Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

Shubo Wang, Xuemei Ren, Jing Na, Dongwu Li

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
299 Downloads (Pure)

Abstract

In this paper, a novel robust controller is proposed for servo mechanisms with nonlinear friction and external disturbance. First, a continuously differentiable friction model is used to represent the nonlinear friction, and neural network (NN) is employed to approximate the nonlinear friction and external disturabance. Then, a novel robust controller is designed by using robust integral of the sign of the error (RISE) term. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. The stability of closed-loop is proved based on Lyapunov stability theory, and all signal are proved to be bounded simultaneously. Finally, comparative simulations based on a turnable servo system are implemented to validate the efficacy of the proposed method.

Original languageEnglish
Title of host publicationChinese Control Conference, CCC
PublisherIEEE Computer Society
Pages3531-3536
Number of pages6
Volume2016-August
ISBN (Print)9789881563910
DOIs
Publication statusPublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameProceedings of the Chinese Control Conference
ISSN (Electronic)1934-1768

Conference

Conference35th Chinese Control Conference, CCC 2016
CountryChina
CityChengdu
Period27/07/1629/07/16

Keywords

  • desired compensation
  • friction compensation
  • robust integral of the sign of the error (RISE) term
  • Servo mechanisms

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