Size Prediction Control Modeling in Cylindrical Grinding

Abstract:

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A dynamic size control model during cylindrical grinding is built. The model consists of Elman neural network, fuzzy control subsystem and deformation optimal adaptive control subsystem. To improve the size prediction accuracy, the first and the second derivative of the actual amount removed from the workpiece are added into the Elman network input; To self-adapt and adjust the quantification factor and scale factor in the fuzzy control, the flexible factor is introduced to the fuzzy control model. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.

Info:

Periodical:

Advanced Materials Research (Volumes 154-155)

Edited by:

Zhengyi Jiang, Xianghua Liu and Jinglong Bu

Pages:

977-980

DOI:

10.4028/www.scientific.net/AMR.154-155.977

Citation:

N. Ding et al., "Size Prediction Control Modeling in Cylindrical Grinding", Advanced Materials Research, Vols. 154-155, pp. 977-980, 2011

Online since:

October 2010

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Price:

$35.00

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