Search Results (23)

Multi-robot collaboration and marine robotics constitute key research directions in intelligent autonomous systems. In this context, multi-ROV cooperative operations are increasingly deployed for sunken ship search missions. A central technical challenge in such applications is to ensure efficient, non-redundant coverage while maintaining accurate formation tracking. This scenario confronts two principal difficulties. First, overlapping operational regions among multiple ROVs tend to produce both redundant coverage and search blind zones. Second, trajectory tracking accuracy is significantly degraded by the combined effects of hydrodynamic disturbances and inherent actuator constraints in ROVs. To address these challenges, an improved dynamic window approach (DWA), incorporating a search distance penalty mechanism, is proposed for multi-ROV trajectory planning. Concurrently, a cascaded tracking control architecture is constructed, wherein a model predictive kinematic controller generates constrained velocity references, while an adaptive sliding mode dynamic controller augmented with an extended state observer provides robust disturbance rejection. Collaborative search is conducted using a three-ROV leader–follower formation. Simulation results indicate that regional search coverage is effectively improved and areas of repeated detection are significantly reduced by the proposed planning algorithm. Real-time trajectory tracking is achieved by the designed controller under two typical extreme strong disturbance conditions, namely, time-varying disturbances and abrupt disturbances, on the premise of satisfying thruster thrust constraints. The proposed scheme enables all three ROVs to successfully complete the tracking task under time-varying disturbances while reducing the frequency of thrust saturation events by up to seven times. In contrast, under the conventional MPC–ASMC controller, one ROV deviates from the formation and fails to complete the tracking task. Under abrupt disturbances, the proposed approach reduces the trajectory tracking error by up to six times and decreases the frequency of thrust saturation events by up to four times. Full article

This paper presents a fixed-time fault-tolerant control strategy based on an improved long short-term memory network for dynamic positioning of unmanned marine vehicles subject to signal quantization, disturbances, and input saturation. Firstly, an improved long short-term memory network optimized by an adaptive mixed-gradient algorithm is developed to accurately estimate external disturbances. Secondly, a fixed-time extended state observer is designed to rapidly predict thruster faults. Subsequently, within a fixed-time control framework, a novel terminal sliding-mode surface incorporating signal quantization parameters is constructed. In addition, a dynamic uniform quantization strategy with tunable sensitivity is introduced to effectively alleviate the performance degradation induced by quantization errors. Based on this, a fixed-time fault-tolerant controller is constructed. Finally, simulation results and comparative experiments are provided to demonstrate the effectiveness of the proposed control scheme. Full article

Currently, Japan’s fishing industry is facing a severe decline in its workforce. As a response, fishing mechanization using small underwater robots is promoted. These robots offer advantages due to their compact size, although their operating time is limited. A major source of this limited operating time is posture stabilization, which requires continuous thruster use and rapidly drains the battery. To reduce power consumption, anchoring the robot to the seabed with anchors is proposed. However, due to neutral buoyancy, the available thrust is limited, making penetration into the seabed difficult and reducing stability. To address this, we focus on composite-shaped anchors and vibration. The anchors combine a conical tip and a cylindrical shaft to achieve both penetrability and holding force. However, a trade-off exists between these functions depending on the tip angle; anchors with larger angles provide better holding capacity but lower penetrability. To overcome this limitation, vibration is applied to reduce soil resistance and facilitate anchor penetration. While vibration is known to aid penetration in saturated soft soils, the effect of tip angle under such conditions remains unclear. This study aims to clarify the optimal tip angle for achieving sufficient penetration and holding performance under vibratory conditions. Experiments in underwater saturated soft soil showed that vibration improves both penetration and holding. This effect was strong in anchors with tip angles optimized for holding force. These findings support the development of energy-efficient anchoring systems for autonomous underwater operations in soft seabed environments. Full article

