Comparative Control Strategies of an Underactuated Aircraft Wing Model
Bibliographic record
Abstract
This paper describes four fundamental control schemes for a 2D aeroelastic wing model under quasi-steady flow conditions: partial feedback linearization control (PFLC), energybased control (EC), flatness-based control (FC), and servo-constraint based feedforward control (SCFC).PFLC effectively categorizes degrees of freedom (DOFs) into active and passive groups, controlling the active DOFs while letting the stability of the passive joints depend on their internal dynamics.However, this approach has two limitations: the control law contains the inverse of the inertia matrix, and the evaluation of the internal stability of the passive joint dynamics is required.The control in EC is energy related -no more or less than the given energy -but the control law encounters problems with the computation of the energy inverse of the system.In contrast, FC linearizes the wing system and then obtains an output variable to be controlled; however, this method requires high-order derivatives of the system state, which can be very tedious.The strength of FC is that the controlled output can integrate most state variables.Kinematic constraints associated with the output to be produced are incorporated into the SCFC, and the equations of motion are reformulated to reflect the changes.Feedback and feedforward control terms come into play, as does the need to verify the stability of the internal dynamics of the control system.Modeling and simulation evaluations using MATLAB/SIMULINK confirmed that most of the control approaches were able to produce nearly similar dynamic responses with properly damped oscillations; however, the SCFC gives a fast response due to the presence of a feedforward term.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".