Sliding Mode Tracking Differentiator With Adaptive Gains for Filtering and Derivative Estimation of Noisy Signals

Autor: Jingdong Yu, Shanhai Jin
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IEEE Access, Vol 9, Pp 86017-86024 (2021)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3088544
Popis: This paper proposes a new model-free sliding mode tracking differentiator with adaptive gains for reliable filtering and derivative estimations from noisy signals by improving a Levant and Yu’s sliding mode tracking differentiator. Particularly, the proposed tracking differentiator employs a nested generalized signum function for reducing overshoot during convergence. Moreover, a model-free adaptive gain scheduling is adopted for balancing the tracking and filtering performances. The advantages of the proposed tracking differentiator is validated through numerical examples.
Databáze: Directory of Open Access Journals