Please use this identifier to cite or link to this item: https://doi.org/10.1109/TCST.2004.841648
Title: Adaptive online correction and interpolation of quadrature encoder signals using radial basis functions
Authors: Tan, K.K. 
Tang, K.-Z. 
Keywords: Interpolation
Motion control and neural networks
Issue Date: May-2005
Source: Tan, K.K., Tang, K.-Z. (2005-05). Adaptive online correction and interpolation of quadrature encoder signals using radial basis functions. IEEE Transactions on Control Systems Technology 13 (3) : 370-377. ScholarBank@NUS Repository. https://doi.org/10.1109/TCST.2004.841648
Abstract: This paper considers the development of an adaptive online approach for the correction and interpolation of quadrature encoder signals, suitable for application to precision motion control systems. It is based on the use of a two-stage double-layered radial basis function (RBF) neural network. The first RBF stage is used to adaptively correct for the imperfections in the encoder signals such as mean, phase offsets, amplitude deviation and waveform distortion. The second RBF stage serves as the inferencing machine to adaptively map the quadrature encoder signals to higher order sinusoids, thus, enabling intermediate positions to be derived. Experimental and simulation results are provided to verify the effectiveness of the RBF approach. © 2005 IEEE.
Source Title: IEEE Transactions on Control Systems Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/54927
ISSN: 10636536
DOI: 10.1109/TCST.2004.841648
Appears in Collections:Staff Publications

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