Barrier function-Based Variable Gain Super-Twisting Controller

TL;DR

This paper introduces a barrier function-based variable gain super-twisting controller that guarantees convergence and maintains the output within a predefined neighborhood despite disturbances and uncertainties.

Contribution

It presents a novel control algorithm that ensures convergence and prevents overestimation of control gain for uncertain disturbed systems.

Findings

Guarantees convergence of the output variable.

Maintains output within a predefined neighborhood of zero.

Prevents overestimation of control gain.

Abstract

In this paper, 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 they 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 of 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 which yields the non-overestimation of the control gain.