Altitude Control of Heavy-Lift Hexacopter using Direct Inverse Control Based on Elman Recurrent Neural Network
| Autor: | Benyamin Kusumoputro, Herwin Suprijono, M Ary Heryanto, Bhakti Yudho Suprapto |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
Artificial neural network business.industry Lift (data mining) 020209 energy 02 engineering and technology Recurrent neural network Control theory 0202 electrical engineering electronic engineering information engineering Inverse control 020201 artificial intelligence & image processing business Altitude control Flight data Movement control Test data |
| Zdroj: | ICCMS |
| DOI: | 10.1145/3036331.3036354 |
| Popis: | This paper proposes the use of Direct Inverse Control (DIC) with Elman Recurrent Neural Network (ERNN) learning algorithm for the altitude control of a heavy-lift hexacopter. The study was conducted analytically using the real flight data obtained from real plant experiment. The results showed that the ERNN can successfully control the altitude of the heavy-lift hexacopter, where the response generated by the DIC system was in good agreement with the test data with low error. Furthermore, the proposed DIC system can also control the attitude, e.g. roll, pitch and yaw of the hexacopter which are also crucial for the hexacopter movement control. |
| Databáze: | OpenAIRE |
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