학술논문

A Generalized Supertwisting Algorithm
Document Type
Periodical
Author
Source
IEEE Transactions on Cybernetics IEEE Trans. Cybern. Cybernetics, IEEE Transactions on. 53(6):3951-3960 Jun, 2023
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Robotics and Control Systems
General Topics for Engineers
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Convergence
Lyapunov methods
Robustness
Uncertainty
System performance
Steady-state
Heuristic algorithms
Finite-time convergence
generalized supertwisting algorithm (GSTA)
Lyapunov method
Language
ISSN
2168-2267
2168-2275
Abstract
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.