Multivariable Super-Twisting Algorithm for Systems with Uncertain Input Matrix and Perturbations

Jaime A. Moreno, Hector Rios, Luis Ovalle, Leonid Fridman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper proposes a Lyapunov approach to the design of a multivariable generalized Super-Twisting algorithm (MGSTA), which is able to control a system with perturbations and uncertain control matrix, both depending on time and the system states. The presented procedure shows that, under reasonable assumptions for the uncertainties, it is always possible to find a set of constant gains for the MGSTA in order to ensure global and robust finite-time stability of the system's outputs. Simulation results on an omnidirectional mobile robot illustrate the performance of the MGSTA.

Original languageEnglish
JournalIEEE Transactions on Automatic Control
DOIs
StateAccepted/In press - 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Convergence
  • Jacobian matrices
  • Mobile robots
  • Perturbation methods
  • Robust control
  • Sliding-mode control
  • Super-Twisting algorithm
  • Symmetric matrices
  • Transmission line matrix methods
  • Uncertain systems
  • Wheels

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