Abstract
Wind turbines are a key technology in sustainable energy generation, but their performance is often challenged by strong aerodynamic disturbances, parameter uncertainties, and rapidly varying operating conditions. Achieving reliable maximum power point tracking (MPPT) under such conditions requires control strategies with fast dynamic response and strong robustness. This paper proposes a robust high-gain control scheme for MPPT of variable-speed wind turbines. The method uses high-gain feedback to enforce accurate rotor speed tracking while attenuating the effects of unmodeled dynamics and external disturbances. By appropriately tuning the gain parameters, the controller achieves rapid error convergence without sacrificing robustness or stability. A rigorous Lyapunov-based analysis establishes closed-loop stability under model uncertainties. Simulation studies, conducted under both smooth and highly turbulent wind profiles, demonstrate that the proposed high-gain control achieves faster tracking, improved disturbance rejection, and higher energy capture efficiency, while maintaining smooth control actions suitable for practical implementation.
| Original language | English |
|---|---|
| Title of host publication | 2025 Saudi Arabia Smart Grid, SASG 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331577506 |
| DOIs | |
| State | Published - 2025 |
| Event | 2025 Saudi Arabia Smart Grid, SASG 2025 - Riyadh, Saudi Arabia Duration: 15 Dec 2025 → 18 Dec 2025 |
Publication series
| Name | 2025 Saudi Arabia Smart Grid, SASG 2025 |
|---|
Conference
| Conference | 2025 Saudi Arabia Smart Grid, SASG 2025 |
|---|---|
| Country/Territory | Saudi Arabia |
| City | Riyadh |
| Period | 15/12/25 → 18/12/25 |
Bibliographical note
Publisher Copyright:© 2025 IEEE.
Keywords
- High gain control
- Lyapunov theory
- maximum power point tracking
- offshore wind turbines
- renewable energy
- robustness
- wind energy conversion system
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Control and Optimization
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