• 제어로봇시스템학회논문지
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• 제6권2호
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• pp.127-137
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• 2000

This paper presents a novel neural based controller which controls the water level of the nuclear power plant steam generator. The controller consists of a model reference feedback linearization controller and a PI controller for stabilizing the feedback linearization controller. The feedback linearization controller consists of a neural network model and an inversing module which uses the neural network model for computing the control input to the steam generator. We chose Piecewise Linearly Trained Network(PLTN) and Recurrent Neural Netwrok(RNN) for an approximator of the plant and used these approximators in calculating the input from the feedback linearization controller. Combining the above two controllers gives a result of better performance than the case which uses only a PI controller Each control result of PLTN and RNN is given.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.20-24
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• 1997

In general, pantograph type manipulators are used for carrying heavy payloads with positional accuracy. In this paper, a double pantograph type manipulator, activated by two slider joints, is studied for applying to file handing machine in atomic power plant. In order to realize the stable horizontal movement of a heavy fuel rod whit good positional accuracy, methods for allocating slider and finding constant joint rates are proposed. In addition, the static deflection of the proposed mechanism was studied using transfer-stiffness matrix method. A neural network control algorithm which compensates static deflections is explored with computer simulations.