Skip to main navigation Skip to search Skip to main content

Prescribed Performance Control of Euler-Lagrange System with Unknown Dead-zone and Uncertain Disturbances

  • Harbin Institute of Technology

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

Abstract

In this paper, the full state feedback tracking control problem for Euler-Lagrange system with unknown dead-zone and uncertain disturbances is considered and an adaptive neural-network-based prescribed performance control algorithm is proposed. The performance function is employed to constrain tracking errors and describe the expected region of transient behavior. Radial basis function neural network (RBFNN) is utilized to approximate unknown nonlinearities. The proposed controller is able to track the desired trajectory, guarantee transient performance and compensate for the estimated dead-zone effect. Lyapunov direct method is utilized to ensure asymptotical stability of the closed-loop system. Simulation example is presented to illustrate the effectiveness and feasibility of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages503-508
Number of pages6
ISBN (Electronic)9781728148786
DOIs
StatePublished - Oct 2019
Event45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 - Lisbon, Portugal
Duration: 14 Oct 201917 Oct 2019

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2019-October

Conference

Conference45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019
Country/TerritoryPortugal
CityLisbon
Period14/10/1917/10/19

Keywords

  • Euler-Lagrange system
  • RBFNN
  • prescribed performance control
  • unknown dead-zone

Fingerprint

Dive into the research topics of 'Prescribed Performance Control of Euler-Lagrange System with Unknown Dead-zone and Uncertain Disturbances'. Together they form a unique fingerprint.

Cite this