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Sub-resonance tapping (SRT) mode of atomic force microscopy (AFM) enables researchers to image surfaces with well-controlled load forces and to collect maps of multiple physical properties of samples. The major bottleneck of this mode is a relatively low scan speed compared to other scanning modes. This paper presents a novel control algorithm that substantially improves the scanning speed over the standard SRT. We propose naming the new modality Trajectory Tracking SRT (TT-SRT). In contrast with the standard SRT control, TT-SRT uses the feedback within every single touch of the sample by the AFM probe. To demonstrate the advantage of TT-SRT, we conduct scans on a variety of samples with differing topologies, roughnesses, and mechanical properties. Each sample region is scanned with both standard SRT and TT-SRT at the same set of speeds. The control gains are tuned before each scan for maximum performance in each mode. Performance is evaluated by selecting a given level of image quality and finding the maximum speed that can be achieved by each algorithm. We find that with increased demand for data quality, the utility of TT-SRT becomes more apparent; for example, the speed of TT-SRT can be ten times faster or more than standard SRT for a reasonable expectation of data quality.

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Automated methods for deriving dynamic models from frequency response data of high-order dynamics systems are the default choice of most engineers. However, these methods themselves often require manual tuning of weighting parameters, a priori selection of system order, and even by hand removal of extraneous dynamics. On the other hand, manually matching complicated features in the Bode plot of the frequency response of high-order system is difficult with conventional first and second order numerators and denominators. In this papers we present a manual technique for systematically creating a dynamic model from Bode plots of frequency response data with complicated features. We apply the method to identifying dynamics of a piezoelectric stage holding the sample of an atomic force microscope (AFM). We show the manual method works better than the tfest command of Matlab™ for this example system.