Enhanced Flight Envelope Protection: A Novel Reinforcement Learning Approach
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914832220946432 |
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| author | Catak, Akin Altunkaya, Ege C. Demir, Mustafa Koyuncu, Emre Ozkol, Ibrahim |
| author_facet | Catak, Akin Altunkaya, Ege C. Demir, Mustafa Koyuncu, Emre Ozkol, Ibrahim |
| contents | This paper introduces a flight envelope protection algorithm on a longitudinal axis that leverages reinforcement learning (RL). By considering limits on variables such as angle of attack, load factor, and pitch rate, the algorithm counteracts excessive pilot or control commands with restoring actions. Unlike traditional methods requiring manual tuning, RL facilitates the approximation of complex functions within the trained model, streamlining the design process. This study demonstrates the promising results of RL in enhancing flight envelope protection, offering a novel and easy-to-scale method for safety-ensured flight. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_05586 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhanced Flight Envelope Protection: A Novel Reinforcement Learning Approach Catak, Akin Altunkaya, Ege C. Demir, Mustafa Koyuncu, Emre Ozkol, Ibrahim Systems and Control This paper introduces a flight envelope protection algorithm on a longitudinal axis that leverages reinforcement learning (RL). By considering limits on variables such as angle of attack, load factor, and pitch rate, the algorithm counteracts excessive pilot or control commands with restoring actions. Unlike traditional methods requiring manual tuning, RL facilitates the approximation of complex functions within the trained model, streamlining the design process. This study demonstrates the promising results of RL in enhancing flight envelope protection, offering a novel and easy-to-scale method for safety-ensured flight. |
| title | Enhanced Flight Envelope Protection: A Novel Reinforcement Learning Approach |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2406.05586 |