Design of a tolerant flight control system in response to multiple actuator control signal faults induced by cosmic rays
Bibliographic record
Abstract
Due to continued miniaturization, semiconductor-based components used in high-performance digital microelectronics are becoming increasingly sensitive to cosmic rays and solar particle events. In the context of high-altitude flight control systems based on fly-by-wire techniques, this may produce sensor noise or affect actuator control signals. Although the consequences so far have been simply reductions in aircraft performance, catastrophic scenarios may be envisioned. In this article, we propose a novel architecture for a fault-tolerant flight control system able to detect and compensate for cosmic ray-induced multiple-bit upsets that affect actuator control signals in modern fly-by-wire avionics systems while assuming that the actuator itself remains healthy. A fault detection and diagnosis procedure was designed using a geometric approach combined with an extended multiple-model adaptive estimation technique. This procedure is able to process multiple faulty actuator-control signals and identify their parameters. The parameters thus obtained are then used with a reconfigurable sliding-mode control to compensate for such errors by mobilizing the remaining actuators' healthy control signals. Lyapunov stability theory is used to analyze the closed-loop system stability. Simulation results using Matlab /Simulink showed the effectiveness of the proposed approach in the case of a system challenged with double faults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".