Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/70426
Title: Geometrical error compensation of gantry stage using neural networks
Authors: Tan, K.K. 
Huang, S. 
Prahlad, V. 
Lee, T.H. 
Issue Date: 2005
Source: Tan, K.K.,Huang, S.,Prahlad, V.,Lee, T.H. (2005). Geometrical error compensation of gantry stage using neural networks. Lecture Notes in Computer Science 3498 (III) : 897-902. ScholarBank@NUS Repository.
Abstract: This paper presents some results on geometrical error compensation using multilayer neural networks (NNs). It is the objective to attain higher compensation performance with less or comparable memory, using this approach. There are three main contributions. First, multilayer NNs are used to approximate the components of geometrical errors. This results in a significantly less number of neurons compared to the use of radial basis functions (RBFs). Secondly, the direction of motion is considered in the compensator. This is important as the geometrical errors can be quite distinct depending on the direction of motion due to backlash and other nonlinearities in the servo systems. Thirdly, the Abbe error is explicitly addressed in the compensator. © Springer-Verlag Berlin Heidelberg 2005.
Source Title: Lecture Notes in Computer Science
URI: http://scholarbank.nus.edu.sg/handle/10635/70426
ISSN: 03029743
Appears in Collections:Staff Publications

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