• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1916-1922
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• 2004

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.855-860
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• 2007

This paper describes a human driver model developed based on finite preview optimal control method. The human driver steering model is constructed to minimize a performance index which is a quadratic form of lateral position error, yaw angle error and steering input. Simulation studies are conducted using a vehicle simulation software, Carsim. The Carsim vehicle model is validated using vehicle test data. In order to validate the human driving steering model, the human driver steering model is compared to the driving data on a virtual test track(VTT) and the actual vehicle test data. It is shown that human driver steering behaviors can be well represented by the human driver steering model presented in this paper

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.158-164
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• 2000

In recent year, desire and request fer micro automation are growing rapidly covering the whole range of the industry. This has been caused mainly by request of more accurate manufacturing process due to a higher density of integrated circuits in semiconductor industry. This paper presents a six d.o.f fine motion stage using magnetic levitation technique, which is one of actuating techniques that have the potential for achieving such a micro motion. There is no limit in motion resolution theoretically that the magnetically levitated part over a fixed stator can realize. In addition, it Is possible to manipulate the position and the force of the moving part at the same time. Then, the magnetic levitation technique is chosen into the actuating method. However, we discuss issues of design, kinematics, dynamics, and control of the proposed system. And a few experimental results fur step input are given.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.311-314
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• 1995

Biped locomotion can be simply modeled as a linear inverted pendulum mode. This model considers only the CG (center of gravity) of the entire system. But in real biped robot systems, the free-leg motion dynamics is not negligible. So if its dynamics is not considered in designing the reference CG motion, it is badly influence to the ZMP(zero moment point) position of the biped robot walking in the sagittal plane. Therefore, we modeled the biped locomotion similar to the linear inverted pendulum mode but considered the predetermined free-leg dynamics. To verify that the proposed biped locomotion is more stable than the linear inverted pendulum mode, we constructed a biped robot simulator and designed a serco controller to track both the reference motion of the free leg and the reference motion of CG of the biped robot using the computed torque control low. And through simulations, we verified that the proposed walking is better in stability than the one based on the linear inverted pendulum mode.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.922-925
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• 2004

The paper presents the component parts and their models of the Switched Reluctance motor drive system with the angle position-current chopping control and with the fixed angle pulse width modulation control. The calculation of the parameters and the simulated models based on the MATLAB SIMULINK software package are introduced by a four-phase 8/6 structure prototype with the four-phase asymmetric bridge power converter. The simulation of the prototype in the course of starting is made by the simulated models at the different control strategies and the different given rotor speed.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.38-41
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• 2003

An Autonomous Mobile Robot(AMR) performs duty by sensing a recognized situation and controlling suitably. The existing algorithm has some advantages that it is possible to express the obstacle exactly and the robot is sensitive to the change of environment. However, this algorithm needs to control repeatedly according to the modelling and working environment that requires a great quantity of calculations. In this paper, We supplement shortcoming and designed direction algorithm of AMR using fuzzy controller. Fuzzy controller does not derive special quality spinning expression for system, and uses rules by value expressed by language. It is used extensively to non-linear, plant which mathematical modelling is difficult etc... Fuzzy control algorithm of AMR that is used by this research applies obstacle position, distance of obstacle, Progress direction of robot, speed of robot, Perception area of sensor, etc... by fuzzy control and decide steering angle of robot.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.378-380
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• 2009

For the autonomous movement, the optimal pat]1 planning connecting between current and target positions is essential, and the optimal path of mobile robot means obstacle-free and the shortest length path to a target position. Many actual mobile robots should move without any information of surrounded obstacles. This paper suggests a new method of obstacle avoidment which is suitable in unknown environments. This method of obstacle avoidance is designed with a distributed fuzzy control system, and imitates a Potential Field method. A simulation confirms the performance and correctness of the obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.130.1-130
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• 2001

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effector of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded ...

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.800-807
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• 1999

A Periodic disturbance canceller is proposed to compensate for the periodic disturbance due to cutting process in a CNC machining center. The periodic disturbance canceller estimates the Periodic disturbance without phase delay. This is achieved by using linear phase low-pass filter and frequency response reciprocal filter of plant at the frequency of the periodic disturbance. This method is implemented in the position control system of the CNC machining center with general disturbance compensators in order to compensate for both the frictional force and the periodic disturbance. The experimental results are described to show its effectiveness.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.305-310
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• 2002

The measured rate of the tracking sensor becomes biased under some operational situation. For a highly maneuverable aircraft in 3D space, the target dynamics changes from time to time, and the Kalman filter using position measurement only can not be used effectively to reject the rate measurement bias error. To cope with this problem, we present a new algorithm which incorporate FIR-type filter and FIR-type fixed-lag smoother, and demonstrate that it has the optimal performance in terms of both estimation accuracy and response time through an application example to the anti-aircraft gun fire control system(AAGFCS).