Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network

The mathematic model for the harmonic drive mechanism with multi- variable and nonlinear external disturbance is established,the system error is defined and virtual function is introduced gradually. The RBF neural network is employed to approximate the nonlinear part of the harmonic drive mechanism...

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Main Authors: Li Xiangwei, Hou Gaoqiang
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2016-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.07.013
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author Li Xiangwei
Hou Gaoqiang
author_facet Li Xiangwei
Hou Gaoqiang
author_sort Li Xiangwei
collection DOAJ
description The mathematic model for the harmonic drive mechanism with multi- variable and nonlinear external disturbance is established,the system error is defined and virtual function is introduced gradually. The RBF neural network is employed to approximate the nonlinear part of the harmonic drive mechanism on- line.The dynamic surface controller is developed based on RBF neural network. The closed- loop system convergence is demonstrated with the Lyapunov stabilization theory,through the theory analysis and simulation results comparing with general PID control show that the proposed controller not only satisfies high performance position tracking,but also have good accuracy and stability,which effectively suppresses the influence of the harmonic drive mechanism like nonlinear external disturbance.
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spelling doaj.art-acbc0cfa41c94b72935931898d2b12652023-05-26T09:41:25ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392016-01-0140626629924726Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural NetworkLi XiangweiHou GaoqiangThe mathematic model for the harmonic drive mechanism with multi- variable and nonlinear external disturbance is established,the system error is defined and virtual function is introduced gradually. The RBF neural network is employed to approximate the nonlinear part of the harmonic drive mechanism on- line.The dynamic surface controller is developed based on RBF neural network. The closed- loop system convergence is demonstrated with the Lyapunov stabilization theory,through the theory analysis and simulation results comparing with general PID control show that the proposed controller not only satisfies high performance position tracking,but also have good accuracy and stability,which effectively suppresses the influence of the harmonic drive mechanism like nonlinear external disturbance.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.07.013Harmonic drive mechanism;Nonlinear external disturbance;RBF neural network;Dynamic surface control
spellingShingle Li Xiangwei
Hou Gaoqiang
Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
Jixie chuandong
Harmonic drive mechanism;Nonlinear external disturbance;RBF neural network;Dynamic surface control
title Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
title_full Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
title_fullStr Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
title_full_unstemmed Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
title_short Dynamic Surface Control of Harmonic Drive Mechanism based on RBF Neural Network
title_sort dynamic surface control of harmonic drive mechanism based on rbf neural network
topic Harmonic drive mechanism;Nonlinear external disturbance;RBF neural network;Dynamic surface control
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.07.013
work_keys_str_mv AT lixiangwei dynamicsurfacecontrolofharmonicdrivemechanismbasedonrbfneuralnetwork
AT hougaoqiang dynamicsurfacecontrolofharmonicdrivemechanismbasedonrbfneuralnetwork