A New Method for Tuning PI Gains for Position Control of BLDC Motor Based Wing Morphing Actuators
Bibliographic record
Abstract
The paper presents the control design of a BLDC motor used in the actuation mechanism of an experimental morphing wing model. The actuation system of the morphing wing includes four similar actuators, placed on two actuation lines. Each actuator has in its structure a BLDC motor, and a part that turns rotation movement into the linear movement, containing a gearbox, a gearing and a trapezoidal screw. The control design procedure is based on the Internal Model Control methodology, in the paper being exposed successively the modeling, the simulation and the experimental testing of the controlled electrical actuator. At a first step, the transfer function of the motor is established and the mechanical coupling between it and the linear actuator is modeled. Secondly, by using motor transfer function with current, speed and position control loops, the Matlab/Simulink model of the morphing actuator control is obtained. Further, the Internal Model Control methodology is applied in the tuning of the actuator control, and the obtained control gains are validated by using an experimental model based on some drives and on the NI PXI technology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".