Taha, Z. and Deboucha, A. and Dahari, M. (2010) Small-scale helicopter system identification model using recurrent neural networks. In: Trends in Electronics Conference, 21-24 Nov 2010, Fukuoka, Japan.
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Abstract
Designing a reliable flight control for an autonomous helicopter requires a high performance dynamics model. This paper studies the recurrent neural network nonlinear model identification of a small scale helicopter. We have selected a Nonlinear AutoRegressive with eXogenous Inputs Series- Parallel (NARXSP) network model which identifies the dynamics model of an unmanned aerial helicopter from real flight data. The identification process is conducted by using the well known Levenberg-Marquardt learning algorithm. The obtained dynamics model shows good fitness with the actual data. This accuracy might be used to realize a reliable flight control for an autonomous helicopter.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Dynamics model, Recurrent Neural Network (RNN), System Identification, Small-Scale Helicopter |
| Subjects: | T Technology > T Technology (General) |
| Depositing User: | Mr. Mohd Samsul Ismail |
| Date Deposited: | 18 Dec 2014 02:41 |
| Last Modified: | 18 Dec 2014 02:41 |
| URI: | http://eprints.um.edu.my/id/eprint/11328 |
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