• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.47.3-47
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• 2002

1. Introduction 2. Dynamics of the lunar-lander 3. Nonlinear tracking control 4. Numerical simulation 5. Conclusions

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.132.4-132
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• 2001

Field robot represented by excavator can be applied for various kinds of working in manufacturing, construction, agriculture etc. because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. In general, the dynamics of field robot have strong coupling, various kinds of non-linearity, and time varying parameters according to working conditions. Therefore, it is very difficult to describe the system well, and design controller systematically based on its model. This paper established the mathematical model of field robot driven by electro-hydraulic servomechanism and constructed the adaptive control system robust to external load variations. The proposed control system for the field robot was evaluated by the computer simulation, and the performance results of trajectory tracking were compared with that of PID control system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.463-466
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this paper, to field-robotize a hydraulic excavator, we have proposed a robust and systematic controller design method. Disturbance observer is used as inner controller to reshape the excavating system into the linear dynamics of nominal model by compensating coupled nonlinear terms, model uncertainties and external load variations. Using the linear model that is obtained through off-line system identification, a H control scheme is applied to construct a disturbance observer and a servo-controller systematically.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.417-425
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• 2012

This paper presents reference ZMP trajectory generation and implementation for a biped robot via linear inverted dumbbell model (LIDM), which can consider the effect of external momentum on the center of mass (COM) of robot. Based on a reference ZMP trajectory derived by using LIDM, a base trajectory is proposed not only to make the locomotion of robot similar to that of human but also to facilitate its implementation and tuning. In order to realize a dynamic walking using the proposed trajectory, compliance, impedance and ZMP tracking controllers are adopted together. Extensive experiments show that the proposed locomotion of a biped robot is stable and also, similar to that of human. Further researches on balance recovery of a biped robot will be carried out to guarantee its robust locomotion in combination with the proposed trajectory.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1190-1195
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• 2003

In this paper, it is shown how a robot with n passive trailers can be controlled in backward direction. When driving backward direction, a kinematic model of the system is represented highly nonlinear equations. The problem is formulated as a trajectory following problem, rather than control of independent generalized coordinates. Also, the state and input saturation problems are formulated as a trajectory generation problem. The trajectory is traced by a rear hinge point of the last trailer, and reference trajectories include line segments, circular shapes and rectangular turns. Experimental verifications were carried out with the PSR-2(public service robot $2^{nd}$ version) with three passive trailers. Experimental result showed that the backward motion control can be successfully carried out using the proposed control scheme.

• 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 Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1759-1766
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• 2003

This paper proposes a neuro­fuzzy controllers for trajectory tracking control of robot manipulators. The computed torque method is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. Therefore, the proposed controller is used to compensate the uncertainties of robot manipulators. In the neuro­fuzzy controllers, the number of fuzzy rules used forty­nine. The effectiveness of the proposed controllers is demonstrated by computer simulations using two­link robot manipulator, As a result, it is confirmed that the output of the proposed neuro­fuzzy controllers can efficiently decrease the uncertainties of robot manipulator.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.34-41
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• 2011

This paper presents a frequency-response test performed on an antagonistic actuation system consisting of two Mckibben pneumatic artificial muscles and a pneumatic circuit. A linear model, capable of estimating the dynamic characteristics of the antagonistic system in the operating range of pneumatic artificial muscles, was optimally calculated based on frequency-response results and applied to a multiple simultaneous specification control scheme. Trajectory tracking results showed that the presented multiple simultaneous specification controller, built experimentally by three PD typed sample controllers, satisfied successfully all required control specifications; rising time, maximum overshoot, steady-state error.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.121-126
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• 1999

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed. In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the manipulator of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.187-187
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• 1999

in order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed. Also, the learning architecture to compute inverse kinematic coordinates transformations in the manipulator of auto-equipment system is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulation are provided to demonstrate the effectiveness of the proposed learning method using the DNP.