Fault-Tolerant Individual Pitch Control of a Wind Turbine with Actuator Faults
Bibliographic record
Abstract
The sizes of wind turbines have been steadily increasing over the past decade, especially on the offshore sites. The greater structural flexibility of such machines necessitates considerations of reliable load mitigation techniques in order to alleviate the effects of asymmetric wind loads and fatigue. This paper proposes a reliable load mitigation scheme, referred to as ‘fault-tolerant individual pitch control’, which involves adjustments in pitch angles of the wind turbine blades individually in the presence of blade pitch actuator faults. The proposed scheme consists of a collective pitch control augmented with an individual pitch control, and a fault detection and diagnosis system. Simulation results obtained for a large-scale offshore wind turbine with a stochastic wind field illustrate effectiveness as well as fault-tolerance of the proposed scheme compared to the scheme based on control of pitch angles collectively. Moreover, the proposed scheme not only ensures more uniform output power with reduced loads on the turbine, but also tolerates the effects of possible faults in pith actuators of the blades.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".