• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1585-1588
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• 1997

In this paper, divide total workspace of robot manipulator into several subspaces and construct PID controller ineach subspace. Using EvolutionSTrategy we optimize the gains of PID controller in each subspace. But the gains may have a large difference on the boundary of subspaces, which can cause bad oscillatory performance. So we use Aritificial Neural Network to have continuous gain curves htrough the entire subspaces. Simualtion results show that the proposed method is quite useful.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.139-142
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• 1997

In this paper, a robust controller is proposed to achieve an accurate tracking for an uncertain nonlinear plant with actuator dynamics. The extent of parameter uncertainty can be quantified by using linear parameterization technique. A switching controller is proposed to guarantee the global asymptotic stability of the plant. In order to eliminate the chattering caused by the switching controller, a smoothing controller is designed using the boundary layer technique around the sliding surface and guarantees the uniform ultimate boundedness of the tracking error.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.512-515
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• 1997

In this paper the fuzzy-genetic controller for path-tracking of WMRs is proposed. Fuzzy controller is implemented to adaptive adjust the crossover rate and mutation rate, and genetic algorithm is implemented to adaptive adjust the control gain during the optimization. The computer simulation shows that the proposed fuzzy-genetic controller is effective.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.532-535
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• 1997

This paper describes the design of a fuzzy-logic controller for a differential-drive mobile robots. This controller uses absolute position information to modify control parameters to compensate the orientation error. CC-Control method is compensated for the internal error by wheel encoders and the fuzzy-logic control provides compensation for external errors. The validities of the proposed scheme is evaluated using simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1168-1171
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• 2003

The visuo-motor map is based on the Kohonen's self-organizing map. The map is learned the relation of the end effecter coordinates and the joint angles. In this paper, a 3 d-o-fmanipulator which moves in the 2D space is targeted. A CCD camera is set beside the manipulator, and the end effecter coordinates are given from the image of a manipulator. As a result of learning, the end effecter can be moved to the destination without exact teaching.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2654-2659
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• 2003

In this paper, we present biomimetic hopping strategy which is more human-like for legged robot through stiffness modulation. Stiffness value is calculated from the motion of body center of gravity. This method enable to reduce impact force on touch-down, adaption on ground stiffness change and height modulation. Simple selected models will be used to validate this method. For general model, singular perturbation is used for control and simulation using stiffness modulation is presented.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2709-2712
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• 2003

In this paper, dynamic constraints are considered for the analysis of manipulability of robotics systems comprised of two cooperating arms. Given bounds on the torques of joint actuators for each robot, the purpose of this study is to derive the bounds of task acceleration of object carried by the system. Under the assumption of complete constraint contact, a set of examplar polytope describing acceleration bounds of two cooperating robots are included.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1779-1784
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• 1991

The problem of fine manipulation is considered in this paper. By fine manipulation, we mean the positioning of the object relative to the palm as opposed to gross manipulation by the arm. The compliance in the fingers and the object is modeled by linear springs. It is shown that the motion of the fingers and object can be predicted by minimizing a quadratic objective function. A method for simulating position control algorithms is developed.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.150-153
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• 2007

The intent of this paper is to describe a neural network structure called multi dynamic neural network(MDNN), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the MDNN, are described. Computer simulations are demonstrate the effectiveness of the proposed learning using the MDNN.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.8-13
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• 1993

This paper presents deterministic and adaptive control laws for two-link flexible arm. The flexible arm has considerable structural flexibility. Because of its flexbility, dynamic equations are very complex and difficult to get, dynamic equations for two-link flexible arm are derived from Bernoulli-Euler beam theory and Lagrangian equation. Using the fact that matrix is skew symmetric, controllers which have a simplified structure with less computational burden are proposed by using Lyapunov stability theory.