• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1203-1211
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• 2009

The dynamics of underwater vehicles can be greatly influenced by the dynamics of the vehicle thrusters. The control of the state of the hovering or very slow motion of the underwater vehicle is most important for automatic docking or control of the manipulator of the vehicle. The dynamics of the thruster based on the electric motor is nonlinear and has uncertain parameters. Since the dynamics of the vehicle coupled with the dynamics of the thruster is nonlinear and has uncertain parameters, a robust control is very effective for a desired motion tracking of the uncertain and nonlinear vehicle. In this paper a study was performed on the robust control scheme of the very slow motion or hovering motion of the underwater vehicle actuated by the electric motor. Also, a concurrent control on the state of the vehicle with nonlinearity and uncertain parameters was performed. A sliding mode control algorithm out of robust controllers was designed and applied, which compensates the nonlinear forces and uncertain parameters of the vehicle and actuator. Through a computer simulation, the proposed control scheme was compared with a linear PD controller and its superior performance was validated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.3
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• pp.219-229
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• 2018

This paper proposes Kalman Filter-based relative navigation algorithms for proximity tasks such as rendezvous/docking/cluster-operation of spacecraft using PSD Sensors and Infrared Beacon Modules. Numerical simulations are performed for comparative analysis of the performance of each relative-navigation technique. Based on the operation principle and optical modeling of the PSD Sensor and the Infrared Beacon Module used in the relative navigation algorithm, a measurement model for the Kalman filter is constructed. The Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF) are used as probabilistic relative navigation based on measurement fusion to utilize kinematics and dynamics information on translational and rotation motions of satellites. Relative position and relative attitude estimation performance of two filters is compared. Especially, through the simulation of various scenarios, performance changes are also investigated depending on the number of PSD Sensors and IR Beacons in target and chaser satellites.