Design of a fault-tolerant flight control system against multiple actuator failures
Bibliographic record
Abstract
Actuator faults occurring suddenly in avionic systems can deteriorate aircraft dynamics and may lead to catastrophic instability. Since conventional flight control systems are not reliable in the presence of such risks, for many years ago and until quite recently, these faults have been handled using actuator redundancy. However, this technique leads to extra weight and costs, and thus affects the overall space, weight and power. \n \nRecent research approaches have been focused on new analytical methods, known in the literature as fault-tolerant control systems. Based on both an online fault detection and diagnosis process and a reconfigurable flight control law, these systems are capable of adapting in real time to such sudden faults while keeping avionic systems lighter and less expensive. Although the concept of reconfigurable control still remains in the experimental phase and there is no system implemented on commercial aircraft, several research programs have been created over the past 20 years to study their potential. \n \nIn this thesis, fault-tolerant control systems combined the sliding mode technique and the geometric approach for fault reconstruction are developed based on Lyapunov theory of stability. The purpose is to handle multiple simultaneous actuator faults while preserving stability and maintaining desired performances. To validate the effectiveness and robustness of the proposed algorithms in faulty situations, several Matlab®/Simulink® numerical simulations are performed on high fidelity aircraft models. FlightGear software simulator is used to show the performance and the behavior of the aircraft on a graphical user interface.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".