• 한국공작기계학회논문집
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• 제15권5호
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• pp.114-122
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• 2006

This paper presents a new control scheme that combines a sliding mode control and a neural network. In the proposed sliding mode control, a continuous control is employed removing the switching phenomena and the equivalent control within the boundary layer is estimated through on-line teaming of the neural network. The performances of the proposed control are compared with off-line neural network and on-line neural sliding mode control by computer simulation. The simulation results show that the proposed control reduces high frequency chattering and tracking error in example of the two link manipulator.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1993년도 춘계학술대회논문집
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• pp.18-26
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• 1993

When designing workplaces, controls should be placed within the reach of operator's arm or foot to guarantee effective performance. The aviation industry is perhaps the chief user of anthropometric data for its need to weight minimization and space optimization. In designing a workplace which must cater to a wide range of operator size, it might be sufficient to plan only for the 'average person'. Static arm reach measurements which are taken in conventional, standardized positions provide the necessary information, but they cannot be directly applied to dynamic situations. In this research, an approximate algorithm to generate the workspace of the human body including foot reach and trunk motion is proposed and tested. The robot kinematics was employed to represent the human body as a multi-link system.