• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.330-333
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• 2005

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.592-600
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• 2010

The problem of motion control for AUV (Autonomous Underwater Vehicles) is addressed. The utilization of such robotic vehicles has gained an increasing importance in many marine activities. In this paper the objective is to describe how to design and apply FGS (Fuzzy Gain Scheduling) PD (Proportional Derivative) controller for an AUV (Autonomous Underwater Vehicle) to control the yaw and depth of the vehicle by keeping the path of the navigation to a desired point, and/or changing the path according to a set point.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.63-70
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• 2008

In this paper, we propose a bearing redundant coordinates and decoupled PD controller for 5-axes active magnetic bearing system, which consists of two bearing parts such as three-pole hybrid active magnetic bearing for stabilize the radial direction and ring-type permanent magnetic bearing stabilizing in axial and tilting motion. Based on derived system equation with decoupled control scheme, we conduct the modal analysis and measure of modal controllability and observability.

• Journal of the Korean Institute of Navigation
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• v.25 no.4
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• pp.407-415
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• 2001

In the present study, irregular disturbances to ship dynamics is proposed, where irregular disturbances implying irregular wave and the fluctuating component of wind for the evaluation of automatic steering system of ship in following seas. Prediction method based on the principle of linear superposition. Irregular wave disturbances in following seas is calculated by frequency variation method. The mathematical model of each element of an automatic steering system is derived, which takes account of a few non-linear mechanisms. PD(Proportional-Derivative) controller and low-pass filter with a weather adjustment are adopted to modelling the characteristics of an autopilot. Performance index is introduced from the viewpoint of energy saving, which derived from the concept of energy loss on ship propulsion. Finally, the present methods are applied to two typical types of ship ; an ore carrier and a fishing boat. The various effects of control constants of autopilot on propulsive energy loss are investigated

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.280-285
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• 1991

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, a learning control architecture for the dynamic control of a robot manipulator is developed using inverse dynamic neurocontroller and linear neurocontroher. The inverse dynamic neurocontrouer consists of a MLP (multi-layer perceptron) and the linear neurocontroller consists of SLPs (single layer perceptron). Compared with the previous type of neurocontroller which is using an inverse dynamic neurocontroller and a fixed PD gain controller, proposed architecture shows the superior performance over the previous type of neurocontroller because linear neurocontroller can adapt its gain according to the applied task. This superior performance is tested and verified through the control of PUMA 560. Without any knowledge on the dynamic model, its parameters of a robot , (The robot is treated as a complete black box), the neurocontroller, through practice, gradually and implicitly learns the robot's dynamic properties which is essential for fast and accurate control.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.738-746
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• 1998

This paper presents a neural network-based adaptive controller for a single flexible-link. The control for feedback-error loaming of neural network is designed by using the re-definition approach. The neural network controllers are implemented on an single flexible-link experimental test-bed. The tip response is significantly improved and the vibrations of the flexible modes are damped very fast. Experimental and simulation results are presented of the proposed tip position tracking controllers over the conventional PD-type, passive controllers.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.262-266
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• 1999

In this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PID control system, but the position control system have difficulty in controling variable load and changing parameter. We propose neural network 2-DOF PID control system having feature for removal disturbrances and tracking function in the target value point. The back propagation algorithm of neural network used for tuning the 2-DOF parameter ($\alpha$, $\beta$, ${\gamma}$, η). We investigate the 2-DOF PID control system in the position control system and verify the effectiveness of proposal method through the result of computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.244-244
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• 2000

We proposed the above-knee prosthesis using rotary MR damper in which knee joint is semi-actively controlled by microprocessor. Dissipation torque in the knee joint can be controlled by the magnetic field which is induced by applying current to a solenoid, Tracking control of knee joint angle was tested by 3-DOF Leg simulator. The experimental results show that the proposed above-knee prosthesis system had good performance in swing phase tracking and repetitive controller in conjunction with a computed control law and PD control law, reduced RMS tracking error as the repetitions of tracking. Moreover, desired knee angle trajectory was generated based on the estimation of gait period with the gyro signal and the tracking control was performed.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.154-166
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• 1992

A kinematic nonlinear multivariable launcher is modeled of which the azimuth and elevation axes are drived simultaneously and position control systems are designed for this system by the PD and LQG/LTR control methods. Also, the suitable command input fonction is suggested for the desired command following performance and the two control systems with disturbances and load variation are evaluated for the entire operating range by computer simulation. It is found that the two linear controllers can be used for the kinematic nonlinear multivariable launcher in the entire operating range and LQG/LTR controller is more effective for disturbance rejection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.346-350
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• 1996

In optical disk drives, one of commonly used pickup actuator is a Sliding and rotary type of pickup actuator which is cheaper than other pickup actuators and has simple assembly. However, it reported that non-linearity due to friction between a shaft and a sleeve had to be considerably analyzed in design and servo system in employing this type of pickup actuator. In this paper, this friction is modeled as a Coulomb's friction and the effect of friction is examined in the simulation. A digital servo system is applied to pickup actuator with friction in order to have good focusing servo. To enhance focusing servo performance using digital servo merit, frist PD-controller is applied to have fast response performance, second lead-lag compensator is applied to have stable focusing performance.