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Learning-based Path Tracking Control of a Flapping-wing Micro Air Vehicle : 학습 기반의 날갯짓 비행체 경로 제어
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- Authors
- Advisor
- 김현진
- Major
- 공과대학 기계항공공학부
- Issue Date
- 2018-08
- Publisher
- 서울대학교 대학원
- Description
- 학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 8. 김현진.
- Abstract
- Flapping-wing micro air vehicles (FWMAVs) become promising research platforms due to their advantages
such as various maneuverability, and concealment. However, periodic and unsteady airflows generated
by flapping-wing motion make their dynamics time-varying and highly non-linear. Therefore, it is
difficult to apply model-based control techiques and even if applied, performance is not so good. Consequently, in practical control problems, simple model-free controllers or rule-based controllers are widely
used, but they are impractical to track diverse flight trajectories and require many trials and errors for gaintunings. In this paper, we suggest a model-based control strategy for FWMAV using learning architecture.
For this task, we construct a ground station for logging flight data and control inputs, and train dynamics
with a neural network. Then, we apply model predictive control (MPC) to the trained model. We validate
our method by hardware experiments and compare with other control methods.
- Language
- English
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