A Robust Fractional-Order Nonsingular Terminal Sliding Mode Control With Deep Learning-Based Lie Derivative Estimation for Maximum Power Point Tracking in Wind Turbine

A Robust Fractional-Order Nonsingular Terminal Sliding Mode Control With Deep Learning-Based Lie Derivative Estimation for Maximum Power Point Tracking in Wind Turbine

This paper presents a Robust Fractional-Order Sliding Mode Control (FOSMC) with Nonsingular Integral Terminal Dynamics, integrated with Densely Connected Convolutional Networks (DenseNet) for Lie Derivatives Estimation, to achieve Maximum Power Point Tracking (MPPT) in Wind Energy Conversion Systems...

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Bibliographic Details
Main Authors: Ahmed S. Alsafran, Safeer Ullah, Ameen Ullah, Ghulam Hafeez, Muhammad Zeeshan Babar, Baheej Alghamdi, Abdullah A. Algethami
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Fractional-order sliding mode
nonsingular terminal sliding mode
wind energy system
maximum power point tracking
renewable energy
machine learning
Online Access:https://ieeexplore.ieee.org/document/11072148/
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https://ieeexplore.ieee.org/document/11072148/

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