Geometrical error compensation of gantry stage using neural networks

Authors:
Kok Kiong Tan;Sunan Huang;V. Prahlad;Tong Heng Lee
Affiliations:
National University of Singapore, Singapore;National University of Singapore, Singapore;National University of Singapore, Singapore;National University of Singapore, Singapore
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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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.