CEAS EuroGNC 2026
|
Reinforcement-learning-inspired Autonomous Flight Envelope Protection
|
| Aristeidis Antonakis |
Research Engineer, ONERA, DTIS, 31055, Toulouse, France. | | Sofiane Kraïem |
Research Engineer, ONERA, DTIS, 31055, Toulouse, France. |
|
| Abstract:
In aerospace engineering, many systems exhibit strongly nonlinear, divergent, or unstable behavior when driven outside their nominal operating regimes: Their control design has to rely upon conservative assumptions and dedicated envelope protection logics restricting operation within regions with substantially linear dynamics. This often leads to a laborious, expensive, and time-consuming development process. In this paper, we propose a reinforcement-learning-inspired technique for envelope protection aimed explicitly at reducing the required designer workload by removing the requirement to explicitly define envelope limits. Our method comprises three key elements: (1) Neural nets for data-only dynamic identification, (2) a novel method for exploiting the neural model's parametric uncertainty to generate gradients that contain the dynamics within the known, safe envelope and, finally, (3) a Temporal Backpropagation (TB) calculation which converts the resulting optimal control problem to one of training of a deep, recurrent neural net architecture. The method's performance is assessed in simulated experiments: A simple numerical case demonstrates the algorithm's key characteristics. Finally, testing on a 6-DoF aircraft simulator evaluates the effectiveness of a TB-based Flight Envelope Protection (FEP) in flight sequences including aggressive pilot inputs and highly nonlinear post-stall aerodynamics.
|
| Keywords: Flight Envelope Protection; Reinforcement Learning; Uncertainty Propagation; Neural networks |
 View PDF CEAS-GNC-2026-052 doi: 10.82124/CEAS-GNC-2026-052 |
| Aristeidis Antonakis, Sofiane Kraïem: Reinforcement-learning-inspired Autonomous Flight Envelope Protection. Proceedings of the 2026 CEAS EuroGNC conference. Madrid, Spain. May 2026. doi: 10.82124/CEAS-GNC-2026-052.
|
| BibTeX entry (UTF-8):
@Incollection{CEAS-GNC-2026-052,
author = {Antonakis, Aristeidis and Kraïem, Sofiane},
title = {Reinforcement-learning-inspired Autonomous Flight Envelope Protection},
booktitle = {Proceedings of the 2026 {CEAS EuroGNC} conference},
address = {Madrid, Spain},
month = may,
year = {2026},
doi = {10.82124/CEAS-GNC-2026-052}
}
|