Skip to main navigation Skip to search Skip to main content

Sliding mode control of manipulator based on nominal model and nonlinear disturbance observer

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

Abstract

A sliding mode control method based on nonlinear disturbance observer and nominal model is proposed to track the trajectory of manipulator with uncertain interference. A dynamic model of the manipulator is established, a sliding mode control law is designed, and the stability of the system is verified by the Lyapunov stability theory. A nonlinear disturbance observer is introduced to improve the performance of the control system. The results show that the control method reduces the unmodelled dynamic errors and the influence of uncertain external interference. Furthermore, simulation results based on Matlab prove that compared with the traditional PD position control method, proposed method has higher accuracy and better robustness.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5519-5524
Number of pages6
ISBN (Electronic)9781509066841
DOIs
StatePublished - 26 Dec 2018
Event44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States
Duration: 20 Oct 201823 Oct 2018

Publication series

NameProceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Country/TerritoryUnited States
CityWashington
Period20/10/1823/10/18

Keywords

  • Lyapunov stability
  • Manipulator dynamics
  • Nominal model
  • Nonlinear disturbance observer
  • Sliding mode control

Fingerprint

Dive into the research topics of 'Sliding mode control of manipulator based on nominal model and nonlinear disturbance observer'. Together they form a unique fingerprint.

Cite this