Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy

In this paper, a radial basis function neural network (RBFNN) is designed and used for such purpose. The network is used in conjunction with a self-tuning PID controller. The differential equation of Jenkine element is adopted for hysteresis modeling. The simulation results show that the proposed co...

Full description

Bibliographic Details
Main Authors: Othman, Yahya Sheriff, Mahmood, Iskandar Al-Thani, Alang Md Rashid, Nahrul Khair
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
Online Access:http://irep.iium.edu.my/25831/
http://irep.iium.edu.my/25831/
http://irep.iium.edu.my/25831/1/Hysteresis_Compensation_for_Piezoelectric_Tube_Scanner_in_Atomic_Force.pdf
id iium-25831
recordtype eprints
spelling iium-258312012-10-19T03:13:40Z http://irep.iium.edu.my/25831/ Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy Othman, Yahya Sheriff Mahmood, Iskandar Al-Thani Alang Md Rashid, Nahrul Khair Q Science (General) TJ212 Control engineering In this paper, a radial basis function neural network (RBFNN) is designed and used for such purpose. The network is used in conjunction with a self-tuning PID controller. The differential equation of Jenkine element is adopted for hysteresis modeling. The simulation results show that the proposed controller improves the system performance better than open loop system and direct closed loop system by minimizing the effect of hysteresis. 2012-01 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/25831/1/Hysteresis_Compensation_for_Piezoelectric_Tube_Scanner_in_Atomic_Force.pdf Othman, Yahya Sheriff and Mahmood, Iskandar Al-Thani and Alang Md Rashid, Nahrul Khair (2012) Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy. In: 2012 International Conference on Enabling Science and Nanotechnology (ESciNano), 5-7 January 2012, Persada Johor International Convention Center, Johor Bharu. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6149633&tag=1
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic Q Science (General)
TJ212 Control engineering
spellingShingle Q Science (General)
TJ212 Control engineering
Othman, Yahya Sheriff
Mahmood, Iskandar Al-Thani
Alang Md Rashid, Nahrul Khair
Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
description In this paper, a radial basis function neural network (RBFNN) is designed and used for such purpose. The network is used in conjunction with a self-tuning PID controller. The differential equation of Jenkine element is adopted for hysteresis modeling. The simulation results show that the proposed controller improves the system performance better than open loop system and direct closed loop system by minimizing the effect of hysteresis.
format Conference or Workshop Item
author Othman, Yahya Sheriff
Mahmood, Iskandar Al-Thani
Alang Md Rashid, Nahrul Khair
author_facet Othman, Yahya Sheriff
Mahmood, Iskandar Al-Thani
Alang Md Rashid, Nahrul Khair
author_sort Othman, Yahya Sheriff
title Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
title_short Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
title_full Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
title_fullStr Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
title_full_unstemmed Hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
title_sort hysteresis compensation for piezoelectric tube scanner in atomic force microscopy
publishDate 2012
url http://irep.iium.edu.my/25831/
http://irep.iium.edu.my/25831/
http://irep.iium.edu.my/25831/1/Hysteresis_Compensation_for_Piezoelectric_Tube_Scanner_in_Atomic_Force.pdf
first_indexed 2023-09-18T20:38:29Z
last_indexed 2023-09-18T20:38:29Z
_version_ 1777409206404513792