An iterative based feedforward-feedback control approach to high-speed AFM imaging

AFM imaging requires precision positioning of the AFM probe relative to the sample in all x-y-z axes, especially the vertical z-axis direction. Recently, the currentcycle- feedback iterative-learning-control (CCF-ILC) approach is proposed for high-speed AFM imaging. The CCF-ILC feedforward-feedback 2 degree-of-freedom (DOF) controller design has been successfully implemented for iteratively imaging on one scanline. In this article, we extend this CCFILC approach to the entire imaging of samples. The main contribution of this article is the analysis and the use of the CCF-ILC approach for tracking sample profiles with variations between scanlines (called line-to-line sample variations). The convergence (stability) of the CCF-ILC system is analyzed for the general case where the line-to-line sample variation occurs at each iteration. The allowable line-to-line sample profile variation is quantified. The performance improvement of the CCF-ILC is discussed by comparing the tracking error of the CCF-ILC technique to that of using feedback control alone. The proposed CCF-ILC control approach is illustrated by implementing it to the z-axis direction control in AFM imaging. Experimental results show that the imaging speed can be significantly increased by using the proposed approach.