Flight Control Fault Models Based on SEU Emulation
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The increased use of FPGAs over the past decade has induced an increased concern about radiation effects, in particular the effects of single event upsets (SEU) in SRAM-based FPGAs. Technology scaling and density increase have caused FPGAs to be more vulnerable to SEU. Therefore, external radiations present an issue not only for space based systems; but also for critical terrestrial applications operating in harsh environment, such as commercial avionics.</div><div class="htmlview paragraph">In order to build robust fault tolerant systems, SEU effects have to be analyzed and modeled so that the designer understands and considers the system's possible faulty behaviors. In this paper, we present a complete automated methodology, based on the use of SEU controller provided by Xilinx, to efficiently emulate SEUs on an FPGA design and extract possible fault models based on radiation effects. The proposed method is applied on a reconfigurable flight control system based on a reference adaptive control model. With the automatic aspect of the proposed methodology, it was possible to emulate a large number of SEUs with reduced time and effort. Experimental results present the design sensitivity, its failure rate as well as its faulty output behavior. Moreover, results analysis disclose the existence of new actuator control fault models that are not considered in fault tolerant systems, these systems being mainly based on the existing well-known models in the literature. The new fault models can be used by the designer at an earlier stage in the design to build robust flight control systems.</div></div>
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".