Search Results (52)

Autonomous Underwater Vehicle (AUV) swarms possess advantages such as efficiency, reliability, flexibility, and extensive coverage in underwater operations. However, their coordinated control is challenged by communication interruptions and actuator failures in complex marine environments. This paper proposes a fixed-time event-triggered fault-tolerant formation control method to address these challenges. First, the Prim algorithm and the Hungarian algorithm are employed to reconstruct the communication topology, mitigating AUV disconnections due to communication failures and ensuring formation stability. Second, a fixed-time extended state observer (ESO) is designed to estimate the lumped disturbance arising from model uncertainties, unknown ocean disturbances, and actuator failures. Finally, a performance function is introduced to reformulate error variables, and a fixed-time event-triggered formation control law is developed based on an auxiliary saturation system and an event-triggering mechanism. In addition, this paper demonstrates the stability of the entire closed-loop system, and no Zeno phenomenon will occur. Simulation experiments demonstrate the effectiveness and superiority of the proposed method in maintaining robust formation control of AUV systems under adverse conditions. Full article

This paper studies the trajectory tracking control problem of an autonomous underwater vehicle (AUV). A robust model predictive control (MPC) framework based on the implementation of the receding horizon is implemented to address the challenges of unknown external disturbances and model uncertainties faced by the AUV in trajectory tracking control. Within this MPC framework, a formulation that simultaneously handles both practical actuator limitations and dynamic environmental constraints is introduced. Specifically, the controller enforces hard constraints on both the maximum driving force and also the maximum rate of change in the propeller driving force. This rate constraint is essential for ensuring the control signal respects the physical dynamics of the thrusters and prevents hardware damage. These hardware-level constraints are integrated with online updates of system state constraints which define the AUV’s working space, granting it autonomous obstacle avoidance capabilities. Finally, the performance of the controller is demonstrated by simulations and physical experiment results. Full article

This paper addresses the cooperative formation control problem for a heterogeneous unmanned system composed of Unmanned Surface Vehicles (USVs) and Autonomous Underwater Vehicles (AUVs) under coexisting constraints of actuator faults, time-varying communication topology, and communication delay. First, a unified dynamic model is established under the Euler–Lagrange framework. Building on this, a novel distributed adaptive fault-tolerant control (DAFTC) framework is proposed. This framework integrates a Dynamic Event-Triggered Mechanism (DETM) to address communication bandwidth limitations, alongside an adaptive fault-tolerant strategy to enhance system robustness. The novelty lies in the cohesive integration of DETM for communication efficiency and adaptive laws for online fault compensation (both loss of effectiveness and bias), while rigorously handling communication delays via Lyapunov–Krasovskii analysis. It is proven via Lyapunov stability analysis that the proposed control protocol ensures all signals in the closed-loop system remain semi-globally uniformly ultimately bounded, with the formation tracking error converging to an adjustable compact set. Simulation results demonstrate the framework’s effectiveness. Compared to periodic communication (0.1 s interval), the proposed DETM reduces the communication load by over 99.6%. Even when subjected to a 25% effectiveness fault and a 5 Nm bias fault, the root-mean-square (RMS) tracking error is maintained below 0.15 m, validating the system’s high performance and robustness. Full article

An adaptive fault-tolerant containment control approach is developed for nonlinear multi-agent systems to address issues related to both communication link and actuator faults. This approach achieves fault-tolerant containment control through the introduction of a convex hull signal estimator and a fault compensation mechanism. First, a leader–follower network model with communication link faults is constructed, and distributed containment errors are established. The proposed framework involves three key components: the design of an adaptive backstepping control law, the introduction of a nonlinear filter for boundary error elimination, and the application of a radial basis function neural network (RBFNN) for the approximation of unknown nonlinear terms. Meanwhile, an adaptive convex hull estimator is designed to estimate the signals formed by the leaders, and an actuator fault estimator is constructed to compensate for fault signals online. Additionally, Lyapunov stability analysis demonstrates that all containment errors remain uniformly bounded. To support simulation teaching and validation, numerical simulations and autonomous underwater vehicle (AUV) simulations are used to not only to confirm the efficacy of the presented control technique but also to provide illustrative cases for educational purposes. Full article

