Unified Solver Based Real-Time Multi-Domain Simulation of Aircraft Electro-Mechanical-Actuator
Bibliographic record
Abstract
Electro-mechanical-actuator (EMA) is the key component to convert electrical power into mechanical power for flight control in next-generation aircrafts. Multi-domain simulation of EMA can benefit its on-going evolution process. This paper presents the real-time multi-domain modeling and simulation of an EMA as elevator for flight control by utilization of a unified solver. Several key issues concerning the computational efficiency and successful implementation of this solver are provided and its relationship with state-variable model is also elaborated. Analysis shows that this solver could be a competitive candidate for multi-domain simulation because of its high computational efficiency and relatively less modeling effort. Electrical, mechanical, and thermal parts of the EMA are modeled and simulated interactively based on the proposed solver. The multi-domain model is implemented on FPGA board and executes in real time. Simulation results from FPGA board and commercial softwares under several test scenarios coincide with each other in very high degree, which showcases the efficacy of the proposed solver with respect to computational efficiency and ability to accommodate multi-domain models. The proposed model and solver are useful for hardware-in-the-loop design and testing of EMA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".