Multiple specification controller design for F‐16 fighters
Bibliographic record
Abstract
Purpose The purpose of this paper is to show how to design effective and practical controllers that satisfy multiple simultaneous specifications (MSS) criteria concurrently. Design/methodology/approach In automatic flight control system or autopilots, MSS such as good holding (small static altitude holding error), fast response, smooth transition (less oscillation, overshoot) are needed to be satisfied concurrently. So how to design the MSS controller effectively and practically is a very significant and challenging job. An MSS controller design method is proposed. The paper further applies the method together with the fine‐tuning technique to the 6 DoF non‐linear F‐16 fighter longitudinal control channel. Simulation results show its applicability to non‐linear flight control system. Findings It was found that the simulation results demonstrate that the MSS design method with controller fine‐tuning can be applied to the nonlinear F‐16 fighter longitudinal control system. Research limitations/implications The practical implementation of this research work needs further investigation. Practical implications The simplicity of the design algorithm facilitates the application of the design to other aircrafts by use of Matlab. Originality/value The simulation results presented demonstrate that the proposed MSS apply well to non‐linear F‐16 fighters.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".