"Nanomanipulation Using Atomic Force Microscope with Drift Compensation" by Qinmin Yang and Jagannathan Sarangapani
 

Abstract

This paper proposes an atomic force microscope (AFM) based force controller to push nanoparticles on the substrates since it is tedious for human. A block phase correlation-based algorithm is embedded into the controller for compensating the thermal drift during nanomanipulation. Further, a neural network (NN) is employed to approximate the unknown nanoparticle and substrate contact dynamics including the roughness effects. Using the NN-based adaptive force controller the task of pushing nanoparticles is demonstrated. Finally, using the Lyapunov-based stability analysis, the uniform ultimately boundedness (UUB) of the closed-loop signals is demonstrated

Meeting Name

American Control Conference, 2006

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Keywords and Phrases

Lyapunov Methods; Adaptive Control; Atomic Force Microscopy; Closed Loop Systems; Compensation; Control System Analysis; Force Control; Manipulators; Neurocontrollers; Stability; Substrates

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2006 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2006

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