Abstract
“Teaching by Showing” control of a small helicopter’s aggressive maneuvering often needs inner aided controllers based on helicopter’s dynamics, which is very complex to identify. In this paper, a neural network based control is proposed, based on the identification of the relationship between the pilot’s control and flight states, and it is a model-free control method. Flight test is done in simulation environment based on real flight data. The results show the effectiveness of the neural network based controller for aggressive flight control.
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Song, D., Wu, C., Qi, J., Han, J. (2013). Aggressive Manuevering of Unmanned Helicopters: Learning from Human Based on Neural Networks. In: Lee, S., Cho, H., Yoon, KJ., Lee, J. (eds) Intelligent Autonomous Systems 12. Advances in Intelligent Systems and Computing, vol 193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33926-4_66
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DOI: https://doi.org/10.1007/978-3-642-33926-4_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33925-7
Online ISBN: 978-3-642-33926-4
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