Hysteresis compensation for Piezoelectric tube scanner in atomic force microscopy

Hysteresis compensation for Piezoelectric tube scanner in atomic force microscopy

In this paper, a radial basis function neural network (RBFNN) is designed and used for such purpose. The network is used in conjunction with a self-tuning PID controller. The differential equation of Jenkine element is adopted for hysteresis modeling. The simulation results show that the proposed co...

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Bibliographic Details
Published in:2012 International Conference on Enabling Science and Nanotechnology pp. 1 - 2
Main Authors: Othman, Y. S., Mahmood, I. A., Rashid, N. K. A. M.
Format: Conference Proceeding
Language:English
Published: IEEE 01-01-2012
Subjects:
Atomic force microscopy
Electron tubes
Hysteresis
Laser beams
Mathematical model
Tracking loops
Online Access:Get full text
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Summary:In this paper, a radial basis function neural network (RBFNN) is designed and used for such purpose. The network is used in conjunction with a self-tuning PID controller. The differential equation of Jenkine element is adopted for hysteresis modeling. The simulation results show that the proposed controller improves the system performance better than open loop system and direct closed loop system by minimizing the effect of hysteresis.
ISBN:1457707993
9781457707995
DOI:10.1109/ESciNano.2012.6149633