Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks
In this paper, we present the performance analysis of a fully tuned neural network trained with the extended minimal resource allocating network (EMRAN) algorithm for real-time identification of a quadcopter. Radial basis function network (RBF) based on system identification can be utilised as...
Saved in:
Main Authors: | Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi, Mohd Anwar, Mohd Shazlan |
---|---|
Format: | Article |
Language: | English |
Published: |
Inder Science
2021
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/6616/1/J13840_86bfec0ace2c4bbe3417b0d967ad1cc3.pdf http://eprints.uthm.edu.my/6616/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Real-time system identification of an unmanned
quadcopter system using fully tuned radial basis
function neural networks
by: Pairan, Mohammad Fahmi, et al.
Published: (2021) -
Real-time identification of an unmanned quadcopter flight dynamics using fully tuned radial basis function network
by: Pairan, Mohammad Fahmi
Published: (2018) -
Modelling magneto-rheological damper using radial basis function neural network
by: Mohd Fikri, Arifin
Published: (2013) -
The development of autopilot system for an unmanned aerial vehicle (UAV) helicopter model
by: Shamsudin, Syariful Syafiq
Published: (2007) -
Modelling and manual tuning PID control of quadcopter
by: Sahrir, Nur Hayati, et al.
Published: (2022)