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

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-ban...

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Bibliographic Details
Published inSensors (Basel, Switzerland) Vol. 12; no. 1; pp. 686 - 703
Main Authors Otero, Jorge, Guerrero, Hector, Gonzalez, Laura, Puig-Vidal, Manel
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.01.2012
MDPI Publishing
Molecular Diversity Preservation International (MDPI)
Subjects
adaptive control
Adaptive control systems
Atomic force microscopy
Bacteria
Bacteris
biological samples
Calibration
Citologia
Cytology
E coli
Electron microscope
Equipment Design
Escherichia coli - cytology
Experiments
fast imaging
feedforward control
Imaging, Three-Dimensional - instrumentation
Imaging, Three-Dimensional - methods
Microscopis electrònics
Microscopy
Microscopy, Scanning Probe - instrumentation
Microscòpia de força atòmica
Models, Theoretical
nanorobotics
Nanotechnology
Nanotecnologia
Physiology
Sample Size
scanning probe microscopy
Sensors
Sistemes adaptatius
Software
System theory
Teoria de sistemes
Time Factors
Topography
scanning probe microscopy
bacteria
adaptive control
feedforward control
nanorobotics
biological samples
fast imaging
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1424-8220
1424-8220
DOI:10.3390/s120100686