Finite-Time Intermittent-Update Control for Aircraft Electric Antiskid Braking System via Sliding Mode Approach
Bibliographic record
Abstract
In order to achieve optimal slip ratio tracking, this article proposes a sliding mode intermittent-update control (SMIC) method for the aircraft electric antiskid braking system. Based on analyzing the aircraft braking process and the electromechanical characteristics of actuators, a comprehensive model is established, incorporating slip ratio, braking pressure, and rotor angular velocity in a cascade structure. Due to the complex runway environment and diverse climate conditions, the inherent variability and nonlinearity of the optimal slip ratio pose significant challenges to the sustained utilization of maximum friction. To address the above challenges and enhance braking performance, a switching extremum search approach is proposed to optimize the slip ratio in real time. A sliding mode intermittent-update controller is designed to track the real-time optimal slip ratio, ensuring finite-time convergence and effectively preventing wheel slip and lock-up. Finally, the proposed control strategy is validated on a realtime hardware-in-the-loop-based platform, which demonstrates that the SMIC strategy can not only effectively improve the braking efficiency but also reduces the switching frequency of the electromechanical actuators.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".