TY - JOUR
T1 - A current cycle feedback iterative learning control approach for AFM imaging
AU - Wu, Ying
AU - Zou, Qingze
AU - Su, Chanmin
N1 - Funding Information:
Manuscript received April 6, 2008; revised October 7, 2008 and January 7, 2009. First published February 10, 2009; current version published July 9, 2009. This work was supported by the National Science Foundation (NSF) under Grant CMMI-0626417 and Grant DUE-0632908. The review of this paper was arranged by Associate Editor K. Matsumoto.
PY - 2009/7
Y1 - 2009/7
N2 - In this paper, we proposed a novel current cycle feedback (CCF) iterative learning control (ILC) approach to achieve high-speed imaging on atomic force microscope (AFM). AFM imaging requires precision positioning of the AFM probe relative to the sample in 3-D ($x$ $y$$ z$). It has been demonstrated that, with advanced control techniques such as the inversion-based iterative control (IIC), precision positioning of the AFM probe in the lateral ($x$ $y$) scanning can be successfully achieved. Precision positioning of the probe in the vertical $z$-axis direction, however, is still challenging because the issues such as the sample topography are unknown, in general; the probesample interaction is complicated, and the probesample position is sensitive to the probesample interaction. The main contribution of this paper is the development of the CCF-ILC approach for the AFM $z$-axis control, which decouples the robustness of the feedback control from the precision tracking of the feedforward control. Particularly, the proposed CCF-ILC controller design utilizes the recently developed robust inversion technique to minimize the model uncertainty effect on the feedforward control and to remove the causality constraints in other CCF-ILC approaches. It is shown that the iterative law converges and attains a bounded tracking error upon noise and disturbances. The proposed method is illustrated through experimental implementation, and the experimental results show an increase of eight times faster imaging speed for contact-mode imaging.
AB - In this paper, we proposed a novel current cycle feedback (CCF) iterative learning control (ILC) approach to achieve high-speed imaging on atomic force microscope (AFM). AFM imaging requires precision positioning of the AFM probe relative to the sample in 3-D ($x$ $y$$ z$). It has been demonstrated that, with advanced control techniques such as the inversion-based iterative control (IIC), precision positioning of the AFM probe in the lateral ($x$ $y$) scanning can be successfully achieved. Precision positioning of the probe in the vertical $z$-axis direction, however, is still challenging because the issues such as the sample topography are unknown, in general; the probesample interaction is complicated, and the probesample position is sensitive to the probesample interaction. The main contribution of this paper is the development of the CCF-ILC approach for the AFM $z$-axis control, which decouples the robustness of the feedback control from the precision tracking of the feedforward control. Particularly, the proposed CCF-ILC controller design utilizes the recently developed robust inversion technique to minimize the model uncertainty effect on the feedforward control and to remove the causality constraints in other CCF-ILC approaches. It is shown that the iterative law converges and attains a bounded tracking error upon noise and disturbances. The proposed method is illustrated through experimental implementation, and the experimental results show an increase of eight times faster imaging speed for contact-mode imaging.
KW - Atomic force microscope (AFM)
KW - Inversion-based feedforward control
KW - Iterative learning control (ILC)
KW - Nanotechnology
KW - Piezoelectric materials
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U2 - 10.1109/TNANO.2009.2015051
DO - 10.1109/TNANO.2009.2015051
M3 - Article
AN - SCOPUS:67949097286
SN - 1536-125X
VL - 8
SP - 515
EP - 527
JO - IEEE Transactions on Nanotechnology
JF - IEEE Transactions on Nanotechnology
IS - 4
M1 - 4781804
ER -