arrow
Return

Barrier Function-Based Adaptive Super-Twisting Controller

delete2020-11-01
delete86
delete
OA
AI
H
Hussein Obeid
S
Salah Laghrouche *
L
Leonid Fridman
Y
Yacine Chitour
M
Mohamed Harmouche
DOI:10.1109/TAC.2020.2974390delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
In this article, a variable gain super-twisting algorithm based on a barrier function is proposed for a class of first order disturbed systems with uncertain control coefficient and whose disturbances derivatives are bounded but the upper bounds of those derivatives are unknown. The specific feature of this algorithm is that it can ensure the convergence of the output variable and maintain it in a predefined neighborhood of zero independent from the upper bound of the disturbances derivatives. Moreover, thanks to the structure of the barrier function, it forces the gain to decrease together with the output variable and the control signal follows the absolute value of the disturbances.
Keywords:
Gain
Upper bound
Trajectory
Convergence
Actuators
Drives
Standards
Adaptive super-twisting
barrier function
sliding mode
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Automatic Control cover
IEEE Transactions on Automatic Control
IF:
7
Papers:
1.3W
Citations:
6.7W

Organization

U
Universidad Nacional Autonoma de Mexico
Scholars:
3.8W
Papers: 2.6W
Citations: 28
C
centre national de la recherche scientifique (cnrs)
Scholars:
24.5W
Papers: 18.2W
Citations: 279
U
universite de franche-comte
Scholars:
8.1K
Papers: 6.1K
Citations: 9
U
universite de technologie de belfort-montbeliard (utbm)
Scholars:
2.6K
Papers: 2.1K
Citations: 2
researcher View more organizations