Autonomous underwater vehicles (AUVs) play a critical role in underwater remote sensing and monitoring applications. This paper addresses the problem of navigating multiple AUVs to perform sweep video sensing of unknown underwater regions over uneven seafloors, where visibility is limited by the conical field of view (FoV) of the onboard cameras and by occlusions caused by terrain. Coverage is formulated as a feasibility objective of achieving a prescribed target fraction while respecting vehicle kinematics, actuation limits, terrain clearance, and inter-vehicle spacing constraints. We propose an online, occlusion-aware trajectory planning algorithm that integrates frontier-based goal selection, safe viewing depth estimation with clearance constraints, and model predictive control (MPC) for trajectory tracking. The algorithm adaptively guides a team of AUVs to preserve line of sight (LoS) visibility, maintain safe separation, and ensure sufficient clearance while progressively expanding coverage. The approach is validated through MATLAB simulations on randomly generated 2.5D seafloor surfaces with varying elevation characteristics. Benchmarking against classical lawnmower baselines demonstrates the effectiveness of the proposed method in achieving occlusion-aware coverage in scenarios where fixed-pattern strategies are insufficient. Full article

This paper proposes an optimal-sliding-mode-based adaptive dynamic programming (ADP) master–slave synchronous control strategy for the actuator saturation and performance constraints that AUVs face in dynamic recovery. First, by introducing the sliding-mode function into the value function to optimize the state error and its derivative simultaneously, the convergence speed is significantly improved. Second, by designing the performance constraint function to directly map the sliding-mode function, the evolution trajectory of the sliding-mode function is constrained, ensuring the steady-state and transient characteristics. In addition, the hyperbolic tangent function (tanh) is introduced into the value function to project the control inputs into an unconstrained policy domain, thereby eliminating the phase lag inherent in conventional saturation compensation schemes. Finally, the requirement for initial stability is relaxed by constructing a single-critic network to approximate the optimal control policy. The simulation results show that the proposed method has significant advantages in terms of the position and attitude synchronization error convergence rate, steady-state accuracy, and control signal continuity compared with the conventional ADP method. Full article

In this work, a predefined-time formation output constraint control method is proposed for underactuated AUVs with input saturation. First, a coordinate transformation method is utilized to convert the underactuated AUV system into a fully actuated system form. A universal time-varying asymmetric barrier function is constructed to convert the system to an unconstrained form and construct the formation tracking error. Then, a predefined-time formation output constraint control law is designed based on the active disturbance rejection control framework and predefined-time control method, which can achieve the control objective without relying on the precise mathematical model of the system. In addition, to address the input saturation issue, a novel predefined-time auxiliary dynamic system (ADS) is proposed. The proposed method with ADS can ensure that the multi-AUV system with input saturation can complete the formation output constraint tracking control task within a predefined time. Finally, a simulation is designed to verify the effectiveness of the proposed method. Full article

This paper studies the distributed robust predefined-time sliding mode control (DRPSC) problem for high-order heterogeneous multi-agent systems under input saturation while considering external disturbances and model uncertainties. Firstly, a distributed predefined-time state observer (PTSO) is designed for each agent to achieve individual estimation of the state information of the virtual leader within a predefined time, and the observer does not need to count on the global information of the system. Secondly, a predefined-time auxiliary dynamic system (PTADS) is developed to solve the actuator’s input saturation problem. Thirdly, a distributed predefined-time sliding mode controller (PTSMC) is proposed, which ensures that the error converges to a small region near zero within a predefined time and combines H_∞ control to deal with the lumped uncertainty disturbances in the system to improve the robustness of the system. In addition, a memory event-triggered mechanism (METM) is designed to reduce the communication frequency of the underactuated AUV-USV multi-agent system and reduce the consumption of communication resources. Finally, Lyapunov theory is employed to prove that the closed-loop system is predefined-time stable, and the simulation results demonstrate that the proposed method is effective. Full article

