Small-scale helicopter system identification model using recurrent neural networks

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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