• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.1-7
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• 2003

Autonomous underwater vehicles (AUVs) are unmanned, underwater vessels that are used to investigate sea environments in the study of oceanography. Docking systems are required to increase the capability of the AUVs, to recharge the batteries, and to transmit data in real time for specific underwater works, such as repented jobs at sea bed. This paper presents a visual :em control system used to dock an AUV into an underwater station. A camera mounted at the now center of the AUV is used to guide the AUV into dock. To create the visual servo control system, this paper derives an optical flow model of a camera, where the projected motions of the image plane are described with the rotational and translational velocities of the AUV. This paper combines the optical flow equation of the camera with the AUVs equation of motion, and deriver a state equation for the visual servo AUV. Further, this paper proposes a discrete-time MIMO controller, minimizing a cost function. The control inputs of the AUV are automatically generated with the projected target position on the CCD plane of the camera and with the AUVs motion. To demonstrate the effectiveness of the modeling and the control law of the visual servo AUV simulations on docking the AUV to a target station are performed with the 6-dof nonlinear equations of REMUS AUV and a CCD camera.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.91-96
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• 2001

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate to effectiveness of the proposed techniques.

• Ocean Systems Engineering
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• v.7 no.2
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• pp.157-177
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• 2017

This research is based on the concept of safety airbag to design a self-rescue system for the autonomous underwater vehicle (AUV) using micro inertial sensing module. To reduce the possibility of losing the underwater vehicle and the difficulty of searching and rescuing, when the AUV self-rescue system (ASRS) detects that the AUV is crashing or encountering a serious collision, it can pump carbon dioxide into the airbag immediately to make the vehicle surface. ASRS consists of 10-DOF sensing module, sensing attitude algorithm and air-pumping mechanism. The attitude sensing modules are a nine-axis micro-inertial sensor and a barometer. The sensing attitude algorithm is designed to estimate failure attitude of AUV properly using sensor calibration and extended Kalman filter (SCEKF), feature extraction and backpropagation network (BPN) classify. SCEKF is proposed to be used subsequently to calibrate and fuse the data from the micro-inertial sensors. Feature extraction and BPN training algorithms for classification are used to determine the activity malfunction of AUV. When the accident of AUV occurred, the ASRS will immediately be initiated; the airbag is soon filled, and the AUV will surface due to the buoyancy. In the future, ASRS will be developed successfully to solve the problems such as the high losing rate and the high difficulty of the rescuing mission of AUV.

• Ocean Systems Engineering
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• v.2 no.2
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• pp.83-97
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• 2012

In the present work, design procedure and computer simulation of an AUV are documented briefly. The design procedure containing the design of propulsion system and CFD simulation of hydrodynamics behavior of the hull leads to achieve an optimum mechanical performance of AUV system. After designing, a comprehensive one dimensional model including motor, propeller, and AUV hull behavior simulates the whole dynamics of AUV system. In this design, to select the optimum AUV hull, several noses and tails are examined by CFD tools and the brushless motor is selected based on the first order model of DC electrical motor. By calculating thrust and velocity in functional point, OpenProp as a tool to select the optimum propeller is applied and the characteristics of appropriate propeller are determined. Finally, a computer program is developed to simulate the interaction between different components of AUV. The simulation leads to determine the initial acceleration, final velocity, and angular velocity of electrical motor and propeller. Results show the final AUV performance point is in the maximum efficiency regions of DC electrical motor and propeller.

• Ocean Systems Engineering
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• v.1 no.4
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• pp.297-315
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• 2011

New applications of streamlined Autonomous Underwater Vehicles require an AUV capable of completing missions with both high-speed straight-line runs and slow maneuvers or station keeping tasks. At low, or zero, forward speeds, the AUV's control surfaces become ineffective. To improve an AUV's low speed maneuverability, while maintaining a low drag profile, through-body tunnel thrusters have become a popular addition to modern AUV systems. The effect of forward vehicle motion and sideslip on these types of thrusters is not well understood. In order to characterize these effects and to adapt existing tunnel thruster models to include them, an experimental system was constructed. This system includes a transverse tunnel thruster mounted in a streamlined AUV. A 6-axis load cell mounted internally was used to measure the thrust directly. The AUV was mounted in Memorial University of Newfoundland's tow tank, and several tests were run to characterize the effect of vehicle motion on the transient and steady state thruster performance. Finally, a thruster model was modified to include these effects.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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• pp.130-135
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• 2004

This paper presents a 3-D localization of an autonomous underwater vehicle(AUV). Conventional methods of localization, such as LBL or SBL, require additional beacon systems, which reduces the flexibility and availability of the AUV We use a digital compass, a pressure sensor, a clinometer and ultrasonic sensors for localization. From the orientation and velocity information, a priori position of the AUV is estimated based on the dead reckoning. With the aid of extended Kalman filter algorithm, a posteriori position of the AUV is estimated by using the distance between the AUV and a mother ship on the surface of the water together with the water depth information from the pressure sensor. Simulation results show the possibility of practical application of the method to autonomous navigation of the AUV.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.14-22
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• 2009

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.23-32
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• 2009

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.4
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• pp.451-458
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• 2012

In this paper, the design study of a new convertible six d.o.f underwater robot which can be a ROV or AUV according to underwater work purpose is presented. A structure design about the ROV and the AUV and its design on the control system is presented. In case of the AUV, an analysis on thruster forces in accordance with operating speed has been performed. A sensor fusion board which can proceed various sensor signals to identify correct positions and speeds has been developed and a total control system including EKF(Extended Kalman Filter) has been designed and developed.