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Neural network position control of XY piezo actuator stage by visual feedback

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Abstract

This paper describes the visual feedback positional control of the XY piezo actuator stage (PAS). The XY PAS control system consists of four main components, i.e. XY PAS as controlled object, supply electronics for piezoelectric actuators (PEAs), microscope with digital camera for visualization and for measuring the actual position and a vision processing module in combination with a desktop PC, as processing hardware. XY PAS is fabricated by a photo structuring process from photosensitive glass, and PEAs are built-onto meet the request for its precise movement. It is evident from the electromechanical model of XY PAS, that accurate positioning of XY PAS is an exacting piece of work, due to the nonlinear hysteresis inherent in PEAs. Accordingly, two neural network control techniques were developed, i.e. the feedforward neural network controller (FFNNC) and the feedforward/feedback neural network controller (FF/FBNNC). Proposed neural network controllers are compared with the traditional linear controllers.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science/Institute of Robotics, University of Maribor, 2000, Maribor, Slovenia

    Jure Čas & Riko Šafarič

  2. RESISTEC UPR d.o.o. & Co.k.d., Krška Cesta 8, 8311, Kostanjevica na Krki, Slovenia

    Gregor Škorc

Authors
  1. Jure Čas
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  2. Gregor Škorc
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  3. Riko Šafarič
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Correspondence to Jure Čas.

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Čas, J., Škorc, G. & Šafarič, R. Neural network position control of XY piezo actuator stage by visual feedback. Neural Comput & Applic 19, 1043–1055 (2010). https://doi.org/10.1007/s00521-010-0339-y

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  • DOI: https://doi.org/10.1007/s00521-010-0339-y

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