This article presents an iterative-based feedforward-feedback control approach to achieve high-speed atomic force microscope (AFM) imaging. AFM-imaging requires precision positioning of the probe relative to the sample in all x-y-z axes directions. Particularly, this article is focused on the vertical z-axis positioning. Recently, a current-cycle-feedback iterative-learning-control (CCF-ILC) approach has been developed for precision tracking of a given desired trajectory (even when the desired trajectory is unknown), which can be applied to achieve precision tracking of sample profile on one scanline. In this article, we extend this CCF-ILC approach to imaging of entire sample area. The main contribution of this article is the convergence analysis and the use of the CCF-ILC approach for output tracking in the presence of desired trajectory varation between iterations—the sample topography variations between adjacent scanlines. For general case where the desired trajectory variation occurs between any two successive iterations, the convergence (stability) of the CCF-ILC system is addressed and the allowable size of desired trajectory variation is quantified. The performance improvement achieved by using the CCF-ILC approach is discussed by comparing the tracking error of using the CCF-ILC technique to that of using feedback control alone. The efficacy of the proposed CCF-ILC control approach is illustrated by implementing it to the z-axis control during AFM-imaging. Experimental results are presented to show that the AFM-imaging speed can be substantially increased.

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