Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM
Positioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoe...
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Hindawi-Wiley
2021-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2021/5537998 |
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doaj-ccad2cbc5b574f7cb38ac98f6c0aeaa22021-05-10T00:27:31ZengHindawi-WileyComplexity1099-05262021-01-01202110.1155/2021/5537998Application of Compound Control Method Based on WOA in Micropositioning Stage of SICMHuiting Wen0Xiaolong Lu1Shiping Zhao2Xiaoyu Liu3Yang Yang4Song Leng5School of Mechanical EngineeringSchool of Mechanical EngineeringSchool of Mechanical EngineeringSchool of Mechanical EngineeringSchool of Mechanical EngineeringSchool of Mechanical EngineeringPositioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoelectric ceramics and the influence on the control accuracy. In order to solve this problem, backpropagation algorithm based on whale optimization algorithm is used to model the hysteresis, which is directly used as a feedforward controller to compensate the hysteresis effect, and the robust adaptive moving average control method is used for feedback control. The results show that the hysteresis model of backpropagation algorithm based on the whale optimization algorithm can fit the hysteresis curve well, and the maximum fitting error is 0.2050 μm, only 0.256%. By adopting feedforward and feedback, feedforward robust adaptive moving average control algorithm decreases the hysteresis from 17.64% to 2.51%, which enables the output of the piezoelectric ceramic controller to track the expected displacement well and makes it possible to improve the scanning accuracy.http://dx.doi.org/10.1155/2021/5537998 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Huiting Wen Xiaolong Lu Shiping Zhao Xiaoyu Liu Yang Yang Song Leng |
spellingShingle |
Huiting Wen Xiaolong Lu Shiping Zhao Xiaoyu Liu Yang Yang Song Leng Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM Complexity |
author_facet |
Huiting Wen Xiaolong Lu Shiping Zhao Xiaoyu Liu Yang Yang Song Leng |
author_sort |
Huiting Wen |
title |
Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM |
title_short |
Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM |
title_full |
Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM |
title_fullStr |
Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM |
title_full_unstemmed |
Application of Compound Control Method Based on WOA in Micropositioning Stage of SICM |
title_sort |
application of compound control method based on woa in micropositioning stage of sicm |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1099-0526 |
publishDate |
2021-01-01 |
description |
Positioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoelectric ceramics and the influence on the control accuracy. In order to solve this problem, backpropagation algorithm based on whale optimization algorithm is used to model the hysteresis, which is directly used as a feedforward controller to compensate the hysteresis effect, and the robust adaptive moving average control method is used for feedback control. The results show that the hysteresis model of backpropagation algorithm based on the whale optimization algorithm can fit the hysteresis curve well, and the maximum fitting error is 0.2050 μm, only 0.256%. By adopting feedforward and feedback, feedforward robust adaptive moving average control algorithm decreases the hysteresis from 17.64% to 2.51%, which enables the output of the piezoelectric ceramic controller to track the expected displacement well and makes it possible to improve the scanning accuracy. |
url |
http://dx.doi.org/10.1155/2021/5537998 |
work_keys_str_mv |
AT huitingwen applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm AT xiaolonglu applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm AT shipingzhao applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm AT xiaoyuliu applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm AT yangyang applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm AT songleng applicationofcompoundcontrolmethodbasedonwoainmicropositioningstageofsicm |
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1721453759875252224 |