This paper presents a fault-tolerant thruster configuration scheme and a thrust control allocation strategy for an underwater vehicle. First, to accommodate the vehicle’s flexible spatial motion capabilities and address potential thruster failures, an 8-thruster vector arrangement is designed, and the impact of thruster failures on vehicle maneuverability is analyzed. Based on this configuration, a mathematical model of the vector propulsion system is then developed, establishing the relationship between the thrust generated by the individual thrusters and the virtual control forces applied to the vehicle’s 6 degrees of freedom (DOF). Subsequently, a thrust allocation strategy based on quadratic programming (QP) is proposed to optimize thrust allocation, enhancing energy efficiency while satisfying thrust saturation constraints. Finally, simulation results demonstrate that the proposed thruster configuration exhibits strong fault-tolerance. Moreover, compared to the least squares (LS) method based on the pseudo-inverse of the configuration matrix, the QP-based thrust allocation strategy achieves significantly better energy-saving performance. Full article

To enhance the autonomy of semi-submersibles, a Model Predictive Control (MPC) strategy was proposed based on real-time Line-of-Sight (LOS) to address the issue of thruster saturation. By identifying parameters using experimental data from sea trials, the dynamic model of the semi-submersible was derived and established. The kinematic and dynamic models were combined to construct a complete MPC prediction model, and the LOS method was integrated into the MPC strategy to achieve trajectory-tracking functionality. Unlike prior research that was validated exclusively through simulations, this paper further validated the efficacy of the improved LOS-MPC in real path tracking through a series of sea trials. The experimental findings indicate that the improved LOS-MPC approach is capable of rapidly guiding the semi-submersible to precisely follow the reference trajectory. In comparison to conventional PID controllers, the LOS-MPC-based path-tracking controller demonstrates enhanced effectiveness in terms of response speed, tracking accuracy, and robustness. Full article

Shaftless propulsion technology delivers high efficiency and low noise for subsea installations and marine vessels. To enhance thrust performance, the streamlined aft-body contour imposes stringent demands on geometric compatibility between the rim-driven thruster (RDT) motor and hull. This necessitates advanced electromagnetic characterization of conical motors. This paper proposes an equivalent magnetic circuit model (EMCM) that accounts for end effects and magnetic saturation in both the stator and rotor cores for the magnetic field analysis of conical permanent magnet synchronous motor (CPMSM). A 3D EMCM is developed by decomposing the air-gap flux into radial/axial/tangential components. End-field nonlinearities are addressed via lumped-parameter network modeling. Innovatively, a trapezoidal expanded magnet layout and magnet-pole-trimming technology are adopted to ensure sinusoidal flux distribution. Finally, a 10.5 kW prototype with a conical angle of 6.7 degrees is designed using the EMCM and verified through a finite-element analysis (FEA) and experiments. This research provides a theoretical framework for the rapid electromagnetic analysis of the CPMSM. Full article

This paper proposes an adaptive dynamic positioning (DP) control method based on a multi-observer fusion architecture with minimal sensor requirements. A sliding mode observer is designed based on a high- and low-frequency superposition model to filter high-frequency state variables, while a finite-time convergence disturbance observer estimates unknown time-varying low-frequency disturbances online. For efficient handling of model uncertainties, a single-parameter learning neural network is implemented that requires only one parameter to be estimated online. The control system employs auxiliary dynamic systems to handle input saturation constraints and considers thruster system dynamics. Theoretical analysis demonstrates the stability of the observer-fusion control strategy, while simulation results based on the SimuNPS platform validate its effectiveness in state estimation and disturbance rejection compared to traditional sensor-dependent methods. Full article

