A wavelet neural control scheme for a quadrotor unmanned aerial vehicle.
Philos Trans A Math Phys Eng Sci
; 376(2126)2018 Aug 13.
Article
em En
| MEDLINE
| ID: mdl-29986917
Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time-frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results.This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Philos Trans A Math Phys Eng Sci
Assunto da revista:
BIOFISICA
/
ENGENHARIA BIOMEDICA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
México
País de publicação:
Reino Unido