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Lookup NU author(s): Professor Cheng ChinORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© The Author(s) 2025.This paper presents a comprehensive study on predefined-time sliding mode control applied to quadrotor systems with variable exponent coefficients. The main goal is to achieve efficient control with predefined-time convergence to the desired target. Novel predefined-time sliding mode control and predefined-time neural networks sliding model control algorithms are developed to adapt to the dynamics of variable coefficients and ensure system stability. The stability analysis confirms their capability to achieve predefined-time convergence. Extensive numerical simulations on diverse nonlinear systems validate the superiority of the proposed approach over conventional sliding mode control and neural networks control.
Author(s): Hou L, Zhang J, Yu Z, Wang X, Chin CS
Publication type: Article
Publication status: Published
Journal: Scientific Reports
Year: 2025
Volume: 15
Issue: 1
Online publication date: 12/11/2025
Acceptance date: 06/10/2025
Date deposited: 27/11/2025
ISSN (electronic): 2045-2322
Publisher: Nature Research
URL: https://doi.org/10.1038/s41598-025-23330-2
DOI: 10.1038/s41598-025-23330-2
Data Access Statement: All data generated or analysed during this study are included in this published article
PubMed id: 41224976
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