High resolution imaging in scanning probe microscopes is conducted by rastering a sharp probe over a sample surface. The rastering is done using piezoelectric elements, converting applied voltage into mechanical motion. For example, imaging of a rectangular field of view is done by applying triangular waveforms with different frequencies to X and Y piezoelectric stage, respectively. A disadvantage of piezoelectric stages is their non-linear response to applied voltage. In addition to that, they show creep, i.e. moving even though the applied voltage is constant. This results in distortions of the acquired image. Furthermore, it can result in not precisely imaging the requested area. A common solution is to add position sensors to the piezoelectric stages and measure actual movements. By using a feedback it would be almost guaranteed that the piezoelectric stage moves as requested. The disadvantage of this approach is that it reduces the bandwidth and increases the noise. The aim of this paper is to study advanced piezoelectric stage models to better control the actual stage movement in an open-loop scan.
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ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 28–30, 2016
Stowe, Vermont, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5049-7
PROCEEDINGS PAPER
Nonlinear Dynamic Models of Piezoelectric Nano-Stages
S. Nima Mahmoodi,
S. Nima Mahmoodi
University of Alabama, Tuscaloosa, AL
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Ehsan Omidi,
Ehsan Omidi
Keysight Technologies, Inc., Santa Clara, CA
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Christian Rankl
Christian Rankl
Keysight Technologies, Inc., Santa Clara, CA
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S. Nima Mahmoodi
University of Alabama, Tuscaloosa, AL
Ehsan Omidi
Keysight Technologies, Inc., Santa Clara, CA
Christian Rankl
Keysight Technologies, Inc., Santa Clara, CA
Paper No:
SMASIS2016-9228, V002T03A021; 6 pages
Published Online:
November 29, 2016
Citation
Mahmoodi, SN, Omidi, E, & Rankl, C. "Nonlinear Dynamic Models of Piezoelectric Nano-Stages." Proceedings of the ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. Stowe, Vermont, USA. September 28–30, 2016. V002T03A021. ASME. https://doi.org/10.1115/SMASIS2016-9228
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