• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.113.1-113
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• 2001

The robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The neural network structure presents the bound function and does not need the concave property of the bound function, The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulators.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.104.4-104
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• 2002

$\textbullet$ Contents 1 : PD control of an elastic joint robot $\textbullet$ Contents 2 Dynamic output feedback law without velocity measurements $\textbullet$ Contents 3 : Robust analysis for parameter uncertainties of the robot system $\textbullet$ Contents 4 : Simulation studies with a three joint robot system $\textbullet$ Contents 5 : Performance comparison with an another control law

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.188-193
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• 1989

This paper is proposed of multirate nonlinear controller for robot manipulator. The proposed controller is obtained by structure changes of feedback controller with C.T.M and for time differences commanded in caculating each term of controller, multirate sampling is used. And more robust controller is proposed by considering one-step ahead predictive action. In order to evaluate proposed controller, computer simulation is performed for a 3 D.O.F robot manipulator with varying load.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.658-662
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• 1991

In this paper, a real-time obstacle avoidance for mobile robot based on the readings of the ultrasonic sensors is presented. The twenty eight ultrasonic sensors are arranged in ring and controlled by microprocessor. The readings of the ultrasonic sensor is converted into the virtual forces called repulsive forces, which are the elastic and damping forces. Then, the direction and speed of mobile robot in the cluttered environment are determined by the virtual forces. The effectiveness of the proposed method is verified from a series of simulation studies.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.177-182
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• 1989

In this paper a new adaptive control algorithm is derived, with the unknown manipulator and payload parameters being estimated online. In practice, we may simplify the algorithm by not explicity estimating all unknown parameters. Further, the controller must be robust to residual time-varying disturbance, such as striction or torque ripple. Also, the reference model is a simple douple integrator and the acceleration input for robot manipulator consists of a proportion and derivative controller for trajectory tracking purposes. The validity of this control is confirmed in simulation where two-link robot manipulator shows the robust performances in spite of the existing nonlinear interaction and unknown parametrictings

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.1-5
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• 1988

The realization of high quality robot control needs the improvement of computing speed of controller. In this paper, parallel processing method is considered for this purpose. A S/W algorithm for task scheduling is developed first, and then, an appropriate H/W structure is proposed. This scheme is applied to calculate inverse kinematics of PUMA robot. The simulation results show that the computing time when using three 8086/87's is reduced to 4.23 msec compared to 10 msec in case using one 8086/87.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.67-71
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• 1988

We present an algorithm that uses trajectory following errors to improve a feedforward command to a robot in the iterative manner. It has been shown that when the manipulator handles an unknown object, the P-type learning algorithm can make the trajectory converge to a desired path and also that the proposed learning control algorithm performs better than the other type learning control algorithm. A numerical simulation of a three degree of freedom manipulator such as PUMA-560 ROBOT has been performed to illustrate the effectiveness of the proposed learning algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.161-164
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• 2000

An improved robust hybrid control law is proposed This law uses the separated bounding function: so uncertainties of each axis does not affect the others. Also, this law uses the separated $\varepsilon$, so we can take different $\varepsilon$ for each axis This law 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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• 1990.10a
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• pp.722-725
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• 1990

This paper proposes a new path planning method for obstacle avoidance of mobile robot. In order to achieve easy planning of the path, a simple representation of the empty space is achieved based on thinning algorithm. The proposed Planning technique facilitates the direct use of information obtained by camera. Comparing to the V-graph method, the task of determining the shortest path from the resulting skeleton of empty space is optimized in terms of number of computation steps. The usefulness of the proposed method is ascertained by simulation.