Novel full fractional-order control and Lyapunov stability approach using genetic algorithm optimization for high-performance wind turbines

•Proposes full fractional-order sliding mode controllers for wind turbines.•Employs a fractional-order two-mass model for flexible shaft dynamics.•Optimizes controller parameters using a genetic algorithm.•Reduces chattering and improves speed and torque tracking.•Enhances energy capture and mechani...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Computers & electrical engineering Ročník 128; s. 110658
Hlavní autoři: Zoubaa, Yassamine, Chouiekh, Sihame, Bakri, Ayoub EL, Sefriti, Selma, Boumhidi, Ismail
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.12.2025
Témata:
ISSN:0045-7906
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:•Proposes full fractional-order sliding mode controllers for wind turbines.•Employs a fractional-order two-mass model for flexible shaft dynamics.•Optimizes controller parameters using a genetic algorithm.•Reduces chattering and improves speed and torque tracking.•Enhances energy capture and mechanical stress reduction. Wind energy systems play a key role in the global shift toward renewable energy. However, effectively controlling variable-speed wind turbines (VSWTs) under fluctuating wind conditions remains challenging. This paper presents a nonlinear fractional-order control method designed for VSWTs, using a fractional-order two-mass model that captures flexible shaft dynamics at low speeds. A novel control strategy based on full fractional-order sliding mode control (FFOSMC) and full fractional-order integral sliding mode control (FFOISMC) is introduced to enhance system stability, accuracy, and robustness. The fractional-order design leverages memory and non-local effects for improved performance. To tune control parameters, an evolutionary optimization technique is applied, ensuring adaptability across operating conditions. Stability is analyzed using the fractional-order Lyapunov method. Simulation results show that the proposed method outperforms conventional approaches in tracking accuracy, torque response, and energy efficiency. This work contributes to advanced wind turbine control and supports the development of smart renewable energy systems. [Display omitted]
ISSN:0045-7906
DOI:10.1016/j.compeleceng.2025.110658