System Identification of multi-rotor UAVs using echo state networks

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,

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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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
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ireland, Dr Murray and Anderson, Dr David
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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