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23 January 2012 Software-based neural network assisted movement compensation for nanoresolution piezo actuators
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Proceedings Volume 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques; 830102 (2012) https://doi.org/10.1117/12.905749
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marko Kauppinen and Juha Röning "Software-based neural network assisted movement compensation for nanoresolution piezo actuators", Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 830102 (23 January 2012); https://doi.org/10.1117/12.905749
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