Development of an Attitude Control System of a Heavy-lift Hexacopter using Elman Recurrent Neural Networks
| Main Authors: | Kusumoputro,, Benyamin, Suprijono, Herwin, Heryanto, M Ary, Suprapto, Bhakti Yudho |
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| Format: | Article PeerReviewed application/pdf |
| Terbitan: |
IEEE
, 2016
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| Subjects: | |
| Online Access: |
http://eprints.unsri.ac.id/6892/1/07604889.pdf http://ieeexplore.ieee.org/ http://eprints.unsri.ac.id/6892/ |
Daftar Isi:
- Hexacopter is a type of multicopter that can be used to lift a heavy load, hence very convenient to be utilized in agricultural fields. As the consequence, however, the attitude control of this hexacopter is rather difficult compare with that of a quadcopter with four motors, due to gyroscopic effet of the additional motors and in its combination with the heavy loads. In this paper, we have developed a direct inverse controller system using an Elman neural networks for the attitude and altitude control of the hexacopter. Experiments are conducted using a flight data taken from a test-bed system. Results show that the attitude characteristics of the heavy-lift hexacopter can be controlled successfully, especially when an optimized Elman neural networks as the direct inverse controller system is utilized.