Adaptive Gain Super-Twisting-Algorithm: Design and Discretization

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

In this paper, an eigenvalue-based discretization scheme is applied to a novel adaptive super-twisting-algorithm. Following the proposed procedure the discretization chattering effect is avoided entirely. An attractive property of the adaptation law is the insensitivity of the closed-loop system to overly large gains which in existing laws potentially leads to instability. Using Lyapunov's direct method the stability of the feedback loop is shown. Numerical examples underline the beneficial properties of the proposed methodology.
Originalspracheenglisch
Titel2021 60th IEEE Conference on Decision and Control, CDC 2021
PublikationsstatusAngenommen/In Druck - 2021

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