xianku Zhang

J. Mar. Sci. Eng. 2022, 10(2), 227; https://doi.org/10.3390/jmse10020227 - 08 Feb 2022

Cited by 3 | Viewed by 1338

Abstract

In this paper, a robust composite dynamic event-triggered formation control scheme is proposed for multiple underactuated surface vehicles (USVs) from two aspects, i.e., guidance and control. In the guidance module, a novel dual-layer line-of-sight (DLLOS) guidance principle is incorporated into the leader–follower framework [...] Read more.

In this paper, a robust composite dynamic event-triggered formation control scheme is proposed for multiple underactuated surface vehicles (USVs) from two aspects, i.e., guidance and control. In the guidance module, a novel dual-layer line-of-sight (DLLOS) guidance principle is incorporated into the leader–follower framework to generate the reference path. To overcome the problem of unavailable leader velocity information, an adaptive speed controller is designed to adjust the navigational speed of followers. As for the control part, by utilizing the dynamic event-triggered method, the operational frequency of actuators can be reduced in a flexible manner. That can effectively avoid the excessive wear and chattering phenomenon of actuators. Furthermore, by the fusing of the radial basis function neural networks (RBF NNs) and the robust neural damping technique, the model uncertainty, environmental disturbances and some unknown parameters can be remodeled, and only two gain-related adaptive laws need to be updated online. The serial–parallel estimation model (SPEM) is established to predict the velocity variables, and the approximation performance of NNs can be enhanced by virtue of the derived prediction error. Through the Lyapunov stable theorem, all control signals in the closed-loop system are guaranteed semi-globally uniformly ultimately bounded (SGUUB) stability. Finally, digital simulations are illustrated to verify the effectiveness and superiority of the proposed algorithm. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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17 pages, 4433 KiB

Open AccessArticle

Anti-Roll Characteristics of Marine Gyrostabilizer Based on Adaptive Control and Hydrodynamic Simulation

by Biao Li, Xianku Zhang, Jun Wang and Ning Chen

J. Mar. Sci. Eng. 2022, 10(1), 83; https://doi.org/10.3390/jmse10010083 - 09 Jan 2022

Cited by 6 | Viewed by 2001

Abstract

The gyrostabilizer produces the anti-roll effect through the precession output moment generated by a high-speed rotating flywheel. As a floating-base multi-body system composed of ship and gyrostabilizer, the recent research that has only focused on the control strategies or multi-body dynamics is obviously [...] Read more.

The gyrostabilizer produces the anti-roll effect through the precession output moment generated by a high-speed rotating flywheel. As a floating-base multi-body system composed of ship and gyrostabilizer, the recent research that has only focused on the control strategies or multi-body dynamics is obviously not comprehensive. This study presents an adaptive controller based on the variable gain control strategy for a marine gyrostabilizer installed on a port salvage tug. The variable gain control strategy controlled the flywheel precession output moment of the gyrostabilizer and thereby of the precession process, to reduce the ship roll motion effectively. Furthermore, a full-system hydrodynamic model of a gyrostabilizer-ship-wave based on three-dimensional numerical wave flume technology was innovatively established to evaluate its anti-roll performance under irregular wave conditions. The simulation results show that, for the sea state considered, the increase of spin rate of gyrostabilizer flywheel improved the anti-roll effect significantly. The average anti-roll rate of the gyrostabilizer decreased with the increase of significant wave height, wave period and wave encounter angle. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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19 pages, 3218 KiB

Open AccessArticle

Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

by Jiqiang Li, Guoqing Zhang and Bo Li

J. Mar. Sci. Eng. 2022, 10(1), 51; https://doi.org/10.3390/jmse10010051 - 03 Jan 2022

Cited by 38 | Viewed by 2879

Abstract

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” [...] Read more.

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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16 pages, 2045 KiB

Open AccessArticle

Path Tracking of an Underwater Snake Robot and Locomotion Efficiency Optimization Based on Improved Pigeon-Inspired Algorithm

by Bo Xu, Mingyu Jiao, Xianku Zhang and Dalong Zhang

J. Mar. Sci. Eng. 2022, 10(1), 47; https://doi.org/10.3390/jmse10010047 - 02 Jan 2022

Cited by 6 | Viewed by 1955

Abstract

This paper considers the tracking control of curved paths for an underwater snake robot, and investigates the methods used to improve energy efficiency. Combined with the path-planning method based on PCSI (parametric cubic-spline interpolation), an improved LOS (light of sight) method is proposed [...] Read more.

This paper considers the tracking control of curved paths for an underwater snake robot, and investigates the methods used to improve energy efficiency. Combined with the path-planning method based on PCSI (parametric cubic-spline interpolation), an improved LOS (light of sight) method is proposed to design the controller and guide the robot to move along the desired path. The evaluation of the energy efficiency of robot locomotion is discussed. In particular, a pigeon-inspired optimization algorithm improved by quantum rules (QPIO) is proposed for dynamically selecting the gait parameters that maximize energy efficiency. Simulation results show that the proposed controller enables the robot to accurately follow the curved path and that the QPIO algorithm is effective in improving robot energy efficiency. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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23 pages, 17324 KiB

Open AccessArticle

Station-Keeping Control of Autonomous and Remotely-Operated Vehicles for Free Floating Manipulation

by Ningning Ding, Yuangui Tang, Zhibin Jiang, Yunfei Bai and Shixun Liang

J. Mar. Sci. Eng. 2021, 9(11), 1305; https://doi.org/10.3390/jmse9111305 - 21 Nov 2021

Cited by 4 | Viewed by 1835

Abstract

This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) enhanced by adaptive tracking differentiator (ATD) and reduced-order extended state observer (RESO) is proposed. The [...] Read more.

This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) enhanced by adaptive tracking differentiator (ATD) and reduced-order extended state observer (RESO) is proposed. The ATD is used to obtain the smooth reference signal and its derivative. The RESO is used to estimate and compensate for the model uncertainties and external disturbances in real-time, which enhances the robustness of the controller. The modified AGSTA ensures the fast convergence of the system states and maintains them in a predefined neighborhood of origin without overestimating control gains. Besides, the proposed new variable gain strategy completely avoids the control gains vibrating near the set minimum value. Thanks to the RESO, the proposed controller is model-free and can be easily implemented in practice. The stability of the closed-loop system is analyzed based on Lyapunov’s direct method in the time domain. Finally, the proposed control scheme is applied to the station-keeping control of Haidou-1 ARV, and the simulation results confirm the superiority of the proposed control scheme over the original AGSTA. Full article

(This article belongs to the Special Issue Control Theory and Applications in Marine Autonomous Vehicles)

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