Analysis of Hydrodynamic Characteristics in the Process of Autonomous Underwater Vehicle Docking

2015 ◽  
Author(s):  
Xiaoxu Du ◽  
Huan Wang
Keyword(s):  
Drag Coefficient ◽  
Autonomous Underwater Vehicle ◽  
Simple Algorithm ◽  
Underwater Vehicle ◽  
Navier Stokes ◽  
Hydrodynamic Characteristics ◽  
Successful Operation ◽  
Underwater Docking ◽  
Computational Fluid Dynamics Cfd ◽  
Volume Method

The successful operation of an Autonomous Underwater Vehicle (AUV) requires the capability to return to a dock. A number of underwater docking technologies have been proposed and tested in the past. The docking allows the AUV to recharge its batteries, download data and upload new instructions, which is helpful to improve the working time and efficiency. During the underwater docking process, unsteady hydrodynamic interference occurs between the docking device and an AUV. To ensure a successful docking, it is very important that the underwater docking hydrodynamics of AUV is understood. In this paper, numerical simulations based on the computational fluid dynamics (CFD) solutions were carried out for a 1.85m long AUV with maximum 0.2 m in diameter during the docking process. The two-dimensional AUV model without fin and rudder was used in the simulation. The mathematical model based on the Reynolds-averaged Navier-Stokes (RANS) equations was established. The finite volume method (FVM) and the dynamic structured mesh technique were used. SIMPLE algorithm and the k-ε turbulence model in the Descartes coordinates were also adopted. The hydrodynamics characteristics of different docking states were analyzed, such as the different docking velocity, the docking device including baffle or not. The drag coefficients of AUV in the process of docking were computed for various docking conditions, i.e., the AUV moving into the docking in the speed of 1m/s, 2m/s, 5m/s. The results indicate that the drag coefficient increases slowly in the process of AUV getting close to the docking device. When the AUV moves into the docking device, the drag coefficient increases rapidly. Then the drag coefficient decreases rapidly. The drag coefficient decreases with the increase of velocity when AUV enters the docking device. It was also found that the drag coefficient can be effectively reduced by dislodging the baffle of docking device.

scholarly journals Saturation Based Nonlinear FOPD Motion Control Algorithm Design for Autonomous Underwater Vehicle

2019 ◽  
Vol 9 (22) ◽  
pp. 4958 ◽  
Author(s):  
Lichuan Zhang ◽  
Lu Liu ◽  
Shuo Zhang ◽  
Sheng Cao
Keyword(s):  
Control System ◽  
Motion Control ◽  
Simple Structure ◽  
Autonomous Underwater Vehicle ◽  
Dynamic Performance ◽  
Dynamic Control ◽  
Algorithm Design ◽  
Underwater Vehicle ◽  
Motion Control System ◽  
The Stability

The application of Autonomous Underwater Vehicle (AUV) is expanding rapidly, which drives the urgent need of its autonomy improvement. Motion control system is one of the keys to improve the control and decision-making ability of AUVs. In this paper, a saturation based nonlinear fractional-order PD (FOPD) controller is proposed for AUV motion control. The proposed controller is can achieve better dynamic performance as well as robustness compared with traditional PID type controller. It also has the advantages of simple structure, easy adjustment and easy implementation. The stability of the AUV motion control system with the proposed controller is analyzed through Lyapunov method. Moreover, the controlled performance can also be adjusted to satisfy different control requirements. The outperformed dynamic control performance of AUV yaw and depth systems with the proposed controller is shown by the set-point regulation and trajectory tracking simulation examples.

scholarly journals The Backseat Control Architecture for Autonomous Robotic Vehicles: A Case Study with the Iver2 AUV

2010 ◽  
Vol 44 (4) ◽  
pp. 42-54 ◽  
Author(s):  
Donald P. Eickstedt ◽  
Scott R. Sideleau
Keyword(s):  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Dynamic Control ◽  
Underwater Vehicle ◽  
Control Architecture ◽  
Classical Dynamic ◽  
Time Dynamic ◽  
Intelligent Controller ◽  
Dynamic Controller ◽  
Robotic Vehicles

