Colloquium: Willem Völker (C&O)

04 juli 2022 09:30 - Locatie: LECTURE ROOM D, FACULTY OF AEROSPACE ENGINEERING, KLUYVERWEG 1, DELFT | Zet in mijn agenda

Reinforcement Learning for Flight Control of the Flying V

Recent research on the Flying V - a flying-wing long-range passenger aircraft - shows that its airframe design is 25% more aerodynamically efficient than a conventional tube-and-wing airframe. The Flying V is therefore a promising contribution towards reduction in climate impact of long-haul flights. However, some design aspects of the Flying V still remain to be investigated, one of which is automatic flight control. Due to the unconventional airframe shape of the Flying V, aerodynamic modelling cannot rely on validated aerodynamic-modelling tools and the accuracy of the aerodynamic model is uncertain. Therefore, this contribution investigates how Twin-Delayed Deep Deterministic Policy Gradient (TD3) - a recent deepreinforcement-learning algorithm - can be used to develop an automatic flight controller that is robust to aerodynamic-model uncertainty. The results show that an offline-trained single-loop altitude controller that is fully based on TD3 can track a given altitude-reference signal and is robust to aerodynamic-model uncertainty of more than 25%.

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