This work studies the dynamic positioning (DP) control issue of unmanned surface vessels subjected to thruster saturation, error constraints, and lumped disturbances composed of time-varying marine environmental disturbances and model parameter uncertainties. Combining the disturbance-accurate estimation technique and the prescribed performance control strategy, a novel prescribed-time DP control scheme is established to address this challenging problem. In particular, the prescribed-time lumped disturbance observer is designed to accurately estimate external marine disturbances, which guarantees that the estimation error converges to zero within a prescribed time. Subsequently, a prescribed performance control strategy is proposed to guarantee that the positioning errors of DP surface vessels with thruster saturation constraints meet the error constraints requirements within a prescribed time. Furthermore, an anti-windup compensator is presented to mitigate the thruster saturation and improve the robustness of the DP control system. The stability analysis demonstrates that all positioning errors of the closed-loop system can converge to predefined performance constraints within a prescribed time. Finally, the numerical simulation confirms the efficacy and superiority of the proposed PTDP scheme. Full article

This study proposes a receding horizon optimization-based docking control method to address the autonomy and safety challenge of underwater docking between manned submersibles and unmanned vehicles, facilitating the integration of docking trajectory generation and tracking control. A novel approach for optimizing and generating reference trajectory is proposed to construct a docking corridor that satisfies safe collision-free and visual guidance effective regions. It generates dynamically feasible and continuously smooth docking trajectories by rolling optimization. Subsequently, a docking trajectory tracking control method based on nonlinear model predictive control (NMPC) is designed, which is specifically tailored to address thruster saturation and system state constraints while ensuring the feasibility and stability of the control system. The control performance and robustness of underwater docking were validated through simulation experiments. The optimized trajectory generated is continuous, smooth, and complies with the docking constraints. The control system demonstrates superior tracking accuracy than backstepping control, even under conditions where the model has a 40% error and bounded disturbances from currents are present. The research findings presented in this study contribute significantly to enhancing safety and efficiency in deep-sea development. Full article

Underactuated Unmanned Surface Vessels (USVs) are widely used in civil and military fields due to their small size and high flexibility, and trajectory tracking control is a critical research area for underactuated USVs. This paper proposes a trajectory tracking control strategy using the Biologically Inspired Neural Network (BINN) for USVs to improve tracking speed and accuracy. A virtual control law is designed to obtain the required virtual velocity for trajectory tracking control, in which the velocity error is calibrated to ensure that the position error converges to zero. To observe and compensate for unknown and complex environmental disturbances such as wind, waves, and currents, a nonlinear extended state observer (NESO) is designed. Then, a controller based on Non-singular Terminal Sliding Mode (NTSM) is designed to resolve the problems of singular value and controller chattering and to improve the controller response speed. A BINN is introduced to simplify the process of differentiation, reduce the input values of the initial state, and solve the problem of thruster input saturation. Finally, the Lyapunov stability theory is utilized to analyze the stability of the proposed algorithm. The simulation results show that the proposed algorithm has a higher trajectory tracking accuracy and speed than traditional methods. Full article

The ejection of the plasma plume produced by laser ablation is an important process for inducing mechanical effects. Therefore, in this paper, the characteristics of the plasma plume are investigated in order to analyze the impulse coupling mechanism with two laser spot diameters, 300 μm and 1100 μm, respectively. The impulse generated by laser irradiating the copper target was measured by the torsion pendulum, and the plasma plume was investigated using fast photography and optical emission spectroscopy. The experimental results show that the optimal laser intensity is independent of the beam spot size. However, when the laser intensity is greater than 2.8 × 10⁹ W/cm², the impulse coupling coefficient with the small beam spot starts to gradually decrease, while that with the large beam spot tends to saturate. Additionally, the stream-like structure and the semi-ellipsoid structure of the plasma plume were observed, respectively. Furthermore, the electron number density was estimated using the Stark broadening method, and the effect of the plasma plume on the impulse coupling coefficient was discussed. The results provide a technical reference for several applications including orbital debris removal with lasers, laser thrusters, and laser despinning. Full article

