RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer

RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer

Hydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the performance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is presented. An extended state observer (ESO) with switched...

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Main Authors: Zhi Liu, Tefang Chen
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2016/8390529
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spelling doaj-b58d29d549804177913f4e3a2f1bde502020-11-24T23:11:58ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2016-01-01201610.1155/2016/83905298390529RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State ObserverZhi Liu0Tefang Chen1School of Traffic and Transportation Engineering, Central South University, Changsha, ChinaSchool of Traffic and Transportation Engineering, Central South University, Changsha, ChinaHydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the performance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is presented. An extended state observer (ESO) with switched gain was utilized to estimate the influence of the hydraulic power and other load disturbances. Meanwhile, Radial Basis Function (RBF) neural network was utilized to optimize the parameters in this intelligent controller. The results of the dynamic tests demonstrate the performance with rapid response and improved accuracy could be attained by the proposed control scheme.http://dx.doi.org/10.1155/2016/8390529
collection DOAJ
language English
format Article
sources DOAJ
author Zhi Liu
Tefang Chen
spellingShingle Zhi Liu
Tefang Chen
RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
Discrete Dynamics in Nature and Society
author_facet Zhi Liu
Tefang Chen
author_sort Zhi Liu
title RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
title_short RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
title_full RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
title_fullStr RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
title_full_unstemmed RBF Neural Network Control for Linear Motor-Direct Drive Actuator Based on an Extended State Observer
title_sort rbf neural network control for linear motor-direct drive actuator based on an extended state observer
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2016-01-01
description Hydraulic power and other kinds of disturbance in a linear motor-direct drive actuator (LM-DDA) have a great impact on the performance of the system. A mathematical model of the LM-DDA system is established and a double-loop control system is presented. An extended state observer (ESO) with switched gain was utilized to estimate the influence of the hydraulic power and other load disturbances. Meanwhile, Radial Basis Function (RBF) neural network was utilized to optimize the parameters in this intelligent controller. The results of the dynamic tests demonstrate the performance with rapid response and improved accuracy could be attained by the proposed control scheme.
url http://dx.doi.org/10.1155/2016/8390529
work_keys_str_mv AT zhiliu rbfneuralnetworkcontrolforlinearmotordirectdriveactuatorbasedonanextendedstateobserver
AT tefangchen rbfneuralnetworkcontrolforlinearmotordirectdriveactuatorbasedonanextendedstateobserver
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