• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.68-75
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• 2004

Recently, need of the parallel manipulator requiring superior precision is increasing for medical application and precision manufacturing. In this study, we convert a given complex translation trajectory of the moving platform into a set of segments and hence a complex motion of the moving platform can be tractable and easily controled in a very limited workspace. In addition force exerted. to each link is minimized so that the minimized force can be transmitted to the end effector of the moving platform. An user friendly program is developed to design Gough-type 6DOF parallel manupulator based on the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.116-123
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• 2004

The demand for the stable and comfortable cabin of a high speed passenger ship is increasing. The study on shipboard comfort has been mainly concentrated on the motion control of a whole hull body. In this study, however, a new control system operated by two parallel robots (3RPS, 3SPR) such as the active suspension system of motor vehicle is proposed. The goal of this control is keeping zero velocity of the upper robot (cabin) although the lower robot (ship) is moving by the waves. Jacobian matrix was used to design the controller, From the simulation results, the remarkable reduction of motion of the cabin (upper platform) was observed. The 3SPR parallel robot shows better performance compared to the 3RPS robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.1
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• pp.17-32
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• 1992

The multi-layer neural network that has broadly been utilized in designing the controller of robot manipulator possesses the desirable characteristics of learning capacity, by which the uncertain variation of the dynamic parameters of robot can be handled adaptively, and parallel distributed processing that makes it possible to control on real-time. However the error back propagation algorithm that has been utilized popularly in the learning of the multi-layer neural network has the problem of its slow convergence speed. In this paper, an approach to improve the convergence speed is proposed using the fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manupulator.