In this paper, the sliding mode technique is used to study the quantized fault-tolerant control of unmanned marine vehicles with thruster saturation. Firstly, the sliding mode surface is constructed according to the full rank decomposition of input matrix, and the stability of sliding mode is guaranteed by linear matrix inequalities. An improved dynamic adjustment scheme of quantization parameter is proposed. Compared with the original adjustment scheme, the relationship between quantization parameter and desired targets is increased, so that the adjustment range of quantization parameters is more comprehensive. The sliding mode controller is combined with quantization parameter adjustment strategy to ensure the asymptotic stability of unmanned marine vehicles system. In addition, compared with the existing research results of quantitative fault tolerance problem without considering saturation, this paper gives a result of the domain of attraction affected by the fault of the thruster. Finally, the superiority of the proposed method is verified by simulation comparison. Full article

Autonomous Underwater Vehicles (AUVs) or underwater vehicle-manipulator systems often have large model uncertainties from degenerated or damaged thrusters, varying payloads, disturbances from currents, etc. Other constraints, such as input dead zones and saturations, make the feedback controllers difficult to tune online. Model-free Reinforcement Learning (RL) has been applied to control AUVs, but most results were validated through numerical simulations. The trained controllers often perform unsatisfactorily on real AUVs; this is because the distributions of the AUV dynamics in numerical simulations and those of real AUVs are mismatched. This paper presents a model-free RL via Data-informed Domain Randomization (DDR) for controlling AUVs, where the mismatches between the trajectory data from numerical simulations and the real AUV were minimized by adjusting the parameters in the simulated AUVs. The DDR strategy extends the existing adaptive domain randomization technique by aggregating an input network to learn mappings between control signals across domains, enabling the controller to adapt to sudden changes in dynamics. The proposed RL via DDR was tested on the problems of AUV pose regulation through extensive numerical simulations and experiments in a lab tank with an underwater positioning system. These results have demonstrated the effectiveness of RL-DDR for transferring trained controllers to AUVs with different dynamics. Full article

In order to simultaneously address the issues of ship operating area limitation, unknown time-varying disturbances, immeasurable ship speed, unknown dynamics, and input saturation, this paper investigates the position-constrained ship dynamic positioning output feedback control, taking thruster system dynamics into account. Firstly, a barrier Lyapunov function (BLF) is utilized to limit the ship position inside the dynamic positioning system’s acceptable working range and to limit the ship position error. Second, the set total disturbance, which is made up of unknown time-varying disturbances and unknown dynamics and is further handled by the control strategy, is estimated using a fixed-time extended state observer (FDESO). Additionally, the thruster system dynamics equations are incorporated into the controller design process so that the generated thrust signal varies gradually without abrupt fluctuations, in keeping with engineering realities. Furthermore, the thruster input saturation issue is dealt with using a finite-time auxiliary dynamic system. Finally, a robust control term is introduced to handle the errors generated in the controller design. The stability proof section demonstrates that the designed control strategy can cause the ship to arrive and maintain at the desired location and heading, as well as stay continuously inside the designated operating area with all signals of the closed-loop control system being consistently and eventually bounded. The simulation results demonstrate that the proposed system is valid. Full article

This paper focuses on the fault tolerant control of autonomous underwater vehicles (AUVs) in the presence of dynamic uncertainties and potential thruster failure issues. For this, an adaptive proportional-integral sliding mode-based fault tolerant control (APISM-FTC) is proposed to drive the AUV to follow the desired trajectory, in the event of unknown thrusters failure and thrusters saturation. Radial basis function neural network (RBFNN) and an adaptive approach are used to evaluate the dynamics uncertainty during the construction of the APISM-FTC controller. To guarantee that all tracking errors asymptotically converge to zero, a comprehensive theoretical analysis and mathematical proof based on Lyapunov stability analysis are implemented. The simulation experiments on two fault conditions are carried out, respectively, and the control effects under normal conditions are compared. It can be shown that the designed APISM-FTC method can make the system reach a stable state quickly, and can still have a good control performance in the case of the failure of the thruster. Full article