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Artificial neural network based hysteresis compensation for piezoelectric tube scanner in atomic force microscopy

Othman, Yahya Sheriff and Mahmood, Iskandar Al-Thani and Alang Md Rashid, Nahrul Khair and Ridhuan Siradj , Fadly Jashi Darsivan (2012) Artificial neural network based hysteresis compensation for piezoelectric tube scanner in atomic force microscopy. IEEE Region 10 Annual International Conference, Proceedings/TENCON. pp. 1-5. ISSN 2159-3442

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Abstract

Piezoelectric tube scanner is a major component that used in nanoscale imaging tools such as atomic force microscopy (AFM). This is because it can provide precise nanoscale positioning. However the precision is limited by vibration and some nonlinear drawbacks represented by creep and hysteresis. Hysteresis problem appears when positioning is needed at wide range. In this paper, a feed forward multi-layer neural network (MLNN) is trained to shape a proper control signal based on reference input and actual output signals. The experimental results show that the developed neural network scheme improves the performance of the system by significantly minimizing the effect of hysteresis.

Item Type: Article (other)
Additional Information: 3614/34971
Uncontrolled Keywords: Atomic Force Microscopy; Hysteresis; Neural Network; Piezoelectric Tube Scanner
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User: Engr. Dr. Fadly Jashi Darsivan Ridhuan
Date Deposited: 11 Feb 2014 11:07
Last Modified: 11 Feb 2014 11:07
URI: http://irep.iium.edu.my/id/eprint/34971

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