Compensation of Scanner Creep and Hysteresis for AFM Nanomanipulation

Nanomanipulation with atomic force microscopes (AFMs) for nanoparticles with overall sizes on the order of 10 nm has been hampered in the past by the large spatial uncertainties encountered in tip positioning. This paper addresses the compensation of nonlinear effects of creep and hysteresis on the...

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Bibliographic Details
Published in:IEEE transactions on automation science and engineering 2008-04, Vol.5 (2), p.197-206
Main Authors: Mokaberi, B., Requicha, A.A.G.
Format: Article
Language:English
Subjects:
Applied sciences
Atomic force microscopes (AFMs)
Atomic force microscopy
automatic nanomanipulation
Cartography
Compensation
Computer science
control theory
systems
Control theory. Systems
Creep
Creep (materials)
Exact sciences and technology
Hysteresis
Instruments, apparatus, components and techniques common to several branches of physics and astronomy
Inverse
Inverse problems
Laboratories
Mathematical models
Mechanical engineering. Machine design
Mechanical instruments, equipment and techniques
Micromechanical devices and systems
Modelling and identification
nano manipulation
nanolithography
Nanomaterials
Nanoparticles
nanorobotics
Nanostructure
nonlinearities
Physics
Precision engineering, watch making
Prototypes
Robot sensing systems
Robotics
Robotics and automation
Scanners
Scanning electron microscopy
scanning probe microscopes (SPMs)
Sensor arrays
spatial uncertainty
Uncertainty
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Description
Summary:Nanomanipulation with atomic force microscopes (AFMs) for nanoparticles with overall sizes on the order of 10 nm has been hampered in the past by the large spatial uncertainties encountered in tip positioning. This paper addresses the compensation of nonlinear effects of creep and hysteresis on the piezo scanners which drive most AFMs. Creep and hysteresis are modeled as the superposition of fundamental operators, and their inverse model is obtained by using the inversion properties of the Prandtl-Ishlinskii operator. Identification of the parameters in the forward model is achieved by a novel method that uses the topography of the sample and does not require position sensors. The identified parameters are used to compute the inverse model, which in turn serves to drive the AFM in an open-loop, feedforward scheme. Experimental results show that this approach effectively reduces the spatial uncertainties associated with creep and hysteresis, and supports automated, computer-controlled manipulation operations that otherwise would fail.
ISSN:1545-5955
1558-3783
DOI:10.1109/TASE.2007.895008