Optimal control based on artificial neural network for flameout approach ff fighter jet = 전투기의 무추력 접근을 위한 인공신경망 기반 최적 조종기법

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Loss of thrust due to engine failure induces dangerous situation for a single-engine fighter jet. For this reason, particularly almost every military aircraft has well established flameout approach procedures destined to the base or an alternate airfield. The flameout approach procedures enables the aircraft to safely return to the destination while ensuring utmost safety. The control strategy consisting the procedures is rather a recommendation provided to a pilot, rather than an optimal control strategy. Hence, detailed control techniques are different depending on pilots. Because the optimization process to calculate an optimal control strategy is accompanied by a massive computation time, it is almost impossible to calculate and apply the optimal control onboard in real-time. In this thesis, an optimal control strategy based on real-time optimal control method for conducting the flameout approach procedures under arbitrary flight situation is proposed by using the artificial neural network which is actively studied as a part of the artificial intelligence research.
Advisors
Tahk, Min-Jearesearcher탁민제researcher
Description
한국과학기술원 :항공우주공학과,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 항공우주공학과, 2019.2,[v, 76 p. :]

Keywords

real-time optimal control▼aartificial intelligence▼aartificial neural network▼aguidance▼aemergency procedures; 실시간 최적제어▼a인공지능▼a인공신경망▼a유도법칙▼a비상절차

URI
http://hdl.handle.net/10203/267318
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843709&flag=dissertation
Appears in Collection
AE-Theses_Master(석사논문)
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