Multi-layer barrier function-based adaptive super-twisting controller

TL;DR

This paper introduces an adaptive super-twisting control method using multi-layer barrier functions to handle uncertain systems with bounded but unknown perturbations, ensuring bounded solutions even under sudden disturbances.

Contribution

It extends barrier function-based adaptation to super-twisting controllers with a nested barriers scheme for improved robustness and boundedness guarantees.

Findings

The proposed method guarantees boundedness of solutions under sudden perturbations.

Simulations confirm the effectiveness of the multi-layer barrier approach.

The framework enhances robustness against rate-bounded uncertainties.

Abstract

This article presents an adaptive Super-Twisting Sliding Mode Control framework for uncertain first-order systems, with rate-bounded perturbations, where the bound is constant but unknown. Positive definite barrier functions, when used in self-tuning super-twisting controllers may introduce some conservatism in relation to initial estimations of the perturbation rate bound. Moreover, discrete time implementation of the algorithm does not necessarily guarantee the boundedness of the closed-loop trajectories when sudden changes in the perturbation occur in between two time samples. The salient features of the proposed methodology pertain to extending the use of positive semidefinite barrier functions to Super-Twisting controller adaptation and the employment of a "nested barriers" scheme that ensures boundedness of the solutions even for "unfavourable" perturbations-to-sampling time ratios. The stability of the closed-loop system is assessed via Lyapunov analysis and simulations demonstrate the efficacy of the proposed framework.