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

Abstract

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.