• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.493-497
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• 2010

Real time coordinate conversion of vessel was realized, we developed motion control algorithm of DC Servo Motor. We made servo control circuit and PCB, also We developed the system using 3-axis Gyro Sensor based Servo Motion Controller. For ship's movement simulation, we made the ship simulator of 6 degree of freedom. With a mounted camera on developed simulator, We tested the desired ship's movement, and the desired result of error tolerance was obtained.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3105-3107
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• 1999

In this paper, we propose a new approach to autonomous wall-following of wheeled mobile robots using hybrid control system. The hybrid control approach IS introduced to the motion control of nonholonomic mobile robots in the Indoor navigation problems. In hybrid control architecture, the discrete states are defined by the user-defined constraints, and the reference motion commands are specified In the abstracted motions. The hybrid control system applied to motion planning and autonomous navigation with obstacle avoidance In indoor navigation problem. Simulation results show that it is an effective method for the autonomous navigation in indoor environments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.75.3-75
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• 2002

1. introduction 2. Related Work 3. Overview of the Avatar Control System 4. A Hybrid Control Method 5. Motion Conversion 6. Experimental result and Conclusion References

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.102-111
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• 1994

This article deals with the problem of designing a robust algorithm for the motion control of robot manipulator whose nonlinear dynamics contain various uncertainties. To ensure high performance of control system, a model-based feedforward compensation with continuous robust control has been developed. The control structure based on the deterministic approach consists of two parts : the nominal control law is first introduced to stabilize the system without uncertainties, then a robust nonlinear control law is adopted to compensate for both the resulting errors(or structured uncertainties) and unstructured uncertainties. The uncertainties assumed in this study are bounded by polynomials in the Euclidean norms of system states with known bounding coefficients. The presented control scheme is relatively simple as well as computationally efficient. With a feasible class of desired trajectories, the proposed control law provides sufficient criteria which guarantee that all possible responses of the closed-loop system are uniformly ultimately bounded in the presence of uncertainties. Therefore, the control algorithm proposed is shown to be robust with respect to the involved uncertainties.

• Journal of Ocean Engineering and Technology
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• v.2 no.2
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• pp.37-45
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• 1988

A dynamically positioned vessel must be capable of maintaining a specified position and direction by controlling the thruster devices. The motions of a vessel are often assuned to tne sum of low frequency(LF)motions and high frequency(HF)motions. The former is mainly due to wind, current and second order wave forces, while the latter is mainly due to first order wave forces. In order to avoid the high frequency thruser modulation, the control system must include filters to estimate the low frequency motions from the measured motion signals, This paper presents a control system based on Kalman filtering technique and optimal control tyeory. Using the combined kalmam filter, LF motion estimates and HF ones are achieved from the motion measurement of the vessel. The estimated low frequency motions are used as inputs to the dynamic positioning system. The thruster modulation is minimized using the optimal control theory; Linear Quadratic Gaussian(LQG)controller. The performances of the Kalman filter and the dynamic positioned vessel are investigated by computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.452-460
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• 1999

Sawing experiments using a two-arm system have been performed in this work. The two-arm system under consideration of two kinematically-nonidentical arms. A passive joint is inserted at the end-point of one robot in order to increase the mobility up to the motion degree required for sawing tasks. A hybrid control algorithm for control of the two-arm system is designed. We experimentally show that the performance of the velocity and force response are satisfactory, and that one additional passive joint not only prevents the system from unwanted yaw motion in the sawing task, but also allows an unwanted pitch motion to be notably reduced by an internal load control. To show the general applicability of the proposed algorithms, we perform experimentation under several different conditions for saw, such as three saw blades, two sawing speeds, and two vertical forces.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.713-718
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• 2002

Motion controllers are essential components for operating industrial equipments. Compared with general industrial controllers, motion controllers allow motion control requiring greater speed and precision. This paper presents a method for controlling multi-axes motors via industrial networks. To achieve a line or arc interpolation, the master system delivers instructions to slave systems connected to the network. The network instruction transmitted from the master controller is re-interpolated by the individual slaves through sub-interpolators. The re-interpolated feedrate information is transmitted to the motion control loop in which the current position and the reference position are then calculated. In this way, the interpolation driving between control units is achieved via industrial networks.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1074-1080
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• 2006

Motion capture systems are gaining popularity in entertainment, medicine, sports, education, and industry, with animation and gaming applications for entertainment taking the lead. A wide variety of systems are available for motion capture, but most of them are complicated and expensive. In the general class of optical motion capture, two or more optical sensors are needed to measure the 3D positions of the markers attached to the body. Recently, a 3D motion capture system using two Position Sensitive Detector (PSD) optical sensors was introduced to capture high-speed motion of an active infrared LED marker. The PSD-based system, however, is limited by a geometric calibration procedure for two PSD sensor modules that is too difficult for common customers. In this research, we have introduced a new system that used a single PSD sensor unit to obtain 3D positions of active IR LED-based markers. This new system is easy to calibrate and inexpensive.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1159-1168
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• 2006

In this paper, a new revolute mobile robot arm with five degree of freedom (d.o.f) was developed for autonomous moving robots. As a control system for the robot arm, a distributed control system composed of the main controller and five motor controllers for arm joints was developed. The main controller and the motor controllers w ε re developed using the ARM microprocessor and the TMS320c2407 microprocessor, respectively. A new trajectory tracking algorithm for the motor controllers was devised employing pre-generated off-line trajectory data. Also, a 3-D simulator based on the openGL software to simulate the motion of the robot arm was developed. To validate the performance of the robot system, experiments to track a specified trajectory were performed.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.725-735
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• 2006

This paper deals with the problem of self-learning cooperative motion control for the pushing task of a humanoid robot in the sagittal plane. A model with 27 linked rigid bodies is developed to simulate the system dynamics. A simple genetic algorithm(SGA) is used to find the cooperative motion, which is to minimize the total energy consumption for the entire humanoid robot body. And the multi-layer neural network based on backpropagation(BP) is also constructed and applied to generalize parameters, which are obtained from the optimization procedure by SGA, in order to control the system.