Recursive adaptive integral sliding mode control based on extended state observer for dual-motor servo system

Kang Wang, Xuemei Ren*, Zimei Sun, Wei Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper presents a novel recursive adaptive integral sliding mode (RAISM) control method based on extended state observer (ESO) for the class of dual-motor nonlinear servo system with unknown backlash. The ESO is utilized to estimate the useful states and predigest the designing course. Then, applying the Chebyshev neural network, the RAISM controller is designed to effectively eliminate the reaching phase and avoid the problem of singularity. The simulation results of comparative experiments verify the validity and higher tracking accuracy of the proposed method.

Original languageEnglish
Title of host publicationProceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages663-668
Number of pages6
ISBN (Electronic)9781509065738
DOIs
Publication statusPublished - 2 Jul 2017
Event9th International Conference on Modelling, Identification and Control, ICMIC 2017 - Kunming, China
Duration: 10 Jul 201712 Jul 2017

Publication series

NameProceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
Volume2018-March

Conference

Conference9th International Conference on Modelling, Identification and Control, ICMIC 2017
Country/TerritoryChina
CityKunming
Period10/07/1712/07/17

Keywords

  • ESO
  • RAISM control method
  • dual-motor nonlinear servo system

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