• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.106-111
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• 1992

The flexible arm has considerable structural flexibility. Because of its flexibility, the dynamic nodel is very complex and difficult to get. In this paper, fuzzy logic controller(FLC) of the single-link flexible arm is proposed, for FLC does not require any mathematical model of the plant. Noncolocated control is used and the choice of linguistic variables are examined. The simulation results are presented to show the possibility of FLC for flexible arm.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.