• Journal of Ocean Engineering and Technology
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• v.9 no.2
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• pp.30-40
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• 1995

In this paper, it is proposed a robust control scheme for real time control of a robot manipulator with parameter uncertainties. The focus of this paper is a new approach of multivariable control schemes for an assembly robot manipulator to achieve the accurate trajectory tracking by joint angles. The proposed control scheme consists of a multivariable feedforward controller and feedback controller. In this control scheme, the feedback controller consists of proportional-derivative type and is designed by the pole placement method. The feedforward controller uses the inverse of the linealized model of robot manipulator dynamics. This feedback controller ensures that each joint enables to track any reference trajectory. The proposed robot controller scheme has a computational efficiency.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.575-578
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• 1995

In general, the control of robot manipulator is classified into position control and force control. Position controllers give adequate performance when a manipulator is following a trajectory through space and end-effector has no contact with environment. However for most tasks performed by robot manipulator in industry, contact is made between the end-effector and manipulator's environment, so position control may not suffice. The objective of this study is to control both position of a manipulator and the contact forces generated at the hand by using a conceptually simple control law. Position and force control problem is decoupled into subtasts via taskspace formulation and inverse dynamics. Then, the position controllers are designed for the task space variable which represent tangent motion and the forte controllers are designed for the lash space variables which represent normal force.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.539-546
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• 2004

Conventional robot manipulators actuated by motors with the speed reducer such as the harmonic drive have weakness in the load capacity, since the speed reducer does not have enough strength. To overcome this, a new type of the robot actuator based on the four-bar-link mechanism driven by the ball screw was proposed and constructed. Also, a new type of a revolute-jointed robot manipulator composed of the developed actuators was developed. The base axis is actuated by the motor with the conventional speed reducer, but the other axes are actuated by the proposed actuators. The kinematics and dynamics of the robot were analyzed, and the performance test of the robot was made. Through the test results, the performance of superior load capacity versus the robot weight is shown.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.58-62
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• 1988

Recently many adaptive control schemes for the industrial robot manipulator have been developed. Especially, learning control utilizing the repetitive motion of robot and based on iterative signal synthesis attracts much interests. However, since most of these approaches excludes the boundness of the input torque supplied to the manipulator, its effectiveness may be limited and also the full dynamic capacity of the robot manipulator can not be utilized. To overcome the above-mentioned difficulties and meet the desired performance, we propose an approach which yields the effective learning control schemes in this paper. In this study, some stability conditions derived from applying the Lyapunov theory to the discrete linear time-varying dynamic system are established and also an optimization scheme considering the bounded input torque is introduced. These results are simulated on a digital computer using a three-joint revolute manipulator to show their effectiveness.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.299-301
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• 1994

Visual feedback has traditionally been used in robot manipulator control to a limited extent. However in varying environment, visual data is needed to control the manipulator to complete the desired task. In this paper we present a method of manipulator control scheme called image-based visual servo. In this scheme we use image data as feedback to control robot manipulator. And we also show the experimental results with an industrial robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.698-701
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• 1996

A novel neural network control scheme is proposed to identify the inverse dynamic model of robot manipulator and to compensate for uncertainties in robot dynamics. The proposed controller is called reference compensation technique(RCT) by compensating at reference input trajectory. The proposed RCT scheme has many benefits due to the differences in compensating position and learning algorithm. Since the compensation is done outside the plant it can be applied to many control systems without modifying the inside controller. It performs well with low controller gain because the operating range of input values is small and the output of the neural network controller is amplified through the controller gain. The back-propagation algorithm is used to train and simulations of three link robot manipulator are carried out to prove the proposed controller's performances.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.596-601
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• 1990

When using robot manipulator to carry out autonomous tasks, the positioning accuracy of the robot manipulator relative to a reference coordinate frame is of greate importance. The task program, which is generated by off-line CAD-system and used in actual robot positioning, may cause serious amount of the absolute positioning error of the robot manipulator. In this study, a robot performance test and calibration algorithms are proposed in order to improve the absolute positioning accuracy of the robot end effector. Experiments were also carried out by utilizing the HYUNDAI Robot AE 7601 and KIM2-Tester, a three dimensional measurement system, which is developed in Robotics & Fluid Power Control Lab. at Korea Institute of Science and Technology.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.2
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• pp.318-324
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• 2010

In this paper, the structure of the gravity compensator has been designed and applied to a light structure of a new 6-axis robot manipulator to enhance its torque performance. Also, analyses on the kinematics and inverse-kinematics of the manipulator have been performed. An FEM analysis has been performed on the structure of robot links to have an excellent performance of delivering 25 kg payload despite of 30kg weight, which is very light compared with other manipulators. Through the FEM analysis, the stability on the vending or fracture of the links of the robot manipulator has been verified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.490-493
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• 1996

This paper presents a control scheme for the motion of a 2 DOF robot manipulator. Robot manipulators are multivariable nonlinear systems. Fuzzy logic is avaliable human-like control without complex mathematical operation and is suitable to nonlinear system control. In this paper, Implementation of fuzzy logic control of robotic manipulators shows. Algorithm has been performed with simulation packages MATRIXx and SystemBuild.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.519-526
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• 1990

In this paper we propose the resolved motion controller using a neural network for a robot manipulator. Neural identifier designed by a neural network is trained by using a feedback force as an error signal. The identifier approximates the output of a unknown nonlinear system by monitoring both the input and the output of this system. If the neural network is sufficiently trained well, it does not require either strict modelling of the manipulator or precise parameter estimation. The effectiveness of the proposed controller is demonstrated by computer simulation using a two-link planar robot.