Vargas, A., Ireland, M. and Anderson, D. (2015) System Identification of multi-rotor UAVs using echo state networks. In: AUVSI's Unmanned Systems 2015, Atlanta, GA, USA, 4-7 May 2015,
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104989.pdf - Accepted Version 1MB |
Publisher's URL: http://www.auvsishow.org/auvsi2015/public/enter.aspx
Abstract
Controller design for aircraft with unusual configurations presents unique challenges, particularly in extracting valid mathematical models of the MRUAVs behaviour. System Identification is a collection of techniques for extracting an accurate mathematical model of a dynamic system from experimental input-output data. This can entail parameter identification only (known as grey-box modelling) or more generally full parameter/structural identification of the nonlinear mapping (known as black-box). In this paper we propose a new method for black-box identification of the non-linear dynamic model of a small MRUAV using Echo State Networks (ESN), a novel approach to train Recurrent Neural Networks (RNN).
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Anderson, Dr David and Ireland, Dr Murray |
Authors: | Vargas, A., Ireland, M., and Anderson, D. |
College/School: | College of Science and Engineering > School of Engineering |
Copyright Holders: | Copyright © 2015 The Authors |
Publisher Policy: | Reproduced with the permission of the authors |
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