Linear parameter varying control of unmanned quadrotor helicopter with mass variation and battery drainage
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a linear parameter varying (LPV) control technique is proposed for the control of unmanned quadrotor helicopter (UQH), compensating the adverse effects of system variations, such as mass changes due to payload grasping, carrying, and dropping as well as battery voltage variations caused by battery drainage. The magnitudes of these variations, in this study, are assumed to be obtainable from the estimation scheme or priori knowable. Based on the information of these system variations, a linear parameter dependent state-feedback controller in a convex polytopic LPV representation is devised so that the corresponding adverse effects can be counteracted. The system parameters that vary with time are then specified as the design parameters for LPV controller, while the ultimate control law can be obtained online employing the well-established linear matrix inequality (LMI) conditions. Finally, both simulation and experimental validations are conducted to demonstrate the performance of the proposed control method on an UQH undergoing the changes of payload mass and battery voltage.
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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) | 0.000 | 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 it