In complex marine environments, ramp-based recovery systems for autonomous underwater vehicles (AUVs) often encounter engineering challenges such as reduced docking accuracy and success rate due to disturbances in the capture window attitude. In this study, a desktop-scale physical experimental platform for recovery compensation was designed and constructed. The system integrates attitude feedback provided by an attitude sensor and dual-motor actuation to achieve active roll and pitch compensation of the capture window. Based on the structural and geometric characteristics of the platform, a dual-channel closed-loop control strategy was proposed utilizing midpoint tracking of the capture window, accompanied by multi-level software limit protection and automatic centering mechanisms. The control algorithm was implemented using a discrete-time PID structure, with gain parameters optimized through experimental tuning under repeatable disturbance conditions. A first-order system approximation was adopted to model the actuator dynamics. Experiments were conducted under various disturbance scenarios and multiple control parameter configurations to evaluate the attitude tracking performance, dynamic response, and repeatability of the system. The results show that, compared to the uncompensated case, the proposed compensation mechanism reduces the $MSE$ by up to 76.4% and the $MaxAE$ by 73.5%, significantly improving the tracking accuracy and dynamic stability of the recovery window. The study also discusses the platform’s limitations and future optimization directions, providing theoretical and engineering references for practical AUV recovery operations. Full article

Steel lazy wave risers (SLWRs) are critical in offshore hydrocarbon transport for linking subsea wells to floating production facilities in deep-water environments. The incorporation of buoyancy modules reduces curvature-induced stress concentrations in the touchdown zone (TDZ); however, extended operational exposure under cyclic environmental and operational loads results in repeated seabed contact. This repeated interaction modifies the seabed soil over time, gradually forming a trench and altering the riser configuration, which significantly impacts stress patterns and contributes to fatigue degradation. Accurately reconstructing the riser’s evolving profile in the TDZ is essential for reliable fatigue life estimation and structural integrity evaluation. This study proposes a simulation-based framework for the autonomous tracking of SLWRs using a fin-actuated autonomous underwater vehicle (AUV) equipped with a monocular camera and multibeam echosounder. By fusing visual and acoustic data, the system continuously estimates the AUV’s relative position concerning the riser. A dedicated image processing pipeline, comprising bilateral filtering, edge detection, Hough transform, and K-means clustering, facilitates the extraction of the riser’s centerline and measures its displacement from nearby objects and seabed variations. The framework was developed and validated in the underwater unmanned vehicle (UUV) Simulator, a high-fidelity underwater robotics and pipeline inspection environment. Simulated scenarios included the riser’s dynamic lateral and vertical oscillations, in which the system demonstrated robust performance in capturing complex three-dimensional trajectories. The resulting riser profiles can be integrated into numerical models incorporating riser–soil interaction and non-linear hysteretic behavior, ultimately enhancing fatigue prediction accuracy and informing long-term infrastructure maintenance strategies. Full article

This paper presents an energy-optimized path planning approach for fully actuated autonomous underwater vehicles (AUVs) in three-dimensional ocean environments to enhance their operational range and endurance. A fully actuated AUV is characterized by its high degrees of freedom and precise controllability. Using real terrain data, we construct environmental models incorporating a Lamb vortex and random obstacles. We develop a mathematical model of the AUV’s total energy consumption, accounting for constraints imposed by its fully actuated design and extensive maneuverability. To minimize energy usage, we propose an energy-optimized path planning algorithm that combines energy-optimized particle swarm optimization (EOPSO) and sequential quadratic programming (SQP). The proposed method identifies the optimal path for energy consumption and the corresponding optimal surge speed. The efficacy of the algorithm in optimizing the total energy consumption of the AUV is demonstrated through the simulation of various scenarios. In comparison to other algorithms, paths planned by this algorithm are shown to have superior robustness and optimized energy consumption. Full article

