First Order Dynamic Sliding Mode Control of a Wind Turbine with Optimized Tip Speed Ratio
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a novel sliding mode control method to enhance power generation from wind turbines, with a focus on power optimization. Generator torque only is used as an input since maximizing power using pitch and yaw control is not deemed worth decreasing the life of the turbine due to wear of the mechanical system. The controller is designed based on a 3rd-order model with rotor aerodynamic torque as a disturbance input. Simulation is done using a nonlinear wind turbine model. The first objective is to determine the optimal tip speed ratio for maximum power. To do this, Recursive Least Squares (RLS) is used to estimate a polynomial relating the Tip-Speed Ratio (TSR) and aerodynamic power coefficient. This gives the optimal operating point. To ensure that the system can adapt to changing environments, a forgetting factor is used. The second objective, a first-order dynamic sliding mode controller with integration (FODSMCI), is used to control the wind turbine and maintain it at the optimal TSR with good transient dynamics. The results show that the RLS with high forgetting factor is effective in determining the optimal TSR. FODSMCI allows the user to adjust trade-offs between controller performance and rotor speed tracking, resulting in a response without chattering.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it