A feedfordward adaptive controller to reduce the imaging time of large-sized biological samples with a SPM-based multiprobe station

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Abstract

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. © 2012 by the authors; licensee MDPI, Basel, Switzerland.

Figures

  • Figure 1. The multiprobe SPM-based nanocharacterization station presented in [10,11,24]. (a) Scheme of the different micro and nanopositioning stages. (b) Photograph of the developed station with a quartz tuning fork probe and an AFM cantilever as nanotools (optical microscope image).
  • Figure 2. Feedback and feedfordward control scheme. Indexes are the classical nomenclature and the parameters in our system are into brackets.
  • Figure 3. (a) The feedforward control is based on predicting the following slope in the sample (mp) by computing the last two slopes in the sample. (b) Comparison between the real and the predicted slope for a randomly generated scan line. The predictive algorithm slightly overestimates the future slope but this fact prevents tip or sample damaging in the experiments.
  • Figure 4. Bang-bang optimal control implementation. A is the cantilever oscillation amplitude; X, Y and Z are the scanner driving signals; mp is the predicted slope.
  • Figure 5. Exponential adaptive controller implementation. A is the cantilever oscillation amplitude; X, Y and Z are the scanner driving signals; mp is the predicted slope.
  • Figure 6. (a) Calibration grid imaged using the bang-bang controller, imaging time = 1 min 22 s. (b) Calibration grid imaged using the adaptive controller, imaging time = 52 s.
  • Figure 7. Experimental setup. The controllers were implemented in software; an I/O board was used as interface with the analog control of the SPM controller. The main PID control was executed in the SPM controller.
  • Figure 8. Image acquired with the bang-bang controller of an Escherichia coli bacterium. vmax = 8 µm/s, vmin = 2 µm/s, imaging time = 1 min 41 s.

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CITATION STYLE

APA

Otero, J., Guerrero, H., Gonzalez, L., & Puig-Vidal, M. (2012). A feedfordward adaptive controller to reduce the imaging time of large-sized biological samples with a SPM-based multiprobe station. Sensors, 12(1), 686–703. https://doi.org/10.3390/s120100686

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