A Design Method of BTT Missile Autopilot with the Impact of Feedforward
Bibliographic record
Abstract
In order to solve the feedforward problem of traditional back-to-turn (BTT) missile autopilot, this paper proposed a controller design method considering the forward effect. Firstly, according to the three-channel mathematic model of BTT missile, we built a mathematic model of autopilot control system. Secondly, by employing the Nussbaum-type gain technique as well as the adding a power integrator design, and based on the design needs of tracking and controlling overload steadily, we proposed a global nonlinear control strategy, and then designed a continuous nonlinear autopilot, which solved the feedforward problem of BTT missile on pitching channel. Thirdly, we strictly proved the stability of the control system in finite time by applying the method of Lyapunov stability theory. Finally, we gave a simulation example to show that the designed control system not only overcome the influence of uncertain factors and the problem of the stable error, but also improved the tracking precision.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".