Hydrodynamic coefficient estimation is crucial to the shape design, dynamic modeling, and control of underwater vehicles. In this paper, we conduct a numerical study on the hydrodynamic coefficient estimation of an underactuated underwater vehicle (actuated only in the surge, heave, and yaw degrees of freedom) by adopting the computational fluid dynamics (CFD) approach. Firstly, the mechanical structure of an underactuated underwater vehicle is briefly introduced, and the dynamic model of the underwater vehicle with hydrodynamic effects is established. Then, steady and unsteady Reynolds Averaged Navier–Stokes (RANS) simulations are carried out to numerically simulate the towing test, rotating arm test, and Planar Motion Mechanism (PMM) test of the underwater vehicle numerically. To simulate unsteady motions of the underactuated underwater vehicle, a sliding mesh model is adopted to simulate flows in the computational fluid domain that contain multiple moving zones and capture the unsteady interactions between the underwater vehicle and the flow field. Finally, the estimated hydrodynamic coefficients of the underwater vehicle are validated in a physical experiment platform, and the results show that the numerical estimates are in good agreement with the experimental data.

This paper presents the development of a portable autonomous underwater vehicle (AUV) named Shark, along with the design of its hovering control system for vision-based underwater inspection. Firstly, the mechanical structure design, electrical system configuration, and software system development of the Shark AUV are introduced, highlighting its cost-effectiveness, compact size, and streamlined torpedo shape to enhance the flexibility of underwater inspections. Secondly, the dynamic model of the Shark AUV is established, and the hydrodynamic coefficients are numerical estimated utilizing computational fluid dynamics (CFD) simulations. Thirdly, considering that the developed Shark AUV is underactuated in the sway degree of freedom, a novel heading control model is developed that reasonably tackles the motion coupling between sway and yaw. This model facilitates the design of a robust $\mathcal {H}_{\infty }$ controller to regulate the heading angle of the Shark AUV for vision-based underwater inspections. Finally, the effectiveness of the designed hovering control method and vision-based underwater inspection system are validated in both a 3D simulation platform and a laboratory test pool. The experimental results demonstrate that the Shark AUV prototype can achieve satisfactory vision-based underwater inspection performance within a pixel error of 5 × 5, and the proposed $\mathcal {H}_{\infty }$ heading controller consistently provides superior performance in handling motion coupling, parametric uncertainty, and external disturbances.

In order to establish a proper geometry of an Unmanned Underwater Vehicle (UUV) for stable motion control and energy usage reduction, this paper analyzes the hydrodynamic performance of a complex shape underwater vehicle and develops a systematic Computational Fluid Dynamics (CFD) simulation method to solve the hydrodynamic parameters of the system. Based on the simulation method and their results, the streamlines and pressure distributions of the water flow around the underwater vehicle are analyzed, and the geometric model design is improved based on the drag characteristics. Also, a comparison scheme is designed to evaluate the vehicle model before and after the geometry improvement. Simulation result shows that the design schemes brings 18% drag reductions in surge direction and 32% in heave direction. Moreover, by establishing the physical and mathematical models of the UUV on a physical simulation platform, a complete model of the underwater vehicle is constructed, laying the foundation for further simulations and experiments.

Remotely operated underwater vehicles (ROVs) have been widely used in deep-sea resource exploitation and industrial engineering operations. To perform these tasks accurately in the deep-sea environment, stable motion control has become a key area of research on ROV systems, which has led to the importance of analyzing the hydrodynamic characteristic of ROVs. But a systematic methodology for analyzing the hydrodynamic characteristics of ROVs is still lacking nowadays. In this paper, systematic numerical simulation methods for analyzing hydrodynamic characteristics and shape optimization of a work-class ROV are conducted, and details of simulation procedures based on computational fluid dynamics are studied, which can be a foundation for robust controller design.

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.