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|Title:||Geometrical error modeling and compensation using neural networks|
|Authors:||Tan, K.K. |
Computer aided engineering
|Source:||Tan, K.K., Huang, S.N., Lim, S.Y., Leow, Y.P., Liaw, H.C. (2006-11). Geometrical error modeling and compensation using neural networks. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 36 (6) : 797-809. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCC.2005.855527|
|Abstract:||This paper describes an approach based on neural networks (NNs) for geometrical error modeling and compensation for precision motion systems. A laser interferometer is used to obtain the systematic error measurements of the geometrical errors, based on which an error model may be constructed and, consequently, a model-based compensation may be incorporated in the motion-control system. NNs are used to approximate the components of geometrical errors, thus dispensing with the conventional lookup table. Apart from serving as a more adequate model due to its inherent nonlinear characteristics, the use of NNs also results in less memory requirements to implement the error compensation for a specified precision compared to the use of lookup table. The adequacy and clear benefits of the proposed approach are illustrated via applications to various configurations of precision-positioning stages, including a single-axis, a gantry, and a complete XY stage. © 2006 IEEE.|
|Source Title:||IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews|
|Appears in Collections:||Staff Publications|
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