• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.886-888
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• 1995

Models of industrial robot manipulators are characterized by highly nonlinear equation with coupling between the variables of motion. In this paper, a case study that illustrates the use or nonlinear state feedback to decouple the control of a two axis SCARA type robot manipulator is presented. This method is based on a suitable partition about the dynamic equation of industrial robots. The performance of this method is showed by the computer simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.59-68
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• 1992

In this paper, we proposed coordinator description and ambiguity on the hybrid controller for position/force control of robot manipulator. When the hybrid controller is desiged based on the PID control conception, the parameter sharing problem must be considered. However, selection problem of coordinate system on n-DOF robot manipulator control is unsolved. Moreover, contact force on object and change of shape make another problems. And it is very difficult to figure out the accurate mathematical model of manipulator on account of ambiguity and nonlinearity of actuator. Therfore, we design a new hybrid controller, FPID(Fuzzy PID). For verifying the validity of the controller, we tried computer simulation of this system. As a result, we can get remarkable improvement of overdamping and overshooting. Also we can solve compicance problem effectively. Furthermore, ambiguity problem is solved by adding control knowledge based compensator. So robust controller can be acheived, too.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.25-34
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• 1992

This paper proposes a Self-Tuning control algorithm for tracking the reference trajectory by measuring the end-point of robot manipulator whose links are light and flexible, and the performance of it is tested through the computer simulation. As an object of system, a flexible robot manipulator with two-links is considered and an assumed mode shape method including gravity force is adopted to analyze the vibration modes for each links and dynamics equation is derived. The controller is designed as a combined form which consists of dynamic feedforward compensator and self-tuning feedback controller. The one supplies nominal torque and the other supplies variational torque to manipulator. Apart from the, K-incremental predictor is also proposed in order to eliminate the offset error. and it shows that the result of simulation adapted well to load change and rapid velocity.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1137-1153
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• 1995

It is not yet possible to solve the optimal number of neurons in hidden layer at neural networks. However, it has been proposed and proved by experiments that there is a limit in increasing the number of neuron in hidden layer, because too much incrememt will cause instability,local minima and large error. This paper proposes a module neural controller with pattern recognition ability to solve the above trade-off problems and to obtain fast learning convergence speed. The proposed neural controller is composed of several module having Multi-layer Perrceptron(MLP). Each module have the less neurons in hidden layer, because it learns only input patterns having a similar learning directions. Experiments with six joint robot manipulator have shown the effectiveness and the feasibility of the proposed the parallel module neural controller with pattern recognition perceptron.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.590-595
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• 1996

The robust control technique is generally the iterative design method to determine a robust control for perturbed system with prescribed range of perturbation based on the robust stability measure. However, robot manipulator has the structured pertubation and the unstructured one. This paper proposes the robust technique for designing controller such that the trajectory of end-effector of robot manipulator tracks asymptotically the desired trajectory for all allowable variations in the manipulator's parameter. For satisfying asymptotical stability though we can not know the bound of perturbations and the parameter variations, the relation between the unknown parameter and the parameter of nominal system can be derived from Krasovskii theorem and we construct the new robust control using that relation. (author). 12 refs., 6 figs.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1234-1236
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• 1996

In this paper, the trajectory needed to be tracked by the manipulator was defined in a new plot differently from conventional methods. And the trajectory provides Solution directly related to coordinates of output variables from the plant. So, it overcomes nonlinearity between joint and Cartesian coordinates in movement mode and it makes use of inverse Kinematics unnecessary, which was obstacle for real-time control. The 2-axis SCARA robot was modelled and simulation was performed to validate in this paper. And it proved this has better performance in rapidity and decrease of position-error, compared to the conventional FLCs.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.305-307
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• 1994

In this paper, the desist and the implementation of a robust adaptive controller for trajectory tracking control of the robot manipulator is presented. The proposed control scheme ensures that without any prior knowledge of the robot manipulator parameters, tracking errors are converged to some boundary in the presence of a state-dependent input disturbances as well as the ideal case. The 3 DOF robot manipulator including actuator dynamics is used for the implementation of the proposed control scheme. The experimental results show that the proposed control scheme is valid for trajectory tracking control of the robot manipulator.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.25-32
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• 1994

This paper presents a robust impedance controller design to coordinate a robot manipulator under system uncertainties while regulating external forces. By an impedance approach, the relationship between the motion and external forces is defined. Due to the system uncertainties, two kind of sliding mode control schemes based on the impedance approach are derived to ensure that the manipulator end-effector follows a desired trajectory and the force applied to end effector is regulated according to a target impendance. A stability condition is shown according to a sliding condition. To evaluate the devised control scheme, a numerical example is shown.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.7
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• pp.610-614
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• 1991

This paper proposes a trajectory constrol fo a robot manipulator by using neural network. The inverse dynamic model of manipuator is learned by neural network. The manipulator is controlled by weight values of the learned neural network. The weight valuese is change with a torque of liner vontroller and a acceleration error. Phsically, the totlal torque for a manipualator is a sum of the liner controller torque and the nerural network controller torque. The proposed control effect is estimated by computer simulation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.2
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• pp.207-214
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• 1987

In this paper, we developed a method of describing the structure of robot arms and a systematic way to use it as a robt-design-aid tool. To describe the structure of robot arms, a robot was regarded as a collection of various links in the form of polygonal pillars. With the aid of the homogeneous transformation, a set of commands for describing the information on how all the links in the robot are connected was defined and used in graphically realizing complex link-based structures including robot manipulators.