Abstract
Conventional control methods, such as Proportional Integral Derivative (PID) control, have been extensively utilized for speed regulation in renewable energy wind turbine units. However, the limitations and disadvantages of PID, including difficulties in handling nonlinearities and uncertainties inherent in wind turbine dynamics, necessitate the exploration of alternative approaches. This research paper proposes the adoption of Iterative Learning Control (ILC) as an intelligent controller for addressing the shortcomings of PID. By exploiting the repetitive nature of wind turbine operation, ILC offers the potential to enhance speed regulation performance by iteratively refining control actions based on past experiences for advancing renewable energy. Through simulation studies, the effectiveness of ILC in improving the transient response and tracking accuracy of wind turbine units is demonstrated.
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