Artificial neural network based controller for fast and accurate atomic force microscope /

Despite its wide use in Atomic Force Microscopies (AFM), the performance of Piezoelectric Tube Scanner is limited by vibration and inherent nonlinearities that include hysteresis and creep. These limitations restrict the use of Piezoelectric Tube Scanner in fast and accurate operation of atomic forc...

Full description

Saved in:
Bibliographic Details
Main Author: Othman, Yahya Sherif
Format: Thesis
Language:English
Published: Kuala Lumpur: Kulliyyah of Engineering, International Islamic University Malaysia, 2013
Subjects:
Online Access:Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library.
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 026870000a22002770004500
008 130722t2013 my a g m 000 0 eng d
040 |a UIAM  |b eng 
041 |a eng 
043 |a a-my--- 
050 0 0 |a QA76.87 
100 1 |a Othman, Yahya Sherif 
245 1 |a Artificial neural network based controller for fast and accurate atomic force microscope /  |c by Yahya Sherif Othman 
260 |a Kuala Lumpur:   |b Kulliyyah of Engineering, International Islamic University Malaysia,   |c 2013 
300 |a xv, 79 leaves :  |b ill. ;  |c 30cm. 
502 |a Thesis (MCT)--International Islamic University Malaysia, 2013. 
504 |a Includes bibliographical references (leaves 76-78). 
520 |a Despite its wide use in Atomic Force Microscopies (AFM), the performance of Piezoelectric Tube Scanner is limited by vibration and inherent nonlinearities that include hysteresis and creep. These limitations restrict the use of Piezoelectric Tube Scanner in fast and accurate operation of atomic force microscopies. Vibration is a linear problem that can be solved efficiently using conventional techniques. However hysteresis that is a nonlinear problem cannot be handled efficiently using these conventional techniques. In this research work, a new nonlinear model of Piezoelectric Tube Scanner has been developed for simulation analysis. Two intelligent approaches using Artificial Neural Network (ANN) have been developed to overcome these hysteresis and vibration limitations. First, a time based ANN control scheme is developed for hysteresis compensation, the results shows that this control approach has efficiently reduced hysteresis effect but not vibration. Hence, another control scheme based on frequency domain analysis has been developed. The results proved the efficiency of the frequency based approach by reducing hysteresis effect and controlling vibration. 
596 |a 1 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Mechatronics Engineering  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Mechatronics Engineering 
856 4 |u https://lib.iium.edu.my/mom/services/mom/document/getFile/lBrFXq1XLa5wVuBllRgRZzcUH2fr36Ua20140404104211152  |z Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. 
900 |a hab-ls 
999 |c 437126  |d 470223 
952 |0 0  |6 T QA 000076.87 O87A 2013  |7 0  |8 THESES  |9 759049  |a IIUM  |b IIUM  |c MULTIMEDIA  |g 0.00  |o t QA 76.87 O87A 2013  |p 00011291501  |r 2017-10-20  |t 1  |v 0.00  |y THESIS 
952 |0 0  |6 TS CDF QA 76.87 O87A 2013  |7 0  |8 THESES  |9 851135  |a IIUM  |b IIUM  |c MULTIMEDIA  |g 0.00  |o ts cdf QA 76.87 O87A 2013  |p 00011291502  |r 2017-10-26  |t 1  |v 0.00  |y THESISDIG