• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.426-432
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• 2009

In this paper, redundancy resolution of UVMS (underwater vehicle-manipulate. system) is addressed. In general, UVMS has redundant DOFs (degrees of freedom) as many as DOFs of manipulator and these redundant DOFs can be used to optimize the configuration of UVMS while satisfying given tasks. We propose a performance index for redundancy resolution which minimizes the restoring moments of UVMS. The restoring moment can cause unintentional change of poses of UVMS. If the restoring moments remain small, control effort for keeping the poses of UVMS decreases. This means that energy consumption can be reduced by minimizing the restoring moments during conducting tasks. Proposed performance measure is optimized by gradient projection method. Generated trajectories by this redundancy resolution are tracked by robust PID controller. Numerical simulations are presented to demonstrate performance of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.305-312
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• 2000

This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.526-530
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• 2011

This paper presents a new fuzzy model-based design approach for waypoints-tracking control of nonlinear underwater vehicles (UUVs) on a horizontal plane. The waypoints-tracking control problem is converted into the stabilization one for the error model between the given nonlinear UUV and the waypoints. By using the sector nonlinearity, the error model is modeled in Takagi-Sugeno's form. We then derive stabilization conditions for the error model in the format of linear matrix inequality. A numerical simulation is provided to illustrate the effectiveness of the proposed methodology.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.197-208
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• 2010

The ostraciiform swimming mode allows the simplest mechanical design and control for underwater vehicle swimming. Propulsion is achieved via the flapping of caudal fin without the body undulatory motion. In this research, the propulsion of underwater vehicles by ostraciiform swimming mode is explored experimentally using an ostraciiform fish robot and some rigid caudal fins. The effects of caudal fin flapping frequency and amplitude on the cruising performance are studied in particular. A theoretical model of propulsion using rigid caudal fin is proposed and identified with the experimental data. An experimental method to obtain the drag coefficient and the added mass of the fish robot is also proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.227-237
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• 1997

Autonomous Underwater Vehicles(AUVs) have become an important tool for various purposes in subsea: inspection, recovery, construction, etc., and the development of autonomous control system is luglay desirable- thete zffe many problems associated with designing the control system for AUV due to unknown underwater envimn-Tnent, the possibility of subsystem failures, and unpredictable changes in the dynamics of the vehicle. In this paper, an autonomous control system based on the intelligent control theory to enhance operation efficiency of the ALTV is presented. The control system has a hierarchical structure which consists of mission planning level, mission control level, navigation level, and execution level. The performance of the control system is investigated by computer simulation. The results show that the proposed control system can be applied successfully to the AUV in spite of the possibility of failures in the vehicle and the collision hazard in the sea environment.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.82-87
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• 2023

This paper proposes a disturbance observer-based control for 6-DOF remotely operated underwater vehicles with model uncertainties. The sum of external disturbance and the forces generated from model parameters except for the inertial matrix of the hydrodynamic model is defined as a lumped disturbance in this paper. Then, the lumped disturbance caused by model uncertainties and the external forces is estimated using the disturbance observer. Fortunately, the disturbance observer is constructed as a linear form because all the elements of the inertial matrix of the hydrodynamic model are constants. To verify the proposed control scheme, we show that the actual lumped disturbance is similar to the estimated lumped disturbance obtained by the disturbance observer. Finally, the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.8-15
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• 2024

This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H_∞ optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.527-532
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• 1993

Generally the method of depth controlling is classified into buoyancy control and thrust control. In this study, we employed thrust control system. And mathematical modeling and computer simulation are performed in order to design auto depth control system for underwater vehicle. Consequently, the specifications of components are determined, and the performance of system is analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.653-657
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• 1990

Since linearized equations of notion have much modelling errors, robust controller for disturbances and noises Is necessary for autopilot. In this paper, notion equations for underwater vehicle with six degree-of-freedom are derived and linearized. And robust autopilot for this system is designed by using LQG/LTR methodology.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.