This paper proposes a dynamic event-triggered adaptive backstepping control for underactuated autonomous underwater vehicle systems (AUVs) with input saturation. The proposed method ensures the system’s stability by introducing a new auxiliary signal system to compensate for the input saturation. Firstly, the underactuated AUVs is separated into the underactuated part and the actuated part, and then the dynamic auxiliary signal system is introduced. A transformation is used to combine the actuated part with the auxiliary signal system. The controller is designed using the adaptive backstepping method, and a dynamic event-triggering mechanism is constructed to obtain the event-triggering controller. A strict theoretical analysis is provided to avoid the Zeno phenomenon. Finally, the effectiveness of the dynamic event-triggered adaptive backstepping controller is verified by simulation. Full article

Autonomous Underwater Vehicles (AUVs) have shown significant promise across various underwater applications, yet face challenges in dynamic environments due to the limitations of traditional motion planning methods while Artificial Potential Field (APF)-based control barrier functions focus solely on obstacle proximity and distance-based methods oversimplify obstacle geometries, and both fail to ensure safety and satisfy turning radius constraints for under-actuated AUVs in intricate environments. This paper proposes a robust Model Predictive Control (MPC) framework integrating an enhanced fast marching control barrier function, specifically designed for AUVs equipped with fully directional sonar systems. The framework introduces a novel improvement for moving obstacles by extending the control barrier function field propagation along the obstacle’s movement direction. This enhancement generates precise motion plans that ensure safety, satisfy kinematic constraints, and effectively handle static and dynamic obstacles. Simulation results demonstrate superior obstacle avoidance and motion planning performance in complex scenarios, with key outcomes including a minimum safety margin of 1.86 m in cluttered environments (vs. 0 m for A* and FMM) and 1.76 m in dynamic obstacle scenarios (vs. 0.13 m for MPC-APFCBF), highlighting the framework’s ability to enhance navigation safety and efficiency for real-world AUV deployments in unpredictable marine environments. Full article

This paper presents a three-dimensional (3D) robust adaptive finite-time path-following controller for underactuated Autonomous Underwater Vehicles (AUVs), addressing model uncertainties, external disturbances, and actuator magnitude and rate saturations. A path-following error system is built in a path frame using the virtual guidance method. The proposed cascaded closed-loop control scheme can be described in two separate steps: (1) A kinematic law based on a finite-time backstepping control (FTBSC) is introduced to transform the 3D path-following position errors into the command velocities; (2) The actual control inputs are designed in the dynamic controller using an adaptive fixed-time disturbance observer (AFTDO)-based FTBSC to stabilize the velocity tracking errors. Moreover, the adverse effects of magnitude and rate saturations are reduced by an auxiliary compensation system. A Lyapunov-based stability analysis proves that the path-following errors converge to an arbitrarily small region around zero within a finite time. Comparative simulations illustrate the effectiveness and robustness of the proposed controller. Full article

To address the control challenges posed by increasingly complex mission scenarios, this paper aims to develop an advanced formation control and obstacle avoidance strategy for autonomous underwater vehicles (AUVs) in SE(3). This study establishes a dynamic model for fully actuated AUVs and designs a consensus-based formation control strategy to achieve coordinated movement. Motivated by limitations of existing obstacle avoidance strategies such as local minima issues and mutual interference between formation members in high-density environments, this paper introduces a novel gyroscopic force-based obstacle avoidance method. The proposed approach leverages the principles of rotation and angular momentum conservation to enable effective obstacle avoidance while maintaining formation integrity. Simulation results demonstrate the effectiveness of the proposed methodology in achieving robust formation control and collision avoidance under challenging conditions. Full article