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Proceedings Paper

Software-based neural network assisted movement compensation for nanoresolution piezo actuators
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Paper Abstract

Micro- and nanoresolution applications are important part of functional material research, where imaging and observation of material interaction may go down to the molecular or even atomic level. Much of the nanometer range movement of scanning and manipulation instruments is made possible by usage of piezoelectric actuation systems. This paper presents a software based controller implementation utilizing neural networks for high precision positioning of a piezoelectric actuator. The controller developed can be used for controlling nanopositioning piezo actuators when sufficiently accurate feedback information is available. Piezo actuators exhibit complex hysteresis dynamics that need to be taken into account when designing an accurate control system. For inverse modelling purposes of the hysteresis related phenomena, a static hysteresis operator and a new developed dynamic creep operator are presented to be used in conjunction with a feed-forward type neural network. The controller utilizing the neural network inverse hybrid model is implemented as a software component for the existing Scalable Modular Control framework (SMC). Using the SMC framework and off-the-shelf components, a measurement and control system for the nanopositioning actuator is constructed and tested using two different capacitive sensors operating on y- and z-axes of the actuator. Using the developed controller, piezo actuator related hysteresis phenomena were successfully reduced making the nanometer range positioning of the actuator axes possible. Also, the effect of using a lower accuracy position sensor with more noise to control accuracy is briefly discussed.

Paper Details

Date Published: 23 January 2012
PDF: 14 pages
Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 830102 (23 January 2012); doi: 10.1117/12.905749
Show Author Affiliations
Marko Kauppinen, Univ. of Oulu (Finland)
Juha Röning, Univ. of Oulu (Finland)

Published in SPIE Proceedings Vol. 8301:
Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques
Juha Röning; David P. Casasent, Editor(s)

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