Modified elman recurrent neural network for attitude and altitude control of heavy-lift hexacopter

Bhakti Yudho Suprapto, Amsa Mustaqim, Wahidin Wahab, Benyamin Kusumo Putro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hexacopter is a member of rotor-wing Unmanned Aerial Vehicle (UAV) which has 6 six rotors with fixed pitch blades and nonlinear characteristics that cause controlling the attitude of hexacopter is difficult. In this paper, Modified Elman Recurrent Neural Network (MERNN) is used to control attitude and altitude of Heavy-lift Hexacopter to get better performance than Elman Recurrent Neural Network (ERNN). This Modified Elman Recurrent Neural Network has a self-feedback which provides a dynamic trace of the gradients in the parameter space. In the self-feedback, the gain coefficients are trained as connection weight. This connection weight could enhance the adaptability of Elman Recurrent Neural Network to the time-varying system. The flight data are taken from a real flight experiment. Results show that the Modified Elman Recurrent Neural Network can increase performance with small error and generate a better response than Elman Recurrent Neural Network.

Original languageEnglish
Title of host publicationQiR 2017 - 2017 15th International Conference on Quality in Research (QiR)
Subtitle of host publicationInternational Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages309-314
Number of pages6
ISBN (Electronic)9781509063970
DOIs
Publication statusPublished - 5 Dec 2017
Event15th International Conference on Quality in Research: International Symposium on Electrical and Computer Engineering, QiR 2017 - Nusa Dua, Bali, Indonesia
Duration: 24 Jul 201727 Jul 2017

Publication series

NameQiR 2017 - 2017 15th International Conference on Quality in Research (QiR): International Symposium on Electrical and Computer Engineering
Volume2017-December

Conference

Conference15th International Conference on Quality in Research: International Symposium on Electrical and Computer Engineering, QiR 2017
CountryIndonesia
CityNusa Dua, Bali
Period24/07/1727/07/17

Keywords

  • Direct Inverse Control
  • Elman Recurrent Neural Network
  • Heavy-lift Hexacopter
  • Modified Elman Recurrent Neural Network

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