A General Tracking Control Framework for Uncertain Systems with Exponential Convergence Performance

Bing Xiao, Quanchao Dong, Dong Ye, Liang Liu, Xing Huo

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

A difficult problem of exponential tracking control for uncertain systems even with external disturbance is investigated. The systems studied have a general/representative form with the lossless second-order differential systems and Euler-Lagrange systems included. A general control design framework is presented using observer technique. An observer-based estimator is first developed to precisely estimate and or reconstruct the uncertainty and the disturbance, and an estimator-based controller is then developed. Globally exponential stability of the closed-loop tracking system can be achieved by that controller. Moreover, the resulted estimation error of uncertainty can be stabilized with finite-time convergence. The key advantage of this control architecture is that the controller is able to achieve a perfect tracking performance with no overshoot observed and the settling time tuned to be as less as possible. The effectiveness of the approach is validated on a rigid-flexible coupling satellite example.

Original languageEnglish
Pages (from-to)111-120
Number of pages10
JournalIEEE/ASME Transactions on Mechatronics
Volume23
Issue number1
DOIs
StatePublished - Feb 2018
Externally publishedYes

Keywords

  • Estimator
  • exponential convergence
  • tracking control
  • uncertain systems
  • uncertainty

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