• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1181-1184
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• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this paper, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• 전자공학회논문지B
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• 제33B권2호
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• pp.1-9
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• 1996

Although the fuzzy logic controller (FLC) has been adopted in many engineering applications, one hesitates to adopt the FLC in critical applications, since there was no definite control theoretic analysis. In this paper, based on the stability/robustness analysis of an FLC by S.Y.Yi$^{[3]}$, we apply the FLC to robot manipulator with the structured and unstructured uncertainties e.g., load variation and firction, etc. And we verify the performance of the FLC by computer simulation on a simple two-link robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.1113-1119
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• 1989

Neural network control has many innovative potentials for intelligent adaptive control. Among many, it promises real time adaption, robustness, fault tolerance, and self-learning which can be achieved with little or no system models. In this paper, a dynamic robot controller has been developed based on a backpropagation neural network. It gradually learns the robot's dynamic properties through repetitive movements being initially trained with a PD controller. Its control performance has been tested on a simulated PUMA 560 demonstrating fast learning and convergence.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.990-995
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• 1991

The integration of intelligent robots into manufacturing systems should positively impact the product quality and productivity. A new theory of object location and recognition using the supporting plane is presented. The unknown supporting points are determined by image coordinates, known camera parameters, and joint coordinates of the robot manipulators. This is developed by using the geometrical interpretation of perspective projection and the geometrical constraints of industrial environments. This can be applied to solve typical robot vision problems such as determination of position, orientation, and recognition of objects.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.669-674
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• 1989

Robot manipulators are highly coupled nonlinear systems and their motions are influenced by uncertain dynamics. In this paper a design methodology which is called model feedback control system or plant model control scheme is presented for the purpose of reducing the influence of the uncertain dynamics. This control system is applied to the trajectly control of the directly drived robot. Theoretically and experimentally performances resulting from use of this control scheme show that the influences of the uncertain dynamics are reduced obviously.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.259-262
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• 2001

An improved robust hybrid control law is proposed. This law used the separated bounding function and the stiffness bound. It satisfied the performance though we don't know precise information of contact environments. It guarantees the practical stability in sense of Lyapunov. Simulation was performed to validate this law using a four-axis SCARA type robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.258-262
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• 1990

Several optimum control algorithms have been proposed to minimize the robot cycle time by velocity scheduling. Most of these algorithms assume that the dynamic and kinematic characteristics of a manipulator are fixed. This paper presents the study of a minimum-time optimum control for robotic manipulators considering parameter changes. A complete set of solutions for parameter identification of the robot dynamics has been developed. The minimum-time control algorithm has been revised to be updated using estimated parameters from measurements.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.480-484
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• 1990

A simple time-delay method for avoiding collisions between two articulated robot manipulators is proposed. Links of robot are approximated by polyhedra and the danger of collision between two robots is expressed by distances between the robots. An algorithm, which can fast obtain the minimum time-delay value needed for collision avoidance, using scheme of following the boundary contour of collision region in the collision map which has information about collisions between two robots, is described.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.74-74
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• 2000

This paper presents a neural network controller for a rigid-link electrically-driven robot. The proposed controller is designed in conjunction with three neural networks approximating for complicated nonlinear functions. Particularly, the fact, different from conventional schemes, is that the neural network based current observer is used. Therefore, no accurate measurement of the actuator driving current is required. In the proposed controller-observer scheme, the derived weight update rule guarantees the stability of closed-loop system in the sense of Lyapunov. The effectiveness and performance of the proposed method are demonstrated through computer simulation.

• 제어로봇시스템학회논문지
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• 제10권4호
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• pp.312-316
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• 2004

In this paper, it is presented an adaptive robust control system to implement real-time control of a robot manipulator. There are Quantitative or qualitative differences between a real robot manipulator and a robot modeling. In order to compensate these differences, uncertain factors are added to a robot modeling. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, etc. Also, uncertainty is often nonlinear and time-varying. In the proceeding work, we proposed a class of robust control of a robot manipulator and provided the stability analysis. In the work, we propose a class of adaptive robust control of robot manipulator with bound estimation. Through experiments, the proposed adaptive robust control scheme is proved to be an efficient control technique for real-time control of a robot system using DSP.