System identification for Quad-rotor parameters using neural network

Tarek N. Dief, Shigeo Yoshida

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)6-11
Number of pages6
JournalEvergreen
Volume3
Issue number1
DOIs
Publication statusPublished - 2016

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'System identification for Quad-rotor parameters using neural network'. Together they form a unique fingerprint.

Cite this