System identification for Quad-rotor parameters using neural network

Tarek N. Dief, Shigeo Yoshida

研究成果: ジャーナルへの寄稿記事

2 引用 (Scopus)

抄録

This paper presents a new technique to identify the system parameters without using the system governing equations. This technique is the time series prediction using neural network. The theoretical model was applied using simulations, after that the experiments were done to get the suitable construction for the neural model. A comparison between neural network and placket’s model is discussed. The advantages and disadvantages of both models were explained. The main idea of neural network is based on back-propagation algorithm. The equations and steps for iteration are presented and the relation between changing the number of iteration with the system frequency. The controller used is pole placement controller based on the neural network results as a system model.

元の言語英語
ページ(範囲)6-11
ページ数6
ジャーナルEvergreen
3
発行部数1
DOI
出版物ステータス出版済み - 1 1 2016

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Identification (control systems)
Rotors
Neural networks
Controllers
Backpropagation algorithms
back propagation
Time series
Poles
Elvitegravir, Cobicistat, Emtricitabine, Tenofovir Disoproxil Fumarate Drug Combination
parameter
time series
prediction
simulation
experiment
Experiments

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Ceramics and Composites
  • Surfaces, Coatings and Films
  • Management, Monitoring, Policy and Law

これを引用

System identification for Quad-rotor parameters using neural network. / Dief, Tarek N.; Yoshida, Shigeo.

:: Evergreen, 巻 3, 番号 1, 01.01.2016, p. 6-11.

研究成果: ジャーナルへの寄稿記事

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