A Comparison of Back Propagation Neural Network and Elman Recurrent Neural Network Algorithms on Altitude Control of Heavy-lift Hexacopter Based on Direct Inverse Control

Bhakti Yudho Suprapto, Benyamin Kusumoputro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

The altitude control is one of the important factors in controlling the heavy-lift hexacopter. This altitude control needs precise control since the heavy-lift hexacopter moves based on the speed of its driving motors. This paper uses a control based on Direct Inverse Controller with Neural Network Algorithm. The algorithm which used in this paper is Elman Recurrent Neural Network compared with Backpropagation Neural Network. The Backpropagation is the most used algorithm in Neural Network. In the testing result, The Elman Recurrent Neural Network algorithm result in smaller MSE value and capable to keep up with given data test compared with Backpropagation Neural Network algorithm.

Original languageEnglish
Title of host publicationProceedings of 2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages79-84
Number of pages6
ISBN (Electronic)9781538657201
DOIs
Publication statusPublished - 7 Jan 2019
Event2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018 - Pangkal Pinang, Indonesia
Duration: 2 Oct 20184 Oct 2018

Publication series

NameProceedings of 2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018

Conference

Conference2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018
Country/TerritoryIndonesia
CityPangkal Pinang
Period2/10/184/10/18

Keywords

  • Altitude Control
  • Backpropagation Neural Network
  • Direct Inverse Controller
  • Elman Recurrent Neural Network
  • Heavy-lift Hexacopter

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