• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.181-189
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• 2000

This paper presents the optimal redundant actuation of parallel manipulators for complicated robotic applications such as cutting grinding drilling and digging that require a high degree of operational stiffness as well as the balance between force applicability and dexterity. First by taking into account the distribution(number and location) of active joints the statics and the operational stiffness of a redundant parallel manipulator are formulated and the effects of actuation redundancy are analyzed, Second for given task requirements including joint torque limit task force maximum allowable disturbance and maximum allowable deflection the task execution conditions of a redundant parallel manipulator are derived and the efficient testing formulas are provided. Third to achieve high operational stiffness while maintaining moderate dexterity the redundant actuation of a parallel manipulator is optimized which determines the optimal distribution of active joints and the optimal internal joint torque, Finally the simulation results for the optimal redundant actuation of a planar parallel manipulator are given.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.898-904
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• 1987

A new control algorithm using the VSS theory is developed for accurate trajectory control of robot manipulators. This paper focuses on the implementation of VSS controller with smoothing laws in the design of effective tracking control for robotic arms. The VSS controller for multi-linkage robot arm is realized using balance condition and its simplification which possesses powerful smoothing capability to reduce or even remove undesirable chattering and meanwhile keep the robust characteristic to reject system uncertainties. The design principle of selecting different smoothing methods, which aims at achieving trade-off between smoothing and robust behaviors while considering the actual system constraints, is also given and further confirmed through experimental results.

• Journal of Mechanical Science and Technology
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• v.14 no.2
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• pp.188-196
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• 2000

In this paper, our aim is to develop a model for two cooperating flexible manipulators handling a rigid object by using lumped parameters. This model is in turn analyzed on MATLAB. In order to validate the model, a precise simulation model is developed using $ADAMS^{TM}$ (Automatic Dynamic Analysis of Mechanical System). Moreover, to clarify the discussion, the motions of a dual-arm experimental flexible manipulator are considered. Using the developed model, we control a robotic system with a symmetric hybrid position/force control scheme. Finally, experiments and simulations are performed, and a comparison of simulation results with experimental results is given to a rerify the validity of our model.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.22-29
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• 2004

This paper studies the coordinated trajectory control of an excavator as a kind of robotic manipulators driven by hydraulic actuators. Hydraulic robot system has many non-linearity in dynamics and kinematics, and strong coupling among joints(or hydraulic cylinders). This paper proposes a combined controller frame of the adaptive robust control(ARC) and the sliding mode control(SMC) for the trajectory tracking control of the excavator to preserve the advantages of the both methods while overcoming their drawbacks, namely, asymptotic stability of adaptive system for parametric uncertainties and guaranteed transient performance of sliding mode control for both parametric uncertainties and external disturbance. The suggested control technique is applied for the tracking of a straight-line motion of end-effector of manipulators, and through computer simulations, its trajectory tracking performances and the robustness to payload variation and uncertainties are illustrated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.186-193
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• 1988

A pointwise PD-optimal control method is proposed for the continuous path control of robot manipulators with bounded inputs. The controller employs the desired acceleration plus PD (proportional and derivative) actions in the Cartesian space. The gain parameters of the controller are adjusted so that the Euclidean norm of the deviation between the actual and desired accelerations is minimized subject to the constraints of bounded input torques and the system guarantees negative feedback. To show the Validities of the proposed mithods, computer simulations are performed for a SCARA type robot.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.2
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• pp.152-161
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• 1988

In this paper, a direct method for obtaining the trajectory set points is investigated in discrete-time, which is different from the other conventional schemes. We consider the tracking of a straight line path, where the trajectory set points for manipulator control are determined exactly on the straight line path. For the purpose of the munimum-time operation of manipulators, the problem is formulated as a maximization of the Cartesian distance between two consecutive servo time instants. The maximization is subject to the smoothness and torque constraints. Several algorithms are developed and utilized to maximize the Cartesian distance. The proposed approach has been simulated on a VAX-11/780 computer to verify its performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.41-47
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• 2000

A better tracking performance can be achieved, if visual sensors such as CCD cameras are used in controling a robot manipulator, than when only relative sensors such as encoders are used. However, for precise visual servoing of a robot manipulator, an expensive vision system which has fast sampling rate must be used. Moreover, even if a fast vision system is implemented for visual servoing, one cannot get a reliable performance without use of robust and stable inner joint servo-loop. In this paper, we propose a dynamic control scheme for robot manipulators with eye-in-hand camera configuration, where a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to be robust to parameter uncertainty, disturbances, low sampling rate, etc.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.513-518
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• 1998

In this paper, a robust fault-tolerant control scheme for robot manipulators overcoming actuator failures is presented. The joint(or actuator) fault considered in this paper is the free-swinging joint failure and causes the loss of torque on a joint. The presented fault-tolerant control framework includes a normal control with normal(non-failed) operation, a fault detection and a fault-tolerant control to achieve task completion. For both no uncertainty case and uncertainty case, a stable normal con-troller and an on-line fault detection scheme are presented. After the detection and identification of joint failures, the robot manipulator becomes the underactuated robot system with failed actuators. A robust adaptive control scheme of robot manipulators with the detected failed-actuators using the brakes equipped at the failed(passive) joints is proposed in the presence of parametric uncertainty and external disturbances. To illustrate the feasibility and validity of the proposed fault-tolerant control scheme, simulation results for a three-link planar robot arm with a failed joint are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.