The work proposes a generalized supertwisting algorithm (GSTA) and its constructive design strategy. In contrast with the conventional STA, the most remarkable characteristic of the proposed method is that the discontinuous term in the conventional STA is replaced with a fractional power term, which can fundamentally improve the performance of the conventional STA. It is shown that if the fractional power in the nonsmooth term becomes -1/2, the GSTA will reduce to the conventional STA. Under the GSTA, it will be rigorously verified by taking advantage of strict Lyapunov analysis that the sliding variables can finite-time converge to an arbitrarily small region in a neighborhood of the origin by tuning the gains and the fractional power. Finally, simulation studies are provided to demonstrate the superiority of the theoretically obtained results.
CITATION STYLE
Mei, K., Ding, S., & Yu, X. (2023). A Generalized Supertwisting Algorithm. IEEE Transactions on Cybernetics, 53(6), 3951–3960. https://doi.org/10.1109/TCYB.2022.3188877
Mendeley helps you to discover research relevant for your work.