Abstract In this paper, an innovative hybrid control architecture for real-time control of autonomous robotic vehicles is described as well as its implementation on a commercially available autonomous underwater vehicle (AUV). This architecture has two major components, a behavior-based intelligent autonomous controller and an interface to a classical dynamic controller that is responsible for real-time dynamic control of the vehicle given the decisions of the intelligent controller over the decision state space (e.g., vehicle course, speed, and depth). The driving force behind the development of this architecture was a desire to make autonomy software development for underwater vehicles independent from the dynamic control specifics of any given vehicle. The resulting software portability allows significant code reuse and frees autonomy software developers from being tied to a particular vehicle manufacturer’s autonomy software and support as long as the vehicle supports the required interface between the intelligent controller and the dynamic controller. This paper will describe in detail the components of the backseat driver architecture as implemented on the Iver2 underwater vehicle, provide several examples of its use, and discuss the future direction of the architecture.

Designing of the body shape of an autonomous underwater vehicle using the design of experiments method

2018 ◽  
Vol 233 (18) ◽  
pp. 6307-6325
Author(s):  
Majid Alijani ◽  
Marhamat Zeinali ◽  
Nowrouz Mohammad Nouri
Keyword(s):  
Design Of Experiments ◽  
Drag Coefficient ◽  
Body Shape ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
The Body ◽  
Vehicle Body ◽  
Test Model

The process of designing autonomous underwater vehicles comprises several steps, including the designing of the body shape. The hydrodynamic designing of the body shape is a major step in designing the body of an underwater vehicle. The effective parameters in the hydrodynamic design of body shape include the lengths of nose and tail, nose and tail profiles, and also the dimensions of the blunt sections in front of the nose and behind the tail. In the present study, the design of experiments method has been employed to investigate the effect of each of the above parameters on the drag coefficient of an autonomous underwater vehicle body. For this purpose, in addition to introducing the body classes of the Hydrolab family of underwater vehicles, the numerical simulation results of fluid flow over the body of a Hydrolab500 AUV have been used for the design of experiments. In the first step, an experiment has been performed in water tunnel on a test model in order to validate the pressure profile for the body of Hydrolab500. The comparison between the empirical and numerical results related to Hydrolab500 body confirms the validity of the numerical approach used in this paper. The results of the present work show that the drag coefficient of an autonomous submersible in the final design can be accurately estimated with the help of the presented method.

scholarly journals Modeling and Development of an Autonomous Underwater Vehicle ARYA for Object Recognition

2019 ◽  
Vol 8 (2) ◽  
pp. 5505-5510
Keyword(s):  
Undergraduate Students ◽  
Structural Design ◽  
Power Distribution ◽  
Autonomous Underwater Vehicle ◽  
Vision System ◽  
Dynamic Control ◽  
Underwater Vehicle ◽  
Control Algorithms ◽  
Technological University ◽  
Made In

Arya is an autonomous underwater vehicle (AUV) modeled and developed by team DTU-AUV comprising of undergraduate students from multidisciplinary backgrounds of Delhi Technological University (DTU), India, to participate in an IEEE backed Singapore AUV Challenge (SAUVC). This paper entails the rationale and methodology employed to design and integrate various systems onboard. Significant improvisations have been made in the structural design of the vehicle to enhance its hydrodynamic stability and maneuverability to perform discrete tasks in comparison to the previous vehicles developed by the team. The focus is laid on the embedded and power system to enhance reliability, modularity, and power distribution. The software stack is designed to run in decentralized multi-threaded agent architecture, with the threads handling pressure sensor, cameras, control system, IMU, mission planner each performing input and output operations in continuous loops. PID control algorithms achieve the desired dynamic control. The vision system is devised to monitor the marine environment and detect underwater contoured objects.

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